An Anatomically Resolved Mouse Brain Proteome Reveals Parkinson Disease-relevant Pathways *

PubMed Central

Choi, Jong Min; Rousseaux, Maxime W. C.; Malovannaya, Anna; Kim, Jean J.; Kutzera, Joachim; Wang, Yi; Huang, Yin; Zhu, Weimin; Maity, Suman; Zoghbi, Huda Yahya; Qin, Jun

2017-01-01

Here, we present a mouse brain protein atlas that covers 17 surgically distinct neuroanatomical regions of the adult mouse brain, each less than 1 mm3 in size. The protein expression levels are determined for 6,500 to 7,500 gene protein products from each region and over 12,000 gene protein products for the entire brain, documenting the physiological repertoire of mouse brain proteins in an anatomically resolved and comprehensive manner. We explored the utility of our spatially defined protein profiling methods in a mouse model of Parkinson's disease. We compared the proteome from a vulnerable region (substantia nigra pars compacta) of wild type and parkinsonian mice with that of an adjacent, less vulnerable, region (ventral tegmental area) and identified several proteins that exhibited both spatiotemporal- and genotype-restricted changes. We validated the most robustly altered proteins using an alternative profiling method and found that these modifications may highlight potential new pathways for future studies. This proteomic atlas is a valuable resource that offers a practical framework for investigating the molecular intricacies of normal brain function as well as regional vulnerability in neurological diseases. All of the mouse regional proteome profiling data are published on line at http://mbpa.bprc.ac.cn/. PMID:28153913

Cortical Thinning in Network-Associated Regions in Cognitively Normal and Below-Normal Range Schizophrenia

PubMed Central

Pinnock, Farena; Parlar, Melissa; Hawco, Colin; Hanford, Lindsay; Hall, Geoffrey B.

2017-01-01

This study assessed whether cortical thickness across the brain and regionally in terms of the default mode, salience, and central executive networks differentiates schizophrenia patients and healthy controls with normal range or below-normal range cognitive performance. Cognitive normality was defined using the MATRICS Consensus Cognitive Battery (MCCB) composite score (T = 50 ± 10) and structural magnetic resonance imaging was used to generate cortical thickness data. Whole brain analysis revealed that cognitively normal range controls (n = 39) had greater cortical thickness than both cognitively normal (n = 17) and below-normal range (n = 49) patients. Cognitively normal controls also demonstrated greater thickness than patients in regions associated with the default mode and salience, but not central executive networks. No differences on any thickness measure were found between cognitively normal range and below-normal range controls (n = 24) or between cognitively normal and below-normal range patients. In addition, structural covariance between network regions was high and similar across subgroups. Positive and negative symptom severity did not correlate with thickness values. Cortical thinning across the brain and regionally in relation to the default and salience networks may index shared aspects of the psychotic psychopathology that defines schizophrenia with no relation to cognitive impairment. PMID:28348889

Activation of writing-specific brain regions when reading Chinese as a second language. Effects of training modality and transfer to novel characters.

PubMed

Lagarrigue, Aurélie; Longcamp, Marieke; Anton, Jean Luc; Nazarian, Bruno; Prévot, Laurent; Velay, Jean-Luc; Cao, Fan; Frenck-Mestre, Cheryl

2017-03-01

We examined the implication of training modality on the cortical representation of Chinese words in adult second language learners of Chinese. In particular, we tested the implication of the neural substrates of writing in a reading task. The brain network sustaining finger writing was defined neuroanatomically based on an independent functional localizer. We examined the brain activations elicited by Chinese words learned via writing vs. pronunciation, and by novel untrained words, within regions of interest (ROIs) defined according to the position of the activation peaks in the localizer, and at the whole brain level. We revealed activations in the reading task that overlapped with several parts of the finger writing network. In addition, our results provide evidence that the neural substrates of writing are differentially involved in reading depending on the stored knowledge for words, as revealed by the fine-grained response of several regions including the left superior parietal lobule and left precentral gyrus / superior frontal sulcus to the experimental manipulations. Training modality and the linguistic properties of the characters also impacted the response of the left mid-fusiform gyrus, confirming its involvement as the brain region where linguistic, visual and sensorimotor information converge during orthographic processing. At the behavioral level, global handwriting quality during the training sessions was positively correlated to the final translation performance. Our results demonstrate substantial overlap in the neural substrates of reading and writing, and indicate that some regions sustaining handwriting are differentially involved in reading depending on the type of knowledge associated with words. Copyright © 2017 Elsevier Ltd. All rights reserved.

Mapping Resting-State Brain Networks in Conscious Animals

PubMed Central

Zhang, Nanyin; Rane, Pallavi; Huang, Wei; Liang, Zhifeng; Kennedy, David; Frazier, Jean A.; King, Jean

2010-01-01

In the present study we mapped brain functional connectivity in the conscious rat at the “resting state” based on intrinsic blood-oxygenation-level dependent (BOLD) fluctuations. The conscious condition eliminated potential confounding effects of anesthetic agents on the connectivity between brain regions. Indeed, using correlational analysis we identified multiple cortical and subcortical regions that demonstrated temporally synchronous variation with anatomically well-defined regions that are crucial to cognitive and emotional information processing including the prefrontal cortex (PFC), thalamus and retrosplenial cortex. The functional connectivity maps created were stringently validated by controlling for false positive detection of correlation, the physiologic basis of the signal source, as well as quantitatively evaluating the reproducibility of maps. Taken together, the present study has demonstrated the feasibility of assessing functional connectivity in conscious animals using fMRI and thus provided a convenient and non-invasive tool to systematically investigate the connectional architecture of selected brain networks in multiple animal models. PMID:20382183

The role of domain-general cognitive control in language comprehension

PubMed Central

Fedorenko, Evelina

2014-01-01

What role does domain-general cognitive control play in understanding linguistic input? Although much evidence has suggested that domain-general cognitive control and working memory resources are sometimes recruited during language comprehension, many aspects of this relationship remain elusive. For example, how frequently do cognitive control mechanisms get engaged when we understand language? And is this engagement necessary for successful comprehension? I here (a) review recent brain imaging evidence for the neural separability of the brain regions that support high-level linguistic processing vs. those that support domain-general cognitive control abilities; (b) define the space of possibilities for the relationship between these sets of brain regions; and (c) review the available evidence that constrains these possibilities to some extent. I argue that we should stop asking whether domain-general cognitive control mechanisms play a role in language comprehension, and instead focus on characterizing the division of labor between the cognitive control brain regions and the more functionally specialized language regions. PMID:24803909

An edge-centric perspective on the human connectome: link communities in the brain.

PubMed

de Reus, Marcel A; Saenger, Victor M; Kahn, René S; van den Heuvel, Martijn P

2014-10-05

Brain function depends on efficient processing and integration of information within a complex network of neural interactions, known as the connectome. An important aspect of connectome architecture is the existence of community structure, providing an anatomical basis for the occurrence of functional specialization. Typically, communities are defined as groups of densely connected network nodes, representing clusters of brain regions. Looking at the connectome from a different perspective, instead focusing on the interconnecting links or edges, we find that the white matter pathways between brain regions also exhibit community structure. Eleven link communities were identified: five spanning through the midline fissure, three through the left hemisphere and three through the right hemisphere. We show that these link communities are consistently identifiable and investigate the network characteristics of their underlying white matter pathways. Furthermore, examination of the relationship between link communities and brain regions revealed that the majority of brain regions participate in multiple link communities. In particular, the highly connected and central hub regions showed a rich level of community participation, supporting the notion that these hubs play a pivotal role as confluence zones in which neural information from different domains merges. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Identification of alterations associated with age in the clustering structure of functional brain networks.

PubMed

Guzman, Grover E C; Sato, Joao R; Vidal, Maciel C; Fujita, Andre

2018-01-01

Initial studies using resting-state functional magnetic resonance imaging on the trajectories of the brain network from childhood to adulthood found evidence of functional integration and segregation over time. The comprehension of how healthy individuals' functional integration and segregation occur is crucial to enhance our understanding of possible deviations that may lead to brain disorders. Recent approaches have focused on the framework wherein the functional brain network is organized into spatially distributed modules that have been associated with specific cognitive functions. Here, we tested the hypothesis that the clustering structure of brain networks evolves during development. To address this hypothesis, we defined a measure of how well a brain region is clustered (network fitness index), and developed a method to evaluate its association with age. Then, we applied this method to a functional magnetic resonance imaging data set composed of 397 males under 31 years of age collected as part of the Autism Brain Imaging Data Exchange Consortium. As results, we identified two brain regions for which the clustering change over time, namely, the left middle temporal gyrus and the left putamen. Since the network fitness index is associated with both integration and segregation, our finding suggests that the identified brain region plays a role in the development of brain systems.

Functional specificity for high-level linguistic processing in the human brain.

PubMed

Fedorenko, Evelina; Behr, Michael K; Kanwisher, Nancy

2011-09-27

Neuroscientists have debated for centuries whether some regions of the human brain are selectively engaged in specific high-level mental functions or whether, instead, cognition is implemented in multifunctional brain regions. For the critical case of language, conflicting answers arise from the neuropsychological literature, which features striking dissociations between deficits in linguistic and nonlinguistic abilities, vs. the neuroimaging literature, which has argued for overlap between activations for linguistic and nonlinguistic processes, including arithmetic, domain general abilities like cognitive control, and music. Here, we use functional MRI to define classic language regions functionally in each subject individually and then examine the response of these regions to the nonlinguistic functions most commonly argued to engage these regions: arithmetic, working memory, cognitive control, and music. We find little or no response in language regions to these nonlinguistic functions. These data support a clear distinction between language and other cognitive processes, resolving the prior conflict between the neuropsychological and neuroimaging literatures.

A regulatory toolbox of MiniPromoters to drive selective expression in the brain.

PubMed

Portales-Casamar, Elodie; Swanson, Douglas J; Liu, Li; de Leeuw, Charles N; Banks, Kathleen G; Ho Sui, Shannan J; Fulton, Debra L; Ali, Johar; Amirabbasi, Mahsa; Arenillas, David J; Babyak, Nazar; Black, Sonia F; Bonaguro, Russell J; Brauer, Erich; Candido, Tara R; Castellarin, Mauro; Chen, Jing; Chen, Ying; Cheng, Jason C Y; Chopra, Vik; Docking, T Roderick; Dreolini, Lisa; D'Souza, Cletus A; Flynn, Erin K; Glenn, Randy; Hatakka, Kristi; Hearty, Taryn G; Imanian, Behzad; Jiang, Steven; Khorasan-zadeh, Shadi; Komljenovic, Ivana; Laprise, Stéphanie; Liao, Nancy Y; Lim, Jonathan S; Lithwick, Stuart; Liu, Flora; Liu, Jun; Lu, Meifen; McConechy, Melissa; McLeod, Andrea J; Milisavljevic, Marko; Mis, Jacek; O'Connor, Katie; Palma, Betty; Palmquist, Diana L; Schmouth, Jean-François; Swanson, Magdalena I; Tam, Bonny; Ticoll, Amy; Turner, Jenna L; Varhol, Richard; Vermeulen, Jenny; Watkins, Russell F; Wilson, Gary; Wong, Bibiana K Y; Wong, Siaw H; Wong, Tony Y T; Yang, George S; Ypsilanti, Athena R; Jones, Steven J M; Holt, Robert A; Goldowitz, Daniel; Wasserman, Wyeth W; Simpson, Elizabeth M

2010-09-21

The Pleiades Promoter Project integrates genomewide bioinformatics with large-scale knockin mouse production and histological examination of expression patterns to develop MiniPromoters and related tools designed to study and treat the brain by directed gene expression. Genes with brain expression patterns of interest are subjected to bioinformatic analysis to delineate candidate regulatory regions, which are then incorporated into a panel of compact human MiniPromoters to drive expression to brain regions and cell types of interest. Using single-copy, homologous-recombination "knockins" in embryonic stem cells, each MiniPromoter reporter is integrated immediately 5' of the Hprt locus in the mouse genome. MiniPromoter expression profiles are characterized in differentiation assays of the transgenic cells or in mouse brains following transgenic mouse production. Histological examination of adult brains, eyes, and spinal cords for reporter gene activity is coupled to costaining with cell-type-specific markers to define expression. The publicly available Pleiades MiniPromoter Project is a key resource to facilitate research on brain development and therapies.

Regional growth and atlasing of the developing human brain

PubMed Central

Makropoulos, Antonios; Aljabar, Paul; Wright, Robert; Hüning, Britta; Merchant, Nazakat; Arichi, Tomoki; Tusor, Nora; Hajnal, Joseph V.; Edwards, A. David; Counsell, Serena J.; Rueckert, Daniel

2016-01-01

Detailed morphometric analysis of the neonatal brain is required to characterise brain development and define neuroimaging biomarkers related to impaired brain growth. Accurate automatic segmentation of neonatal brain MRI is a prerequisite to analyse large datasets. We have previously presented an accurate and robust automatic segmentation technique for parcellating the neonatal brain into multiple cortical and subcortical regions. In this study, we further extend our segmentation method to detect cortical sulci and provide a detailed delineation of the cortical ribbon. These detailed segmentations are used to build a 4-dimensional spatio-temporal structural atlas of the brain for 82 cortical and subcortical structures throughout this developmental period. We employ the algorithm to segment an extensive database of 420 MR images of the developing brain, from 27 to 45 weeks post-menstrual age at imaging. Regional volumetric and cortical surface measurements are derived and used to investigate brain growth and development during this critical period and to assess the impact of immaturity at birth. Whole brain volume, the absolute volume of all structures studied, cortical curvature and cortical surface area increased with increasing age at scan. Relative volumes of cortical grey matter, cerebellum and cerebrospinal fluid increased with age at scan, while relative volumes of white matter, ventricles, brainstem and basal ganglia and thalami decreased. Preterm infants at term had smaller whole brain volumes, reduced regional white matter and cortical and subcortical grey matter volumes, and reduced cortical surface area compared with term born controls, while ventricular volume was greater in the preterm group. Increasing prematurity at birth was associated with a reduction in total and regional white matter, cortical and subcortical grey matter volume, an increase in ventricular volume, and reduced cortical surface area. PMID:26499811

Regional growth and atlasing of the developing human brain.

PubMed

Makropoulos, Antonios; Aljabar, Paul; Wright, Robert; Hüning, Britta; Merchant, Nazakat; Arichi, Tomoki; Tusor, Nora; Hajnal, Joseph V; Edwards, A David; Counsell, Serena J; Rueckert, Daniel

2016-01-15

Detailed morphometric analysis of the neonatal brain is required to characterise brain development and define neuroimaging biomarkers related to impaired brain growth. Accurate automatic segmentation of neonatal brain MRI is a prerequisite to analyse large datasets. We have previously presented an accurate and robust automatic segmentation technique for parcellating the neonatal brain into multiple cortical and subcortical regions. In this study, we further extend our segmentation method to detect cortical sulci and provide a detailed delineation of the cortical ribbon. These detailed segmentations are used to build a 4-dimensional spatio-temporal structural atlas of the brain for 82 cortical and subcortical structures throughout this developmental period. We employ the algorithm to segment an extensive database of 420 MR images of the developing brain, from 27 to 45weeks post-menstrual age at imaging. Regional volumetric and cortical surface measurements are derived and used to investigate brain growth and development during this critical period and to assess the impact of immaturity at birth. Whole brain volume, the absolute volume of all structures studied, cortical curvature and cortical surface area increased with increasing age at scan. Relative volumes of cortical grey matter, cerebellum and cerebrospinal fluid increased with age at scan, while relative volumes of white matter, ventricles, brainstem and basal ganglia and thalami decreased. Preterm infants at term had smaller whole brain volumes, reduced regional white matter and cortical and subcortical grey matter volumes, and reduced cortical surface area compared with term born controls, while ventricular volume was greater in the preterm group. Increasing prematurity at birth was associated with a reduction in total and regional white matter, cortical and subcortical grey matter volume, an increase in ventricular volume, and reduced cortical surface area. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Music modulation of pain perception and pain-related activity in the brain, brain stem, and spinal cord: a functional magnetic resonance imaging study.

PubMed

Dobek, Christine E; Beynon, Michaela E; Bosma, Rachael L; Stroman, Patrick W

2014-10-01

The oldest known method for relieving pain is music, and yet, to date, the underlying neural mechanisms have not been studied. Here, we investigate these neural mechanisms by applying a well-defined painful stimulus while participants listened to their favorite music or to no music. Neural responses in the brain, brain stem, and spinal cord were mapped with functional magnetic resonance imaging spanning the cortex, brain stem, and spinal cord. Subjective pain ratings were observed to be significantly lower when pain was administered with music than without music. The pain stimulus without music elicited neural activity in brain regions that are consistent with previous studies. Brain regions associated with pleasurable music listening included limbic, frontal, and auditory regions, when comparing music to non-music pain conditions. In addition, regions demonstrated activity indicative of descending pain modulation when contrasting the 2 conditions. These regions include the dorsolateral prefrontal cortex, periaqueductal gray matter, rostral ventromedial medulla, and dorsal gray matter of the spinal cord. This is the first imaging study to characterize the neural response of pain and how pain is mitigated by music, and it provides new insights into the neural mechanism of music-induced analgesia within the central nervous system. This article presents the first investigation of neural processes underlying music analgesia in human participants. Music modulates pain responses in the brain, brain stem, and spinal cord, and neural activity changes are consistent with engagement of the descending analgesia system. Copyright © 2014 American Pain Society. Published by Elsevier Inc. All rights reserved.

Evaluation of Cross-Protocol Stability of a Fully Automated Brain Multi-Atlas Parcellation Tool.

PubMed

Liang, Zifei; He, Xiaohai; Ceritoglu, Can; Tang, Xiaoying; Li, Yue; Kutten, Kwame S; Oishi, Kenichi; Miller, Michael I; Mori, Susumu; Faria, Andreia V

2015-01-01

Brain parcellation tools based on multiple-atlas algorithms have recently emerged as a promising method with which to accurately define brain structures. When dealing with data from various sources, it is crucial that these tools are robust for many different imaging protocols. In this study, we tested the robustness of a multiple-atlas, likelihood fusion algorithm using Alzheimer's Disease Neuroimaging Initiative (ADNI) data with six different protocols, comprising three manufacturers and two magnetic field strengths. The entire brain was parceled into five different levels of granularity. In each level, which defines a set of brain structures, ranging from eight to 286 regions, we evaluated the variability of brain volumes related to the protocol, age, and diagnosis (healthy or Alzheimer's disease). Our results indicated that, with proper pre-processing steps, the impact of different protocols is minor compared to biological effects, such as age and pathology. A precise knowledge of the sources of data variation enables sufficient statistical power and ensures the reliability of an anatomical analysis when using this automated brain parcellation tool on datasets from various imaging protocols, such as clinical databases.

A Functional Cartography of Cognitive Systems

PubMed Central

Mattar, Marcelo G.; Cole, Michael W.; Thompson-Schill, Sharon L.; Bassett, Danielle S.

2015-01-01

One of the most remarkable features of the human brain is its ability to adapt rapidly and efficiently to external task demands. Novel and non-routine tasks, for example, are implemented faster than structural connections can be formed. The neural underpinnings of these dynamics are far from understood. Here we develop and apply novel methods in network science to quantify how patterns of functional connectivity between brain regions reconfigure as human subjects perform 64 different tasks. By applying dynamic community detection algorithms, we identify groups of brain regions that form putative functional communities, and we uncover changes in these groups across the 64-task battery. We summarize these reconfiguration patterns by quantifying the probability that two brain regions engage in the same network community (or putative functional module) across tasks. These tools enable us to demonstrate that classically defined cognitive systems—including visual, sensorimotor, auditory, default mode, fronto-parietal, cingulo-opercular and salience systems—engage dynamically in cohesive network communities across tasks. We define the network role that a cognitive system plays in these dynamics along the following two dimensions: (i) stability vs. flexibility and (ii) connected vs. isolated. The role of each system is therefore summarized by how stably that system is recruited over the 64 tasks, and how consistently that system interacts with other systems. Using this cartography, classically defined cognitive systems can be categorized as ephemeral integrators, stable loners, and anything in between. Our results provide a new conceptual framework for understanding the dynamic integration and recruitment of cognitive systems in enabling behavioral adaptability across both task and rest conditions. This work has important implications for understanding cognitive network reconfiguration during different task sets and its relationship to cognitive effort, individual variation in cognitive performance, and fatigue. PMID:26629847

[Franz Joseph Gall and his "talking skulls" established the basis of modern brain sciences].

PubMed

Wolfgang, Regal; Michael, Nanut

2008-01-01

The anatomist and brain scientist Franz Joseph Gall (1758-1828) developed the "phrenology" in the early 19(th) century. At this time, his new teachings were more seen as a temporary fashion than science and were discredited. No more than hundred years ago, it was realised that the phrenology established the basis of modern brain sciences. By all means Gall was the first one to combine defined regions of the cerebral cortex with distinct cognitive functions.

Automatic Semantic Segmentation of Brain Gliomas from MRI Images Using a Deep Cascaded Neural Network.

PubMed

Cui, Shaoguo; Mao, Lei; Jiang, Jingfeng; Liu, Chang; Xiong, Shuyu

2018-01-01

Brain tumors can appear anywhere in the brain and have vastly different sizes and morphology. Additionally, these tumors are often diffused and poorly contrasted. Consequently, the segmentation of brain tumor and intratumor subregions using magnetic resonance imaging (MRI) data with minimal human interventions remains a challenging task. In this paper, we present a novel fully automatic segmentation method from MRI data containing in vivo brain gliomas. This approach can not only localize the entire tumor region but can also accurately segment the intratumor structure. The proposed work was based on a cascaded deep learning convolutional neural network consisting of two subnetworks: (1) a tumor localization network (TLN) and (2) an intratumor classification network (ITCN). The TLN, a fully convolutional network (FCN) in conjunction with the transfer learning technology, was used to first process MRI data. The goal of the first subnetwork was to define the tumor region from an MRI slice. Then, the ITCN was used to label the defined tumor region into multiple subregions. Particularly, ITCN exploited a convolutional neural network (CNN) with deeper architecture and smaller kernel. The proposed approach was validated on multimodal brain tumor segmentation (BRATS 2015) datasets, which contain 220 high-grade glioma (HGG) and 54 low-grade glioma (LGG) cases. Dice similarity coefficient (DSC), positive predictive value (PPV), and sensitivity were used as evaluation metrics. Our experimental results indicated that our method could obtain the promising segmentation results and had a faster segmentation speed. More specifically, the proposed method obtained comparable and overall better DSC values (0.89, 0.77, and 0.80) on the combined (HGG + LGG) testing set, as compared to other methods reported in the literature. Additionally, the proposed approach was able to complete a segmentation task at a rate of 1.54 seconds per slice.

Individual Functional ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles

PubMed Central

Li, Kaiming; Guo, Lei; Zhu, Dajiang; Hu, Xintao; Han, Junwei; Liu, Tianming

2013-01-01

Studying connectivities among functional brain regions and the functional dynamics on brain networks has drawn increasing interest. A fundamental issue that affects functional connectivity and dynamics studies is how to determine the best possible functional brain regions or ROIs (regions of interest) for a group of individuals, since the connectivity measurements are heavily dependent on ROI locations. Essentially, identification of accurate, reliable and consistent corresponding ROIs is challenging due to the unclear boundaries between brain regions, variability across individuals, and nonlinearity of the ROIs. In response to these challenges, this paper presents a novel methodology to computationally optimize ROIs locations derived from task-based fMRI data for individuals so that the optimized ROIs are more consistent, reproducible and predictable across brains. Our computational strategy is to formulate the individual ROI location optimization as a group variance minimization problem, in which group-wise consistencies in functional/structural connectivity patterns and anatomic profiles are defined as optimization constraints. Our experimental results from multimodal fMRI and DTI data show that the optimized ROIs have significantly improved consistency in structural and functional profiles across individuals. These improved functional ROIs with better consistency could contribute to further study of functional interaction and dynamics in the human brain. PMID:22281931

Support vector machine classification and characterization of age-related reorganization of functional brain networks

PubMed Central

Meier, Timothy B.; Desphande, Alok S.; Vergun, Svyatoslav; Nair, Veena A.; Song, Jie; Biswal, Bharat B.; Meyerand, Mary E.; Birn, Rasmus M.; Prabhakaran, Vivek

2012-01-01

Most of what is known about the reorganization of functional brain networks that accompanies normal aging is based on neuroimaging studies in which participants perform specific tasks. In these studies, reorganization is defined by the differences in task activation between young and old adults. However, task activation differences could be the result of differences in task performance, strategy, or motivation, and not necessarily reflect reorganization. Resting-state fMRI provides a method of investigating functional brain networks without such confounds. Here, a support vector machine (SVM) classifier was used in an attempt to differentiate older adults from younger adults based on their resting-state functional connectivity. In addition, the information used by the SVM was investigated to see what functional connections best differentiated younger adult brains from older adult brains. Three separate resting-state scans from 26 younger adults (18-35 yrs) and 26 older adults (55-85) were obtained from the International Consortium for Brain Mapping (ICBM) dataset made publically available in the 1000 Functional Connectomes project www.nitrc.org/projects/fcon_1000. 100 seed-regions from four functional networks with 5 mm3 radius were defined based on a recent study using machine learning classifiers on adolescent brains. Time-series for every seed-region were averaged and three matrices of z-transformed correlation coefficients were created for each subject corresponding to each individual’s three resting-state scans. SVM was then applied using leave-one-out cross-validation. The SVM classifier was 84% accurate in classifying older and younger adult brains. The majority of the connections used by the classifier to distinguish subjects by age came from seed-regions belonging to the sensorimotor and cingulo-opercular networks. These results suggest that age-related decreases in positive correlations within the cingulo-opercular and default networks, and decreases in negative correlations between the default and sensorimotor networks, are the distinguishing characteristics of age-related reorganization. PMID:22227886

Support vector machine classification and characterization of age-related reorganization of functional brain networks.

PubMed

Meier, Timothy B; Desphande, Alok S; Vergun, Svyatoslav; Nair, Veena A; Song, Jie; Biswal, Bharat B; Meyerand, Mary E; Birn, Rasmus M; Prabhakaran, Vivek

2012-03-01

Most of what is known about the reorganization of functional brain networks that accompanies normal aging is based on neuroimaging studies in which participants perform specific tasks. In these studies, reorganization is defined by the differences in task activation between young and old adults. However, task activation differences could be the result of differences in task performance, strategy, or motivation, and not necessarily reflect reorganization. Resting-state fMRI provides a method of investigating functional brain networks without such confounds. Here, a support vector machine (SVM) classifier was used in an attempt to differentiate older adults from younger adults based on their resting-state functional connectivity. In addition, the information used by the SVM was investigated to see what functional connections best differentiated younger adult brains from older adult brains. Three separate resting-state scans from 26 younger adults (18-35 yrs) and 26 older adults (55-85) were obtained from the International Consortium for Brain Mapping (ICBM) dataset made publically available in the 1000 Functional Connectomes project www.nitrc.org/projects/fcon_1000. 100 seed-regions from four functional networks with 5mm(3) radius were defined based on a recent study using machine learning classifiers on adolescent brains. Time-series for every seed-region were averaged and three matrices of z-transformed correlation coefficients were created for each subject corresponding to each individual's three resting-state scans. SVM was then applied using leave-one-out cross-validation. The SVM classifier was 84% accurate in classifying older and younger adult brains. The majority of the connections used by the classifier to distinguish subjects by age came from seed-regions belonging to the sensorimotor and cingulo-opercular networks. These results suggest that age-related decreases in positive correlations within the cingulo-opercular and default networks, and decreases in negative correlations between the default and sensorimotor networks, are the distinguishing characteristics of age-related reorganization. Copyright © 2011 Elsevier Inc. All rights reserved.

A multi-atlas based method for automated anatomical Macaca fascicularis brain MRI segmentation and PET kinetic extraction.

PubMed

Ballanger, Bénédicte; Tremblay, Léon; Sgambato-Faure, Véronique; Beaudoin-Gobert, Maude; Lavenne, Franck; Le Bars, Didier; Costes, Nicolas

2013-08-15

MRI templates and digital atlases are needed for automated and reproducible quantitative analysis of non-human primate PET studies. Segmenting brain images via multiple atlases outperforms single-atlas labelling in humans. We present a set of atlases manually delineated on brain MRI scans of the monkey Macaca fascicularis. We use this multi-atlas dataset to evaluate two automated methods in terms of accuracy, robustness and reliability in segmenting brain structures on MRI and extracting regional PET measures. Twelve individual Macaca fascicularis high-resolution 3DT1 MR images were acquired. Four individual atlases were created by manually drawing 42 anatomical structures, including cortical and sub-cortical structures, white matter regions, and ventricles. To create the MRI template, we first chose one MRI to define a reference space, and then performed a two-step iterative procedure: affine registration of individual MRIs to the reference MRI, followed by averaging of the twelve resampled MRIs. Automated segmentation in native space was obtained in two ways: 1) Maximum probability atlases were created by decision fusion of two to four individual atlases in the reference space, and transformation back into the individual native space (MAXPROB)(.) 2) One to four individual atlases were registered directly to the individual native space, and combined by decision fusion (PROPAG). Accuracy was evaluated by computing the Dice similarity index and the volume difference. The robustness and reproducibility of PET regional measurements obtained via automated segmentation was evaluated on four co-registered MRI/PET datasets, which included test-retest data. Dice indices were always over 0.7 and reached maximal values of 0.9 for PROPAG with all four individual atlases. There was no significant mean volume bias. The standard deviation of the bias decreased significantly when increasing the number of individual atlases. MAXPROB performed better when increasing the number of atlases used. When all four atlases were used for the MAXPROB creation, the accuracy of morphometric segmentation approached that of the PROPAG method. PET measures extracted either via automatic methods or via the manually defined regions were strongly correlated, with no significant regional differences between methods. Intra-class correlation coefficients for test-retest data were over 0.87. Compared to single atlas extractions, multi-atlas methods improve the accuracy of region definition. They also perform comparably to manually defined regions for PET quantification. Multiple atlases of Macaca fascicularis brains are now available and allow reproducible and simplified analyses. Copyright © 2013 Elsevier Inc. All rights reserved.

Region-specific protein misfolding cyclic amplification reproduces brain tropism of prion strains.

PubMed

Privat, Nicolas; Levavasseur, Etienne; Yildirim, Serfildan; Hannaoui, Samia; Brandel, Jean-Philippe; Laplanche, Jean-Louis; Béringue, Vincent; Seilhean, Danielle; Haïk, Stéphane

2017-10-06

Human prion diseases such as Creutzfeldt-Jakob disease are transmissible brain proteinopathies, characterized by the accumulation of a misfolded isoform of the host cellular prion protein (PrP) in the brain. According to the prion model, prions are defined as proteinaceous infectious particles composed solely of this abnormal isoform of PrP (PrP Sc ). Even in the absence of genetic material, various prion strains can be propagated in experimental models. They can be distinguished by the pattern of disease they produce and especially by the localization of PrP Sc deposits within the brain and the spongiform lesions they induce. The mechanisms involved in this strain-specific targeting of distinct brain regions still are a fundamental, unresolved question in prion research. To address this question, we exploited a prion conversion in vitro assay, protein misfolding cyclic amplification (PMCA), by using experimental scrapie and human prion strains as seeds and specific brain regions from mice and humans as substrates. We show here that region-specific PMCA in part reproduces the specific brain targeting observed in experimental, acquired, and sporadic Creutzfeldt-Jakob diseases. Furthermore, we provide evidence that, in addition to cellular prion protein, other region- and species-specific molecular factors influence the strain-dependent prion conversion process. This important step toward understanding prion strain propagation in the human brain may impact research on the molecular factors involved in protein misfolding and the development of ultrasensitive methods for diagnosing prion disease. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Regional and stage-specific effects of prospectively purified vascular cells on the adult V-SVZ neural stem cell lineage.

PubMed

Crouch, Elizabeth E; Liu, Chang; Silva-Vargas, Violeta; Doetsch, Fiona

2015-03-18

Adult neural stem cells reside in specialized niches. In the ventricular-subventricular zone (V-SVZ), quiescent neural stem cells (qNSCs) become activated (aNSCs), and generate transit amplifying cells (TACs), which give rise to neuroblasts that migrate to the olfactory bulb. The vasculature is an important component of the adult neural stem cell niche, but whether vascular cells in neurogenic areas are intrinsically different from those elsewhere in the brain is unknown. Moreover, the contribution of pericytes to the neural stem cell niche has not been defined. Here, we describe a rapid FACS purification strategy to simultaneously isolate primary endothelial cells and pericytes from brain microregions of nontransgenic mice using CD31 and CD13 as surface markers. We compared the effect of purified vascular cells from a neurogenic (V-SVZ) and non-neurogenic brain region (cortex) on the V-SVZ stem cell lineage in vitro. Endothelial and pericyte diffusible signals from both regions differentially promote the proliferation and neuronal differentiation of qNSCs, aNSCs, and TACs. Unexpectedly, diffusible cortical signals had the most potent effects on V-SVZ proliferation and neurogenesis, highlighting the intrinsic capacity of non-neurogenic vasculature to support stem cell behavior. Finally, we identify PlGF-2 as an endothelial-derived mitogen that promotes V-SVZ cell proliferation. This purification strategy provides a platform to define the functional and molecular contribution of vascular cells to stem cell niches and other brain regions under different physiological and pathological states. Copyright © 2015 the authors 0270-6474/15/354528-12$15.00/0.

A quantitative magnetic resonance histology atlas of postnatal rat brain development with regional estimates of growth and variability.

PubMed

Calabrese, Evan; Badea, Alexandra; Watson, Charles; Johnson, G Allan

2013-05-01

There has been growing interest in the role of postnatal brain development in the etiology of several neurologic diseases. The rat has long been recognized as a powerful model system for studying neuropathology and the safety of pharmacologic treatments. However, the complex spatiotemporal changes that occur during rat neurodevelopment remain to be elucidated. This work establishes the first magnetic resonance histology (MRH) atlas of the developing rat brain, with an emphasis on quantitation. The atlas comprises five specimens at each of nine time points, imaged with eight distinct MR contrasts and segmented into 26 developmentally defined brain regions. The atlas was used to establish a timeline of morphometric changes and variability throughout neurodevelopment and represents a quantitative database of rat neurodevelopment for characterizing rat models of human neurologic disease. Published by Elsevier Inc.

Evaluation of software tools for automated identification of neuroanatomical structures in quantitative β-amyloid PET imaging to diagnose Alzheimer's disease.

PubMed

Tuszynski, Tobias; Rullmann, Michael; Luthardt, Julia; Butzke, Daniel; Tiepolt, Solveig; Gertz, Hermann-Josef; Hesse, Swen; Seese, Anita; Lobsien, Donald; Sabri, Osama; Barthel, Henryk

2016-06-01

For regional quantification of nuclear brain imaging data, defining volumes of interest (VOIs) by hand is still the gold standard. As this procedure is time-consuming and operator-dependent, a variety of software tools for automated identification of neuroanatomical structures were developed. As the quality and performance of those tools are poorly investigated so far in analyzing amyloid PET data, we compared in this project four algorithms for automated VOI definition (HERMES Brass, two PMOD approaches, and FreeSurfer) against the conventional method. We systematically analyzed florbetaben brain PET and MRI data of ten patients with probable Alzheimer's dementia (AD) and ten age-matched healthy controls (HCs) collected in a previous clinical study. VOIs were manually defined on the data as well as through the four automated workflows. Standardized uptake value ratios (SUVRs) with the cerebellar cortex as a reference region were obtained for each VOI. SUVR comparisons between ADs and HCs were carried out using Mann-Whitney-U tests, and effect sizes (Cohen's d) were calculated. SUVRs of automatically generated VOIs were correlated with SUVRs of conventionally derived VOIs (Pearson's tests). The composite neocortex SUVRs obtained by manually defined VOIs were significantly higher for ADs vs. HCs (p=0.010, d=1.53). This was also the case for the four tested automated approaches which achieved effect sizes of d=1.38 to d=1.62. SUVRs of automatically generated VOIs correlated significantly with those of the hand-drawn VOIs in a number of brain regions, with regional differences in the degree of these correlations. Best overall correlation was observed in the lateral temporal VOI for all tested software tools (r=0.82 to r=0.95, p<0.001). Automated VOI definition by the software tools tested has a great potential to substitute for the current standard procedure to manually define VOIs in β-amyloid PET data analysis.

Age-related differences in regional brain volumes: A comparison of optimized voxel-based morphometry to manual volumetry

PubMed Central

Kennedy, Kristen M.; Erickson, Kirk I.; Rodrigue, Karen M.; Voss, Michelle W.; Colcombe, Stan J.; Kramer, Arthur F.; Acker, James D.; Raz, Naftali

2009-01-01

Regional manual volumetry is the gold standard of in vivo neuroanatomy, but is labor-intensive, can be imperfectly reliable, and allows for measuring limited number of regions. Voxel-based morphometry (VBM) has perfect repeatability and assesses local structure across the whole brain. However, its anatomic validity is unclear, and with its increasing popularity, a systematic comparison of VBM to manual volumetry is necessary. The few existing comparison studies are limited by small samples, qualitative comparisons, and limited selection and modest reliability of manual measures. Our goal was to overcome those limitations by quantitatively comparing optimized VBM findings with highly reliable multiple regional measures in a large sample (N = 200) across a wide agespan (18–81). We report a complex pattern of similarities and differences. Peak values of VBM volume estimates (modulated density) produced stronger age differences and a different spatial distribution from manual measures. However, when we aggregated VBM-derived information across voxels contained in specific anatomically defined regions (masks), the patterns of age differences became more similar, although important discrepancies emerged. Notably, VBM revealed stronger age differences in the regions bordering CSF and white matter areas prone to leukoaraiosis, and VBM was more likely to report nonlinearities in age-volume relationships. In the white matter regions, manual measures showed stronger negative associations with age than the corresponding VBM-based masks. We conclude that VBM provides realistic estimates of age differences in the regional gray matter only when applied to anatomically defined regions, but overestimates effects when individual peaks are interpreted. It may be beneficial to use VBM as a first-pass strategy, followed by manual measurement of anatomically-defined regions. PMID:18276037

Markers of oxidative damage to lipids, nucleic acids and proteins and antioxidant enzymes activities in Alzheimer's disease brain: A meta-analysis in human pathological specimens.

PubMed

Zabel, Matthew; Nackenoff, Alex; Kirsch, Wolff M; Harrison, Fiona E; Perry, George; Schrag, Matthew

2018-02-01

Oxidative stress and decreased cellular responsiveness to oxidative stress are thought to influence brain aging and Alzheimer's disease, but the specific patterns of oxidative damage and the underlying mechanism leading to this damage are not definitively known. The objective of this study was to define the pattern of changes in oxidative-stress related markers by brain region in human Alzheimer's disease and mild cognitive impairment brain tissue. Observational case-control studies were identified from systematic queries of PubMed, ISI Web of Science and Scopus databases and studies were evaluated with appropriate quality measures. The data was used to construct a region-by-region meta-analysis of malondialdehyde, 4-hydroxynonenal, protein carbonylation, 8-hydroxyguanine levels and superoxide dismutase, glutathione peroxidase, glutathione reductase and catalase activities. We also evaluated ascorbic acid, tocopherol, uric acid and glutathione levels. The analysis was complicated in several cases by publication bias and/or outlier data. We found that malondialdehyde levels were slightly increased in the temporal and occipital lobes and hippocampus, but this analysis was significantly impacted by publication bias. 4-hydroxynonenal levels were unchanged in every brain region. There was no change in 8-hydroxyguanine level in any brain region and protein carbonylation levels were unchanged except for a slight increase in the occipital lobe. Superoxide dismutase, glutathione peroxidase and reductase and catalase activities were not decreased in any brain region. There was limited data reporting non-enzymatic antioxidant levels in Alzheimer's disease brain, although glutathione and tocopherol levels appear to be unchanged. Minimal quantitative data is available from brain tissue from patients with mild cognitive impairment. While there is modest evidence supporting minor regional changes in markers of oxidative damage, this analysis fails to identify a consistent pattern of pro-oxidative changes and accumulation of oxidative damage in bulk tissue analysis in the setting of Alzheimer's disease, as has been widely reported. Copyright © 2017 Elsevier Inc. All rights reserved.

Dynamic Repertoire of Intrinsic Brain States Is Reduced in Propofol-Induced Unconsciousness

PubMed Central

Liu, Xiping; Pillay, Siveshigan

2015-01-01

Abstract The richness of conscious experience is thought to scale with the size of the repertoire of causal brain states, and it may be diminished in anesthesia. We estimated the state repertoire from dynamic analysis of intrinsic functional brain networks in conscious sedated and unconscious anesthetized rats. Functional resonance images were obtained from 30-min whole-brain resting-state blood oxygen level-dependent (BOLD) signals at propofol infusion rates of 20 and 40 mg/kg/h, intravenously. Dynamic brain networks were defined at the voxel level by sliding window analysis of regional homogeneity (ReHo) or coincident threshold crossings (CTC) of the BOLD signal acquired in nine sagittal slices. The state repertoire was characterized by the temporal variance of the number of voxels with significant ReHo or positive CTC. From low to high propofol dose, the temporal variances of ReHo and CTC were reduced by 78%±20% and 76%±20%, respectively. Both baseline and propofol-induced reduction of CTC temporal variance increased from lateral to medial position. Group analysis showed a 20% reduction in the number of unique states at the higher propofol dose. Analysis of temporal variance in 12 anatomically defined regions of interest predicted that the largest changes occurred in visual cortex, parietal cortex, and caudate-putamen. The results suggest that the repertoire of large-scale brain states derived from the spatiotemporal dynamics of intrinsic networks is substantially reduced at an anesthetic dose associated with loss of consciousness. PMID:24702200

Quantitative autoradiographic mapping of herpes simplex virus encephalitis with a radiolabeled antiviral drug

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saito, Y.; Price, R.W.; Rottenberg, D.A.

1982-09-17

2'-Fluoro-5-methyl-1-..beta..-D-arabinosyluracil (FMAU) labeled with carbon-14 was used to image herpes simplex virus type 1-infected regions of rat brain by quantitative autoradiography. FMAU is a potent antiviral pyrimidine nucleoside which is selectively phosphorylated by virus-coded thymidine kinase. When the labeled FMAU was administered 6 hours before the rats were killed, the selective uptake and concentration of the drug and its metabolites by infected cells (defined by immunoperoxidase staining of viral antigens) allowed quantitative definition and mapping of HSV-1-infected structures in autoradiograms of brain sections. These results shown that quantitative autoradiography can be used to characterize the local metabolism of antiviral drugsmore » by infected cells in vivo. They also suggest that the selective uptake of drugs that exploit viral thymidine kinase for their antiviral effect can, by appropriate labeling, be used in conjunction with clinical neuroimaging techniques to define infected regions of human brain, thereby providing a new approach to the diagnosis of herpes encephalitis in man.« less

Measuring Brain Connectivity: Diffusion Tensor Imaging Validates Resting State Temporal Correlations

PubMed Central

Skudlarski, Pawel; Jagannathan, Kanchana; Calhoun, Vince D.; Hampson, Michelle; Skudlarska, Beata A.; Pearlson, Godfrey

2015-01-01

Diffusion tensor imaging (DTI) and resting state temporal correlations (RSTC) are two leading techniques for investigating the connectivity of the human brain. They have been widely used to investigate the strength of anatomical and functional connections between distant brain regions in healthy subjects, and in clinical populations. Though they are both based on magnetic resonance imaging (MRI) they have not yet been compared directly. In this work both techniques were employed to create global connectivity matrices covering the whole brain gray matter. This allowed for direct comparisons between functional connectivity measured by RSTC with anatomical connectivity quantified using DTI tractography. We found that connectivity matrices obtained using both techniques showed significant agreement. Connectivity maps created for a priori defined anatomical regions showed significant correlation, and furthermore agreement was especially high in regions showing strong overall connectivity, such as those belonging to the default mode network. Direct comparison between functional RSTC and anatomical DTI connectivity, presented here for the first time, links two powerful approaches for investigating brain connectivity and shows their strong agreement. It provides a crucial multi-modal validation for resting state correlations as representing neuronal connectivity. The combination of both techniques presented here allows for further combining them to provide richer representation of brain connectivity both in the healthy brain and in clinical conditions. PMID:18771736

Measuring brain connectivity: diffusion tensor imaging validates resting state temporal correlations.

PubMed

Skudlarski, Pawel; Jagannathan, Kanchana; Calhoun, Vince D; Hampson, Michelle; Skudlarska, Beata A; Pearlson, Godfrey

2008-11-15

Diffusion tensor imaging (DTI) and resting state temporal correlations (RSTC) are two leading techniques for investigating the connectivity of the human brain. They have been widely used to investigate the strength of anatomical and functional connections between distant brain regions in healthy subjects, and in clinical populations. Though they are both based on magnetic resonance imaging (MRI) they have not yet been compared directly. In this work both techniques were employed to create global connectivity matrices covering the whole brain gray matter. This allowed for direct comparisons between functional connectivity measured by RSTC with anatomical connectivity quantified using DTI tractography. We found that connectivity matrices obtained using both techniques showed significant agreement. Connectivity maps created for a priori defined anatomical regions showed significant correlation, and furthermore agreement was especially high in regions showing strong overall connectivity, such as those belonging to the default mode network. Direct comparison between functional RSTC and anatomical DTI connectivity, presented here for the first time, links two powerful approaches for investigating brain connectivity and shows their strong agreement. It provides a crucial multi-modal validation for resting state correlations as representing neuronal connectivity. The combination of both techniques presented here allows for further combining them to provide richer representation of brain connectivity both in the healthy brain and in clinical conditions.

Neuroanatomical Correlates of Intelligence

PubMed Central

Luders, Eileen; Narr, Katherine L.; Thompson, Paul M.; Toga, Arthur W.

2009-01-01

With the advancement of image acquisition and analysis methods in recent decades, unique opportunities have emerged to study the neuroanatomical correlates of intelligence. Traditional approaches examining global measures have been complemented by insights from more regional analyses based on pre-defined areas. Newer state-of-the-art approaches have further enhanced our ability to localize the presence of correlations between cerebral characteristics and intelligence with high anatomic precision. These in vivo assessments have confirmed mainly positive correlations, suggesting that optimally increased brain regions are associated with better cognitive performance. Findings further suggest that the models proposed to explain the anatomical substrates of intelligence should address contributions from not only (pre)frontal regions, but also widely distributed networks throughout the whole brain. PMID:20160919

Diagnostic imaging of herpes simplex virus encephalitis using a radiolabeled antiviral drug: autoradiographic assessment in an animal model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saito, Y.; Rubenstein, R.; Price, R.W.

1984-06-01

To develop a new approach to the diagnosis of herpes simplex encephalitis, we used a radiolabeled antiviral drug, 2'-fluoro-5-methyl-1-beta-D-arabinosyluracil labeled with carbon 14 ((14C)FMAU), as a probe for selectively imaging brain infection in a rat model by quantitative autoradiography. A high correlation was found between focal infection, as defined by immunoperoxidase viral antigen staining, and increased regional (14C)FMAU uptake in brain sections. Two potential sources of false-positive imaging were defined: high concentrations of drug in the choroid plexus because of its higher permeability compared with brain, and drug sequestration by proliferating uninfected cell populations. Our results support the soundness ofmore » the proposed strategy of using a labeled antiviral drug that is selectively phosphorylated by herpes simplex virus type 1 thymidine kinase in conjunction with scanning methods for human diagnosis, and also define some of the factors that must be taken into account when planning clinical application.« less

A regulatory toolbox of MiniPromoters to drive selective expression in the brain

PubMed Central

Portales-Casamar, Elodie; Swanson, Douglas J.; Liu, Li; de Leeuw, Charles N.; Banks, Kathleen G.; Ho Sui, Shannan J.; Fulton, Debra L.; Ali, Johar; Amirabbasi, Mahsa; Arenillas, David J.; Babyak, Nazar; Black, Sonia F.; Bonaguro, Russell J.; Brauer, Erich; Candido, Tara R.; Castellarin, Mauro; Chen, Jing; Chen, Ying; Cheng, Jason C. Y.; Chopra, Vik; Docking, T. Roderick; Dreolini, Lisa; D'Souza, Cletus A.; Flynn, Erin K.; Glenn, Randy; Hatakka, Kristi; Hearty, Taryn G.; Imanian, Behzad; Jiang, Steven; Khorasan-zadeh, Shadi; Komljenovic, Ivana; Laprise, Stéphanie; Liao, Nancy Y.; Lim, Jonathan S.; Lithwick, Stuart; Liu, Flora; Liu, Jun; Lu, Meifen; McConechy, Melissa; McLeod, Andrea J.; Milisavljevic, Marko; Mis, Jacek; O'Connor, Katie; Palma, Betty; Palmquist, Diana L.; Schmouth, Jean-François; Swanson, Magdalena I.; Tam, Bonny; Ticoll, Amy; Turner, Jenna L.; Varhol, Richard; Vermeulen, Jenny; Watkins, Russell F.; Wilson, Gary; Wong, Bibiana K. Y.; Wong, Siaw H.; Wong, Tony Y. T.; Yang, George S.; Ypsilanti, Athena R.; Jones, Steven J. M.; Holt, Robert A.; Goldowitz, Daniel; Wasserman, Wyeth W.; Simpson, Elizabeth M.

2010-01-01

The Pleiades Promoter Project integrates genomewide bioinformatics with large-scale knockin mouse production and histological examination of expression patterns to develop MiniPromoters and related tools designed to study and treat the brain by directed gene expression. Genes with brain expression patterns of interest are subjected to bioinformatic analysis to delineate candidate regulatory regions, which are then incorporated into a panel of compact human MiniPromoters to drive expression to brain regions and cell types of interest. Using single-copy, homologous-recombination “knockins” in embryonic stem cells, each MiniPromoter reporter is integrated immediately 5′ of the Hprt locus in the mouse genome. MiniPromoter expression profiles are characterized in differentiation assays of the transgenic cells or in mouse brains following transgenic mouse production. Histological examination of adult brains, eyes, and spinal cords for reporter gene activity is coupled to costaining with cell-type–specific markers to define expression. The publicly available Pleiades MiniPromoter Project is a key resource to facilitate research on brain development and therapies. PMID:20807748

Warnings and caveats in brain controllability.

PubMed

Tu, Chengyi; Rocha, Rodrigo P; Corbetta, Maurizio; Zampieri, Sandro; Zorzi, Marco; Suweis, S

2018-08-01

A recent article by Gu et al. (Nat. Commun. 6, 2015) proposed to characterize brain networks, quantified using anatomical diffusion imaging, in terms of their "controllability", drawing on concepts and methods of control theory. They reported that brain activity is controllable from a single node, and that the topology of brain networks provides an explanation for the types of control roles that different regions play in the brain. In this work, we first briefly review the framework of control theory applied to complex networks. We then show contrasting results on brain controllability through the analysis of five different datasets and numerical simulations. We find that brain networks are not controllable (in a statistical significant way) by one single region. Additionally, we show that random null models, with no biological resemblance to brain network architecture, produce the same type of relationship observed by Gu et al. between the average/modal controllability and weighted degree. Finally, we find that resting state networks defined with fMRI cannot be attributed specific control roles. In summary, our study highlights some warning and caveats in the brain controllability framework. Copyright © 2018 Elsevier Inc. All rights reserved.

Acupuncture Modulates Resting State Connectivity in Default and Sensorimotor Brain Networks

PubMed Central

Dhond, Rupali P.; Yeh, Calvin; Park, Kyungmo; Kettner, Norman; Napadow, Vitaly

2008-01-01

Previous studies have defined low-frequency, spatially consistent networks in resting fMRI data which may reflect functional connectivity. We sought to explore how a complex somatosensory stimulation, acupuncture, influences intrinsic connectivity in two of these networks: the default mode network (DMN) and sensorimotor network (SMN). We analyzed resting fMRI data taken before and after verum and sham acupuncture. Electrocardiography data was used to infer autonomic modulation through measures of heart rate variability (HRV). Probabilistic independent component analysis was used to separate resting fMRI data into DMN and SMN components. Following verum, but not sham, acupuncture there was increased DMN connectivity with pain (anterior cingulate cortex (ACC), periaqueductal gray), affective (amygdala, ACC), and memory (hippocampal formation, middle temporal gyrus) related brain regions. Furthermore, increased DMN connectivity with the hippocampal formation, a region known to support memory and interconnected with autonomic brain regions, was negatively correlated with acupuncture-induced increase in a sympathetic related HRV metric (LFu), and positively correlated with a parasympathetic related metric (HFu). Following verum, but not sham, acupuncture there was also increased SMN connectivity with pain related brain regions (ACC, cerebellum). We attribute differences between verum and sham acupuncture to more varied and stronger sensations evoked by verum acupuncture. Our results demonstrate for the first time that acupuncture can enhance the post-stimulation spatial extent of resting brain networks to include anti-nociceptive, memory, and affective brain regions. This modulation and sympathovagal response may relate to acupuncture analgesia and other potential therapeutic effects. PMID:18337009

Defining functional SMA and pre-SMA subregions in human MFC using resting state fMRI: functional connectivity-based parcellation method.

PubMed

Kim, Jae-Hun; Lee, Jong-Min; Jo, Hang Joon; Kim, Sook Hui; Lee, Jung Hee; Kim, Sung Tae; Seo, Sang Won; Cox, Robert W; Na, Duk L; Kim, Sun I; Saad, Ziad S

2010-02-01

Noninvasive parcellation of the human cerebral cortex is an important goal for understanding and examining brain functions. Recently, the patterns of anatomical connections using diffusion tensor imaging (DTI) have been used to parcellate brain regions. Here, we present a noninvasive parcellation approach that uses "functional fingerprints" obtained by correlation measures on resting state functional magnetic resonance imaging (fMRI) data to parcellate brain regions. In other terms, brain regions are parcellated based on the similarity of their connection--as reflected by correlation during resting state--to the whole brain. The proposed method was used to parcellate the medial frontal cortex (MFC) into supplementary motor areas (SMA) and pre-SMA subregions. In agreement with anatomical landmark-based parcellation, we find that functional fingerprint clustering of the MFC results in anterior and posterior clusters. The probabilistic maps from 12 subjects showed that the anterior cluster is mainly located rostral to the vertical commissure anterior (VCA) line, whereas the posterior cluster is mainly located caudal to VCA line, suggesting the homologues of pre-SMA and SMA. The functional connections from the putative pre-SMA cluster were connected to brain regions which are responsible for complex/cognitive motor control, whereas those from the putative SMA cluster were connected to brain regions which are related to the simple motor control. These findings demonstrate the feasibility of the functional connectivity-based parcellation of the human cerebral cortex using resting state fMRI. Copyright (c) 2009 Elsevier Inc. All rights reserved.

The polygenic risk for bipolar disorder influences brain regional function relating to visual and default state processing of emotional information.

PubMed

Dima, Danai; de Jong, Simone; Breen, Gerome; Frangou, Sophia

2016-01-01

Genome-wise association studies have identified a number of common single-nucleotide polymorphisms (SNPs), each of small effect, associated with risk to bipolar disorder (BD). Several risk-conferring SNPs have been individually shown to influence regional brain activation thus linking genetic risk for BD to altered brain function. The current study examined whether the polygenic risk score method, which models the cumulative load of all known risk-conferring SNPs, may be useful in the identification of brain regions whose function may be related to the polygenic architecture of BD. We calculated the individual polygenic risk score for BD (PGR-BD) in forty-one patients with the disorder, twenty-five unaffected first-degree relatives and forty-six unrelated healthy controls using the most recent Psychiatric Genomics Consortium data. Functional magnetic resonance imaging was used to define task-related brain activation patterns in response to facial affect and working memory processing. We found significant effects of the PGR-BD score on task-related activation irrespective of diagnostic group. There was a negative association between the PGR-BD score and activation in the visual association cortex during facial affect processing. In contrast, the PGR-BD score was associated with failure to deactivate the ventromedial prefrontal region of the default mode network during working memory processing. These results are consistent with the threshold-liability model of BD, and demonstrate the usefulness of the PGR-BD score in identifying brain functional alternations associated with vulnerability to BD. Additionally, our findings suggest that the polygenic architecture of BD is not regionally confined but impacts on the task-dependent recruitment of multiple brain regions.

Global Genetic Variations Predict Brain Response to Faces

PubMed Central

Dickie, Erin W.; Tahmasebi, Amir; French, Leon; Kovacevic, Natasa; Banaschewski, Tobias; Barker, Gareth J.; Bokde, Arun; Büchel, Christian; Conrod, Patricia; Flor, Herta; Garavan, Hugh; Gallinat, Juergen; Gowland, Penny; Heinz, Andreas; Ittermann, Bernd; Lawrence, Claire; Mann, Karl; Martinot, Jean-Luc; Nees, Frauke; Nichols, Thomas; Lathrop, Mark; Loth, Eva; Pausova, Zdenka; Rietschel, Marcela; Smolka, Michal N.; Ströhle, Andreas; Toro, Roberto; Schumann, Gunter; Paus, Tomáš

2014-01-01

Face expressions are a rich source of social signals. Here we estimated the proportion of phenotypic variance in the brain response to facial expressions explained by common genetic variance captured by ∼500,000 single nucleotide polymorphisms. Using genomic-relationship-matrix restricted maximum likelihood (GREML), we related this global genetic variance to that in the brain response to facial expressions, as assessed with functional magnetic resonance imaging (fMRI) in a community-based sample of adolescents (n = 1,620). Brain response to facial expressions was measured in 25 regions constituting a face network, as defined previously. In 9 out of these 25 regions, common genetic variance explained a significant proportion of phenotypic variance (40–50%) in their response to ambiguous facial expressions; this was not the case for angry facial expressions. Across the network, the strength of the genotype-phenotype relationship varied as a function of the inter-individual variability in the number of functional connections possessed by a given region (R2 = 0.38, p<0.001). Furthermore, this variability showed an inverted U relationship with both the number of observed connections (R2 = 0.48, p<0.001) and the magnitude of brain response (R2 = 0.32, p<0.001). Thus, a significant proportion of the brain response to facial expressions is predicted by common genetic variance in a subset of regions constituting the face network. These regions show the highest inter-individual variability in the number of connections with other network nodes, suggesting that the genetic model captures variations across the adolescent brains in co-opting these regions into the face network. PMID:25122193

Altered structural connectivity of pain-related brain network in burning mouth syndrome-investigation by graph analysis of probabilistic tractography.

PubMed

Wada, Akihiko; Shizukuishi, Takashi; Kikuta, Junko; Yamada, Haruyasu; Watanabe, Yusuke; Imamura, Yoshiki; Shinozaki, Takahiro; Dezawa, Ko; Haradome, Hiroki; Abe, Osamu

2017-05-01

Burning mouth syndrome (BMS) is a chronic intraoral pain syndrome featuring idiopathic oral pain and burning discomfort despite clinically normal oral mucosa. The etiology of chronic pain syndrome is unclear, but preliminary neuroimaging research has suggested the alteration of volume, metabolism, blood flow, and diffusion at multiple brain regions. According to the neuromatrix theory of Melzack, pain sense is generated in the brain by the network of multiple pain-related brain regions. Therefore, the alteration of pain-related network is also assumed as an etiology of chronic pain. In this study, we investigated the brain network of BMS brain by using probabilistic tractography and graph analysis. Fourteen BMS patients and 14 age-matched healthy controls underwent 1.5T MRI. Structural connectivity was calculated in 83 anatomically defined regions with probabilistic tractography of 60-axis diffusion tensor imaging and 3D T1-weighted imaging. Graph theory network analysis was used to evaluate the brain network at local and global connectivity. In BMS brain, a significant difference of local brain connectivity was recognized at the bilateral rostral anterior cingulate cortex, right medial orbitofrontal cortex, and left pars orbitalis which belong to the medial pain system; however, no significant difference was recognized at the lateral system including the somatic sensory cortex. A strengthened connection of the anterior cingulate cortex and medial prefrontal cortex with the basal ganglia, thalamus, and brain stem was revealed. Structural brain network analysis revealed the alteration of the medial system of the pain-related brain network in chronic pain syndrome.

Structural brain connectivity and cognitive ability differences: A multivariate distance matrix regression analysis.

PubMed

Ponsoda, Vicente; Martínez, Kenia; Pineda-Pardo, José A; Abad, Francisco J; Olea, Julio; Román, Francisco J; Barbey, Aron K; Colom, Roberto

2017-02-01

Neuroimaging research involves analyses of huge amounts of biological data that might or might not be related with cognition. This relationship is usually approached using univariate methods, and, therefore, correction methods are mandatory for reducing false positives. Nevertheless, the probability of false negatives is also increased. Multivariate frameworks have been proposed for helping to alleviate this balance. Here we apply multivariate distance matrix regression for the simultaneous analysis of biological and cognitive data, namely, structural connections among 82 brain regions and several latent factors estimating cognitive performance. We tested whether cognitive differences predict distances among individuals regarding their connectivity pattern. Beginning with 3,321 connections among regions, the 36 edges better predicted by the individuals' cognitive scores were selected. Cognitive scores were related to connectivity distances in both the full (3,321) and reduced (36) connectivity patterns. The selected edges connect regions distributed across the entire brain and the network defined by these edges supports high-order cognitive processes such as (a) (fluid) executive control, (b) (crystallized) recognition, learning, and language processing, and (c) visuospatial processing. This multivariate study suggests that one widespread, but limited number, of regions in the human brain, supports high-level cognitive ability differences. Hum Brain Mapp 38:803-816, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Dynamic relationships between age, amyloid-β deposition, and glucose metabolism link to the regional vulnerability to Alzheimer’s disease

PubMed Central

Madison, Cindee; Baker, Suzanne; Rabinovici, Gil; Jagust, William

2016-01-01

Abstract See Hansson and Gouras (doi:10.1093/aww146) for a scientific commentary on this article. Although some brain regions such as precuneus and lateral temporo-parietal cortex have been shown to be more vulnerable to Alzheimer’s disease than other areas, a mechanism underlying the differential regional vulnerability to Alzheimer’s disease remains to be elucidated. Using fluorodeoxyglucose and Pittsburgh compound B positron emission tomography imaging glucose metabolism and amyloid-β deposition, we tested whether and how life-long changes in glucose metabolism relate to amyloid-β deposition and Alzheimer’s disease-related hypometabolism. Nine healthy young adults (age range: 20–30), 96 cognitively normal older adults (age range: 61–96), and 20 patients with Alzheimer’s disease (age range: 50–90) were scanned using fluorodeoxyglucose and Pittsburgh compound B positron emission tomography. Among cognitively normal older subjects, 32 were further classified as amyloid-positive, with 64 as amyloid-negative. To assess the contribution of glucose metabolism to the regional vulnerability to amyloid-β deposition, we defined the highest and lowest metabolic regions in young adults and examined differences in amyloid deposition between these regions across groups. Two-way analyses of variance were conducted to assess regional differences in age and amyloid-β-related changes in glucose metabolism. Multiple regressions were applied to examine the association between amyloid-β deposition and regional glucose metabolism. Both region of interest and whole-brain voxelwise analyses were conducted to complement and confirm the results derived from the other approach. Regional differences in glucose metabolism between the highest and lowest metabolism regions defined in young adults (T = 12.85, P < 0.001) were maintained both in Pittsburgh compound B-negative cognitively normal older subjects (T = 6.66, P < 0.001) and Pittsburgh compound B-positive cognitively normal older subjects (T = 10.62, P < 0.001), but, only the Pittsburgh compound B-positive cognitively normal older subjects group showed significantly higher Pittsburgh compound B retention in the highest compared to the lowest glucose metabolism regions defined in young adults (T = 2.05, P < 0.05). Regional differences in age and amyloid-β-dependent changes in glucose metabolism were found such that frontal glucose metabolism was reduced with age, while glucose metabolism in the precuneus was maintained across the lifespan (right hemisphere: F = 7.69, P < 0.001; left hemisphere: F = 8.69, P < 0.001). Greater Alzheimer’s disease-related hypometabolism was observed in brain regions that showed both age-invariance and amyloid-β-related increases in glucose metabolism. Our results indicate that although early and life-long regional variation in glucose metabolism relates to the regional vulnerability to amyloid-β accumulation, Alzheimer’s disease-related hypometabolism is more specific to brain regions showing age-invariant glucose metabolism and amyloid-β-related hypermetabolism. PMID:27190008

Typical cerebral metabolic patterns in neurodegenerative brain diseases.

PubMed

Teune, Laura K; Bartels, Anna L; de Jong, Bauke M; Willemsen, Antoon T M; Eshuis, Silvia A; de Vries, Jeroen J; van Oostrom, Joost C H; Leenders, Klaus L

2010-10-30

The differential diagnosis of neurodegenerative brain diseases on clinical grounds is difficult, especially at an early disease stage. Several studies have found specific regional differences of brain metabolism applying [(18)F]-fluoro-deoxyglucose positron emission tomography (FDG-PET), suggesting that this method can assist in early differential diagnosis of neurodegenerative brain diseases.We have studied patients who had an FDG-PET scan on clinical grounds at an early disease stage and included those with a retrospectively confirmed diagnosis according to strictly defined clinical research criteria. Ninety-six patients could be included of which 20 patients with Parkinson's disease (PD), 21 multiple system atrophy (MSA), 17 progressive supranuclear palsy (PSP), 10 corticobasal degeneration (CBD), 6 dementia with Lewy bodies (DLB), 15 Alzheimer's disease (AD), and 7 frontotemporal dementia (FTD). FDG PET images of each patient group were analyzed and compared to18 healthy controls using Statistical Parametric Mapping (SPM5).Disease-specific patterns of relatively decreased metabolic activity were found in PD (contralateral parietooccipital and frontal regions), MSA (bilateral putamen and cerebellar hemispheres), PSP (prefrontal cortex and caudate nucleus, thalamus, and mesencephalon), CBD (contralateral cortical regions), DLB (occipital and parietotemporal regions), AD (parietotemporal regions), and FTD (frontotemporal regions).The integrated method addressing a spectrum of various neurodegenerative brain diseases provided means to discriminate patient groups also at early disease stages. Clinical follow-up enabled appropriate patient inclusion. This implies that an early diagnosis in individual patients can be made by comparing each subject's metabolic findings with a complete database of specific disease related patterns.

Identification of a Functional Connectome for Long-Term Fear Memory in Mice

PubMed Central

Wheeler, Anne L.; Teixeira, Cátia M.; Wang, Afra H.; Xiong, Xuejian; Kovacevic, Natasa; Lerch, Jason P.; McIntosh, Anthony R.; Parkinson, John; Frankland, Paul W.

2013-01-01

Long-term memories are thought to depend upon the coordinated activation of a broad network of cortical and subcortical brain regions. However, the distributed nature of this representation has made it challenging to define the neural elements of the memory trace, and lesion and electrophysiological approaches provide only a narrow window into what is appreciated a much more global network. Here we used a global mapping approach to identify networks of brain regions activated following recall of long-term fear memories in mice. Analysis of Fos expression across 84 brain regions allowed us to identify regions that were co-active following memory recall. These analyses revealed that the functional organization of long-term fear memories depends on memory age and is altered in mutant mice that exhibit premature forgetting. Most importantly, these analyses indicate that long-term memory recall engages a network that has a distinct thalamic-hippocampal-cortical signature. This network is concurrently integrated and segregated and therefore has small-world properties, and contains hub-like regions in the prefrontal cortex and thalamus that may play privileged roles in memory expression. PMID:23300432

Distributed affective space represents multiple emotion categories across the human brain

PubMed Central

Saarimäki, Heini; Ejtehadian, Lara Farzaneh; Jääskeläinen, Iiro P; Vuilleumier, Patrik; Sams, Mikko; Nummenmaa, Lauri

2018-01-01

Abstract The functional organization of human emotion systems as well as their neuroanatomical basis and segregation in the brain remains unresolved. Here, we used pattern classification and hierarchical clustering to characterize the organization of a wide array of emotion categories in the human brain. We induced 14 emotions (6 ‘basic’, e.g. fear and anger; and 8 ‘non-basic’, e.g. shame and gratitude) and a neutral state using guided mental imagery while participants' brain activity was measured with functional magnetic resonance imaging (fMRI). Twelve out of 14 emotions could be reliably classified from the haemodynamic signals. All emotions engaged a multitude of brain areas, primarily in midline cortices including anterior and posterior cingulate gyri and precuneus, in subcortical regions, and in motor regions including cerebellum and premotor cortex. Similarity of subjective emotional experiences was associated with similarity of the corresponding neural activation patterns. We conclude that different basic and non-basic emotions have distinguishable neural bases characterized by specific, distributed activation patterns in widespread cortical and subcortical circuits. Regionally differentiated engagement of these circuits defines the unique neural activity pattern and the corresponding subjective feeling associated with each emotion. PMID:29618125

Molecular profiling of the developing avian telencephalon: regional timing and brain subdivision continuities.

PubMed

Chen, Chun-Chun; Winkler, Candace M; Pfenning, Andreas R; Jarvis, Erich D

2013-11-01

In our companion study (Jarvis et al. [2013] J Comp Neurol. doi: 10.1002/cne.23404) we used quantitative brain molecular profiling to discover that distinct subdivisions in the avian pallium above and below the ventricle and the associated mesopallium lamina have similar molecular profiles, leading to a hypothesis that they may form as continuous subdivisions around the lateral ventricle. To explore this hypothesis, here we profiled the expression of 16 genes at eight developmental stages. The genes included those that define brain subdivisions in the adult and some that are also involved in brain development. We found that phyletic hierarchical cluster and linear regression network analyses of gene expression profiles implicated single and mixed ancestry of these brain regions at early embryonic stages. Most gene expression-defined pallial subdivisions began as one ventral or dorsal domain that later formed specific folds around the lateral ventricle. Subsequently a clear ventricle boundary formed, partitioning them into dorsal and ventral pallial subdivisions surrounding the mesopallium lamina. These subdivisions each included two parts of the mesopallium, the nidopallium and hyperpallium, and the arcopallium and hippocampus, respectively. Each subdivision expression profile had a different temporal order of appearance, similar in timing to the order of analogous cell types of the mammalian cortex. Furthermore, like the mammalian pallium, expression in the ventral pallial subdivisions became distinct during prehatch development, whereas the dorsal portions did so during posthatch development. These findings support the continuum hypothesis of avian brain subdivision development around the ventricle and influence hypotheses on homologies of the avian pallium with other vertebrates. Copyright © 2013 Wiley Periodicals, Inc.

A New MRI Masking Technique Based on Multi-Atlas Brain Segmentation in Controls and Schizophrenia: A Rapid and Viable Alternative to Manual Masking.

PubMed

Del Re, Elisabetta C; Gao, Yi; Eckbo, Ryan; Petryshen, Tracey L; Blokland, Gabriëlla A M; Seidman, Larry J; Konishi, Jun; Goldstein, Jill M; McCarley, Robert W; Shenton, Martha E; Bouix, Sylvain

2016-01-01

Brain masking of MRI images separates brain from surrounding tissue and its accuracy is important for further imaging analyses. We implemented a new brain masking technique based on multi-atlas brain segmentation (MABS) and compared MABS to masks generated using FreeSurfer (FS; version 5.3), Brain Extraction Tool (BET), and Brainwash, using manually defined masks (MM) as the gold standard. We further determined the effect of different masking techniques on cortical and subcortical volumes generated by FreeSurfer. Images were acquired on a 3-Tesla MR Echospeed system General Electric scanner on five control and five schizophrenia subjects matched on age, sex, and IQ. Automated masks were generated from MABS, FS, BET, and Brainwash, and compared to MM using these metrics: a) volume difference from MM; b) Dice coefficients; and c) intraclass correlation coefficients. Mean volume difference between MM and MABS masks was significantly less than the difference between MM and FS or BET masks. Dice coefficient between MM and MABS was significantly higher than Dice coefficients between MM and FS, BET, or Brainwash. For subcortical and left cortical regions, MABS volumes were closer to MM volumes than were BET or FS volumes. For right cortical regions, MABS volumes were closer to MM volumes than were BET volumes. Brain masks generated using FreeSurfer, BET, and Brainwash are rapidly obtained, but are less accurate than manually defined masks. Masks generated using MABS, in contrast, resemble more closely the gold standard of manual masking, thereby offering a rapid and viable alternative. Copyright © 2015 by the American Society of Neuroimaging.

Functional divisions for visual processing in the central brain of flying Drosophila

PubMed Central

Weir, Peter T.; Dickinson, Michael H.

2015-01-01

Although anatomy is often the first step in assigning functions to neural structures, it is not always clear whether architecturally distinct regions of the brain correspond to operational units. Whereas neuroarchitecture remains relatively static, functional connectivity may change almost instantaneously according to behavioral context. We imaged panneuronal responses to visual stimuli in a highly conserved central brain region in the fruit fly, Drosophila, during flight. In one substructure, the fan-shaped body, automated analysis revealed three layers that were unresponsive in quiescent flies but became responsive to visual stimuli when the animal was flying. The responses of these regions to a broad suite of visual stimuli suggest that they are involved in the regulation of flight heading. To identify the cell types that underlie these responses, we imaged activity in sets of genetically defined neurons with arborizations in the targeted layers. The responses of this collection during flight also segregated into three sets, confirming the existence of three layers, and they collectively accounted for the panneuronal activity. Our results provide an atlas of flight-gated visual responses in a central brain circuit. PMID:26324910

Functional divisions for visual processing in the central brain of flying Drosophila.

PubMed

Weir, Peter T; Dickinson, Michael H

2015-10-06

Although anatomy is often the first step in assigning functions to neural structures, it is not always clear whether architecturally distinct regions of the brain correspond to operational units. Whereas neuroarchitecture remains relatively static, functional connectivity may change almost instantaneously according to behavioral context. We imaged panneuronal responses to visual stimuli in a highly conserved central brain region in the fruit fly, Drosophila, during flight. In one substructure, the fan-shaped body, automated analysis revealed three layers that were unresponsive in quiescent flies but became responsive to visual stimuli when the animal was flying. The responses of these regions to a broad suite of visual stimuli suggest that they are involved in the regulation of flight heading. To identify the cell types that underlie these responses, we imaged activity in sets of genetically defined neurons with arborizations in the targeted layers. The responses of this collection during flight also segregated into three sets, confirming the existence of three layers, and they collectively accounted for the panneuronal activity. Our results provide an atlas of flight-gated visual responses in a central brain circuit.

Probabilistic atlases of default mode, executive control and salience network white matter tracts: an fMRI-guided diffusion tensor imaging and tractography study

PubMed Central

Figley, Teresa D.; Bhullar, Navdeep; Courtney, Susan M.; Figley, Chase R.

2015-01-01

Diffusion tensor imaging (DTI) is a powerful MRI technique that can be used to estimate both the microstructural integrity and the trajectories of white matter pathways throughout the central nervous system. This fiber tracking (aka, “tractography”) approach is often carried out using anatomically-defined seed points to identify white matter tracts that pass through one or more structures, but can also be performed using functionally-defined regions of interest (ROIs) that have been determined using functional MRI (fMRI) or other methods. In this study, we performed fMRI-guided DTI tractography between all of the previously defined nodes within each of six common resting-state brain networks, including the: dorsal Default Mode Network (dDMN), ventral Default Mode Network (vDMN), left Executive Control Network (lECN), right Executive Control Network (rECN), anterior Salience Network (aSN), and posterior Salience Network (pSN). By normalizing the data from 32 healthy control subjects to a standard template—using high-dimensional, non-linear warping methods—we were able to create probabilistic white matter atlases for each tract in stereotaxic coordinates. By investigating all 198 ROI-to-ROI combinations within the aforementioned resting-state networks (for a total of 6336 independent DTI tractography analyses), the resulting probabilistic atlases represent a comprehensive cohort of functionally-defined white matter regions that can be used in future brain imaging studies to: (1) ascribe DTI or other white matter changes to particular functional brain networks, and (2) compliment resting state fMRI or other functional connectivity analyses. PMID:26578930

Localization of PPAR isotypes in the adult mouse and human brain

PubMed Central

Warden, Anna; Truitt, Jay; Merriman, Morgan; Ponomareva, Olga; Jameson, Kelly; Ferguson, Laura B.; Mayfield, R. Dayne; Harris, R. Adron

2016-01-01

Peroxisome proliferator-activated receptors (PPARs) are nuclear hormone receptors that act as ligand-activated transcription factors. PPAR agonists have well-documented anti-inflammatory and neuroprotective roles in the central nervous system. Recent evidence suggests that PPAR agonists are attractive therapeutic agents for treating neurodegenerative diseases as well as addiction. However, the distribution of PPAR mRNA and protein in brain regions associated with these conditions (i.e. prefrontal cortex, nucleus accumbens, amygdala, ventral tegmental area) is not well defined. Moreover, the cell type specificity of PPARs in mouse and human brain tissue has yet to be investigated. We utilized quantitative PCR and double immunofluorescence microscopy to determine that both PPAR mRNA and protein are expressed ubiquitously throughout the adult mouse brain. We found that PPARs have unique cell type specificities that are consistent between species. PPARα was the only isotype to colocalize with all cell types in both adult mouse and adult human brain tissue. Overall, we observed a strong neuronal signature, which raises the possibility that PPAR agonists may be targeting neurons rather than glia to produce neuroprotection. Our results fill critical gaps in PPAR distribution and define novel cell type specificity profiles in the adult mouse and human brain. PMID:27283430

Localization of PPAR isotypes in the adult mouse and human brain.

PubMed

Warden, Anna; Truitt, Jay; Merriman, Morgan; Ponomareva, Olga; Jameson, Kelly; Ferguson, Laura B; Mayfield, R Dayne; Harris, R Adron

2016-06-10

Peroxisome proliferator-activated receptors (PPARs) are nuclear hormone receptors that act as ligand-activated transcription factors. PPAR agonists have well-documented anti-inflammatory and neuroprotective roles in the central nervous system. Recent evidence suggests that PPAR agonists are attractive therapeutic agents for treating neurodegenerative diseases as well as addiction. However, the distribution of PPAR mRNA and protein in brain regions associated with these conditions (i.e. prefrontal cortex, nucleus accumbens, amygdala, ventral tegmental area) is not well defined. Moreover, the cell type specificity of PPARs in mouse and human brain tissue has yet to be investigated. We utilized quantitative PCR and double immunofluorescence microscopy to determine that both PPAR mRNA and protein are expressed ubiquitously throughout the adult mouse brain. We found that PPARs have unique cell type specificities that are consistent between species. PPARα was the only isotype to colocalize with all cell types in both adult mouse and adult human brain tissue. Overall, we observed a strong neuronal signature, which raises the possibility that PPAR agonists may be targeting neurons rather than glia to produce neuroprotection. Our results fill critical gaps in PPAR distribution and define novel cell type specificity profiles in the adult mouse and human brain.

Automatic Semantic Segmentation of Brain Gliomas from MRI Images Using a Deep Cascaded Neural Network

PubMed Central

Mao, Lei; Liu, Chang; Xiong, Shuyu

2018-01-01

Brain tumors can appear anywhere in the brain and have vastly different sizes and morphology. Additionally, these tumors are often diffused and poorly contrasted. Consequently, the segmentation of brain tumor and intratumor subregions using magnetic resonance imaging (MRI) data with minimal human interventions remains a challenging task. In this paper, we present a novel fully automatic segmentation method from MRI data containing in vivo brain gliomas. This approach can not only localize the entire tumor region but can also accurately segment the intratumor structure. The proposed work was based on a cascaded deep learning convolutional neural network consisting of two subnetworks: (1) a tumor localization network (TLN) and (2) an intratumor classification network (ITCN). The TLN, a fully convolutional network (FCN) in conjunction with the transfer learning technology, was used to first process MRI data. The goal of the first subnetwork was to define the tumor region from an MRI slice. Then, the ITCN was used to label the defined tumor region into multiple subregions. Particularly, ITCN exploited a convolutional neural network (CNN) with deeper architecture and smaller kernel. The proposed approach was validated on multimodal brain tumor segmentation (BRATS 2015) datasets, which contain 220 high-grade glioma (HGG) and 54 low-grade glioma (LGG) cases. Dice similarity coefficient (DSC), positive predictive value (PPV), and sensitivity were used as evaluation metrics. Our experimental results indicated that our method could obtain the promising segmentation results and had a faster segmentation speed. More specifically, the proposed method obtained comparable and overall better DSC values (0.89, 0.77, and 0.80) on the combined (HGG + LGG) testing set, as compared to other methods reported in the literature. Additionally, the proposed approach was able to complete a segmentation task at a rate of 1.54 seconds per slice. PMID:29755716

An fMRI paradigm based on Williams inhibition test to study the neural substrates of attention and inhibitory control.

PubMed

Dores, Artemisa R; Barbosa, Fernando; Carvalho, Irene P; Almeida, Isabel; Guerreiro, Sandra; da Rocha, Benedita Martins; Cunha, Gil; Castelo Branco, Miguel; de Sousa, Liliana; Castro Caldas, Alexandre

2017-12-01

The purpose of this study is to present an fMRI paradigm, based on the Williams inhibition test (WIT), to study attentional and inhibitory control and their neuroanatomical substrates. We present an index of the validity of the proposed paradigm and test whether the experimental task discriminates the behavioral performances of healthy participants from those of individuals with acquired brain injury. Stroop and Simon tests present similarities with WIT, but this latter is more demanding. We analyze the BOLD signal in 10 healthy participants performing the WIT. The dorsolateral prefrontal cortex, the inferior prefrontal cortex, the anterior cingulate cortex, and the posterior cingulate cortex were defined for specified region of interest analysis. We additionally compare behavioral data (hits, errors, reaction times) of the healthy participants with those of eight acquired brain injury patients. Data were analyzed with GLM-based random effects and Mann-Whitney tests. Results show the involvement of the defined regions and indicate that the WIT is sensitive to brain lesions. This WIT-based block design paradigm can be used as a research methodology for behavioral and neuroimaging studies of the attentional and inhibitory components of executive functions.

An Improved Representation of Regional Boundaries on Parcellated Morphological Surfaces

PubMed Central

Hao, Xuejun; Xu, Dongrong; Bansal, Ravi; Liu, Jun; Peterson, Bradley S.

2010-01-01

Establishing the correspondences of brain anatomy with function is important for understanding neuroimaging data. Regional delineations on morphological surfaces define anatomical landmarks and help to visualize and interpret both functional data and morphological measures mapped onto the cortical surface. We present an efficient algorithm that accurately delineates the morphological surface of the cerebral cortex in real time during generation of the surface using information from parcellated 3D data. With this accurate region delineation, we then develop methods for boundary-preserved simplification and smoothing, as well as procedures for the automated correction of small, misclassified regions to improve the quality of the delineated surface. We demonstrate that our delineation algorithm, together with a new method for double-snapshot visualization of cortical regions, can be used to establish a clear correspondence between brain anatomy and mapped quantities, such as morphological measures, across groups of subjects. PMID:21144708

TH-A-BRF-09: Integration of High-Resolution MRSI Into Glioblastoma Treatment Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schreibmann, E; Cordova, J; Shu, H

2014-06-15

Purpose: Identification of a metabolite signature that shows significant tumor cell infiltration into normal brain in regions that do not appear abnormal on standard MRI scans would be extremely useful for radiation oncologists to choose optimal regions of brain to treat, and to quantify response beyond the MacDonald criteria. We report on integration of high-resolution magnetic resonance spectroscopic imaging (HR-MRSI) with radiation dose escalation treatment planning to define and target regions at high risk for recurrence. Methods: We propose to supplement standard MRI with a special technique performed on an MRI scanner to measure the metabolite levels within defined volumes.more » Metabolite imaging was acquired using an advanced MRSI technique combining 3D echo-planar spectroscopic imaging (EPSI) with parallel acquisition (GRAPPA) using a multichannel head coil that allows acquisition of whole brain metabolite maps with 108 μl resolution in 12 minutes implemented on a 3T MR scanner. Elevation in the ratio of two metabolites, choline (Cho, elevated in proliferating high-grade gliomas) and N-acetyl aspartate (NAA, a normal neuronal metabolite), was used to image infiltrating high-grade glioma cells in vivo. Results: The metabolite images were co-registered with standard contrast-enhanced T1-weighted MR images using in-house registration software and imported into the treatment-planning system. Regions with tumor infiltration are identified on the metabolic images and used to create adaptive IMRT plans that deliver a standard dose of 60 Gy to the standard target volume and an escalated dose of 75 Gy (or higher) to the most suspicious regions, identified as areas with elevated Cho/NAA ratio. Conclusion: We have implemented a state-of-the-art HR-MRSI technology that can generate metabolite maps of the entire brain in a clinically acceptable scan time, coupled with introduction of an imaging co-registration/ analysis program that combines MRSI data with standard imaging studies in a clinically useful fashion.« less

Optogenetic fMRI and electrophysiological identification of region-specific connectivity between the cerebellar cortex and forebrain.

PubMed

Choe, Katrina Y; Sanchez, Carlos F; Harris, Neil G; Otis, Thomas S; Mathews, Paul J

2018-06-01

Complex animal behavior is produced by dynamic interactions between discrete regions of the brain. As such, defining functional connections between brain regions is critical in gaining a full understanding of how the brain generates behavior. Evidence suggests that discrete regions of the cerebellar cortex functionally project to the forebrain, mediating long-range communication potentially important in motor and non-motor behaviors. However, the connectivity map remains largely incomplete owing to the challenge of driving both reliable and selective output from the cerebellar cortex, as well as the need for methods to detect region specific activation across the entire forebrain. Here we utilize a paired optogenetic and fMRI (ofMRI) approach to elucidate the downstream forebrain regions modulated by activating a region of the cerebellum that induces stereotypical, ipsilateral forelimb movements. We demonstrate with ofMRI, that activating this forelimb motor region of the cerebellar cortex results in functional activation of a variety of forebrain and midbrain areas of the brain, including the hippocampus and primary motor, retrosplenial and anterior cingulate cortices. We further validate these findings using optogenetic stimulation paired with multi-electrode array recordings and post-hoc staining for molecular markers of activated neurons (i.e. c-Fos). Together, these findings demonstrate that a single discrete region of the cerebellar cortex is capable of influencing motor output and the activity of a number of downstream forebrain as well as midbrain regions thought to be involved in different aspects of behavior. Copyright © 2018 Elsevier Inc. All rights reserved.

Improving Brain Magnetic Resonance Image (MRI) Segmentation via a Novel Algorithm based on Genetic and Regional Growth

PubMed Central

A., Javadpour; A., Mohammadi

2016-01-01

Background Regarding the importance of right diagnosis in medical applications, various methods have been exploited for processing medical images solar. The method of segmentation is used to analyze anal to miscall structures in medical imaging. Objective This study describes a new method for brain Magnetic Resonance Image (MRI) segmentation via a novel algorithm based on genetic and regional growth. Methods Among medical imaging methods, brains MRI segmentation is important due to high contrast of non-intrusive soft tissue and high spatial resolution. Size variations of brain tissues are often accompanied by various diseases such as Alzheimer’s disease. As our knowledge about the relation between various brain diseases and deviation of brain anatomy increases, MRI segmentation is exploited as the first step in early diagnosis. In this paper, regional growth method and auto-mate selection of initial points by genetic algorithm is used to introduce a new method for MRI segmentation. Primary pixels and similarity criterion are automatically by genetic algorithms to maximize the accuracy and validity in image segmentation. Results By using genetic algorithms and defining the fixed function of image segmentation, the initial points for the algorithm were found. The proposed algorithms are applied to the images and results are manually selected by regional growth in which the initial points were compared. The results showed that the proposed algorithm could reduce segmentation error effectively. Conclusion The study concluded that the proposed algorithm could reduce segmentation error effectively and help us to diagnose brain diseases. PMID:27672629

Use of Ultrasound Pulses Combined with Definity for Targeted Blood-Brain Barrier Disruption

NASA Astrophysics Data System (ADS)

McDannold, Nathan; Vykhodtseva, Natalia; Hynynen, Kullervo

2007-05-01

We have developed a method to combine an ultrasound contrast agent (USCA) with low-intensity focused ultrasound pulses combined to produce temporary blood-brain barrier disruption (BBBD), a potential non-invasive means for targeted drug delivery in the brain. All of our previous work used the USCA Optison. The purpose of this work was to test the feasibility of using the USCA Definity for BBBD. Thirty-six non-overlapping locations were sonicated through a craniotomy in experiments in the brains of nine rabbits (4 locations per rabbit; US frequency: 0.69MHz, burst: 10ms, PRF: 1Hz, duration: 20s; pressure amplitude: 0.2-1.5 MPa). Eleven locations were sonicated using Optison at 0.5 MPa. For both agents, the probability for BBBD was estimated to be 50% at 0.4 MPa using probit regression. In histology, small isolated areas of extravasated erythrocytes were observed in some locations. At 0.8 MPa and above, this extravasation was sometimes accompanied by tiny (dimensions of 100 μm or less) regions of damaged brain parenchyma. The magnitude of the BBBD was larger with Optison than with Definity at 0.5 MPa (P=0.04), and more areas with extravasated erythrocytes were observed (P=0.03). We conclude that BBBD is possible using Definity for the dosage of USCA and the acoustic parameters tested in this study. While the probability for BBBD as a function of pressure amplitude and the type of acute tissue effects was similar to findings with Optison, under these experimental conditions, Optison produced a larger effect.

Magnetic resonance spectroscopy investigations of functionally defined language areas in schizophrenia patients with and without auditory hallucinations.

PubMed

Homan, Philipp; Vermathen, Peter; Van Swam, Claudia; Federspiel, Andrea; Boesch, Chris; Strik, Werner; Dierks, Thomas; Hubl, Daniela; Kreis, Roland

2014-07-01

Cerebral dysfunction occurring in mental disorders can show metabolic disturbances which are limited to circumscribed brain areas. Auditory hallucinations have been shown to be related to defined cortical areas linked to specific language functions. Here, we investigated if the study of metabolic changes in auditory hallucinations requires a functional rather than an anatomical definition of their location and size to allow a reliable investigation by magnetic resonance spectroscopy (MRS). Schizophrenia patients with (AH; n=12) and without hallucinations (NH; n=8) and healthy controls (HC; n=11) underwent a verbal fluency task in functional MRI (fMRI) to functionally define Broca's and Wernicke's areas. Left and right Heschl's gyri were defined anatomically. The mean distances in native space between the fMRI-defined regions and a corresponding anatomically defined area were 12.4±6.1 mm (range: 2.7-36.1 mm) for Broca's area and 16.8±6.2 mm (range: 4.5-26.4 mm) for Wernicke's area, respectively. Hence, the spatial variance was of similar extent as the size of the investigated regions. Splitting the investigations into a single voxel examination in the frontal brain and a spectroscopic imaging part for the more homogeneous field areas led to good spectral quality for almost all spectra. In Broca's area, there was a significant group effect (p=0.03) with lower levels of N-acetyl-aspartate (NAA) in NH compared to HC (p=0.02). There were positive associations of NAA levels in the left Heschl's gyrus with total (p=0.03) and negative (p=0.006) PANSS scores. In Broca's area, there was a negative association of myo-inositol levels with total PANSS scores (p=0.008). This study supports the neurodegenerative hypothesis of schizophrenia only in a frontal region whereas the results obtained from temporal regions are in contrast to the majority of previous studies. Future research should test the hypothesis raised by this study that a functional definition of language regions is needed if neurochemical imbalances are expected to be restricted to functional foci. Copyright © 2014 Elsevier Inc. All rights reserved.

Sex in the brain: hormones and sex differences.

PubMed

Marrocco, Jordan; McEwen, Bruce S

2016-12-01

Contrary to popular belief, sex hormones act throughout the entire brain of both males and females via both genomic and nongenomic receptors. Many neural and behavioral functions are affected by estrogens, including mood, cognitive function, blood pressure regulation, motor coordination, pain, and opioid sensitivity. Subtle sex differences exist for many of these functions that are developmentally programmed by hormones and by not yet precisely defined genetic factors, including the mitochondrial genome. These sex differences, and responses to sex hormones in brain regions and upon functions not previously regarded as subject to such differences, indicate that we are entering a new era in our ability to understand and appreciate the diversity of gender-related behaviors and brain functions.

Landmark-based deep multi-instance learning for brain disease diagnosis.

PubMed

Liu, Mingxia; Zhang, Jun; Adeli, Ehsan; Shen, Dinggang

2018-01-01

In conventional Magnetic Resonance (MR) image based methods, two stages are often involved to capture brain structural information for disease diagnosis, i.e., 1) manually partitioning each MR image into a number of regions-of-interest (ROIs), and 2) extracting pre-defined features from each ROI for diagnosis with a certain classifier. However, these pre-defined features often limit the performance of the diagnosis, due to challenges in 1) defining the ROIs and 2) extracting effective disease-related features. In this paper, we propose a landmark-based deep multi-instance learning (LDMIL) framework for brain disease diagnosis. Specifically, we first adopt a data-driven learning approach to discover disease-related anatomical landmarks in the brain MR images, along with their nearby image patches. Then, our LDMIL framework learns an end-to-end MR image classifier for capturing both the local structural information conveyed by image patches located by landmarks and the global structural information derived from all detected landmarks. We have evaluated our proposed framework on 1526 subjects from three public datasets (i.e., ADNI-1, ADNI-2, and MIRIAD), and the experimental results show that our framework can achieve superior performance over state-of-the-art approaches. Copyright © 2017 Elsevier B.V. All rights reserved.

Individual Human Brain Areas Can Be Identified from Their Characteristic Spectral Activation Fingerprints.

PubMed

Keitel, Anne; Gross, Joachim

2016-06-01

The human brain can be parcellated into diverse anatomical areas. We investigated whether rhythmic brain activity in these areas is characteristic and can be used for automatic classification. To this end, resting-state MEG data of 22 healthy adults was analysed. Power spectra of 1-s long data segments for atlas-defined brain areas were clustered into spectral profiles ("fingerprints"), using k-means and Gaussian mixture (GM) modelling. We demonstrate that individual areas can be identified from these spectral profiles with high accuracy. Our results suggest that each brain area engages in different spectral modes that are characteristic for individual areas. Clustering of brain areas according to similarity of spectral profiles reveals well-known brain networks. Furthermore, we demonstrate task-specific modulations of auditory spectral profiles during auditory processing. These findings have important implications for the classification of regional spectral activity and allow for novel approaches in neuroimaging and neurostimulation in health and disease.

3D geometric split-merge segmentation of brain MRI datasets.

PubMed

Marras, Ioannis; Nikolaidis, Nikolaos; Pitas, Ioannis

2014-05-01

In this paper, a novel method for MRI volume segmentation based on region adaptive splitting and merging is proposed. The method, called Adaptive Geometric Split Merge (AGSM) segmentation, aims at finding complex geometrical shapes that consist of homogeneous geometrical 3D regions. In each volume splitting step, several splitting strategies are examined and the most appropriate is activated. A way to find the maximal homogeneity axis of the volume is also introduced. Along this axis, the volume splitting technique divides the entire volume in a number of large homogeneous 3D regions, while at the same time, it defines more clearly small homogeneous regions within the volume in such a way that they have greater probabilities of survival at the subsequent merging step. Region merging criteria are proposed to this end. The presented segmentation method has been applied to brain MRI medical datasets to provide segmentation results when each voxel is composed of one tissue type (hard segmentation). The volume splitting procedure does not require training data, while it demonstrates improved segmentation performance in noisy brain MRI datasets, when compared to the state of the art methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

Autonomic responses to exercise: where is central command?

PubMed

Williamson, J W

2015-03-01

A central command is thought to involve a signal arising in a central area of the brain eliciting a parallel activation of the autonomic nervous system and skeletal muscle contraction during exercise. Although much of the neural circuitry involved in autonomic control has been identified, defining the specific higher brain region(s) serving in a central command capacity has proven more challenging. Investigators have been faced with redundancies in regulatory systems, feedback mechanisms and the complexities ofhuman neural connectivity. Several studies have attempted to address these issues and provide more definitive neuroanatomical information. However, none have clearly answered the question, "where is central command?" Copyright © 2014 Elsevier B.V. All rights reserved.

A mesoscale connectome of the mouse brain

PubMed Central

Oh, Seung Wook; Harris, Julie A.; Ng, Lydia; Winslow, Brent; Cain, Nicholas; Mihalas, Stefan; Wang, Quanxin; Lau, Chris; Kuan, Leonard; Henry, Alex M.; Mortrud, Marty T.; Ouellette, Benjamin; Nguyen, Thuc Nghi; Sorensen, Staci A.; Slaughterbeck, Clifford R.; Wakeman, Wayne; Li, Yang; Feng, David; Ho, Anh; Nicholas, Eric; Hirokawa, Karla E.; Bohn, Phillip; Joines, Kevin M.; Peng, Hanchuan; Hawrylycz, Michael J.; Phillips, John W.; Hohmann, John G.; Wohnoutka, Paul; Gerfen, Charles R.; Koch, Christof; Bernard, Amy; Dang, Chinh; Jones, Allan R.; Zeng, Hongkui

2016-01-01

Comprehensive knowledge of the brain’s wiring diagram is fundamental for understanding how the nervous system processes information at both local and global scales. However, with the singular exception of the C. elegans microscale connectome, there are no complete connectivity data sets in other species. Here we report a brain-wide, cellular-level, mesoscale connectome for the mouse. The Allen Mouse Brain Connectivity Atlas uses enhanced green fluorescent protein (EGFP)-expressing adeno-associated viral vectors to trace axonal projections from defined regions and cell types, and high-throughput serial two-photon tomography to image the EGFP-labelled axons throughout the brain. This systematic and standardized approach allows spatial registration of individual experiments into a common three dimensional (3D) reference space, resulting in a whole-brain connectivity matrix. A computational model yields insights into connectional strength distribution, symmetry and other network properties. Virtual tractography illustrates 3D topography among interconnected regions. Cortico-thalamic pathway analysis demonstrates segregation and integration of parallel pathways. The Allen Mouse Brain Connectivity Atlas is a freely available, foundational resource for structural and functional investigations into the neural circuits that support behavioural and cognitive processes in health and disease. PMID:24695228

Regional Brain Shrinkage over Two Years: Individual Differences and Effects of Pro-Inflammatory Genetic Polymorphisms

PubMed Central

Persson, N.; Ghisletta, P.; Dahle, C.L.; Bender, A.R.; Yang, Y.; Yuan, P.; Daugherty, A.M.; Raz, N.

2014-01-01

We examined regional changes in brain volume in healthy adults (N = 167, age 19-79 years at baseline; N = 90 at follow-up) over approximately two years. With latent change score models, we evaluated mean change and individual differences in rates of change in 10 anatomically-defined and manually-traced regions of interest (ROIs): lateral prefrontal cortex (LPFC), orbital frontal cortex (OF), prefrontal white matter (PFw), hippocampus (HC), parahippocampal gyrus (PhG), caudate nucleus (Cd), putamen (Pt), insula (In), cerebellar hemispheres (CbH), and primary visual cortex (VC). Significant mean shrinkage was observed in the HC, CbH, In, OF, and the PhG, and individual differences in change were noted in all regions, except the OF. Pro-inflammatory genetic variants mediated shrinkage in PhG and CbH. Carriers of two T alleles of interleukin-1β (IL-1βC-511T, rs16944) and a T allele of methylenetetrahydrofolate reductase (MTHFRC677T, rs1801133) polymorphisms showed increased PhG shrinkage. No effects of a pro-inflammatory polymorphism for C-reactive protein (CRP-286C>A>T, rs3091244) or apolipoprotein (APOE) ε4 allele were noted. These results replicate the pattern of brain shrinkage observed in previous studies, with a notable exception of the LPFC thus casting doubt on the unique importance of prefrontal cortex in aging. Larger baseline volumes of CbH and In were associated with increased shrinkage, in conflict with the brain reserve hypothesis. Contrary to previous reports, we observed no significant linear effects of age and hypertension on regional brain shrinkage. Our findings warrant further investigation of the effects of neuroinflammation on structural brain change throughout the lifespan. PMID:25264227

Implementation of a computer-aided detection tool for quantification of intracranial radiologic markers on brain CT images

NASA Astrophysics Data System (ADS)

Aghaei, Faranak; Ross, Stephen R.; Wang, Yunzhi; Wu, Dee H.; Cornwell, Benjamin O.; Ray, Bappaditya; Zheng, Bin

2017-03-01

Aneurysmal subarachnoid hemorrhage (aSAH) is a form of hemorrhagic stroke that affects middle-aged individuals and associated with significant morbidity and/or mortality especially those presenting with higher clinical and radiologic grades at the time of admission. Previous studies suggested that blood extravasated after aneurysmal rupture was a potentially clinical prognosis factor. But all such studies used qualitative scales to predict prognosis. The purpose of this study is to develop and test a new interactive computer-aided detection (CAD) tool to detect, segment and quantify brain hemorrhage and ventricular cerebrospinal fluid on non-contrasted brain CT images. First, CAD segments brain skull using a multilayer region growing algorithm with adaptively adjusted thresholds. Second, CAD assigns pixels inside the segmented brain region into one of three classes namely, normal brain tissue, blood and fluid. Third, to avoid "black-box" approach and increase accuracy in quantification of these two image markers using CT images with large noise variation in different cases, a graphic User Interface (GUI) was implemented and allows users to visually examine segmentation results. If a user likes to correct any errors (i.e., deleting clinically irrelevant blood or fluid regions, or fill in the holes inside the relevant blood or fluid regions), he/she can manually define the region and select a corresponding correction function. CAD will automatically perform correction and update the computed data. The new CAD tool is now being used in clinical and research settings to estimate various quantitatively radiological parameters/markers to determine radiological severity of aSAH at presentation and correlate the estimations with various homeostatic/metabolic derangements and predict clinical outcome.

The Richness of Task-Evoked Hemodynamic Responses Defines a Pseudohierarchy of Functionally Meaningful Brain Networks

PubMed Central

Orban, Pierre; Doyon, Julien; Petrides, Michael; Mennes, Maarten; Hoge, Richard; Bellec, Pierre

2015-01-01

Functional magnetic resonance imaging can measure distributed and subtle variations in brain responses associated with task performance. However, it is unclear whether the rich variety of responses observed across the brain is functionally meaningful and consistent across individuals. Here, we used a multivariate clustering approach that grouped brain regions into clusters based on the similarity of their task-evoked temporal responses at the individual level, and then established the spatial consistency of these individual clusters at the group level. We observed a stable pseudohierarchy of task-evoked networks in the context of a delayed sequential motor task, where the fractionation of networks was driven by a gradient of involvement in motor sequence preparation versus execution. In line with theories about higher-level cognitive functioning, this gradient evolved in a rostro-caudal manner in the frontal lobe. In addition, parcellations in the cerebellum and basal ganglia matched with known anatomical territories and fiber pathways with the cerebral cortex. These findings demonstrate that subtle variations in brain responses associated with task performance are systematic enough across subjects to define a pseudohierarchy of task-evoked networks. Such networks capture meaningful functional features of brain organization as shaped by a given cognitive context. PMID:24729172

Delineation of separate brain regions used for scientific versus engineering modes of thinking

NASA Astrophysics Data System (ADS)

Patterson, Clair C.

1994-08-01

Powerful, latent abilities for extreme sophistication in abstract rationalization as potential biological adaptive behavioral responses were installed entirely through accident and inadvertence by biological evolution in the Homo sapiens sapiens species of brain. These potentials were never used, either in precursor species as factors in evolutionary increase in hominid brain mass, nor in less sophisticated forms within social environments characterized by Hss tribal brain population densities. Those latent abilities for unnatural biological adaptive behavior were forced to become manifest in various ways by growths in sophistication of communication interactions engendered by large growths in brain population densities brought on by developments in agriculture at the onset of the Holocene. It is proposed that differences probably exist between regions of the Hss brain involved in utilitarian, engineering types of problem conceptualization-solving versus regions of the brain involved in nonutilitarian, artistic-scientific types of problem conceptualization-solving. Populations isolated on separate continents from diffusive contact and influence on cultural developments, and selected for comparison of developments during equivalent stages of technological and social sophistication in matching 4000 year periods, show, at the ends of those periods, marked differences in aesthetic attributes expressed in cosmogonies, music, and writing (nonutilitarian thinking related to science and art). On the other hand the two cultures show virtually identical developments in three major stages of metallurgical technologies (utilitarian thinking related to engineering). Such archaeological data suggest that utilitarian modes of thought may utilize combinations of neuronal circuits in brain regions that are conserved among tribal populations territorially separated from each other for tens of thousands of years. Such conservation may not be true for neuronal circuits involved in nonutilitarian modes of thought. It is postulated that neuronal circuits involved in nonutilitarian modes of thought are located in specific regions of the brain that are divergent features between populations that have been territorially separated for tens of thousands of years. Anatomical PET and NMRI studies of brains of modern descendants of these cultures are proposed that would seek to define these inferred differences through proper protocols of stimulation devised by those investigators.

Functional grouping and cortical–subcortical interactions in emotion: A meta-analysis of neuroimaging studies

PubMed Central

Kober, Hedy; Barrett, Lisa Feldman; Joseph, Josh; Bliss-Moreau, Eliza; Lindquist, Kristen; Wager, Tor D.

2009-01-01

We performed an updated quantitative meta-analysis of 162 neuroimaging studies of emotion using a novel multi-level kernel-based approach, focusing on locating brain regions consistently activated in emotional tasks and their functional organization into distributed functional groups, independent of semantically defined emotion category labels (e.g., “anger,” “fear”). Such brain-based analyses are critical if our ways of labeling emotions are to be evaluated and revised based on consistency with brain data. Consistent activations were limited to specific cortical sub-regions, including multiple functional areas within medial, orbital, and inferior lateral frontal cortices. Consistent with a wealth of animal literature, multiple subcortical activations were identified, including amygdala, ventral striatum, thalamus, hypothalamus, and periaqueductal gray. We used multivariate parcellation and clustering techniques to identify groups of co-activated brain regions across studies. These analyses identified six distributed functional groups, including medial and lateral frontal groups, two posterior cortical groups, and paralimbic and core limbic/brainstem groups. These functional groups provide information on potential organization of brain regions into large-scale networks. Specific follow-up analyses focused on amygdala, periaqueductal gray (PAG), and hypothalamic (Hy) activations, and identified frontal cortical areas co-activated with these core limbic structures. While multiple areas of frontal cortex co-activated with amygdala sub-regions, a specific region of dorsomedial prefrontal cortex (dmPFC, Brodmann’s Area 9/32) was the only area co-activated with both PAG and Hy. Subsequent mediation analyses were consistent with a pathway from dmPFC through PAG to Hy. These results suggest that medial frontal areas are more closely associated with core limbic activation than their lateral counterparts, and that dmPFC may play a particularly important role in the cognitive generation of emotional states. PMID:18579414

BRAIN NETWORKS. Correlated gene expression supports synchronous activity in brain networks.

PubMed

Richiardi, Jonas; Altmann, Andre; Milazzo, Anna-Clare; Chang, Catie; Chakravarty, M Mallar; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Bromberg, Uli; Büchel, Christian; Conrod, Patricia; Fauth-Bühler, Mira; Flor, Herta; Frouin, Vincent; Gallinat, Jürgen; Garavan, Hugh; Gowland, Penny; Heinz, Andreas; Lemaître, Hervé; Mann, Karl F; Martinot, Jean-Luc; Nees, Frauke; Paus, Tomáš; Pausova, Zdenka; Rietschel, Marcella; Robbins, Trevor W; Smolka, Michael N; Spanagel, Rainer; Ströhle, Andreas; Schumann, Gunter; Hawrylycz, Mike; Poline, Jean-Baptiste; Greicius, Michael D

2015-06-12

During rest, brain activity is synchronized between different regions widely distributed throughout the brain, forming functional networks. However, the molecular mechanisms supporting functional connectivity remain undefined. We show that functional brain networks defined with resting-state functional magnetic resonance imaging can be recapitulated by using measures of correlated gene expression in a post mortem brain tissue data set. The set of 136 genes we identify is significantly enriched for ion channels. Polymorphisms in this set of genes significantly affect resting-state functional connectivity in a large sample of healthy adolescents. Expression levels of these genes are also significantly associated with axonal connectivity in the mouse. The results provide convergent, multimodal evidence that resting-state functional networks correlate with the orchestrated activity of dozens of genes linked to ion channel activity and synaptic function. Copyright © 2015, American Association for the Advancement of Science.

Signals that regulate the oncogenic fate of neural stem cells and progenitors

PubMed Central

Swartling, Fredrik J.; Bolin, Sara; Phillips, Joanna J.; Persson, Anders I.

2013-01-01

Brain tumors have frequently been associated with a neural stem cell (NSC) origin and contain stem-like tumor cells, so-called brain tumor stem cells (BTSCs) that share many features with normal NSCs. A stem cell state of BTSCs confers resistance to radiotherapy and treatment with alkylating agents. It is also a hallmark of aggressive brain tumors and is maintained by transcriptional networks that are also active in embryonic stem cells. Advances in reprogramming of somatic cells into induced pluripotent stem (iPS) cells have further identified genes that drive stemness. In this review, we will highlight the possible drivers of stemness in medulloblastoma and glioma, the most frequent types of primary malignant brain cancer in children and adults, respectively. Signals that drive expansion of developmentally defined neural precursor cells are also active in corresponding brain tumors. Transcriptomal subgroups of human medulloblastoma and glioma match features of NSCs but also more restricted progenitors. Lessons from genetically-engineered mouse (GEM) models show that temporally and regionally defined NSCs can give rise to distinct subgroups of medulloblastoma and glioma. We will further discuss how acquisition of stem cell features may drive brain tumorigenesis from a non-NSC origin. Genetic alterations, signaling pathways, and therapy-induced changes in the tumor microenvironment can drive reprogramming networks and induce stemness in brain tumors. Finally, we propose a model where dysregulation of microRNAs (miRNAs) that normally provide barriers against reprogramming plays an integral role in promoting stemness in brain tumors. PMID:23376224

Disruption of functional networks in dyslexia: A whole-brain, data-driven analysis of connectivity

PubMed Central

Finn, Emily S.; Shen, Xilin; Holahan, John M.; Scheinost, Dustin; Lacadie, Cheryl; Papademetris, Xenophon; Shaywitz, Sally E.; Shaywitz, Bennett A.; Constable, R. Todd

2013-01-01

Background Functional connectivity analyses of fMRI data are a powerful tool for characterizing brain networks and how they are disrupted in neural disorders. However, many such analyses examine only one or a small number of a priori seed regions. Studies that consider the whole brain frequently rely on anatomic atlases to define network nodes, which may result in mixing distinct activation timecourses within a single node. Here, we improve upon previous methods by using a data-driven brain parcellation to compare connectivity profiles of dyslexic (DYS) versus non-impaired (NI) readers in the first whole-brain functional connectivity analysis of dyslexia. Methods Whole-brain connectivity was assessed in children (n = 75; 43 NI, 32 DYS) and adult (n = 104; 64 NI, 40 DYS) readers. Results Compared to NI readers, DYS readers showed divergent connectivity within the visual pathway and between visual association areas and prefrontal attention areas; increased right-hemisphere connectivity; reduced connectivity in the visual word-form area (part of the left fusiform gyrus specialized for printed words); and persistent connectivity to anterior language regions around the inferior frontal gyrus. Conclusions Together, findings suggest that NI readers are better able to integrate visual information and modulate their attention to visual stimuli, allowing them to recognize words based on their visual properties, while DYS readers recruit altered reading circuits and rely on laborious phonology-based “sounding out” strategies into adulthood. These results deepen our understanding of the neural basis of dyslexia and highlight the importance of synchrony between diverse brain regions for successful reading. PMID:24124929

Resting state connectivity of the medial prefrontal cortex covaries with individual differences in high-frequency heart rate variability.

PubMed

Jennings, J Richard; Sheu, Lei K; Kuan, Dora C-H; Manuck, Stephen B; Gianaros, Peter J

2016-04-01

Resting high-frequency heart rate variability (HF-HRV) relates to cardiac vagal control and predicts individual differences in health and longevity, but its functional neural correlates are not well defined. The medial prefrontal cortex (mPFC) encompasses visceral control regions that are components of intrinsic networks of the brain, particularly the default mode network (DMN) and the salience network (SN). Might individual differences in resting HF-HRV covary with resting state neural activity in the DMN and SN, particularly within the mPFC? This question was addressed using fMRI data from an eyes-open, 5-min rest period during which echoplanar brain imaging yielded BOLD time series. Independent component analysis yielded functional connectivity estimates defining the DMN and SN. HF-HRV was measured in a rest period outside of the scanner. Midlife (52% female) adults were assessed in two studies (Study 1, N = 107; Study 2, N = 112). Neither overall DMN nor SN connectivity strength was related to HF-HRV. However, HF-HRV related to connectivity of one region within mPFC shared by the DMN and SN, namely, the perigenual anterior cingulate cortex, an area with connectivity to other regions involved in autonomic control. In sum, HF-HRV does not seem directly related to global resting state activity of intrinsic brain networks, but rather to more localized connectivity. A mPFC region was of particular interest as connectivity related to HF-HRV was shared by the DMN and SN. These findings may indicate a functional basis for the coordination of autonomic cardiac control with engagement and disengagement from the environment. © 2015 Society for Psychophysiological Research.

Morphological covariance in anatomical MRI scans can identify discrete neural pathways in the brain and their disturbances in persons with neuropsychiatric disorders.

PubMed

Bansal, Ravi; Hao, Xuejun; Peterson, Bradley S

2015-05-01

We hypothesize that coordinated functional activity within discrete neural circuits induces morphological organization and plasticity within those circuits. Identifying regions of morphological covariation that are independent of morphological covariation in other regions therefore may therefore allow us to identify discrete neural systems within the brain. Comparing the magnitude of these variations in individuals who have psychiatric disorders with the magnitude of variations in healthy controls may allow us to identify aberrant neural pathways in psychiatric illnesses. We measured surface morphological features by applying nonlinear, high-dimensional warping algorithms to manually defined brain regions. We transferred those measures onto the surface of a unit sphere via conformal mapping and then used spherical wavelets and their scaling coefficients to simplify the data structure representing these surface morphological features of each brain region. We used principal component analysis (PCA) to calculate covariation in these morphological measures, as represented by their scaling coefficients, across several brain regions. We then assessed whether brain subregions that covaried in morphology, as identified by large eigenvalues in the PCA, identified specific neural pathways of the brain. To do so, we spatially registered the subnuclei for each eigenvector into the coordinate space of a Diffusion Tensor Imaging dataset; we used these subnuclei as seed regions to track and compare fiber pathways with known fiber pathways identified in neuroanatomical atlases. We applied these procedures to anatomical MRI data in a cohort of 82 healthy participants (42 children, 18 males, age 10.5 ± 2.43 years; 40 adults, 22 males, age 32.42 ± 10.7 years) and 107 participants with Tourette's Syndrome (TS) (71 children, 59 males, age 11.19 ± 2.2 years; 36 adults, 21 males, age 37.34 ± 10.9 years). We evaluated the construct validity of the identified covariation in morphology using DTI data from a different set of 20 healthy adults (10 males, mean age 29.7 ± 7.7 years). The PCA identified portions of structures that covaried across the brain, the eigenvalues measuring the magnitude of the covariation in morphology along the respective eigenvectors. Our results showed that the eigenvectors, and the DTI fibers tracked from their associated brain regions, corresponded with known neural pathways in the brain. In addition, the eigenvectors that captured morphological covariation across regions, and the principal components along those eigenvectors, identified neural pathways with aberrant morphological features associated with TS. These findings suggest that covariations in brain morphology can identify aberrant neural pathways in specific neuropsychiatric disorders. Copyright © 2015. Published by Elsevier Inc.

On the role of general system theory for functional neuroimaging.

PubMed

Stephan, Klaas Enno

2004-12-01

One of the most important goals of neuroscience is to establish precise structure-function relationships in the brain. Since the 19th century, a major scientific endeavour has been to associate structurally distinct cortical regions with specific cognitive functions. This was traditionally accomplished by correlating microstructurally defined areas with lesion sites found in patients with specific neuropsychological symptoms. Modern neuroimaging techniques with high spatial resolution have promised an alternative approach, enabling non-invasive measurements of regionally specific changes of brain activity that are correlated with certain components of a cognitive process. Reviewing classic approaches towards brain structure-function relationships that are based on correlational approaches, this article argues that these approaches are not sufficient to provide an understanding of the operational principles of a dynamic system such as the brain but must be complemented by models based on general system theory. These models reflect the connectional structure of the system under investigation and emphasize context-dependent couplings between the system elements in terms of effective connectivity. The usefulness of system models whose parameters are fitted to measured functional imaging data for testing hypotheses about structure-function relationships in the brain and their potential for clinical applications is demonstrated by several empirical examples.

On the role of general system theory for functional neuroimaging

PubMed Central

Stephan, Klaas Enno

2004-01-01

One of the most important goals of neuroscience is to establish precise structure–function relationships in the brain. Since the 19th century, a major scientific endeavour has been to associate structurally distinct cortical regions with specific cognitive functions. This was traditionally accomplished by correlating microstructurally defined areas with lesion sites found in patients with specific neuropsychological symptoms. Modern neuroimaging techniques with high spatial resolution have promised an alternative approach, enabling non-invasive measurements of regionally specific changes of brain activity that are correlated with certain components of a cognitive process. Reviewing classic approaches towards brain structure–function relationships that are based on correlational approaches, this article argues that these approaches are not sufficient to provide an understanding of the operational principles of a dynamic system such as the brain but must be complemented by models based on general system theory. These models reflect the connectional structure of the system under investigation and emphasize context-dependent couplings between the system elements in terms of effective connectivity. The usefulness of system models whose parameters are fitted to measured functional imaging data for testing hypotheses about structure–function relationships in the brain and their potential for clinical applications is demonstrated by several empirical examples. PMID:15610393

Probing the brain with molecular fMRI.

PubMed

Ghosh, Souparno; Harvey, Peter; Simon, Jacob C; Jasanoff, Alan

2018-06-01

One of the greatest challenges of modern neuroscience is to incorporate our growing knowledge of molecular and cellular-scale physiology into integrated, organismic-scale models of brain function in behavior and cognition. Molecular-level functional magnetic resonance imaging (molecular fMRI) is a new technology that can help bridge these scales by mapping defined microscopic phenomena over large, optically inaccessible regions of the living brain. In this review, we explain how MRI-detectable imaging probes can be used to sensitize noninvasive imaging to mechanistically significant components of neural processing. We discuss how a combination of innovative probe design, advanced imaging methods, and strategies for brain delivery can make molecular fMRI an increasingly successful approach for spatiotemporally resolved studies of diverse neural phenomena, perhaps eventually in people. Copyright © 2018 Elsevier Ltd. All rights reserved.

Training your brain to be more creative: brain functional and structural changes induced by divergent thinking training.

PubMed

Sun, Jiangzhou; Chen, Qunlin; Zhang, Qinglin; Li, Yadan; Li, Haijiang; Wei, Dongtao; Yang, Wenjing; Qiu, Jiang

2016-10-01

Creativity is commonly defined as the ability to produce something both novel and useful. Stimulating creativity has great significance for both individual success and social improvement. Although increasing creative capacity has been confirmed to be possible and effective at the behavioral level, few longitudinal studies have examined the extent to which the brain function and structure underlying creativity are plastic. A cognitive stimulation (20 sessions) method was used in the present study to train subjects and to explore the neuroplasticity induced by training. The behavioral results revealed that both the originality and the fluency of divergent thinking were significantly improved by training. Furthermore, functional changes induced by training were observed in the dorsal anterior cingulate cortex (dACC), dorsal lateral prefrontal cortex (DLPFC), and posterior brain regions. Moreover, the gray matter volume (GMV) was significantly increased in the dACC after divergent thinking training. These results suggest that the enhancement of creativity may rely not only on the posterior brain regions that are related to the fundamental cognitive processes of creativity (e.g., semantic processing, generating novel associations), but also on areas that are involved in top-down cognitive control, such as the dACC and DLPFC. Hum Brain Mapp 37:3375-3387, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Individual Human Brain Areas Can Be Identified from Their Characteristic Spectral Activation Fingerprints

PubMed Central

Keitel, Anne; Gross, Joachim

2016-01-01

The human brain can be parcellated into diverse anatomical areas. We investigated whether rhythmic brain activity in these areas is characteristic and can be used for automatic classification. To this end, resting-state MEG data of 22 healthy adults was analysed. Power spectra of 1-s long data segments for atlas-defined brain areas were clustered into spectral profiles (“fingerprints”), using k-means and Gaussian mixture (GM) modelling. We demonstrate that individual areas can be identified from these spectral profiles with high accuracy. Our results suggest that each brain area engages in different spectral modes that are characteristic for individual areas. Clustering of brain areas according to similarity of spectral profiles reveals well-known brain networks. Furthermore, we demonstrate task-specific modulations of auditory spectral profiles during auditory processing. These findings have important implications for the classification of regional spectral activity and allow for novel approaches in neuroimaging and neurostimulation in health and disease. PMID:27355236

Chaos Control of Epileptiform Bursting in the Brain

NASA Astrophysics Data System (ADS)

Slutzky, M. W.; Cvitanovic, P.; Mogul, D. J.

Epilepsy, defined as recurrent seizures, is a pathological state of the brain that afflicts over one percent of the world's population. Seizures occur as populations of neurons in the brain become overly synchronized. Although pharmacological agents are the primary treatment for preventing or reducing the incidence of these seizures, over 30% of epilepsy cases are not adequately helped by standard medical therapies. Several groups are exploring the use of electrical stimulation to terminate or prevent epileptic seizures. One experimental model used to test these algorithms is the brain slice where a select region of the brain is cut and kept viable in a well-oxygenated artificial cerebrospinal fluid. Under certain conditions, such slices may be made to spontaneously and repetitively burst, thereby providing an in vitro model of epilepsy. In this chapter, we discuss our efforts at applying chaos analysis and chaos control algorithms for manipulating this seizure-like behavior in a brain slice model. These techniques may provide a nonlinear control pathway for terminating or potentially preventing epileptic seizures in the whole brain.

Warping of a computerized 3-D atlas to match brain image volumes for quantitative neuroanatomical and functional analysis

NASA Astrophysics Data System (ADS)

Evans, Alan C.; Dai, Weiqian; Collins, D. Louis; Neelin, Peter; Marrett, Sean

1991-06-01

We describe the implementation, experience and preliminary results obtained with a 3-D computerized brain atlas for topographical and functional analysis of brain sub-regions. A volume-of-interest (VOI) atlas was produced by manual contouring on 64 adjacent 2 mm-thick MRI slices to yield 60 brain structures in each hemisphere which could be adjusted, originally by global affine transformation or local interactive adjustments, to match individual MRI datasets. We have now added a non-linear deformation (warp) capability (Bookstein, 1989) into the procedure for fitting the atlas to the brain data. Specific target points are identified in both atlas and MRI spaces which define a continuous 3-D warp transformation that maps the atlas on to the individual brain image. The procedure was used to fit MRI brain image volumes from 16 young normal volunteers. Regional volume and positional variability were determined, the latter in such a way as to assess the extent to which previous linear models of brain anatomical variability fail to account for the true variation among normal individuals. Using a linear model for atlas deformation yielded 3-D fits of the MRI data which, when pooled across subjects and brain regions, left a residual mis-match of 6 - 7 mm as compared to the non-linear model. The results indicate a substantial component of morphometric variability is not accounted for by linear scaling. This has profound implications for applications which employ stereotactic coordinate systems which map individual brains into a common reference frame: quantitative neuroradiology, stereotactic neurosurgery and cognitive mapping of normal brain function with PET. In the latter case, the combination of a non-linear deformation algorithm would allow for accurate measurement of individual anatomic variations and the inclusion of such variations in inter-subject averaging methodologies used for cognitive mapping with PET.

Voxel-based statistical analysis of cerebral glucose metabolism in patients with permanent vegetative state after acquired brain injury.

PubMed

Kim, Yong Wook; Kim, Hyoung Seop; An, Young-Sil; Im, Sang Hee

2010-10-01

Permanent vegetative state is defined as the impaired level of consciousness longer than 12 months after traumatic causes and 3 months after non-traumatic causes of brain injury. Although many studies assessed the cerebral metabolism in patients with acute and persistent vegetative state after brain injury, few studies investigated the cerebral metabolism in patients with permanent vegetative state. In this study, we performed the voxel-based analysis of cerebral glucose metabolism and investigated the relationship between regional cerebral glucose metabolism and the severity of impaired consciousness in patients with permanent vegetative state after acquired brain injury. We compared the regional cerebral glucose metabolism as demonstrated by F-18 fluorodeoxyglucose positron emission tomography from 12 patients with permanent vegetative state after acquired brain injury with those from 12 control subjects. Additionally, covariance analysis was performed to identify regions where decreased changes in regional cerebral glucose metabolism significantly correlated with a decrease of level of consciousness measured by JFK-coma recovery scale. Statistical analysis was performed using statistical parametric mapping. Compared with controls, patients with permanent vegetative state demonstrated decreased cerebral glucose metabolism in the left precuneus, both posterior cingulate cortices, the left superior parietal lobule (P(corrected) < 0.001), and increased cerebral glucose metabolism in the both cerebellum and the right supramarginal cortices (P(corrected) < 0.001). In the covariance analysis, a decrease in the level of consciousness was significantly correlated with decreased cerebral glucose metabolism in the both posterior cingulate cortices (P(uncorrected) < 0.005). Our findings suggest that the posteromedial parietal cortex, which are part of neural network for consciousness, may be relevant structure for pathophysiological mechanism in patients with permanent vegetative state after acquired brain injury.

Classification and localization of early-stage Alzheimer's disease in magnetic resonance images using a patch-based classifier ensemble.

PubMed

Simões, Rita; van Cappellen van Walsum, Anne-Marie; Slump, Cornelis H

2014-09-01

Classification methods have been proposed to detect Alzheimer’s disease (AD) using magnetic resonance images. Most rely on features such as the shape/volume of brain structures that need to be defined a priori. In this work, we propose a method that does not require either the segmentation of specific brain regions or the nonlinear alignment to a template. Besides classification, we also analyze which brain regions are discriminative between a group of normal controls and a group of AD patients. We perform 3D texture analysis using Local Binary Patterns computed at local image patches in the whole brain, combined in a classifier ensemble.We evaluate our method in a publicly available database including very mild-to-mild AD subjects and healthy elderly controls. For the subject cohort including only mild AD subjects, the best results are obtained using a combination of large (30×30×30 and 40×40×40 voxels) patches. A spatial analysis on the best performing patches shows that these are located in the medial-temporal lobe and in the periventricular regions. When very mild AD subjects are included in the dataset, the small (10×10×10 voxels) patches perform best, with the most discriminative ones being located near the left hippocampus. We show that our method is able not only to perform accurate classification, but also to localize dis-criminative brain regions, which are in accordance with the medical literature. This is achieved without the need to segment-specific brain structures and without performing nonlinear registration to a template, indicating that the method may be suitable for a clinical implementation that can help to diagnose AD at an earlier stage.

The function of neurocognitive networks. Comment on “Understanding brain networks and brain organization” by Pessoa

NASA Astrophysics Data System (ADS)

Bressler, Steven L.

2014-09-01

Pessoa [5] has performed a valuable service by reviewing the extant literature on brain networks and making a number of interesting proposals about their cognitive function. The term function is at the core of understanding the brain networks of cognition, or neurocognitive networks (NCNs) [1]. The great Russian neuropsychologist, Luria [4], defined brain function as the common task executed by a distributed brain network of complex dynamic structures united by the demands of cognition. Casting Luria in a modern light, we can say that function emerges from the interactions of brain regions in NCNs as they dynamically self-organize according to cognitive demands. Pessoa rightly details the mapping between brain function and structure, emphasizing both its pluripotency (one structure having multiple functions) and degeneracy (many structures having the same function). However, he fails to consider the potential importance of a one-to-one mapping between NCNs and function. If NCNs are uniquely composed of specific collections of brain areas, then each NCN has a unique function determined by that composition.

4-dimensional functional profiling in the convulsant-treated larval zebrafish brain.

PubMed

Winter, Matthew J; Windell, Dylan; Metz, Jeremy; Matthews, Peter; Pinion, Joe; Brown, Jonathan T; Hetheridge, Malcolm J; Ball, Jonathan S; Owen, Stewart F; Redfern, Will S; Moger, Julian; Randall, Andrew D; Tyler, Charles R

2017-07-26

Functional neuroimaging, using genetically-encoded Ca 2+ sensors in larval zebrafish, offers a powerful combination of high spatiotemporal resolution and higher vertebrate relevance for quantitative neuropharmacological profiling. Here we use zebrafish larvae with pan-neuronal expression of GCaMP6s, combined with light sheet microscopy and a novel image processing pipeline, for the 4D profiling of chemoconvulsant action in multiple brain regions. In untreated larvae, regions associated with autonomic functionality, sensory processing and stress-responsiveness, consistently exhibited elevated spontaneous activity. The application of drugs targeting different convulsant mechanisms (4-Aminopyridine, Pentylenetetrazole, Pilocarpine and Strychnine) resulted in distinct spatiotemporal patterns of activity. These activity patterns showed some interesting parallels with what is known of the distribution of their respective molecular targets, but crucially also revealed system-wide neural circuit responses to stimulation or suppression. Drug concentration-response curves of neural activity were identified in a number of anatomically-defined zebrafish brain regions, and in vivo larval electrophysiology, also conducted in 4dpf larvae, provided additional measures of neural activity. Our quantification of network-wide chemoconvulsant drug activity in the whole zebrafish brain illustrates the power of this approach for neuropharmacological profiling in applications ranging from accelerating studies of drug safety and efficacy, to identifying pharmacologically-altered networks in zebrafish models of human neurological disorders.

Machine Learning Classification of Cirrhotic Patients with and without Minimal Hepatic Encephalopathy Based on Regional Homogeneity of Intrinsic Brain Activity.

PubMed

Chen, Qiu-Feng; Chen, Hua-Jun; Liu, Jun; Sun, Tao; Shen, Qun-Tai

2016-01-01

Machine learning-based approaches play an important role in examining functional magnetic resonance imaging (fMRI) data in a multivariate manner and extracting features predictive of group membership. This study was performed to assess the potential for measuring brain intrinsic activity to identify minimal hepatic encephalopathy (MHE) in cirrhotic patients, using the support vector machine (SVM) method. Resting-state fMRI data were acquired in 16 cirrhotic patients with MHE and 19 cirrhotic patients without MHE. The regional homogeneity (ReHo) method was used to investigate the local synchrony of intrinsic brain activity. Psychometric Hepatic Encephalopathy Score (PHES) was used to define MHE condition. SVM-classifier was then applied using leave-one-out cross-validation, to determine the discriminative ReHo-map for MHE. The discrimination map highlights a set of regions, including the prefrontal cortex, anterior cingulate cortex, anterior insular cortex, inferior parietal lobule, precentral and postcentral gyri, superior and medial temporal cortices, and middle and inferior occipital gyri. The optimized discriminative model showed total accuracy of 82.9% and sensitivity of 81.3%. Our results suggested that a combination of the SVM approach and brain intrinsic activity measurement could be helpful for detection of MHE in cirrhotic patients.

Structure-function analysis of genetically defined neuronal populations.

PubMed

Groh, Alexander; Krieger, Patrik

2013-10-01

Morphological and functional classification of individual neurons is a crucial aspect of the characterization of neuronal networks. Systematic structural and functional analysis of individual neurons is now possible using transgenic mice with genetically defined neurons that can be visualized in vivo or in brain slice preparations. Genetically defined neurons are useful for studying a particular class of neurons and also for more comprehensive studies of the neuronal content of a network. Specific subsets of neurons can be identified by fluorescence imaging of enhanced green fluorescent protein (eGFP) or another fluorophore expressed under the control of a cell-type-specific promoter. The advantages of such genetically defined neurons are not only their homogeneity and suitability for systematic descriptions of networks, but also their tremendous potential for cell-type-specific manipulation of neuronal networks in vivo. This article describes a selection of procedures for visualizing and studying the anatomy and physiology of genetically defined neurons in transgenic mice. We provide information about basic equipment, reagents, procedures, and analytical approaches for obtaining three-dimensional (3D) cell morphologies and determining the axonal input and output of genetically defined neurons. We exemplify with genetically labeled cortical neurons, but the procedures are applicable to other brain regions with little or no alterations.

Brain Growth Rate Abnormalities Visualized in Adolescents with Autism

PubMed Central

Hua, Xue; Thompson, Paul M.; Leow, Alex D.; Madsen, Sarah K.; Caplan, Rochelle; Alger, Jeffry R.; O’Neill, Joseph; Joshi, Kishori; Smalley, Susan L.; Toga, Arthur W.; Levitt, Jennifer G.

2014-01-01

Autism spectrum disorder (ASD) is a heterogeneous disorder of brain development with wide-ranging cognitive deficits. Typically diagnosed before age 3, ASD is behaviorally defined but patients are thought to have protracted alterations in brain maturation. With longitudinal magnetic resonance imaging (MRI), we mapped an anomalous developmental trajectory of the brains of autistic compared to those of typically developing children and adolescents. Using tensor-based morphometry (TBM), we created 3D maps visualizing regional tissue growth rates based on longitudinal brain MRI scans of 13 autistic and 7 typically developing boys (mean age/inter-scan interval: autism 12.0 ± 2.3 years/2.9 ± 0.9 years; control 12.3 ± 2.4/2.8 ± 0.8). The typically developing boys demonstrated strong whole-brain white matter growth during this period, but the autistic boys showed abnormally slowed white matter development (p = 0.03, corrected), especially in the parietal (p = 0.008), temporal (p = 0.03) and occipital lobes (p =0.02). We also visualized abnormal overgrowth in autism in some gray matter structures, such as the putamen and anterior cingulate cortex. Our findings reveal aberrant growth rates in brain regions implicated in social impairment, communication deficits and repetitive behaviors in autism, suggesting that growth rate abnormalities persist into adolescence. TBM revealed persisting growth rate anomalies long after diagnosis, which has implications for evaluation of therapeutic effects. PMID:22021093

Brain growth rate abnormalities visualized in adolescents with autism.

PubMed

Hua, Xue; Thompson, Paul M; Leow, Alex D; Madsen, Sarah K; Caplan, Rochelle; Alger, Jeffry R; O'Neill, Joseph; Joshi, Kishori; Smalley, Susan L; Toga, Arthur W; Levitt, Jennifer G

2013-02-01

Autism spectrum disorder is a heterogeneous disorder of brain development with wide ranging cognitive deficits. Typically diagnosed before age 3, autism spectrum disorder is behaviorally defined but patients are thought to have protracted alterations in brain maturation. With longitudinal magnetic resonance imaging (MRI), we mapped an anomalous developmental trajectory of the brains of autistic compared with those of typically developing children and adolescents. Using tensor-based morphometry, we created 3D maps visualizing regional tissue growth rates based on longitudinal brain MRI scans of 13 autistic and seven typically developing boys (mean age/interscan interval: autism 12.0 ± 2.3 years/2.9 ± 0.9 years; control 12.3 ± 2.4/2.8 ± 0.8). The typically developing boys demonstrated strong whole brain white matter growth during this period, but the autistic boys showed abnormally slowed white matter development (P = 0.03, corrected), especially in the parietal (P = 0.008), temporal (P = 0.03), and occipital lobes (P = 0.02). We also visualized abnormal overgrowth in autism in gray matter structures such as the putamen and anterior cingulate cortex. Our findings reveal aberrant growth rates in brain regions implicated in social impairment, communication deficits and repetitive behaviors in autism, suggesting that growth rate abnormalities persist into adolescence. Tensor-based morphometry revealed persisting growth rate anomalies long after diagnosis, which has implications for evaluation of therapeutic effects. Copyright © 2011 Wiley Periodicals, Inc.

Distribution of Non-Persistent Endocrine Disruptors in Two Different Regions of the Human Brain

PubMed Central

van der Meer, Thomas P.; Artacho-Cordón, Francisco; Swaab, Dick F.; Struik, Dicky; Makris, Konstantinos C.; Wolffenbuttel, Bruce H. R.; Frederiksen, Hanne; van Vliet-Ostaptchouk, Jana V.

2017-01-01

Non-persistent endocrine disrupting chemicals (npEDCs) can affect multiple organs and systems in the body. Whether npEDCs can accumulate in the human brain is largely unknown. The major aim of this pilot study was to examine the presence of environmental phenols and parabens in two distinct brain regions: the hypothalamus and white-matter tissue. In addition, a potential association between these npEDCs concentrations and obesity was investigated. Post-mortem brain material was obtained from 24 individuals, made up of 12 obese and 12 normal-weight subjects (defined as body mass index (BMI) > 30 and BMI < 25 kg/m2, respectively). Nine phenols and seven parabens were measured by isotope dilution TurboFlow-LC-MS/MS. In the hypothalamus, seven suspect npEDCs (bisphenol A, triclosan, triclocarban and methyl-, ethyl-, n-propyl-, and benzyl paraben) were detected, while five npEDCs (bisphenol A, benzophenone-3, triclocarban, methyl-, and n-propyl paraben) were found in the white-matter brain tissue. We observed higher levels of methylparaben (MeP) in the hypothalamic tissue of obese subjects as compared to controls (p = 0.008). Our findings indicate that some suspected npEDCs are able to cross the blood–brain barrier. Whether the presence of npEDCs can adversely affect brain function and to which extent the detected concentrations are physiologically relevant needs to be further investigated. PMID:28902174

An extensive assessment of network alignment algorithms for comparison of brain connectomes.

PubMed

Milano, Marianna; Guzzi, Pietro Hiram; Tymofieva, Olga; Xu, Duan; Hess, Christofer; Veltri, Pierangelo; Cannataro, Mario

2017-06-06

Recently the study of the complex system of connections in neural systems, i.e. the connectome, has gained a central role in neurosciences. The modeling and analysis of connectomes are therefore a growing area. Here we focus on the representation of connectomes by using graph theory formalisms. Macroscopic human brain connectomes are usually derived from neuroimages; the analyzed brains are co-registered in the image domain and brought to a common anatomical space. An atlas is then applied in order to define anatomically meaningful regions that will serve as the nodes of the network - this process is referred to as parcellation. The atlas-based parcellations present some known limitations in cases of early brain development and abnormal anatomy. Consequently, it has been recently proposed to perform atlas-free random brain parcellation into nodes and align brains in the network space instead of the anatomical image space, as a way to deal with the unknown correspondences of the parcels. Such process requires modeling of the brain using graph theory and the subsequent comparison of the structure of graphs. The latter step may be modeled as a network alignment (NA) problem. In this work, we first define the problem formally, then we test six existing state of the art of network aligners on diffusion MRI-derived brain networks. We compare the performances of algorithms by assessing six topological measures. We also evaluated the robustness of algorithms to alterations of the dataset. The results confirm that NA algorithms may be applied in cases of atlas-free parcellation for a fully network-driven comparison of connectomes. The analysis shows MAGNA++ is the best global alignment algorithm. The paper presented a new analysis methodology that uses network alignment for validating atlas-free parcellation brain connectomes. The methodology has been experimented on several brain datasets.

Decoding negative affect personality trait from patterns of brain activation to threat stimuli.

PubMed

Fernandes, Orlando; Portugal, Liana C L; Alves, Rita de Cássia S; Arruda-Sanchez, Tiago; Rao, Anil; Volchan, Eliane; Pereira, Mirtes; Oliveira, Letícia; Mourao-Miranda, Janaina

2017-01-15

Pattern recognition analysis (PRA) applied to functional magnetic resonance imaging (fMRI) has been used to decode cognitive processes and identify possible biomarkers for mental illness. In the present study, we investigated whether the positive affect (PA) or negative affect (NA) personality traits could be decoded from patterns of brain activation in response to a human threat using a healthy sample. fMRI data from 34 volunteers (15 women) were acquired during a simple motor task while the volunteers viewed a set of threat stimuli that were directed either toward them or away from them and matched neutral pictures. For each participant, contrast images from a General Linear Model (GLM) between the threat versus neutral stimuli defined the spatial patterns used as input to the regression model. We applied a multiple kernel learning (MKL) regression combining information from different brain regions hierarchically in a whole brain model to decode the NA and PA from patterns of brain activation in response to threat stimuli. The MKL model was able to decode NA but not PA from the contrast images between threat stimuli directed away versus neutral with a significance above chance. The correlation and the mean squared error (MSE) between predicted and actual NA were 0.52 (p-value=0.01) and 24.43 (p-value=0.01), respectively. The MKL pattern regression model identified a network with 37 regions that contributed to the predictions. Some of the regions were related to perception (e.g., occipital and temporal regions) while others were related to emotional evaluation (e.g., caudate and prefrontal regions). These results suggest that there was an interaction between the individuals' NA and the brain response to the threat stimuli directed away, which enabled the MKL model to decode NA from the brain patterns. To our knowledge, this is the first evidence that PRA can be used to decode a personality trait from patterns of brain activation during emotional contexts. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Glucose hypometabolism is highly localized, but lower cortical thickness and brain atrophy are widespread in cognitively normal older adults.

PubMed

Nugent, Scott; Castellano, Christian-Alexandre; Goffaux, Philippe; Whittingstall, Kevin; Lepage, Martin; Paquet, Nancy; Bocti, Christian; Fulop, Tamas; Cunnane, Stephen C

2014-06-01

Several studies have suggested that glucose hypometabolism may be present in specific brain regions in cognitively normal older adults and could contribute to the risk of subsequent cognitive decline. However, certain methodological shortcomings, including a lack of partial volume effect (PVE) correction or insufficient cognitive testing, confound the interpretation of most studies on this topic. We combined [(18)F]fluorodeoxyglucose ([(18)F]FDG) positron emission tomography (PET) and magnetic resonance (MR) imaging to quantify cerebral metabolic rate of glucose (CMRg) as well as cortical volume and thickness in 43 anatomically defined brain regions from a group of cognitively normal younger (25 ± 3 yr old; n = 25) and older adults (71 ± 9 yr old; n = 31). After correcting for PVE, we observed 11-17% lower CMRg in three specific brain regions of the older group: the superior frontal cortex, the caudal middle frontal cortex, and the caudate (P ≤ 0.01 false discovery rate-corrected). In the older group, cortical volumes and cortical thickness were 13-33 and 7-18% lower, respectively, in multiple brain regions (P ≤ 0.01 FDR correction). There were no differences in CMRg between individuals who were or were not prescribed antihypertensive medication. There were no significant correlations between CMRg and cognitive performance or metabolic parameters measured in fasting plasma. We conclude that highly localized glucose hypometabolism and widespread cortical thinning and atrophy can be present in older adults who are cognitively normal, as assessed using age-normed neuropsychological testing measures. Copyright © 2014 the American Physiological Society.

Non-coding-regulatory regions of human brain genes delineated by bacterial artificial chromosome knock-in mice.

PubMed

Schmouth, Jean-François; Castellarin, Mauro; Laprise, Stéphanie; Banks, Kathleen G; Bonaguro, Russell J; McInerny, Simone C; Borretta, Lisa; Amirabbasi, Mahsa; Korecki, Andrea J; Portales-Casamar, Elodie; Wilson, Gary; Dreolini, Lisa; Jones, Steven J M; Wasserman, Wyeth W; Goldowitz, Daniel; Holt, Robert A; Simpson, Elizabeth M

2013-10-14

The next big challenge in human genetics is understanding the 98% of the genome that comprises non-coding DNA. Hidden in this DNA are sequences critical for gene regulation, and new experimental strategies are needed to understand the functional role of gene-regulation sequences in health and disease. In this study, we build upon our HuGX ('high-throughput human genes on the X chromosome') strategy to expand our understanding of human gene regulation in vivo. In all, ten human genes known to express in therapeutically important brain regions were chosen for study. For eight of these genes, human bacterial artificial chromosome clones were identified, retrofitted with a reporter, knocked single-copy into the Hprt locus in mouse embryonic stem cells, and mouse strains derived. Five of these human genes expressed in mouse, and all expressed in the adult brain region for which they were chosen. This defined the boundaries of the genomic DNA sufficient for brain expression, and refined our knowledge regarding the complexity of gene regulation. We also characterized for the first time the expression of human MAOA and NR2F2, two genes for which the mouse homologs have been extensively studied in the central nervous system (CNS), and AMOTL1 and NOV, for which roles in CNS have been unclear. We have demonstrated the use of the HuGX strategy to functionally delineate non-coding-regulatory regions of therapeutically important human brain genes. Our results also show that a careful investigation, using publicly available resources and bioinformatics, can lead to accurate predictions of gene expression.

Atlas based brain volumetry: How to distinguish regional volume changes due to biological or physiological effects from inherent noise of the methodology.

PubMed

Opfer, Roland; Suppa, Per; Kepp, Timo; Spies, Lothar; Schippling, Sven; Huppertz, Hans-Jürgen

2016-05-01

Fully-automated regional brain volumetry based on structural magnetic resonance imaging (MRI) plays an important role in quantitative neuroimaging. In clinical trials as well as in clinical routine multiple MRIs of individual patients at different time points need to be assessed longitudinally. Measures of inter- and intrascanner variability are crucial to understand the intrinsic variability of the method and to distinguish volume changes due to biological or physiological effects from inherent noise of the methodology. To measure regional brain volumes an atlas based volumetry (ABV) approach was deployed using a highly elastic registration framework and an anatomical atlas in a well-defined template space. We assessed inter- and intrascanner variability of the method in 51 cognitively normal subjects and 27 Alzheimer dementia (AD) patients from the Alzheimer's Disease Neuroimaging Initiative by studying volumetric results of repeated scans for 17 compartments and brain regions. Median percentage volume differences of scan-rescans from the same scanner ranged from 0.24% (whole brain parenchyma in healthy subjects) to 1.73% (occipital lobe white matter in AD), with generally higher differences in AD patients as compared to normal subjects (e.g., 1.01% vs. 0.78% for the hippocampus). Minimum percentage volume differences detectable with an error probability of 5% were in the one-digit percentage range for almost all structures investigated, with most of them being below 5%. Intrascanner variability was independent of magnetic field strength. The median interscanner variability was up to ten times higher than the intrascanner variability. Copyright © 2016 Elsevier Inc. All rights reserved.

Using Individualized Brain Network for Analyzing Structural Covariance of the Cerebral Cortex in Alzheimer's Patients.

PubMed

Kim, Hee-Jong; Shin, Jeong-Hyeon; Han, Cheol E; Kim, Hee Jin; Na, Duk L; Seo, Sang Won; Seong, Joon-Kyung

2016-01-01

Cortical thinning patterns in Alzheimer's disease (AD) have been widely reported through conventional regional analysis. In addition, the coordinated variance of cortical thickness in different brain regions has been investigated both at the individual and group network levels. In this study, we aim to investigate network architectural characteristics of a structural covariance network (SCN) in AD, and further to show that the structural covariance connectivity becomes disorganized across the brain regions in AD, while the normal control (NC) subjects maintain more clustered and consistent coordination in cortical atrophy variations. We generated SCNs directly from T1-weighted MR images of individual patients using surface-based cortical thickness data, with structural connectivity defined as similarity in cortical thickness within different brain regions. Individual SCNs were constructed using morphometric data from the Samsung Medical Center (SMC) dataset. The structural covariance connectivity showed higher clustering than randomly generated networks, as well as similar minimum path lengths, indicating that the SCNs are "small world." There were significant difference between NC and AD group in characteristic path lengths (z = -2.97, p < 0.01) and small-worldness values (z = 4.05, p < 0.01). Clustering coefficients in AD was smaller than that of NC but there was no significant difference (z = 1.81, not significant). We further observed that the AD patients had significantly disrupted structural connectivity. We also show that the coordinated variance of cortical thickness is distributed more randomly from one region to other regions in AD patients when compared to NC subjects. Our proposed SCN may provide surface-based measures for understanding interaction between two brain regions with co-atrophy of the cerebral cortex due to normal aging or AD. We applied our method to the AD Neuroimaging Initiative (ADNI) data to show consistency in results with the SMC dataset.

Regional Gray Matter Density Associated with Cognitive Reflectivity–Impulsivity: Evidence from Voxel-Based Morphometry

PubMed Central

Yokoyama, Ryoichi; Nozawa, Takayuki; Takeuchi, Hikaru; Taki, Yasuyuki; Sekiguchi, Atsushi; Nouchi, Rui; Kotozaki, Yuka; Nakagawa, Seishu; Miyauchi, Carlos Makoto; Iizuka, Kunio; Shinada, Takamitsu; Yamamoto, Yuki; Hanawa, Sugiko; Araki, Tsuyoshi; Hashizume, Hiroshi; Kunitoki, Keiko; Hanihara, Mayu; Sassa, Yuko; Kawashima, Ryuta

2015-01-01

When faced with a problem or choice, humans can use two different strategies: “cognitive reflectivity,” which involves slow responses and fewer mistakes, or “cognitive impulsivity,” which comprises of quick responses and more mistakes. Different individuals use these two strategies differently. To our knowledge, no study has directly investigated the brain regions involved in reflectivity–impulsivity; therefore, this study focused on associations between these cognitive strategies and the gray matter structure of several brain regions. In order to accomplish this, we enrolled 776 healthy, right-handed individuals (432 men and 344 women; 20.7 ± 1.8 years) and used voxel-based morphometry with administration of a cognitive reflectivity–impulsivity questionnaire. We found that high cognitive reflectivity was associated with greater regional gray matter density in the ventral medial prefrontal cortex. Our finding suggests that this area plays an important role in defining an individual’s trait associated with reflectivity and impulsivity. PMID:25803809

Multivariate dynamical modelling of structural change during development.

PubMed

Ziegler, Gabriel; Ridgway, Gerard R; Blakemore, Sarah-Jayne; Ashburner, John; Penny, Will

2017-02-15

Here we introduce a multivariate framework for characterising longitudinal changes in structural MRI using dynamical systems. The general approach enables modelling changes of states in multiple imaging biomarkers typically observed during brain development, plasticity, ageing and degeneration, e.g. regional gray matter volume of multiple regions of interest (ROIs). Structural brain states follow intrinsic dynamics according to a linear system with additional inputs accounting for potential driving forces of brain development. In particular, the inputs to the system are specified to account for known or latent developmental growth/decline factors, e.g. due to effects of growth hormones, puberty, or sudden behavioural changes etc. Because effects of developmental factors might be region-specific, the sensitivity of each ROI to contributions of each factor is explicitly modelled. In addition to the external effects of developmental factors on regional change, the framework enables modelling and inference about directed (potentially reciprocal) interactions between brain regions, due to competition for space, or structural connectivity, and suchlike. This approach accounts for repeated measures in typical MRI studies of development and aging. Model inversion and posterior distributions are obtained using earlier established variational methods enabling Bayesian evidence-based comparisons between various models of structural change. Using this approach we demonstrate dynamic cortical changes during brain maturation between 6 and 22 years of age using a large openly available longitudinal paediatric dataset with 637 scans from 289 individuals. In particular, we model volumetric changes in 26 bilateral ROIs, which cover large portions of cortical and subcortical gray matter. We account for (1) puberty-related effects on gray matter regions; (2) effects of an early transient growth process with additional time-lag parameter; (3) sexual dimorphism by modelling parameter differences between boys and girls. There is evidence that the regional pattern of sensitivity to dynamic hidden growth factors in late childhood is similar across genders and shows a consistent anterior-posterior gradient with strongest impact to prefrontal cortex (PFC) brain changes. Finally, we demonstrate the potential of the framework to explore the coupling of structural changes across a priori defined subnetworks using an example of previously established resting state functional connectivity. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

A voxelwise approach to determine consensus regions-of-interest for the study of brain network plasticity.

PubMed

Rajtmajer, Sarah M; Roy, Arnab; Albert, Reka; Molenaar, Peter C M; Hillary, Frank G

2015-01-01

Despite exciting advances in the functional imaging of the brain, it remains a challenge to define regions of interest (ROIs) that do not require investigator supervision and permit examination of change in networks over time (or plasticity). Plasticity is most readily examined by maintaining ROIs constant via seed-based and anatomical-atlas based techniques, but these approaches are not data-driven, requiring definition based on prior experience (e.g., choice of seed-region, anatomical landmarks). These approaches are limiting especially when functional connectivity may evolve over time in areas that are finer than known anatomical landmarks or in areas outside predetermined seeded regions. An ideal method would permit investigators to study network plasticity due to learning, maturation effects, or clinical recovery via multiple time point data that can be compared to one another in the same ROI while also preserving the voxel-level data in those ROIs at each time point. Data-driven approaches (e.g., whole-brain voxelwise approaches) ameliorate concerns regarding investigator bias, but the fundamental problem of comparing the results between distinct data sets remains. In this paper we propose an approach, aggregate-initialized label propagation (AILP), which allows for data at separate time points to be compared for examining developmental processes resulting in network change (plasticity). To do so, we use a whole-brain modularity approach to parcellate the brain into anatomically constrained functional modules at separate time points and then apply the AILP algorithm to form a consensus set of ROIs for examining change over time. To demonstrate its utility, we make use of a known dataset of individuals with traumatic brain injury sampled at two time points during the first year of recovery and show how the AILP procedure can be applied to select regions of interest to be used in a graph theoretical analysis of plasticity.

Regional Delivery of Chimeric Antigen Receptor-Engineered T Cells Effectively Targets HER2+ Breast Cancer Metastasis to the Brain.

PubMed

Priceman, Saul J; Tilakawardane, Dileshni; Jeang, Brook; Aguilar, Brenda; Murad, John P; Park, Anthony K; Chang, Wen-Chung; Ostberg, Julie R; Neman, Josh; Jandial, Rahul; Portnow, Jana; Forman, Stephen J; Brown, Christine E

2018-01-01

Purpose: Metastasis to the brain from breast cancer remains a significant clinical challenge, and may be targeted with CAR-based immunotherapy. CAR design optimization for solid tumors is crucial due to the absence of truly restricted antigen expression and potential safety concerns with "on-target off-tumor" activity. Here, we have optimized HER2-CAR T cells for the treatment of breast to brain metastases, and determined optimal second-generation CAR design and route of administration for xenograft mouse models of breast metastatic brain tumors, including multifocal and leptomeningeal disease. Experimental Design: HER2-CAR constructs containing either CD28 or 4-1BB intracellular costimulatory signaling domains were compared for functional activity in vitro by measuring cytokine production, T-cell proliferation, and tumor killing capacity. We also evaluated HER2-CAR T cells delivered by intravenous, local intratumoral, or regional intraventricular routes of administration using in vivo human xenograft models of breast cancer that have metastasized to the brain. Results: Here, we have shown that HER2-CARs containing the 4-1BB costimulatory domain confer improved tumor targeting with reduced T-cell exhaustion phenotype and enhanced proliferative capacity compared with HER2-CARs containing the CD28 costimulatory domain. Local intracranial delivery of HER2-CARs showed potent in vivo antitumor activity in orthotopic xenograft models. Importantly, we demonstrated robust antitumor efficacy following regional intraventricular delivery of HER2-CAR T cells for the treatment of multifocal brain metastases and leptomeningeal disease. Conclusions: Our study shows the importance of CAR design in defining an optimized CAR T cell, and highlights intraventricular delivery of HER2-CAR T cells for treating multifocal brain metastases. Clin Cancer Res; 24(1); 95-105. ©2017 AACR . ©2017 American Association for Cancer Research.

Disruption of functional networks in dyslexia: a whole-brain, data-driven analysis of connectivity.

PubMed

Finn, Emily S; Shen, Xilin; Holahan, John M; Scheinost, Dustin; Lacadie, Cheryl; Papademetris, Xenophon; Shaywitz, Sally E; Shaywitz, Bennett A; Constable, R Todd

2014-09-01

Functional connectivity analyses of functional magnetic resonance imaging data are a powerful tool for characterizing brain networks and how they are disrupted in neural disorders. However, many such analyses examine only one or a small number of a priori seed regions. Studies that consider the whole brain frequently rely on anatomic atlases to define network nodes, which might result in mixing distinct activation time-courses within a single node. Here, we improve upon previous methods by using a data-driven brain parcellation to compare connectivity profiles of dyslexic (DYS) versus non-impaired (NI) readers in the first whole-brain functional connectivity analysis of dyslexia. Whole-brain connectivity was assessed in children (n = 75; 43 NI, 32 DYS) and adult (n = 104; 64 NI, 40 DYS) readers. Compared to NI readers, DYS readers showed divergent connectivity within the visual pathway and between visual association areas and prefrontal attention areas; increased right-hemisphere connectivity; reduced connectivity in the visual word-form area (part of the left fusiform gyrus specialized for printed words); and persistent connectivity to anterior language regions around the inferior frontal gyrus. Together, findings suggest that NI readers are better able to integrate visual information and modulate their attention to visual stimuli, allowing them to recognize words on the basis of their visual properties, whereas DYS readers recruit altered reading circuits and rely on laborious phonology-based "sounding out" strategies into adulthood. These results deepen our understanding of the neural basis of dyslexia and highlight the importance of synchrony between diverse brain regions for successful reading. © 2013 Society of Biological Psychiatry Published by Society of Biological Psychiatry All rights reserved.

[Mental Space Navigation and Mental Time Travel].

PubMed

Kawamura, Mitsuru

2017-11-01

We examined patients with mental space navigation or mental time travel disorder to identify regions in the brain that may play a critical role in mental time travel in terms of clinical neuropsychology. These regions included the precneus, posterior cingulate gyrus, retrosplenial cortex, and hippocampus, as well as the orbitofrontal cortex: the anterior and posterior medial areas were both shown to be important in this process. Further studies are required to define whether these form a network for mental time travel.

Social Perception in Infancy: A Near Infrared Spectroscopy Study

ERIC Educational Resources Information Center

Lloyd-Fox, Sarah; Blasi, Anna; Volein, Agnes; Everdell, Nick; Elwell, Claire E.; Johnson, Mark H.

2009-01-01

The capacity to engage and communicate in a social world is one of the defining characteristics of the human species. While the network of regions that compose the social brain have been the subject of extensive research in adults, there are limited techniques available for monitoring young infants. This study used near infrared spectroscopy to…

Molecular mechanisms of synaptic remodeling in alcoholism

PubMed Central

Kyzar, Evan J.; Pandey, Subhash C.

2015-01-01

Alcohol use and alcohol addiction represent dysfunctional brain circuits resulting from neuroadaptive changes during protracted alcohol exposure and its withdrawal. Alcohol exerts a potent effect on synaptic plasticity and dendritic spine formation in specific brain regions, providing a neuroanatomical substrate for the pathophysiology of alcoholism. Epigenetics has recently emerged as a critical regulator of gene expression and synaptic plasticity-related events in the brain. Alcohol exposure and withdrawal induce changes in crucial epigenetic processes in the emotional brain circuitry (amygdala) that may be relevant to the negative affective state defined as the “dark side” of addiction. Here, we review the literature concerning synaptic plasticity and epigenetics, with a particular focus on molecular events related to dendritic remodeling during alcohol abuse and alcoholism. Targeting epigenetic processes that modulate synaptic plasticity may yield novel treatments for alcoholism. PMID:25623036

Benevolent sexism alters executive brain responses.

PubMed

Dardenne, Benoit; Dumont, Muriel; Sarlet, Marie; Phillips, Christophe; Balteau, Evelyne; Degueldre, Christian; Luxen, André; Salmon, Eric; Maquet, Pierre; Collette, Fabienne

2013-07-10

Benevolence is widespread in our societies. It is defined as considering a subordinate group nicely but condescendingly, that is, with charity. Deleterious consequences for the target have been reported in the literature. In this experiment, we used functional MRI (fMRI) to identify whether being the target of (sexist) benevolence induces changes in brain activity associated with a working memory task. Participants were confronted by benevolent, hostile, or neutral comments before and while performing a reading span test in an fMRI environment. fMRI data showed that brain regions associated previously with intrusive thought suppression (bilateral, dorsolateral, prefrontal, and anterior cingulate cortex) reacted specifically to benevolent sexism compared with hostile sexism and neutral conditions during the performance of the task. These findings indicate that, despite being subjectively positive, benevolence modifies task-related brain networks by recruiting supplementary areas likely to impede optimal cognitive performance.

Molecular mechanisms of synaptic remodeling in alcoholism.

PubMed

Kyzar, Evan J; Pandey, Subhash C

2015-08-05

Alcohol use and alcohol addiction represent dysfunctional brain circuits resulting from neuroadaptive changes during protracted alcohol exposure and its withdrawal. Alcohol exerts a potent effect on synaptic plasticity and dendritic spine formation in specific brain regions, providing a neuroanatomical substrate for the pathophysiology of alcoholism. Epigenetics has recently emerged as a critical regulator of gene expression and synaptic plasticity-related events in the brain. Alcohol exposure and withdrawal induce changes in crucial epigenetic processes in the emotional brain circuitry (amygdala) that may be relevant to the negative affective state defined as the "dark side" of addiction. Here, we review the literature concerning synaptic plasticity and epigenetics, with a particular focus on molecular events related to dendritic remodeling during alcohol abuse and alcoholism. Targeting epigenetic processes that modulate synaptic plasticity may yield novel treatments for alcoholism. Published by Elsevier Ireland Ltd.

Relationship Between Surface-Based Brain Morphometric Measures and Intelligence in Autism Spectrum Disorders: Influence of History of Language Delay.

PubMed

Balardin, Joana Bisol; Sato, João Ricardo; Vieira, Gilson; Feng, Yeu; Daly, Eileen; Murphy, Clodagh; Murphy, Declan; Ecker, Christine

2015-10-01

Autism spectrum disorders (ASD) are a group of conditions that show abnormalities in the neuroanatomy of multiple brain regions. The variability in the development of intelligence and language among individuals on the autism spectrum has long been acknowledged, but it remains unknown whether these differences impact on the neuropathology of ASD. In this study, we aimed to compare associations between surface-based regional brain measures and general intelligence (IQ) scores in ASD individuals with and without a history of language delay. We included 64 ASD adults of normal intelligence (37 without a history of language delay and 27 with a history of language delay and 80 neurotypicals). Regions with a significant association between verbal and nonverbal IQ and measures of cortical thickness (CT), surface area, and cortical volume were first identified in the combined sample of individuals with ASD and controls. Thicker dorsal frontal and temporal cortices, and thinner lateral orbital frontal and parieto-occipital cortices were associated with greater and lower verbal IQ scores, respectively. Correlations between cortical volume and verbal IQ were observed in similar regions as revealed by the CT analysis. A significant difference between ASD individuals with and without a history of language delay in the association between CT and verbal IQ was evident in the parieto-occipital region. These results indicate that ASD subgroups defined on the basis of differential language trajectories in childhood can have different associations between verbal IQ and brain measures in adulthood despite achieving similar levels of cognitive performance. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

Brain Activation During Autobiographical Memory Retrieval with Special Reference to Default Mode Network

PubMed Central

Ino, Tadashi; Nakai, Ryusuke; Azuma, Takashi; Kimura, Toru; Fukuyama, Hidenao

2011-01-01

Recent neuroimaging studies have suggested that brain regions activated during retrieval of autobiographical memory (ABM) overlap with the default mode network (DMN), which shows greater activation during rest than cognitively demanding tasks and is considered to be involved in self-referential processing. However, detailed overlap and segregation between ABM and DMN remain unclear. This fMRI study focuses first on revealing components of the DMN which are related to ABM and those which are unrelated to ABM, and second on extracting the neural bases which are specifically devoted to ABM. Brain activities relative to rest during three tasks matched in task difficulty assessed by reaction time were investigated by fMRI; category cued recall from ABM, category cued recall from semantic memory, and number counting task. We delineated the overlap between the regions that showed less activation during semantic memory and number counting relative to rest, which correspond to the DMN, and the areas that showed greater or less activation during ABM relative to rest. ABM-specific activation was defined as the overlap between the contrast of ABM versus rest and the contrast of ABM versus semantic memory. The fMRI results showed that greater activation as well as less activation during ABM relative to rest overlapped considerably with the DMN, indicating that the DMN is segregated to the regions which are functionally related to ABM and the regions which are unrelated to ABM. ABM-specific activation was observed in the left-lateralized brain regions and most of them fell within the DMN. PMID:21643504

Wavelet analysis of head acceleration response under dirac excitation for early oedema detection.

PubMed

Kostopoulos, V; Loutas, T H; Derdas, C; Douzinas, E

2008-04-01

The present work deals with the application of an innovative in-house developed wavelet-based methodology for the analysis of the acceleration responses of a human head complex model as a simulated diffused oedema progresses. The human head complex has been modeled as a structure consisting of three confocal prolate spheroids, whereas the three defined regions by the system of spheroids, from the outside to the inside, represent the scull, the region of cerebrospinal fluid, and the brain tissue. A Dirac-like pulse has been used to excite the human head complex model and the acceleration response of the system has been calculated and analyzed via the wavelet-based methodology. For the purpose of the present analysis, a wave propagation commercial finite element code, LS-DYNA 3D, has been used. The progressive diffused oedema was modeled via consecutive increases in brain volume accompanied by a decrease in brain density. It was shown that even a small increase in brain volume (at the level of 0.5%) can be identified by the effect it has on the vibration characteristics of the human head complex. More precisely, it was found that for some of the wavelet decomposition levels, the energy content changes monotonically as the brain volume increases, thus providing a useful index of monitoring an oncoming brain oedema before any brain damage appears due to uncontrolled intracranial hypertension. For the purpose of the present work and for the levels of brain volume increase considered in the present analysis, no pressure increase was assumed into the cranial vault and, associatively, no brain compliance variation.

Perceptual and categorical decision making: goal-relevant representation of two domains at different levels of abstraction.

PubMed

Shankar, Swetha; Kayser, Andrew S

2017-06-01

To date it has been unclear whether perceptual decision making and rule-based categorization reflect activation of similar cognitive processes and brain regions. On one hand, both map potentially ambiguous stimuli to a smaller set of motor responses. On the other hand, decisions about perceptual salience typically concern concrete sensory representations derived from a noisy stimulus, while categorization is typically conceptualized as an abstract decision about membership in a potentially arbitrary set. Previous work has primarily examined these types of decisions in isolation. Here we independently varied salience in both the perceptual and categorical domains in a random dot-motion framework by manipulating dot-motion coherence and motion direction relative to a category boundary, respectively. Behavioral and modeling results suggest that categorical (more abstract) information, which is more relevant to subjects' decisions, is weighted more strongly than perceptual (more concrete) information, although they also have significant interactive effects on choice. Within the brain, BOLD activity within frontal regions strongly differentiated categorical salience and weakly differentiated perceptual salience; however, the interaction between these two factors activated similar frontoparietal brain networks. Notably, explicitly evaluating feature interactions revealed a frontal-parietal dissociation: parietal activity varied strongly with both features, but frontal activity varied with the combined strength of the information that defined the motor response. Together, these data demonstrate that frontal regions are driven by decision-relevant features and argue that perceptual decisions and rule-based categorization reflect similar cognitive processes and activate similar brain networks to the extent that they define decision-relevant stimulus-response mappings. NEW & NOTEWORTHY Here we study the behavioral and neural dynamics of perceptual categorization when decision information varies in multiple domains at different levels of abstraction. Behavioral and modeling results suggest that categorical (more abstract) information is weighted more strongly than perceptual (more concrete) information but that perceptual and categorical domains interact to influence decisions. Frontoparietal brain activity during categorization flexibly represents decision-relevant features and highlights significant dissociations in frontal and parietal activity during decision making. Copyright © 2017 the American Physiological Society.

Perceptual and categorical decision making: goal-relevant representation of two domains at different levels of abstraction

PubMed Central

Kayser, Andrew S.

2017-01-01

To date it has been unclear whether perceptual decision making and rule-based categorization reflect activation of similar cognitive processes and brain regions. On one hand, both map potentially ambiguous stimuli to a smaller set of motor responses. On the other hand, decisions about perceptual salience typically concern concrete sensory representations derived from a noisy stimulus, while categorization is typically conceptualized as an abstract decision about membership in a potentially arbitrary set. Previous work has primarily examined these types of decisions in isolation. Here we independently varied salience in both the perceptual and categorical domains in a random dot-motion framework by manipulating dot-motion coherence and motion direction relative to a category boundary, respectively. Behavioral and modeling results suggest that categorical (more abstract) information, which is more relevant to subjects’ decisions, is weighted more strongly than perceptual (more concrete) information, although they also have significant interactive effects on choice. Within the brain, BOLD activity within frontal regions strongly differentiated categorical salience and weakly differentiated perceptual salience; however, the interaction between these two factors activated similar frontoparietal brain networks. Notably, explicitly evaluating feature interactions revealed a frontal-parietal dissociation: parietal activity varied strongly with both features, but frontal activity varied with the combined strength of the information that defined the motor response. Together, these data demonstrate that frontal regions are driven by decision-relevant features and argue that perceptual decisions and rule-based categorization reflect similar cognitive processes and activate similar brain networks to the extent that they define decision-relevant stimulus-response mappings. NEW & NOTEWORTHY Here we study the behavioral and neural dynamics of perceptual categorization when decision information varies in multiple domains at different levels of abstraction. Behavioral and modeling results suggest that categorical (more abstract) information is weighted more strongly than perceptual (more concrete) information but that perceptual and categorical domains interact to influence decisions. Frontoparietal brain activity during categorization flexibly represents decision-relevant features and highlights significant dissociations in frontal and parietal activity during decision making. PMID:28250149

Mood-dependent integration in discourse comprehension: happy and sad moods affect consistency processing via different brain networks.

PubMed

Egidi, Giovanna; Caramazza, Alfonso

2014-12-01

According to recent research on language comprehension, the semantic features of a text are not the only determinants of whether incoming information is understood as consistent. Listeners' pre-existing affective states play a crucial role as well. The current fMRI experiment examines the effects of happy and sad moods during comprehension of consistent and inconsistent story endings, focusing on brain regions previously linked to two integration processes: inconsistency detection, evident in stronger responses to inconsistent endings, and fluent processing (accumulation), evident in stronger responses to consistent endings. The analysis evaluated whether differences in the BOLD response for consistent and inconsistent story endings correlated with self-reported mood scores after a mood induction procedure. Mood strongly affected regions previously associated with inconsistency detection. Happy mood increased sensitivity to inconsistency in regions specific for inconsistency detection (e.g., left IFG, left STS), whereas sad mood increased sensitivity to inconsistency in regions less specific for language processing (e.g., right med FG, right SFG). Mood affected more weakly regions involved in accumulation of information. These results show that mood can influence activity in areas mediating well-defined language processes, and highlight that integration is the result of context-dependent mechanisms. The finding that language comprehension can involve different networks depending on people's mood highlights the brain's ability to reorganize its functions. Copyright © 2014 Elsevier Inc. All rights reserved.

Episodic reinstatement in the medial temporal lobe.

PubMed

Staresina, Bernhard P; Henson, Richard N A; Kriegeskorte, Nikolaus; Alink, Arjen

2012-12-12

The essence of episodic memory is our ability to reexperience past events in great detail, even in the absence of external stimulus cues. Does the phenomenological reinstatement of past experiences go along with reinstating unique neural representations in the brain? And if so, how is this accomplished by the medial temporal lobe (MTL), a brain region intimately linked to episodic memory? Computational models suggest that such reinstatement (also termed "pattern completion") in cortical regions is mediated by the hippocampus, a key region of the MTL. Although recent functional magnetic resonance imaging studies demonstrated reinstatement of coarse item properties like stimulus category or task context across different brain regions, it has not yet been shown whether reinstatement can be observed at the level of individual, discrete events-arguably the defining feature of episodic memory-nor whether MTL structures like the hippocampus support this "true episodic" reinstatement. Here we show that neural activity patterns for unique word-scene combinations encountered during encoding are reinstated in human parahippocampal cortex (PhC) during retrieval. Critically, this reinstatement occurs when word-scene combinations are successfully recollected (even though the original scene is not visually presented) and does not encompass other stimulus domains (such as word-color associations). Finally, the degree of PhC reinstatement across retrieval events correlated with hippocampal activity, consistent with a role of the hippocampus in coordinating pattern completion in cortical regions.

Neuropathology and Animal Models of Autism: Genetic and Environmental Factors

PubMed Central

Gadad, Bharathi S.; Young, Keith A.; German, Dwight C.

2013-01-01

Autism is a heterogeneous behaviorally defined neurodevelopmental disorder. It is defined by the presence of marked social deficits, specific language abnormalities, and stereotyped repetitive patterns of behavior. Because of the variability in the behavioral phenotype of the disorder among patients, the term autism spectrum disorder has been established. In the first part of this review, we provide an overview of neuropathological findings from studies of autism postmortem brains and identify the cerebellum as one of the key brain regions that can play a role in the autism phenotype. We review research findings that indicate possible links between the environment and autism including the role of mercury and immune-related factors. Because both genes and environment can alter the structure of the developing brain in different ways, it is not surprising that there is heterogeneity in the behavioral and neuropathological phenotypes of autism spectrum disorders. Finally, we describe animal models of autism that occur following insertion of different autism-related genes and exposure to environmental factors, highlighting those models which exhibit both autism-like behavior and neuropathology. PMID:24151553

Functional and anatomical evidence of cerebral tissue hypoxia in young sickle cell anemia mice.

PubMed

Cahill, Lindsay S; Gazdzinski, Lisa M; Tsui, Albert Ky; Zhou, Yu-Qing; Portnoy, Sharon; Liu, Elaine; Mazer, C David; Hare, Gregory Mt; Kassner, Andrea; Sled, John G

2017-03-01

Cerebral ischemia is a significant source of morbidity in children with sickle cell anemia; however, the mechanism of injury is poorly understood. Increased cerebral blood flow and low hemoglobin levels in children with sickle cell anemia are associated with increased stroke risk, suggesting that anemia-induced tissue hypoxia may be an important factor contributing to subsequent morbidity. To better understand the pathophysiology of brain injury, brain physiology and morphology were characterized in a transgenic mouse model, the Townes sickle cell model. Relative to age-matched controls, sickle cell anemia mice demonstrated: (1) decreased brain tissue pO 2 and increased expression of hypoxia signaling protein in the perivascular regions of the cerebral cortex; (2) elevated basal cerebral blood flow , consistent with adaptation to anemia-induced tissue hypoxia; (3) significant reduction in cerebrovascular blood flow reactivity to a hypercapnic challenge; (4) increased diameter of the carotid artery; and (5) significant volume changes in white and gray matter regions in the brain, as assessed by ex vivo magnetic resonance imaging. Collectively, these findings support the hypothesis that brain tissue hypoxia contributes to adaptive physiological and anatomic changes in Townes sickle cell mice. These findings may help define the pathophysiology for stroke in children with sickle cell anemia.

Functional and anatomical evidence of cerebral tissue hypoxia in young sickle cell anemia mice

PubMed Central

Gazdzinski, Lisa M; Tsui, Albert KY; Zhou, Yu-Qing; Portnoy, Sharon; Liu, Elaine; Mazer, C David; Hare, Gregory MT; Kassner, Andrea; Sled, John G

2016-01-01

Cerebral ischemia is a significant source of morbidity in children with sickle cell anemia; however, the mechanism of injury is poorly understood. Increased cerebral blood flow and low hemoglobin levels in children with sickle cell anemia are associated with increased stroke risk, suggesting that anemia-induced tissue hypoxia may be an important factor contributing to subsequent morbidity. To better understand the pathophysiology of brain injury, brain physiology and morphology were characterized in a transgenic mouse model, the Townes sickle cell model. Relative to age-matched controls, sickle cell anemia mice demonstrated: (1) decreased brain tissue pO2 and increased expression of hypoxia signaling protein in the perivascular regions of the cerebral cortex; (2) elevated basal cerebral blood flow , consistent with adaptation to anemia-induced tissue hypoxia; (3) significant reduction in cerebrovascular blood flow reactivity to a hypercapnic challenge; (4) increased diameter of the carotid artery; and (5) significant volume changes in white and gray matter regions in the brain, as assessed by ex vivo magnetic resonance imaging. Collectively, these findings support the hypothesis that brain tissue hypoxia contributes to adaptive physiological and anatomic changes in Townes sickle cell mice. These findings may help define the pathophysiology for stroke in children with sickle cell anemia. PMID:27165012

Structural brain network analysis in families multiply affected with bipolar I disorder.

PubMed

Forde, Natalie J; O'Donoghue, Stefani; Scanlon, Cathy; Emsell, Louise; Chaddock, Chris; Leemans, Alexander; Jeurissen, Ben; Barker, Gareth J; Cannon, Dara M; Murray, Robin M; McDonald, Colm

2015-10-30

Disrupted structural connectivity is associated with psychiatric illnesses including bipolar disorder (BP). Here we use structural brain network analysis to investigate connectivity abnormalities in multiply affected BP type I families, to assess the utility of dysconnectivity as a biomarker and its endophenotypic potential. Magnetic resonance diffusion images for 19 BP type I patients in remission, 21 of their first degree unaffected relatives, and 18 unrelated healthy controls underwent tractography. With the automated anatomical labelling atlas being used to define nodes, a connectivity matrix was generated for each subject. Network metrics were extracted with the Brain Connectivity Toolbox and then analysed for group differences, accounting for potential confounding effects of age, gender and familial association. Whole brain analysis revealed no differences between groups. Analysis of specific mainly frontal regions, previously implicated as potentially endophenotypic by functional magnetic resonance imaging analysis of the same cohort, revealed a significant effect of group in the right medial superior frontal gyrus and left middle frontal gyrus driven by reduced organisation in patients compared with controls. The organisation of whole brain networks of those affected with BP I does not differ from their unaffected relatives or healthy controls. In discreet frontal regions, however, anatomical connectivity is disrupted in patients but not in their unaffected relatives. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Quantitative evaluation of simulated functional brain networks in graph theoretical analysis.

PubMed

Lee, Won Hee; Bullmore, Ed; Frangou, Sophia

2017-02-01

There is increasing interest in the potential of whole-brain computational models to provide mechanistic insights into resting-state brain networks. It is therefore important to determine the degree to which computational models reproduce the topological features of empirical functional brain networks. We used empirical connectivity data derived from diffusion spectrum and resting-state functional magnetic resonance imaging data from healthy individuals. Empirical and simulated functional networks, constrained by structural connectivity, were defined based on 66 brain anatomical regions (nodes). Simulated functional data were generated using the Kuramoto model in which each anatomical region acts as a phase oscillator. Network topology was studied using graph theory in the empirical and simulated data. The difference (relative error) between graph theory measures derived from empirical and simulated data was then estimated. We found that simulated data can be used with confidence to model graph measures of global network organization at different dynamic states and highlight the sensitive dependence of the solutions obtained in simulated data on the specified connection densities. This study provides a method for the quantitative evaluation and external validation of graph theory metrics derived from simulated data that can be used to inform future study designs. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

An Adaptive Complex Network Model for Brain Functional Networks

PubMed Central

Gomez Portillo, Ignacio J.; Gleiser, Pablo M.

2009-01-01

Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence) of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution. PMID:19738902

Disconnection of network hubs and cognitive impairment after traumatic brain injury.

PubMed

Fagerholm, Erik D; Hellyer, Peter J; Scott, Gregory; Leech, Robert; Sharp, David J

2015-06-01

Traumatic brain injury affects brain connectivity by producing traumatic axonal injury. This disrupts the function of large-scale networks that support cognition. The best way to describe this relationship is unclear, but one elegant approach is to view networks as graphs. Brain regions become nodes in the graph, and white matter tracts the connections. The overall effect of an injury can then be estimated by calculating graph metrics of network structure and function. Here we test which graph metrics best predict the presence of traumatic axonal injury, as well as which are most highly associated with cognitive impairment. A comprehensive range of graph metrics was calculated from structural connectivity measures for 52 patients with traumatic brain injury, 21 of whom had microbleed evidence of traumatic axonal injury, and 25 age-matched controls. White matter connections between 165 grey matter brain regions were defined using tractography, and structural connectivity matrices calculated from skeletonized diffusion tensor imaging data. This technique estimates injury at the centre of tract, but is insensitive to damage at tract edges. Graph metrics were calculated from the resulting connectivity matrices and machine-learning techniques used to select the metrics that best predicted the presence of traumatic brain injury. In addition, we used regularization and variable selection via the elastic net to predict patient behaviour on tests of information processing speed, executive function and associative memory. Support vector machines trained with graph metrics of white matter connectivity matrices from the microbleed group were able to identify patients with a history of traumatic brain injury with 93.4% accuracy, a result robust to different ways of sampling the data. Graph metrics were significantly associated with cognitive performance: information processing speed (R(2) = 0.64), executive function (R(2) = 0.56) and associative memory (R(2) = 0.25). These results were then replicated in a separate group of patients without microbleeds. The most influential graph metrics were betweenness centrality and eigenvector centrality, which provide measures of the extent to which a given brain region connects other regions in the network. Reductions in betweenness centrality and eigenvector centrality were particularly evident within hub regions including the cingulate cortex and caudate. Our results demonstrate that betweenness centrality and eigenvector centrality are reduced within network hubs, due to the impact of traumatic axonal injury on network connections. The dominance of betweenness centrality and eigenvector centrality suggests that cognitive impairment after traumatic brain injury results from the disconnection of network hubs by traumatic axonal injury. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain.

Attention Performance Measured by Attention Network Test Is Correlated with Global and Regional Efficiency of Structural Brain Networks

PubMed Central

Xiao, Min; Ge, Haitao; Khundrakpam, Budhachandra S.; Xu, Junhai; Bezgin, Gleb; Leng, Yuan; Zhao, Lu; Tang, Yuchun; Ge, Xinting; Jeon, Seun; Xu, Wenjian; Evans, Alan C.; Liu, Shuwei

2016-01-01

Functional neuroimaging studies have indicated the involvement of separate brain areas in three distinct attention systems: alerting, orienting, and executive control (EC). However, the structural correlates underlying attention remains unexplored. Here, we utilized graph theory to examine the neuroanatomical substrates of the three attention systems measured by attention network test (ANT) in 65 healthy subjects. White matter connectivity, assessed with diffusion tensor imaging deterministic tractography was modeled as a structural network comprising 90 nodes defined by the automated anatomical labeling (AAL) template. Linear regression analyses were conducted to explore the relationship between topological parameters and the three attentional effects. We found a significant positive correlation between EC function and global efficiency of the whole brain network. At the regional level, node-specific correlations were discovered between regional efficiency and all three ANT components, including dorsolateral superior frontal gyrus, thalamus and parahippocampal gyrus for EC, thalamus and inferior parietal gyrus for alerting, and paracentral lobule and inferior occipital gyrus for orienting. Our findings highlight the fundamental architecture of interregional structural connectivity involved in attention and could provide new insights into the anatomical basis underlying human behavior. PMID:27777556

Using normalization 3D model for automatic clinical brain quantative analysis and evaluation

NASA Astrophysics Data System (ADS)

Lin, Hong-Dun; Yao, Wei-Jen; Hwang, Wen-Ju; Chung, Being-Tau; Lin, Kang-Ping

2003-05-01

Functional medical imaging, such as PET or SPECT, is capable of revealing physiological functions of the brain, and has been broadly used in diagnosing brain disorders by clinically quantitative analysis for many years. In routine procedures, physicians manually select desired ROIs from structural MR images and then obtain physiological information from correspondent functional PET or SPECT images. The accuracy of quantitative analysis thus relies on that of the subjectively selected ROIs. Therefore, standardizing the analysis procedure is fundamental and important in improving the analysis outcome. In this paper, we propose and evaluate a normalization procedure with a standard 3D-brain model to achieve precise quantitative analysis. In the normalization process, the mutual information registration technique was applied for realigning functional medical images to standard structural medical images. Then, the standard 3D-brain model that shows well-defined brain regions was used, replacing the manual ROIs in the objective clinical analysis. To validate the performance, twenty cases of I-123 IBZM SPECT images were used in practical clinical evaluation. The results show that the quantitative analysis outcomes obtained from this automated method are in agreement with the clinical diagnosis evaluation score with less than 3% error in average. To sum up, the method takes advantage of obtaining precise VOIs, information automatically by well-defined standard 3-D brain model, sparing manually drawn ROIs slice by slice from structural medical images in traditional procedure. That is, the method not only can provide precise analysis results, but also improve the process rate for mass medical images in clinical.

Global and regional cortical connectivity maturation index (CCMI) of developmental human brain with quantification of short-range association tracts

NASA Astrophysics Data System (ADS)

Ouyang, Minhui; Jeon, Tina; Mishra, Virendra; Du, Haixiao; Wang, Yu; Peng, Yun; Huang, Hao

2016-03-01

From early childhood to adulthood, synaptogenesis and synaptic pruning continuously reshape the structural architecture and neural connection in developmental human brains. Disturbance of the precisely balanced strengthening of certain axons and pruning of others may cause mental disorders such as autism and schizophrenia. To characterize this balance, we proposed a novel measurement based on cortical parcellation and diffusion MRI (dMRI) tractography, a cortical connectivity maturation index (CCMI). To evaluate the spatiotemporal sensitivity of CCMI as a potential biomarker, dMRI and T1 weighted datasets of 21 healthy subjects 2-25 years were acquired. Brain cortex was parcellated into 68 gyral labels using T1 weighted images, then transformed into dMRI space to serve as the seed region of interest for dMRI-based tractography. Cortico-cortical association fibers initiated from each gyrus were categorized into long- and short-range ones, based on the other end of fiber terminating in non-adjacent or adjacent gyri of the seed gyrus, respectively. The regional CCMI was defined as the ratio between number of short-range association tracts and that of all association tracts traced from one of 68 parcellated gyri. The developmental trajectory of the whole brain CCMI follows a quadratic model with initial decreases from 2 to 16 years followed by later increases after 16 years. Regional CCMI is heterogeneous among different cortical gyri with CCMI dropping to the lowest value earlier in primary somatosensory cortex and visual cortex while later in the prefrontal cortex. The proposed CCMI may serve as sensitive biomarker for brain development under normal or pathological conditions.

Local sleep homeostasis in the avian brain: convergence of sleep function in mammals and birds?

PubMed

Lesku, John A; Vyssotski, Alexei L; Martinez-Gonzalez, Dolores; Wilzeck, Christiane; Rattenborg, Niels C

2011-08-22

The function of the brain activity that defines slow wave sleep (SWS) and rapid eye movement (REM) sleep in mammals is unknown. During SWS, the level of electroencephalogram slow wave activity (SWA or 0.5-4.5 Hz power density) increases and decreases as a function of prior time spent awake and asleep, respectively. Such dynamics occur in response to waking brain use, as SWA increases locally in brain regions used more extensively during prior wakefulness. Thus, SWA is thought to reflect homeostatically regulated processes potentially tied to maintaining optimal brain functioning. Interestingly, birds also engage in SWS and REM sleep, a similarity that arose via convergent evolution, as sleeping reptiles and amphibians do not show similar brain activity. Although birds deprived of sleep show global increases in SWA during subsequent sleep, it is unclear whether avian sleep is likewise regulated locally. Here, we provide, to our knowledge, the first electrophysiological evidence for local sleep homeostasis in the avian brain. After staying awake watching David Attenborough's The Life of Birds with only one eye, SWA and the slope of slow waves (a purported marker of synaptic strength) increased only in the hyperpallium--a primary visual processing region--neurologically connected to the stimulated eye. Asymmetries were specific to the hyperpallium, as the non-visual mesopallium showed a symmetric increase in SWA and wave slope. Thus, hypotheses for the function of mammalian SWS that rely on local sleep homeostasis may apply also to birds.

Dipeptidyl Peptidase 10 (DPP10789): A Voltage Gated Potassium Channel Associated Protein Is Abnormally Expressed in Alzheimer's and Other Neurodegenerative Diseases

PubMed Central

Gai, Wei-Ping; Abbott, Catherine A.

2014-01-01

The neuropathological features associated with Alzheimer's disease (AD) include the presence of extracellular amyloid-β peptide-containing plaques and intracellular tau positive neurofibrillary tangles and the loss of synapses and neurons in defined regions of the brain. Dipeptidyl peptidase 10 (DPP10) is a protein that facilitates Kv4 channel surface expression and neuronal excitability. This study aims to explore DPP10789 protein distribution in human brains and its contribution to the neurofibrillary pathology of AD and other tauopathies. Immunohistochemical analysis revealed predominant neuronal staining of DPP10789 in control brains, and the CA1 region of the hippocampus contained strong reactivity in the distal dendrites of the pyramidal cells. In AD brains, robust DPP10789 reactivity was detected in neurofibrillary tangles and plaque-associated dystrophic neurites, most of which colocalized with the doubly phosphorylated Ser-202/Thr-205 tau epitope. DPP10789 positive neurofibrillary tangles and plaque-associated dystrophic neurites also appeared in other neurodegenerative diseases such as frontotemporal lobar degeneration, diffuse Lewy body disease, and progressive supranuclear palsy. Occasional DPP10789 positive neurofibrillary tangles and neurites were seen in some aged control brains. Western blot analysis showed both full length and truncated DPP10789 fragments with the later increasing significantly in AD brains compared to control brains. Our results suggest that DPP10789 is involved in the pathology of AD and other neurodegenerative diseases. PMID:25025038

Background field removal using a region adaptive kernel for quantitative susceptibility mapping of human brain

NASA Astrophysics Data System (ADS)

Fang, Jinsheng; Bao, Lijun; Li, Xu; van Zijl, Peter C. M.; Chen, Zhong

2017-08-01

Background field removal is an important MR phase preprocessing step for quantitative susceptibility mapping (QSM). It separates the local field induced by tissue magnetic susceptibility sources from the background field generated by sources outside a region of interest, e.g. brain, such as air-tissue interface. In the vicinity of air-tissue boundary, e.g. skull and paranasal sinuses, where large susceptibility variations exist, present background field removal methods are usually insufficient and these regions often need to be excluded by brain mask erosion at the expense of losing information of local field and thus susceptibility measures in these regions. In this paper, we propose an extension to the variable-kernel sophisticated harmonic artifact reduction for phase data (V-SHARP) background field removal method using a region adaptive kernel (R-SHARP), in which a scalable spherical Gaussian kernel (SGK) is employed with its kernel radius and weights adjustable according to an energy "functional" reflecting the magnitude of field variation. Such an energy functional is defined in terms of a contour and two fitting functions incorporating regularization terms, from which a curve evolution model in level set formation is derived for energy minimization. We utilize it to detect regions of with a large field gradient caused by strong susceptibility variation. In such regions, the SGK will have a small radius and high weight at the sphere center in a manner adaptive to the voxel energy of the field perturbation. Using the proposed method, the background field generated from external sources can be effectively removed to get a more accurate estimation of the local field and thus of the QSM dipole inversion to map local tissue susceptibility sources. Numerical simulation, phantom and in vivo human brain data demonstrate improved performance of R-SHARP compared to V-SHARP and RESHARP (regularization enabled SHARP) methods, even when the whole paranasal sinus regions are preserved in the brain mask. Shadow artifacts due to strong susceptibility variations in the derived QSM maps could also be largely eliminated using the R-SHARP method, leading to more accurate QSM reconstruction.

Background field removal using a region adaptive kernel for quantitative susceptibility mapping of human brain.

PubMed

Fang, Jinsheng; Bao, Lijun; Li, Xu; van Zijl, Peter C M; Chen, Zhong

2017-08-01

Background field removal is an important MR phase preprocessing step for quantitative susceptibility mapping (QSM). It separates the local field induced by tissue magnetic susceptibility sources from the background field generated by sources outside a region of interest, e.g. brain, such as air-tissue interface. In the vicinity of air-tissue boundary, e.g. skull and paranasal sinuses, where large susceptibility variations exist, present background field removal methods are usually insufficient and these regions often need to be excluded by brain mask erosion at the expense of losing information of local field and thus susceptibility measures in these regions. In this paper, we propose an extension to the variable-kernel sophisticated harmonic artifact reduction for phase data (V-SHARP) background field removal method using a region adaptive kernel (R-SHARP), in which a scalable spherical Gaussian kernel (SGK) is employed with its kernel radius and weights adjustable according to an energy "functional" reflecting the magnitude of field variation. Such an energy functional is defined in terms of a contour and two fitting functions incorporating regularization terms, from which a curve evolution model in level set formation is derived for energy minimization. We utilize it to detect regions of with a large field gradient caused by strong susceptibility variation. In such regions, the SGK will have a small radius and high weight at the sphere center in a manner adaptive to the voxel energy of the field perturbation. Using the proposed method, the background field generated from external sources can be effectively removed to get a more accurate estimation of the local field and thus of the QSM dipole inversion to map local tissue susceptibility sources. Numerical simulation, phantom and in vivo human brain data demonstrate improved performance of R-SHARP compared to V-SHARP and RESHARP (regularization enabled SHARP) methods, even when the whole paranasal sinus regions are preserved in the brain mask. Shadow artifacts due to strong susceptibility variations in the derived QSM maps could also be largely eliminated using the R-SHARP method, leading to more accurate QSM reconstruction. Copyright © 2017. Published by Elsevier Inc.

A human brain network derived from coma-causing brainstem lesions.

PubMed

Fischer, David B; Boes, Aaron D; Demertzi, Athena; Evrard, Henry C; Laureys, Steven; Edlow, Brian L; Liu, Hesheng; Saper, Clifford B; Pascual-Leone, Alvaro; Fox, Michael D; Geerling, Joel C

2016-12-06

To characterize a brainstem location specific to coma-causing lesions, and its functional connectivity network. We compared 12 coma-causing brainstem lesions to 24 control brainstem lesions using voxel-based lesion-symptom mapping in a case-control design to identify a site significantly associated with coma. We next used resting-state functional connectivity from a healthy cohort to identify a network of regions functionally connected to this brainstem site. We further investigated the cortical regions of this network by comparing their spatial topography to that of known networks and by evaluating their functional connectivity in patients with disorders of consciousness. A small region in the rostral dorsolateral pontine tegmentum was significantly associated with coma-causing lesions. In healthy adults, this brainstem site was functionally connected to the ventral anterior insula (AI) and pregenual anterior cingulate cortex (pACC). These cortical areas aligned poorly with previously defined resting-state networks, better matching the distribution of von Economo neurons. Finally, connectivity between the AI and pACC was disrupted in patients with disorders of consciousness, and to a greater degree than other brain networks. Injury to a small region in the pontine tegmentum is significantly associated with coma. This brainstem site is functionally connected to 2 cortical regions, the AI and pACC, which become disconnected in disorders of consciousness. This network of brain regions may have a role in the maintenance of human consciousness. © 2016 American Academy of Neurology.

A human brain network derived from coma-causing brainstem lesions

PubMed Central

Boes, Aaron D.; Demertzi, Athena; Evrard, Henry C.; Laureys, Steven; Edlow, Brian L.; Liu, Hesheng; Saper, Clifford B.; Pascual-Leone, Alvaro; Geerling, Joel C.

2016-01-01

Objective: To characterize a brainstem location specific to coma-causing lesions, and its functional connectivity network. Methods: We compared 12 coma-causing brainstem lesions to 24 control brainstem lesions using voxel-based lesion-symptom mapping in a case-control design to identify a site significantly associated with coma. We next used resting-state functional connectivity from a healthy cohort to identify a network of regions functionally connected to this brainstem site. We further investigated the cortical regions of this network by comparing their spatial topography to that of known networks and by evaluating their functional connectivity in patients with disorders of consciousness. Results: A small region in the rostral dorsolateral pontine tegmentum was significantly associated with coma-causing lesions. In healthy adults, this brainstem site was functionally connected to the ventral anterior insula (AI) and pregenual anterior cingulate cortex (pACC). These cortical areas aligned poorly with previously defined resting-state networks, better matching the distribution of von Economo neurons. Finally, connectivity between the AI and pACC was disrupted in patients with disorders of consciousness, and to a greater degree than other brain networks. Conclusions: Injury to a small region in the pontine tegmentum is significantly associated with coma. This brainstem site is functionally connected to 2 cortical regions, the AI and pACC, which become disconnected in disorders of consciousness. This network of brain regions may have a role in the maintenance of human consciousness. PMID:27815400

Brain imaging of pain sensitization in patients with knee osteoarthritis.

PubMed

Pujol, Jesus; Martínez-Vilavella, Gerard; Llorente-Onaindia, Jone; Harrison, Ben J; López-Solà, Marina; López-Ruiz, Marina; Blanco-Hinojo, Laura; Benito, Pere; Deus, Joan; Monfort, Jordi

2017-09-01

A relevant aspect in osteoarthritic pain is neural sensitization. This phenomenon involves augmented responsiveness to painful stimulation and may entail a clinically worse prognosis. We used functional magnetic resonance imaging (fMRI) to study pain sensitization in patients with knee osteoarthritis. Sixty patients were recruited and pain sensitization was clinically defined on the basis of regional spreading of pain (spreading sensitization) and increased pain response to repeated stimulation (temporal summation). Functional magnetic resonance imaging testing involved assessing brain responses to both pressure and heat stimulation. Thirty-three patients (55%) showed regional pain spreading (simple sensitization) and 19 patients (32%) showed both regional spreading and temporal summation. Sensitized patients were more commonly women. Direct painful pressure stimulation of the joint (articular interline) robustly activated all of the neural elements typically involved in pain perception, but did not differentiate sensitized and nonsensitized patients. Painful pressure stimulation on the anterior tibial surface (sensitized site) evoked greater activation in sensitized patients in regions typically involved in pain and also beyond these regions, extending to the auditory, visual, and ventral sensorimotor cortices. Painful heat stimulation of the volar forearm did not discriminate the sensitization phenomenon. Results confirm the high prevalence of pain sensitization secondary to knee osteoarthritis. Relevantly, the sensitization phenomenon was associated with neural changes extending beyond strict pain-processing regions with enhancement of activity in general sensory, nonnociceptive brain areas. This effect is in contrast to the changes previously identified in primary pain sensitization in fibromyalgia patients presenting with a weakening of the general sensory integration.

Silicon chip with capacitors and transistors for interfacing organotypic brain slice of rat hippocampus.

PubMed

Hutzler, Michael; Fromherz, Peter

2004-04-01

Probing projections between brain areas and their modulation by synaptic potentiation requires dense arrays of contacts for noninvasive electrical stimulation and recording. Semiconductor technology is able to provide planar arrays with high spatial resolution to be used with planar neuronal structures such as organotypic brain slices. To address basic methodical issues we developed a silicon chip with simple arrays of insulated capacitors and field-effect transistors for stimulation of neuronal activity and recording of evoked field potentials. Brain slices from rat hippocampus were cultured on that substrate. We achieved local stimulation of the CA3 region by applying defined voltage pulses to the chip capacitors. Recording of resulting local field potentials in the CA1 region was accomplished with transistors. The relationship between stimulation and recording was rationalized by a sheet conductor model. By combining a row of capacitors with a row of transistors we determined a simple stimulus-response matrix from CA3 to CA1. Possible contributions of inhomogeneities of synaptic projection, of tissue structure and of neuroelectronic interfacing were considered. The study provides the basis for a development of semiconductor chips with high spatial resolution that are required for long-term studies of topographic mapping.

Forebrain neuroanatomy of the neonatal and juvenile dolphin (T. truncatus and S. coeruloalba)

PubMed Central

Parolisi, Roberta; Peruffo, Antonella; Messina, Silvia; Panin, Mattia; Montelli, Stefano; Giurisato, Maristella; Cozzi, Bruno; Bonfanti, Luca

2015-01-01

Knowledge of dolphin functional neuroanatomy mostly derives from post-mortem studies and non-invasive approaches (i.e., magnetic resonance imaging), due to limitations in experimentation on cetaceans. As a consequence the availability of well-preserved tissues for histology is scarce, and detailed histological analyses are referred mainly to adults. Here we studied the neonatal/juvenile brain in two species of dolphins, the bottlenose dolphin (Tursiops truncatus) and the striped dolphin (Stenella coeruleoalba), with special reference to forebrain regions. We analyzed cell density in subcortical nuclei, white/gray matter ratio, and myelination in selected regions at different anterior–posterior levels of the whole dolphin brain at different ages, to better define forebrain neuroanatomy and the developmental stage of the dolphin brain around birth. The analyses were extended to the periventricular germinal layer and the cerebellum, whose delayed genesis of the granule cell layer is a hallmark of postnatal development in the mammalian nervous system. Our results establish an atlas of the young dolphin forebrain and, on the basis of occurrence/absence of delayed neurogenic layers, confirm the stage of advanced brain maturation in these animals with respect to most terrestrial mammals. PMID:26594155

Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands.

PubMed

Deligianni, Fani; Centeno, Maria; Carmichael, David W; Clayden, Jonathan D

2014-01-01

Whole brain functional connectomes hold promise for understanding human brain activity across a range of cognitive, developmental and pathological states. So called resting-state (rs) functional MRI studies have contributed to the brain being considered at a macroscopic scale as a set of interacting regions. Interactions are defined as correlation-based signal measurements driven by blood oxygenation level dependent (BOLD) contrast. Understanding the neurophysiological basis of these measurements is important in conveying useful information about brain function. Local coupling between BOLD fMRI and neurophysiological measurements is relatively well defined, with evidence that gamma (range) frequency EEG signals are the closest correlate of BOLD fMRI changes during cognitive processing. However, it is less clear how whole-brain network interactions relate during rest where lower frequency signals have been suggested to play a key role. Simultaneous EEG-fMRI offers the opportunity to observe brain network dynamics with high spatio-temporal resolution. We utilize these measurements to compare the connectomes derived from rs-fMRI and EEG band limited power (BLP). Merging this multi-modal information requires the development of an appropriate statistical framework. We relate the covariance matrices of the Hilbert envelope of the source localized EEG signal across bands to the covariance matrices derived from rs-fMRI with the means of statistical prediction based on sparse Canonical Correlation Analysis (sCCA). Subsequently, we identify the most prominent connections that contribute to this relationship. We compare whole-brain functional connectomes based on their geodesic distance to reliably estimate the performance of the prediction. The performance of predicting fMRI from EEG connectomes is considerably better than predicting EEG from fMRI across all bands, whereas the connectomes derived in low frequency EEG bands resemble best rs-fMRI connectivity.

Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands

PubMed Central

Deligianni, Fani; Centeno, Maria; Carmichael, David W.; Clayden, Jonathan D.

2014-01-01

Whole brain functional connectomes hold promise for understanding human brain activity across a range of cognitive, developmental and pathological states. So called resting-state (rs) functional MRI studies have contributed to the brain being considered at a macroscopic scale as a set of interacting regions. Interactions are defined as correlation-based signal measurements driven by blood oxygenation level dependent (BOLD) contrast. Understanding the neurophysiological basis of these measurements is important in conveying useful information about brain function. Local coupling between BOLD fMRI and neurophysiological measurements is relatively well defined, with evidence that gamma (range) frequency EEG signals are the closest correlate of BOLD fMRI changes during cognitive processing. However, it is less clear how whole-brain network interactions relate during rest where lower frequency signals have been suggested to play a key role. Simultaneous EEG-fMRI offers the opportunity to observe brain network dynamics with high spatio-temporal resolution. We utilize these measurements to compare the connectomes derived from rs-fMRI and EEG band limited power (BLP). Merging this multi-modal information requires the development of an appropriate statistical framework. We relate the covariance matrices of the Hilbert envelope of the source localized EEG signal across bands to the covariance matrices derived from rs-fMRI with the means of statistical prediction based on sparse Canonical Correlation Analysis (sCCA). Subsequently, we identify the most prominent connections that contribute to this relationship. We compare whole-brain functional connectomes based on their geodesic distance to reliably estimate the performance of the prediction. The performance of predicting fMRI from EEG connectomes is considerably better than predicting EEG from fMRI across all bands, whereas the connectomes derived in low frequency EEG bands resemble best rs-fMRI connectivity. PMID:25221467

Functional organization of human subgenual cortical areas: Relationship between architectonical segregation and connectional heterogeneity.

PubMed

Palomero-Gallagher, Nicola; Eickhoff, Simon B; Hoffstaedter, Felix; Schleicher, Axel; Mohlberg, Hartmut; Vogt, Brent A; Amunts, Katrin; Zilles, Karl

2015-07-15

Human subgenual anterior cingulate cortex (sACC) is involved in affective experiences and fear processing. Functional neuroimaging studies view it as a homogeneous cortical entity. However, sACC comprises several distinct cyto- and receptorarchitectonical areas: 25, s24, s32, and the ventral portion of area 33. Thus, we hypothesized that the areas may also be connectionally and functionally distinct. We performed structural post mortem and functional in vivo analyses. We computed probabilistic maps of each area based on cytoarchitectonical analysis of ten post mortem brains. Maps, publicly available via the JuBrain atlas and the Anatomy Toolbox, were used to define seed regions of task-dependent functional connectivity profiles and quantitative functional decoding. sACC areas presented distinct co-activation patterns within widespread networks encompassing cortical and subcortical regions. They shared common functional domains related to emotion, perception and cognition. A more specific analysis of these domains revealed an association of s24 with sadness, and of s32 with fear processing. Both areas were activated during taste evaluation, and co-activated with the amygdala, a key node of the affective network. s32 co-activated with areas of the executive control network, and was associated with tasks probing cognition in which stimuli did not have an emotional component. Area 33 was activated by painful stimuli, and co-activated with areas of the sensorimotor network. These results support the concept of a connectional and functional specificity of the cyto- and receptorarchitectonically defined areas within the sACC, which can no longer be seen as a structurally and functionally homogeneous brain region. Copyright © 2015 Elsevier Inc. All rights reserved.

Microstructural White Matter Alterations in the Corpus Callosum of Girls With Conduct Disorder.

PubMed

Menks, Willeke Martine; Furger, Reto; Lenz, Claudia; Fehlbaum, Lynn Valérie; Stadler, Christina; Raschle, Nora Maria

2017-03-01

Diffusion tensor imaging (DTI) studies in adolescent conduct disorder (CD) have demonstrated white matter alterations of tracts connecting functionally distinct fronto-limbic regions, but only in boys or mixed-gender samples. So far, no study has investigated white matter integrity in girls with CD on a whole-brain level. Therefore, our aim was to investigate white matter alterations in adolescent girls with CD. We collected high-resolution DTI data from 24 girls with CD and 20 typically developing control girls using a 3T magnetic resonance imaging system. Fractional anisotropy (FA) and mean diffusivity (MD) were analyzed for whole-brain as well as a priori-defined regions of interest, while controlling for age and intelligence, using a voxel-based analysis and an age-appropriate customized template. Whole-brain findings revealed white matter alterations (i.e., increased FA) in girls with CD bilaterally within the body of the corpus callosum, expanding toward the right cingulum and left corona radiata. The FA and MD results in a priori-defined regions of interest were more widespread and included changes in the cingulum, corona radiata, fornix, and uncinate fasciculus. These results were not driven by age, intelligence, or attention-deficit/hyperactivity disorder comorbidity. This report provides the first evidence of white matter alterations in female adolescents with CD as indicated through white matter reductions in callosal tracts. This finding enhances current knowledge about the neuropathological basis of female CD. An increased understanding of gender-specific neuronal characteristics in CD may influence diagnosis, early detection, and successful intervention strategies. Copyright © 2017 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Sexual dimorphism of Broca's region: More gray matter in female brains in Brodmann areas 44 and 45.

PubMed

Kurth, Florian; Jancke, Lutz; Luders, Eileen

2017-01-02

Although a sexual dimorphism in brain structure is generally well established, evidence for sex differences in Brodmann areas (BA) 44 and 45 is inconclusive. This may be due to the difficulty of accurately defining BA 44 and BA 45 in magnetic resonance images, given that these regions are variable in their location and extent and that they do not match well with macroanatomic landmarks. Here we set out to test for possible sex differences in the local gray matter of BA 44/45 by integrating imaging-based signal intensities with cytoarchitectonically defined tissue probabilities in a sample of 50 male and 50 female subjects. In addition to testing for sex differences with respect to left- and right-hemispheric measures of BA 44/45, we also assessed possible sex differences in BA 44/45 asymmetry. Our analyses revealed significantly larger gray matter volumes in females compared with males for BA 44 and BA 45 bilaterally. However, there was a lack of significant sex differences in BA 44/45 asymmetry. These results corroborate reports of a language-related female superiority, particularly with respect to verbal fluency and verbal memory tasks. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Parietal substrates for dimensional effects in visual search: evidence from lesion-symptom mapping

PubMed Central

Humphreys, Glyn W.; Chechlacz, Magdalena

2013-01-01

In visual search, the detection of pop-out targets is facilitated when the target-defining dimension remains the same compared with when it changes across trials. We tested the brain regions necessary for these dimensional carry-over effects using a voxel-based morphometry study with brain-lesioned patients. Participants had to search for targets defined by either their colour (red or blue) or orientation (right- or left-tilted), and the target dimension either stayed the same or changed on consecutive trials. Twenty-five patients were categorized according to whether they showed an effect of dimensional change on search or not. The two groups did not differ with regard to their performance on several working memory tasks, and the dimensional carry-over effects were not correlated with working memory performance. With spatial, sustained attention and working memory deficits as well as lesion volume controlled, damage within the right inferior parietal lobule (the angular and supramarginal gyri) extending into the intraparietal sulcus was associated with an absence of dimensional carry-over (P < 0.001, cluster-level corrected for multiple comparisons). The data suggest that these regions of parietal cortex are necessary to implement attention shifting in the context of visual dimensional change. PMID:23404335

Changes in reward-induced brain activation in opiate addicts.

PubMed

Martin-Soelch, C; Chevalley, A F; Künig, G; Missimer, J; Magyar, S; Mino, A; Schultz, W; Leenders, K L

2001-10-01

Many studies indicate a role of the cerebral dopaminergic reward system in addiction. Motivated by these findings, we examined in opiate addicts whether brain regions involved in the reward circuitry also react to human prototypical rewards. We measured regional cerebral blood flow (rCBF) with H(2)(15)O positron emission tomography (PET) during a visuo-spatial recognition task with delayed response in control subjects and in opiate addicts participating in a methadone program. Three conditions were defined by the types of feedback: nonsense feedback; nonmonetary reinforcement; or monetary reward, received by the subjects for a correct response. We found in the control subjects rCBF increases in regions associated with the meso-striatal and meso-corticolimbic circuits in response to both monetary reward and nonmonetary reinforcement. In opiate addicts, these regions were activated only in response to monetary reward. Furthermore, nonmonetary reinforcement elicited rCBF increases in limbic regions of the opiate addicts that were not activated in the control subjects. Because psychoactive drugs serve as rewards and directly affect regions of the dopaminergic system like the striatum, we conclude that the differences in rCBF increases between controls and addicts can be attributed to an adaptive consequence of the addiction process.

Fast periodic stimulation (FPS): a highly effective approach in fMRI brain mapping.

PubMed

Gao, Xiaoqing; Gentile, Francesco; Rossion, Bruno

2018-06-01

Defining the neural basis of perceptual categorization in a rapidly changing natural environment with low-temporal resolution methods such as functional magnetic resonance imaging (fMRI) is challenging. Here, we present a novel fast periodic stimulation (FPS)-fMRI approach to define face-selective brain regions with natural images. Human observers are presented with a dynamic stream of widely variable natural object images alternating at a fast rate (6 images/s). Every 9 s, a short burst of variable face images contrasting with object images in pairs induces an objective face-selective neural response at 0.111 Hz. A model-free Fourier analysis achieves a twofold increase in signal-to-noise ratio compared to a conventional block-design approach with identical stimuli and scanning duration, allowing to derive a comprehensive map of face-selective areas in the ventral occipito-temporal cortex, including the anterior temporal lobe (ATL), in all individual brains. Critically, periodicity of the desired category contrast and random variability among widely diverse images effectively eliminates the contribution of low-level visual cues, and lead to the highest values (80-90%) of test-retest reliability in the spatial activation map yet reported in imaging higher level visual functions. FPS-fMRI opens a new avenue for understanding brain function with low-temporal resolution methods.

The role of long-range connectivity for the characterization of the functional-anatomical organization of the cortex.

PubMed

Knösche, Thomas R; Tittgemeyer, Marc

2011-01-01

This review focuses on the role of long-range connectivity as one element of brain structure that is of key importance for the functional-anatomical organization of the cortex. In this context, we discuss the putative guiding principles for mapping brain function and structure onto the cortical surface. Such mappings reveal a high degree of functional-anatomical segregation. Given that brain regions frequently maintain characteristic connectivity profiles and the functional repertoire of a cortical area is closely related to its anatomical connections, long-range connectivity may be used to define segregated cortical areas. This methodology is called connectivity-based parcellation. Within this framework, we investigate different techniques to estimate connectivity profiles with emphasis given to non-invasive methods based on diffusion magnetic resonance imaging (dMRI) and diffusion tractography. Cortical parcellation is then defined based on similarity between diffusion tractograms, and different clustering approaches are discussed. We conclude that the use of non-invasively acquired connectivity estimates to characterize the functional-anatomical organization of the brain is a valid, relevant, and necessary endeavor. Current and future developments in dMRI technology, tractography algorithms, and models of the similarity structure hold great potential for a substantial improvement and enrichment of the results of the technique.

Functional MRI Preprocessing in Lesioned Brains: Manual Versus Automated Region of Interest Analysis

PubMed Central

Garrison, Kathleen A.; Rogalsky, Corianne; Sheng, Tong; Liu, Brent; Damasio, Hanna; Winstein, Carolee J.; Aziz-Zadeh, Lisa S.

2015-01-01

Functional magnetic resonance imaging (fMRI) has significant potential in the study and treatment of neurological disorders and stroke. Region of interest (ROI) analysis in such studies allows for testing of strong a priori clinical hypotheses with improved statistical power. A commonly used automated approach to ROI analysis is to spatially normalize each participant’s structural brain image to a template brain image and define ROIs using an atlas. However, in studies of individuals with structural brain lesions, such as stroke, the gold standard approach may be to manually hand-draw ROIs on each participant’s non-normalized structural brain image. Automated approaches to ROI analysis are faster and more standardized, yet are susceptible to preprocessing error (e.g., normalization error) that can be greater in lesioned brains. The manual approach to ROI analysis has high demand for time and expertise, but may provide a more accurate estimate of brain response. In this study, commonly used automated and manual approaches to ROI analysis were directly compared by reanalyzing data from a previously published hypothesis-driven cognitive fMRI study, involving individuals with stroke. The ROI evaluated is the pars opercularis of the inferior frontal gyrus. Significant differences were identified in task-related effect size and percent-activated voxels in this ROI between the automated and manual approaches to ROI analysis. Task interactions, however, were consistent across ROI analysis approaches. These findings support the use of automated approaches to ROI analysis in studies of lesioned brains, provided they employ a task interaction design. PMID:26441816

Respondents, Operants, and Emergents: Toward an Integrated Perspective on Behavior

NASA Technical Reports Server (NTRS)

Rumbaugh, Daune M.; Washburn, David A.; Hillix, William A.

1996-01-01

A triarchic organization of behavior, building on Skinner's description of respondents and operants, is proposed by introducing a third class of behavior called 'emergents.' Emergents are new responses, never specifically reinforced, that require operations more complex than association. Some of these operations occur naturally only in animals above a minimum level of brain complexity, and are developed in an interaction between treatment and organismic variables. (Here complexity is defined in terms of relative levels of hierarchical integration made possible both by the amount of brain, afforded both by brain-body allometric relationships and by encephalization, and, also, the elaboration of dendritic and synaptic connections within the cortex and connections between various parts/regions of the brain.) Examples of emergents are discussed to advance this triarchic view, of behavior. The prime example is language. This triarchic view reflects both the common goals and the cumulative nature of psychological science.

Youthful Brains in Older Adults: Preserved Neuroanatomy in the Default Mode and Salience Networks Contributes to Youthful Memory in Superaging.

PubMed

Sun, Felicia W; Stepanovic, Michael R; Andreano, Joseph; Barrett, Lisa Feldman; Touroutoglou, Alexandra; Dickerson, Bradford C

2016-09-14

Decline in cognitive skills, especially in memory, is often viewed as part of "normal" aging. Yet some individuals "age better" than others. Building on prior research showing that cortical thickness in one brain region, the anterior midcingulate cortex, is preserved in older adults with memory performance abilities equal to or better than those of people 20-30 years younger (i.e., "superagers"), we examined the structural integrity of two large-scale intrinsic brain networks in superaging: the default mode network, typically engaged during memory encoding and retrieval tasks, and the salience network, typically engaged during attention, motivation, and executive function tasks. We predicted that superagers would have preserved cortical thickness in critical nodes in these networks. We defined superagers (60-80 years old) based on their performance compared to young adults (18-32 years old) on the California Verbal Learning Test Long Delay Free Recall test. We found regions within the networks of interest where the cerebral cortex of superagers was thicker than that of typical older adults, and where superagers were anatomically indistinguishable from young adults; hippocampal volume was also preserved in superagers. Within the full group of older adults, thickness of a number of regions, including the anterior temporal cortex, rostral medial prefrontal cortex, and anterior midcingulate cortex, correlated with memory performance, as did the volume of the hippocampus. These results indicate older adults with youthful memory abilities have youthful brain regions in key paralimbic and limbic nodes of the default mode and salience networks that support attentional, executive, and mnemonic processes subserving memory function. Memory performance typically declines with age, as does cortical structural integrity, yet some older adults maintain youthful memory. We tested the hypothesis that superagers (older individuals with youthful memory performance) would exhibit preserved neuroanatomy in key brain networks subserving memory. We found that superagers not only perform similarly to young adults on memory testing, they also do not show the typical patterns of brain atrophy in certain regions. These regions are contained largely within two major intrinsic brain networks: the default mode network, implicated in memory encoding, storage, and retrieval, and the salience network, associated with attention and executive processes involved in encoding and retrieval. Preserved neuroanatomical integrity in these networks is associated with better memory performance among older adults. Copyright © 2016 Sun, Stepanovic et al.

Time, Memory, and Consciousness a View from the Brain

NASA Astrophysics Data System (ADS)

Markowitsch, Hans J.

2005-10-01

Memory can be defined as mental time traveling. Seen in this way, memory provides the glue which combines different time episodes and leads to a coherent view of one's own person. The importance of time becomes apparent in a neuroscientific comparison of animals and human beings. All kinds of animals have biorhythms -- times when they sleep, prefer or avoid sex, or move to warmer places. Mammalian brains have a number of time sensitive structures damage to which alters a subject's behavior to his or her environment. For human beings, damage to certain brain regions may alter the sense of time and consciousness of time in quite different ways. Furthermore, brain damage, drugs, or psychiatric disturbances may lead to an impaired perception of time, sometimes leading to major positive or negative accelerations in time perception. An impaired time perception alters consciousness and awareness of oneself. A proper synchronized action of time perception, brain activation, memory processing, and autonoetic (self-aware) consciousness provides the bases of an integrated personality.

Medial prefrontal cortex subserves diverse forms of self-reflection.

PubMed

Jenkins, Adrianna C; Mitchell, Jason P

2011-01-01

The ability to think about oneself--to self--reflect--is one of the defining features of the human mind. Recent research has suggested that this ability may be subserved by a particular brain region: the medial prefrontal cortex (MPFC). However, although humans can contemplate a variety of different aspects of themselves, including their stable personality traits, current feelings, and physical attributes, no research has directly examined the extent to which these different forms of self-reflection are subserved by common mechanisms. To address this question, participants were scanned using functional magnetic resonance imaging (fMRI) while making judgments about their own personality traits, current mental states, and physical attributes as well as those of another person. Whereas some brain regions responded preferentially during only one form of self-reflection, a robust region of MPFC was engaged preferentially during self-reflection across all three types of judgment. These results suggest that--although dissociable--diverse forms of self-referential thought draw on a shared cognitive process subserved by MPFC.

Propofol disrupts functional interactions between sensory and high-order processing of auditory verbal memory.

PubMed

Liu, Xiaolin; Lauer, Kathryn K; Ward, Barney D; Rao, Stephen M; Li, Shi-Jiang; Hudetz, Anthony G

2012-10-01

Current theories suggest that disrupting cortical information integration may account for the mechanism of general anesthesia in suppressing consciousness. Human cognitive operations take place in hierarchically structured neural organizations in the brain. The process of low-order neural representation of sensory stimuli becoming integrated in high-order cortices is also known as cognitive binding. Combining neuroimaging, cognitive neuroscience, and anesthetic manipulation, we examined how cognitive networks involved in auditory verbal memory are maintained in wakefulness, disrupted in propofol-induced deep sedation, and re-established in recovery. Inspired by the notion of cognitive binding, an functional magnetic resonance imaging-guided connectivity analysis was utilized to assess the integrity of functional interactions within and between different levels of the task-defined brain regions. Task-related responses persisted in the primary auditory cortex (PAC), but vanished in the inferior frontal gyrus (IFG) and premotor areas in deep sedation. For connectivity analysis, seed regions representing sensory and high-order processing of the memory task were identified in the PAC and IFG. Propofol disrupted connections from the PAC seed to the frontal regions and thalamus, but not the connections from the IFG seed to a set of widely distributed brain regions in the temporal, frontal, and parietal lobes (with exception of the PAC). These later regions have been implicated in mediating verbal comprehension and memory. These results suggest that propofol disrupts cognition by blocking the projection of sensory information to high-order processing networks and thus preventing information integration. Such findings contribute to our understanding of anesthetic mechanisms as related to information and integration in the brain. Copyright © 2011 Wiley Periodicals, Inc.

Convergence Analysis of Micro-Lesions (CAML): An approach to mapping of diffuse lesions from carotid revascularization.

PubMed

Rosen, Allyson C; Soman, Salil; Bhat, Jyoti; Laird, Angela R; Stephens, Jeffrey; Eickhoff, Simon B; Fox, P Mickle; Long, Becky; Dinishak, David; Ortega, Mario; Lane, Barton; Wintermark, Max; Hitchner, Elizabeth; Zhou, Wei

2018-01-01

Carotid revascularization (endarterectomy, stenting) prevents stroke; however, procedure-related embolization is common and results in small brain lesions easily identified by diffusion weighted magnetic resonance imaging (DWI). A crucial barrier to understanding the clinical significance of these lesions has been the lack of a statistical approach to identify vulnerable brain areas. The problem is that the lesions are small, numerous, and non-overlapping. Here we address this problem with a new method, the Convergence Analysis of Micro-Lesions (CAML) technique, an extension of the Anatomic Likelihood Analysis (ALE). The method combines manual lesion tracing, constraints based on known lesion patterns, and convergence analysis to represent regions vulnerable to lesions as probabilistic brain atlases. Two studies were conducted over the course of 12 years in an active, vascular surgery clinic. An analysis in an initial group of 126 patients at 1.5 T MRI was cross-validated in a second group of 80 patients at 3T MRI. In CAML, lesions were manually defined and center points identified. Brains were aligned according to side of surgery since this factor powerfully determines lesion distribution. A convergence based analysis, was performed on each of these groups. Results indicated the most consistent region of vulnerability was in motor and premotor cortex regions. Smaller regions common to both groups included the dorsolateral prefrontal cortex and medial parietal regions. Vulnerability of motor cortex is consistent with previous work showing changes in hand dexterity associated with these procedures. The consistency of CAML also demonstrates the feasibility of this new approach to characterize small, diffuse, non-overlapping lesions in patients with multifocal pathologies.

Region-specific DNA synthesis in brains of F344 rats following a six-day bromodeoxyuridine infusion.

PubMed

Bolon, B; Dunn, C; Goldsworthy, T L

1996-09-01

Prolonged exposure to certain alkylating chemicals induces glial and meningeal tumours in rats, probably resulting from DNA damage to dividing neural cells. The present work evaluated DNA synthesis in the brains of untreated, young adult male F344 rats in order to define a BrdUrd infusion protocol to more adequately assess proliferation in slowly dividing neural cell populations. BrdUrd (2.5 to 160 mg/ml) was administered for 6 days via subcutaneous osmotic pumps. Clinical toxicity was not observed at any dose. The labelling index (LI; % of cells per brain area that incorporated BrdUrd) and unit length labelling index (ULLI; % of cells per meningeal length that incorporated BrdUrd) were calculated for selected regions by counting labelled neural cells in defined areas of the right hemisphere in coronal brain sections. Intensely stained cells were numerous in the cerebral subependymal layer (LI = 35.8%); scattered in cerebral white matter tracts (e.g. corpus callosum and internal capsule; LI = 6.2%) as well as cerebral (ULLI = 4.2%) and cerebellar (ULLI = 3.6%) meninges; and rare in the hippocampus (LI > 0.1%). Mildy stained cells were dispersed in the pons (LI = 2.1%), deep cerebral (LI = 1.8%) and cerebellar (LI = 1.0%) grey matter, and thalamus (LI = 0.3%). Phenotypically, BrdUrd-positive cells in neuropil were glial cell precursors and their progeny, while those associated with meninges were usually located in the superficial subarachnoid space and appeared to be fibrocytes. Using BrdUrd infusion, LI for glial precursors at these sites ranged from two- to 10-fold higher than those reported previously after a brief parenteral pulse dose. These data indicate that continuous BrdUrd infusion for 6 days by subcutaneous osmotic pump is an efficient means of labelling neural cells throughout the brain.

Estimating the Integrated Information Measure Phi from High-Density Electroencephalography during States of Consciousness in Humans

PubMed Central

Kim, Hyoungkyu; Hudetz, Anthony G.; Lee, Joseph; Mashour, George A.; Lee, UnCheol; Avidan, Michael S.

2018-01-01

The integrated information theory (IIT) proposes a quantitative measure, denoted as Φ, of the amount of integrated information in a physical system, which is postulated to have an identity relationship with consciousness. IIT predicts that the value of Φ estimated from brain activities represents the level of consciousness across phylogeny and functional states. Practical limitations, such as the explosive computational demands required to estimate Φ for real systems, have hindered its application to the brain and raised questions about the utility of IIT in general. To achieve practical relevance for studying the human brain, it will be beneficial to establish the reliable estimation of Φ from multichannel electroencephalogram (EEG) and define the relationship of Φ to EEG properties conventionally used to define states of consciousness. In this study, we introduce a practical method to estimate Φ from high-density (128-channel) EEG and determine the contribution of each channel to Φ. We examine the correlation of power, frequency, functional connectivity, and modularity of EEG with regional Φ in various states of consciousness as modulated by diverse anesthetics. We find that our approximation of Φ alone is insufficient to discriminate certain states of anesthesia. However, a multi-dimensional parameter space extended by four parameters related to Φ and EEG connectivity is able to differentiate all states of consciousness. The association of Φ with EEG connectivity during clinically defined anesthetic states represents a new practical approach to the application of IIT, which may be used to characterize various physiological (sleep), pharmacological (anesthesia), and pathological (coma) states of consciousness in the human brain. PMID:29503611

Estimating the Integrated Information Measure Phi from High-Density Electroencephalography during States of Consciousness in Humans.

PubMed

Kim, Hyoungkyu; Hudetz, Anthony G; Lee, Joseph; Mashour, George A; Lee, UnCheol

2018-01-01

The integrated information theory (IIT) proposes a quantitative measure, denoted as Φ, of the amount of integrated information in a physical system, which is postulated to have an identity relationship with consciousness. IIT predicts that the value of Φ estimated from brain activities represents the level of consciousness across phylogeny and functional states. Practical limitations, such as the explosive computational demands required to estimate Φ for real systems, have hindered its application to the brain and raised questions about the utility of IIT in general. To achieve practical relevance for studying the human brain, it will be beneficial to establish the reliable estimation of Φ from multichannel electroencephalogram (EEG) and define the relationship of Φ to EEG properties conventionally used to define states of consciousness. In this study, we introduce a practical method to estimate Φ from high-density (128-channel) EEG and determine the contribution of each channel to Φ. We examine the correlation of power, frequency, functional connectivity, and modularity of EEG with regional Φ in various states of consciousness as modulated by diverse anesthetics. We find that our approximation of Φ alone is insufficient to discriminate certain states of anesthesia. However, a multi-dimensional parameter space extended by four parameters related to Φ and EEG connectivity is able to differentiate all states of consciousness. The association of Φ with EEG connectivity during clinically defined anesthetic states represents a new practical approach to the application of IIT, which may be used to characterize various physiological (sleep), pharmacological (anesthesia), and pathological (coma) states of consciousness in the human brain.

Patterns of differences in brain morphology in humans as compared to extant apes.

PubMed

Aldridge, Kristina

2011-01-01

Although human evolution is characterized by a vast increase in brain size, it is not clear whether or not certain regions of the brain are enlarged disproportionately in humans, or how this enlargement relates to differences in overall neural morphology. The aim of this study is to determine whether or not there are specific suites of features that distinguish the morphology of the human brain from that of apes. The study sample consists of whole brain, in vivo magnetic resonance images (MRIs) of anatomically modern humans (Homo sapiens sapiens) and five ape species (gibbons, orangutans, gorillas, chimpanzees, bonobos). Twenty-nine 3D landmarks, including surface and internal features of the brain were located on 3D MRI reconstructions of each individual using MEASURE software. Landmark coordinate data were scaled for differences in size and analyzed using Euclidean Distance Matrix Analysis (EDMA) to statistically compare the brains of each non-human ape species to the human sample. Results of analyses show both a pattern of brain morphology that is consistently different between all apes and humans, as well as patterns that differ among species. Further, both the consistent and species-specific patterns include cortical and subcortical features. The pattern that remains consistent across species indicates a morphological reorganization of 1) relationships between cortical and subcortical frontal structures, 2) expansion of the temporal lobe and location of the amygdala, and 3) expansion of the anterior parietal region. Additionally, results demonstrate that, although there is a pattern of morphology that uniquely defines the human brain, there are also patterns that uniquely differentiate human morphology from the morphology of each non-human ape species, indicating that reorganization of neural morphology occurred at the evolutionary divergence of each of these groups. Copyright © 2010 Elsevier Ltd. All rights reserved.

Patterns of differences in brain morphology in humans as compared to extant apes

PubMed Central

Aldridge, Kristina

2010-01-01

Although human evolution is characterized by a vast increase in brain size, it is not clear whether or not certain regions of the brain are enlarged disproportionately in humans, or how this enlargement relates to differences in overall neural morphology. The aim of this study is to determine whether or not there are specific suites of features that distinguish the morphology of the human brain from that of apes. The study sample consists of whole brain, in vivo magnetic resonance images (MRIs) of anatomically modern humans (Homo sapiens sapiens) and five ape species (gibbons, orangutans, gorillas, chimpanzees, bonobos). Twenty-nine 3D landmarks, including surface and internal features of the brain were located on 3D MRI reconstructions of each individual using MEASURE software. Landmark coordinate data were scaled for differences in size and analyzed using Euclidean Distance Matrix Analysis (EDMA) to statistically compare the brains of each non-human ape species to the human sample. Results of analyses show both a pattern of brain morphology that is consistently different between all apes and humans, as well as patterns that differ among species. Further, both the consistent and species-specific patterns include cortical and subcortical features. The pattern that remains consistent across species indicates a morphological reorganization of 1) relationships between cortical and subcortical frontal structures, 2) expansion of the temporal lobe and location of the amygdala, and 3) expansion of the anterior parietal region. Additionally, results demonstrate that, although there is a pattern of morphology that uniquely defines the human brain, there are also patterns that uniquely differentiate human morphology from the morphology of each non-human ape species, indicating that reorganization of neural morphology occurred at the evolutionary divergence of each of these groups. PMID:21056456

An Evolutionary Computation Approach to Examine Functional Brain Plasticity.

PubMed

Roy, Arnab; Campbell, Colin; Bernier, Rachel A; Hillary, Frank G

2016-01-01

One common research goal in systems neurosciences is to understand how the functional relationship between a pair of regions of interest (ROIs) evolves over time. Examining neural connectivity in this way is well-suited for the study of developmental processes, learning, and even in recovery or treatment designs in response to injury. For most fMRI based studies, the strength of the functional relationship between two ROIs is defined as the correlation between the average signal representing each region. The drawback to this approach is that much information is lost due to averaging heterogeneous voxels, and therefore, the functional relationship between a ROI-pair that evolve at a spatial scale much finer than the ROIs remain undetected. To address this shortcoming, we introduce a novel evolutionary computation (EC) based voxel-level procedure to examine functional plasticity between an investigator defined ROI-pair by simultaneously using subject-specific BOLD-fMRI data collected from two sessions seperated by finite duration of time. This data-driven procedure detects a sub-region composed of spatially connected voxels from each ROI (a so-called sub-regional-pair) such that the pair shows a significant gain/loss of functional relationship strength across the two time points. The procedure is recursive and iteratively finds all statistically significant sub-regional-pairs within the ROIs. Using this approach, we examine functional plasticity between the default mode network (DMN) and the executive control network (ECN) during recovery from traumatic brain injury (TBI); the study includes 14 TBI and 12 healthy control subjects. We demonstrate that the EC based procedure is able to detect functional plasticity where a traditional averaging based approach fails. The subject-specific plasticity estimates obtained using the EC-procedure are highly consistent across multiple runs. Group-level analyses using these plasticity estimates showed an increase in the strength of functional relationship between DMN and ECN for TBI subjects, which is consistent with prior findings in the TBI-literature. The EC-approach also allowed us to separate sub-regional-pairs contributing to positive and negative plasticity; the detected sub-regional-pairs significantly overlap across runs thus highlighting the reliability of the EC-approach. These sub-regional-pairs may be useful in performing nuanced analyses of brain-behavior relationships during recovery from TBI.

Structural basis for serotonergic regulation of neural circuits in the mouse olfactory bulb.

PubMed

Suzuki, Yoshinori; Kiyokage, Emi; Sohn, Jaerin; Hioki, Hiroyuki; Toida, Kazunori

2015-02-01

Olfactory processing is well known to be regulated by centrifugal afferents from other brain regions, such as noradrenergic, acetylcholinergic, and serotonergic neurons. Serotonergic neurons widely innervate and regulate the functions of various brain regions. In the present study, we focused on serotonergic regulation of the olfactory bulb (OB), one of the most structurally and functionally well-defined brain regions. Visualization of a single neuron among abundant and dense fibers is essential to characterize and understand neuronal circuits. We accomplished this visualization by successfully labeling and reconstructing serotonin (5-hydroxytryptamine: 5-HT) neurons by infection with sindbis and adeno-associated virus into dorsal raphe nuclei (DRN) of mice. 5-HT synapses were analyzed by correlative confocal laser microscopy and serial-electron microscopy (EM) study. To further characterize 5-HT neuronal and network function, we analyzed whether glutamate was released from 5-HT synaptic terminals using immuno-EM. Our results are the first visualizations of complete 5-HT neurons and fibers projecting from DRN to the OB with bifurcations. We found that a single 5-HT axon can form synaptic contacts to both type 1 and 2 periglomerular cells within a single glomerulus. Through immunolabeling, we also identified vesicular glutamate transporter 3 in 5-HT neurons terminals, indicating possible glutamatergic transmission. Our present study strongly implicates the involvement of brain regions such as the DRN in regulation of the elaborate mechanisms of olfactory processing. We further provide a structure basis of the network for coordinating or linking olfactory encoding with other neural systems, with special attention to serotonergic regulation. © 2014 Wiley Periodicals, Inc.

Shades of white: diffusion properties of T1- and FLAIR-defined white matter signal abnormalities differ in stages from cognitively normal to dementia.

PubMed

Riphagen, Joost M; Gronenschild, Ed H B M; Salat, David H; Freeze, Whitney M; Ivanov, Dimo; Clerx, Lies; Verhey, Frans R J; Aalten, Pauline; Jacobs, Heidi I L

2018-08-01

The underlying pathology of white matter signal abnormalities (WMSAs) is heterogeneous and may vary dependent on the magnetic resonance imaging contrast used to define them. We investigated differences in white matter diffusivity as an indicator for white matter integrity underlying WMSA based on T1-weighted and fluid-attenuated inversion recovery (FLAIR) imaging contrast. In addition, we investigated which white matter region of interest (ROI) could predict clinical diagnosis best using diffusion metrics. One hundred three older individuals with varying cognitive impairment levels were included and underwent neuroimaging. Diffusion metrics were extracted from WMSA areas based on T1 and FLAIR contrast and from their overlapping areas, the border surrounding the WMSA and the normal-appearing white matter (NAWM). Regional diffusivity differences were calculated with linear mixed effects models. Multinomial logistic regression determined which ROI diffusion values classified individuals best into clinically defined diagnostic groups. T1-based WMSA showed lower white matter integrity compared to FLAIR WMSA-defined regions. Diffusion values of NAWM predicted diagnostic group best compared to other ROI's. To conclude, T1- or FLAIR-defined WMSA provides distinct information on the underlying white matter integrity associated with cognitive decline. Importantly, not the "diseased" but the NAWM is a potentially sensitive indicator for cognitive brain health status. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Evolution of brain region volumes during artificial selection for relative brain size.

PubMed

Kotrschal, Alexander; Zeng, Hong-Li; van der Bijl, Wouter; Öhman-Mägi, Caroline; Kotrschal, Kurt; Pelckmans, Kristiaan; Kolm, Niclas

2017-12-01

The vertebrate brain shows an extremely conserved layout across taxa. Still, the relative sizes of separate brain regions vary markedly between species. One interesting pattern is that larger brains seem associated with increased relative sizes only of certain brain regions, for instance telencephalon and cerebellum. Till now, the evolutionary association between separate brain regions and overall brain size is based on comparative evidence and remains experimentally untested. Here, we test the evolutionary response of brain regions to directional selection on brain size in guppies (Poecilia reticulata) selected for large and small relative brain size. In these animals, artificial selection led to a fast response in relative brain size, while body size remained unchanged. We use microcomputer tomography to investigate how the volumes of 11 main brain regions respond to selection for larger versus smaller brains. We found no differences in relative brain region volumes between large- and small-brained animals and only minor sex-specific variation. Also, selection did not change allometric scaling between brain and brain region sizes. Our results suggest that brain regions respond similarly to strong directional selection on relative brain size, which indicates that brain anatomy variation in contemporary species most likely stem from direct selection on key regions. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

DIAGNOSIS OF ENDOCRINE DISEASE: Expanding the cause of hypopituitarism.

PubMed

Pekic, Sandra; Popovic, Vera

2017-06-01

Hypopituitarism is defined as one or more pituitary hormone deficits due to a lesion in the hypothalamic-pituitary region. By far, the most common cause of hypopituitarism associated with a sellar mass is a pituitary adenoma. A high index of suspicion is required for diagnosing hypopituitarism in several other conditions such as other massess in the sellar and parasellar region, brain damage caused by radiation and by traumatic brain injury, vascular lesions, infiltrative/immunological/inflammatory diseases (lymphocytic hypophysitis, sarcoidosis and hemochromatosis), infectious diseases and genetic disorders. Hypopituitarism may be permanent and progressive with sequential pattern of hormone deficiencies (radiation-induced hypopituitarism) or transient after traumatic brain injury with possible recovery occurring years from the initial event. In recent years, there is increased reporting of less common and less reported causes of hypopituitarism with its delayed diagnosis. The aim of this review is to summarize the published data and to allow earlier identification of populations at risk of hypopituitarism as optimal hormonal replacement may significantly improve their quality of life and life expectancy. © 2017 European Society of Endocrinology.

Spatial organization of astrocytes in ferret visual cortex.

PubMed

López-Hidalgo, Mónica; Hoover, Walter B; Schummers, James

2016-12-01

Astrocytes form an intricate partnership with neural circuits to influence numerous cellular and synaptic processes. One prominent organizational feature of astrocytes is the "tiling" of the brain with non-overlapping territories. There are some documented species and brain region-specific astrocyte specializations, but the extent of astrocyte diversity and circuit specificity are still unknown. We quantitatively defined the rules that govern the spatial arrangement of astrocyte somata and territory overlap in ferret visual cortex using a combination of in vivo two-photon imaging, morphological reconstruction, immunostaining, and model simulations. We found that ferret astrocytes share, on average, half of their territory with other astrocytes. However, a specific class of astrocytes, abundant in thalamo-recipient cortical layers ("kissing" astrocytes), overlap markedly less. Together, these results demonstrate novel features of astrocyte organization indicating that different classes of astrocytes are arranged in a circuit-specific manner and that tiling does not apply universally across brain regions and species. J. Comp. Neurol. 524:3561-3576, 2016. © 2016 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc. © 2016 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc.

Characterizing brain patterns in conversion from mild cognitive impairment (MCI) to Alzheimer's disease

NASA Astrophysics Data System (ADS)

Silva R., Santiago S.; Giraldo, Diana L.; Romero, Eduardo

2017-11-01

Structural Magnetic Resonance (MR) brain images should provide quantitative information about the stage and progression of Alzheimer's disease. However, the use of MRI is limited and practically reduced to corroborate a diagnosis already performed with neuropsychological tools. This paper presents an automated strategy for extraction of relevant anatomic patterns related with the conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) using T1-weighted MR images. The process starts by representing each of the possible classes with models generated from a linear combination of volumes. The difference between models allows us to establish which are the regions where relevant patterns might be located. The approach searches patterns in a space of brain sulci, herein approximated by the most representative gradients found in regions of interest defined by the difference between the linear models. This hypothesis is assessed by training a conventional SVM model with the found relevant patterns under a leave-one-out scheme. The resultant AUC was 0.86 for the group of women and 0.61 for the group of men.

Meta-connectomics: human brain network and connectivity meta-analyses.

PubMed

Crossley, N A; Fox, P T; Bullmore, E T

2016-04-01

Abnormal brain connectivity or network dysfunction has been suggested as a paradigm to understand several psychiatric disorders. We here review the use of novel meta-analytic approaches in neuroscience that go beyond a summary description of existing results by applying network analysis methods to previously published studies and/or publicly accessible databases. We define this strategy of combining connectivity with other brain characteristics as 'meta-connectomics'. For example, we show how network analysis of task-based neuroimaging studies has been used to infer functional co-activation from primary data on regional activations. This approach has been able to relate cognition to functional network topology, demonstrating that the brain is composed of cognitively specialized functional subnetworks or modules, linked by a rich club of cognitively generalized regions that mediate many inter-modular connections. Another major application of meta-connectomics has been efforts to link meta-analytic maps of disorder-related abnormalities or MRI 'lesions' to the complex topology of the normative connectome. This work has highlighted the general importance of network hubs as hotspots for concentration of cortical grey-matter deficits in schizophrenia, Alzheimer's disease and other disorders. Finally, we show how by incorporating cellular and transcriptional data on individual nodes with network models of the connectome, studies have begun to elucidate the microscopic mechanisms underpinning the macroscopic organization of whole-brain networks. We argue that meta-connectomics is an exciting field, providing robust and integrative insights into brain organization that will likely play an important future role in consolidating network models of psychiatric disorders.

A three-plane architectonic atlas of the rat hippocampal region.

PubMed

Boccara, Charlotte N; Kjonigsen, Lisa J; Hammer, Ingvild M; Bjaalie, Jan G; Leergaard, Trygve B; Witter, Menno P

2015-07-01

The hippocampal region, comprising the hippocampal formation and the parahippocampal region, has been one of the most intensively studied parts of the brain for decades. Better understanding of its functional diversity and complexity has led to an increased demand for specificity in experimental procedures and manipulations. In view of the complex 3D structure of the hippocampal region, precisely positioned experimental approaches require a fine-grained architectural description that is available and readable to experimentalists lacking detailed anatomical experience. In this paper, we provide the first cyto- and chemoarchitectural description of the hippocampal formation and parahippocampal region in the rat at high resolution and in the three standard sectional planes: coronal, horizontal and sagittal. The atlas uses a series of adjacent sections stained for neurons and for a number of chemical marker substances, particularly parvalbumin and calbindin. All the borders defined in one plane have been cross-checked against their counterparts in the other two planes. The entire dataset will be made available as a web-based interactive application through the Rodent Brain WorkBench (http://www.rbwb.org) which, together with this paper, provides a unique atlas resource. © 2014 Wiley Periodicals, Inc.

BI-31ANALYSIS AND QUANTIFICATION OF MULTIPLE ANTIGEN EXPRESSION IN GLIOBLASTOMA

PubMed Central

Weng, Lihong; Zhai, Yubo; D'Apuzzo, Massimo; Badie, Behnam; Forman, Stephen J.; Barish, Michael; Brown, Christine E.

2014-01-01

Glioblastoma (GBM), one of the most common and fatal types of brain tumor, is marked by significant antigenic heterogeneity. Identification and quantification of tumor related antigens in the context of GBM tissue is an essential step towards developing antigen- targeted therapies. Immunohistochemistry (IHC) on formalin-fixed paraffin embedded (FFPE) clinical specimens is a valuable technique for evaluating antigen expression in large study cohorts. To overcome the limitations of manual semi-quantitative scoring and subjectivity in the evaluation of IHC staining, we analyzed and quantified multiple antigens across entire tumor sections using Image Pro Premier v9.1 (DAB plug-in). For each slide, dense tumor regions (DTRs, tumor cells >60%), tumor infiltration regions (TIRs, tumor cells <50%) and pseudopalisading necrosis regions (PPNs) were defined from HE section by a neuropathologist. We quantified the expression of tumor-associated antigens IL13Rα2, HER2, EGFR and the proliferation marker Ki67 within these defined regions for 44 brain tumor samples (35 stage IV and 9 stage III). Our results demonstrate the heterogeneous expression patterns of IL13Rα2, HER2 and EGFR in GBMs. For example, in dense tumor regions 52%, 61% and 77% of samples showed IL13Rα2, HER2 or EGFR positivity, respectively. In correlation studies, 25% of samples were triple positive, 11% of samples showed double positivity for IL13Rα2 and HER2 or IL13Rα2 and EGFR, and 25% of samples were double positive of EGFR and HER2. Less than 7% of samples were negative for all three antigens. Interestingly, a higher percentage of samples showed triple positive expression in PPN regions (43%) versus the DTR (25%) and TIR (25%) regions. Also, Ki67 positivity was higher in PPN and DTR regions. In this study we developed methods for combining pathological annotations with DAB-capturing software, which allowed us to quantify protein expression in a more precise, consistent and efficient manner.

Abnormal regional activity and functional connectivity in resting-state brain networks associated with etiology confirmed unilateral pulsatile tinnitus in the early stage of disease.

PubMed

Lv, Han; Zhao, Pengfei; Liu, Zhaohui; Li, Rui; Zhang, Ling; Wang, Peng; Yan, Fei; Liu, Liheng; Wang, Guopeng; Zeng, Rong; Li, Ting; Dong, Cheng; Gong, Shusheng; Wang, Zhenchang

2017-03-01

Abnormal neural activities can be revealed by resting-state functional magnetic resonance imaging (rs-fMRI) using analyses of the regional activity and functional connectivity (FC) of the networks in the brain. This study was designed to demonstrate the functional network alterations in the patients with pulsatile tinnitus (PT). In this study, we recruited 45 patients with unilateral PT in the early stage of disease (less than 48 months of disease duration) and 45 normal controls. We used regional homogeneity (ReHo) and seed-based FC computational methods to reveal resting-state brain activity features associated with pulsatile tinnitus. Compared with healthy controls, PT patients showed regional abnormalities mainly in the left middle occipital gyrus (MOG), posterior cingulate gyrus (PCC), precuneus and right anterior insula (AI). When these regions were defined as seeds, we demonstrated widespread modification of interaction between the auditory and non-auditory networks. The auditory network was positively connected with the cognitive control network (CCN), which may associate with tinnitus related distress. Both altered regional activity and changed FC were found in the visual network. The modification of interactions of higher order networks were mainly found in the DMN, CCN and limbic networks. Functional connectivity between the left MOG and left parahippocampal gyrus could also be an index to reflect the disease duration. This study helped us gain a better understanding of the characteristics of neural network modifications in patients with pulsatile tinnitus. Copyright © 2017 Elsevier B.V. All rights reserved.

Visual Exploration of Genetic Association with Voxel-based Imaging Phenotypes in an MCI/AD Study

PubMed Central

Kim, Sungeun; Shen, Li; Saykin, Andrew J.; West, John D.

2010-01-01

Neuroimaging genomics is a new transdisciplinary research field, which aims to examine genetic effects on brain via integrated analyses of high throughput neuroimaging and genomic data. We report our recent work on (1) developing an imaging genomic browsing system that allows for whole genome and entire brain analyses based on visual exploration and (2) applying the system to the imaging genomic analysis of an existing MCI/AD cohort. Voxel-based morphometry is used to define imaging phenotypes. ANCOVA is employed to evaluate the effect of the interaction of genotypes and diagnosis in relation to imaging phenotypes while controlling for relevant covariates. Encouraging experimental results suggest that the proposed system has substantial potential for enabling discovery of imaging genomic associations through visual evaluation and for localizing candidate imaging regions and genomic regions for refined statistical modeling. PMID:19963597

Hypometabolism as a therapeutic target in Alzheimer's disease.

PubMed

Costantini, Lauren C; Barr, Linda J; Vogel, Janet L; Henderson, Samuel T

2008-12-03

The pathology of Alzheimer's disease (AD) is characterized by cerebral atrophy in frontal, temporal, and parietal regions, with senile plaques, dystrophic neurites, and neurofibrillar tangles within defined areas of the brain. Another characteristic of AD is regional hypometabolism in the brain. This decline in cerebral glucose metabolism occurs before pathology and symptoms manifest, continues as symptoms progress, and is more severe than that of normal aging. Ketone bodies are an efficient alternative fuel for cells that are unable to metabolize glucose or are 'starved' of glucose. AC-1202 is designed to elevate serum ketone levels safely. We previously showed that treatment with AC-1202 in patients with mild-to-moderate AD improves memory and cognition. Treatment outcomes were influenced by apolipoprotein E genotype status. These data suggest that AC-1202 may be an effective treatment for cognitive dysfunction by providing an alternative substrate for use by glucose-compromised neurons.

Effects of acute microinjections of the thyroid hormone derivative 3-iodothyronamine to the preoptic region of adult male rats on sleep, thermoregulation and motor activity

PubMed Central

James, Thomas D.; Moffett, Steven X.; Scanlan, Thomas S.; Martin, Joseph V.

2014-01-01

The decarboxylated thyroid hormone derivative 3-iodothyronamine (T1AM) has been reported as having behavioral and physiological consequences distinct from those of thyroid hormones. Here, we investigate the effects of T1AM on EEG-defined sleep after acute administration to the preoptic region of adult male rats. Our laboratory recently demonstrated a decrease in EEG-defined sleep after administration of 3,3′,5-triiodo-L-thyronine (T3) to the same brain region. After injection of T1AM or vehicle solution, EEG, EMG, activity, and core body temperature were recorded for 24 h. Sleep parameters were determined from EEG and EMG data. Earlier investigations found contrasting systemic effects of T3 and T1AM, such as decreased heart rate and body temperature after intraperitoneal T1AM injection. However, nREM sleep was decreased in the present study after injections of 1 or 3 μg T1AM, but not after 0.3 or 10 μg, closely mimicking the previously reported effects of T3 administration to the preoptic region. The biphasic dose–response observed after either T1AM or T3 administration seems to indicate shared mechanisms and/or functions of sleep regulation in the preoptic region. Consistent with systemic administration of T1AM, however, microinjection of T1AM decreased body temperature. The current study is the first to show modulation of sleep by T1AM, and suggests that T1AM and T3 have both shared and independent effects in the adult mammalian brain. PMID:23702093

Avalanches and generalized memory associativity in a network model for conscious and unconscious mental functioning

NASA Astrophysics Data System (ADS)

Siddiqui, Maheen; Wedemann, Roseli S.; Jensen, Henrik Jeldtoft

2018-01-01

We explore statistical characteristics of avalanches associated with the dynamics of a complex-network model, where two modules corresponding to sensorial and symbolic memories interact, representing unconscious and conscious mental processes. The model illustrates Freud's ideas regarding the neuroses and that consciousness is related with symbolic and linguistic memory activity in the brain. It incorporates the Stariolo-Tsallis generalization of the Boltzmann Machine in order to model memory retrieval and associativity. In the present work, we define and measure avalanche size distributions during memory retrieval, in order to gain insight regarding basic aspects of the functioning of these complex networks. The avalanche sizes defined for our model should be related to the time consumed and also to the size of the neuronal region which is activated, during memory retrieval. This allows the qualitative comparison of the behaviour of the distribution of cluster sizes, obtained during fMRI measurements of the propagation of signals in the brain, with the distribution of avalanche sizes obtained in our simulation experiments. This comparison corroborates the indication that the Nonextensive Statistical Mechanics formalism may indeed be more well suited to model the complex networks which constitute brain and mental structure.

White Matter Connectivity of the Thalamus Delineates the Functional Architecture of Competing Thalamocortical Systems

PubMed Central

O'Muircheartaigh, Jonathan; Keller, Simon S.; Barker, Gareth J.; Richardson, Mark P.

2015-01-01

There is an increasing awareness of the involvement of thalamic connectivity on higher level cortical functioning in the human brain. This is reflected by the influence of thalamic stimulation on cortical activity and behavior as well as apparently cortical lesion syndromes occurring as a function of small thalamic insults. Here, we attempt to noninvasively test the correspondence of structural and functional connectivity of the human thalamus using diffusion-weighted and resting-state functional MRI. Using a large sample of 102 adults, we apply tensor independent component analysis to diffusion MRI tractography data to blindly parcellate bilateral thalamus according to diffusion tractography-defined structural connectivity. Using resting-state functional MRI collected in the same subjects, we show that the resulting structurally defined thalamic regions map to spatially distinct, and anatomically predictable, whole-brain functional networks in the same subjects. Although there was significant variability in the functional connectivity patterns, the resulting 51 structural and functional patterns could broadly be reduced to a subset of 7 similar core network types. These networks were distinct from typical cortical resting-state networks. Importantly, these networks were distributed across the brain and, in a subset, map extremely well to known thalamocortico-basal-ganglial loops. PMID:25899706

Continuous High Frequency Activity: A peculiar SEEG pattern related to specific brain regions

PubMed Central

Melani, Federico; Zelmann, Rina; Mari, Francesco; Gotman, Jean

2015-01-01

Objective While visually marking the high frequency oscillations in the stereo-EEG of epileptic patients, we observed a continuous/semicontinuous activity in the ripple band (80–250 Hz), which we defined continuous High Frequency Activity (HFA). We aim to analyze in all brain regions the occurrence and significance of this particular pattern. Methods Twenty patients implanted in mesial temporal and neocortical areas were studied. One minute of slow-wave sleep was reviewed. The background was classified as continuous/semicontinuous, irregular, or sporadic based on the duration of the fast oscillations. Each channel was classified as inside/outside the seizure onset zone (SOZ) or a lesion. Results The continuous/semicontinuous HFA occurred in 54 of the 790 channels analyzed, with a clearly higher prevalence in hippocampus and occipital lobe. No correlation was found with the SOZ or lesions. In the occipital lobe the continuous/semicontinuous HFA was present independently of whether eyes were open or closed. Conclusions We describe what appears to be a new physiological High Frequency Activity, independent of epileptogenicity, present almost exclusively in the hippocampus and occipital cortex but independent of the alpha rhythm. Significance The continuous HFA may be an intrinsic characteristic of specific brain regions, reflecting a particular type of physiological neuronal activity. PMID:23768436

Novel fingerprinting method characterises the necessary and sufficient structural connectivity from deep brain stimulation electrodes for a successful outcome

NASA Astrophysics Data System (ADS)

Fernandes, Henrique M.; Van Hartevelt, Tim J.; Boccard, Sandra G. J.; Owen, Sarah L. F.; Cabral, Joana; Deco, Gustavo; Green, Alex L.; Fitzgerald, James J.; Aziz, Tipu Z.; Kringelbach, Morten L.

2015-01-01

Deep brain stimulation (DBS) is a remarkably effective clinical tool, used primarily for movement disorders. DBS relies on precise targeting of specific brain regions to rebalance the oscillatory behaviour of whole-brain neural networks. Traditionally, DBS targeting has been based upon animal models (such as MPTP for Parkinson’s disease) but has also been the result of serendipity during human lesional neurosurgery. There are, however, no good animal models of psychiatric disorders such as depression and schizophrenia, and progress in this area has been slow. In this paper, we use advanced tractography combined with whole-brain anatomical parcellation to provide a rational foundation for identifying the connectivity ‘fingerprint’ of existing, successful DBS targets. This knowledge can then be used pre-surgically and even potentially for the discovery of novel targets. First, using data from our recent case series of cingulate DBS for patients with treatment-resistant chronic pain, we demonstrate how to identify the structural ‘fingerprints’ of existing successful and unsuccessful DBS targets in terms of their connectivity to other brain regions, as defined by the whole-brain anatomical parcellation. Second, we use a number of different strategies to identify the successful fingerprints of structural connectivity across four patients with successful outcomes compared with two patients with unsuccessful outcomes. This fingerprinting method can potentially be used pre-surgically to account for a patient’s individual connectivity and identify the best DBS target. Ultimately, our novel fingerprinting method could be combined with advanced whole-brain computational modelling of the spontaneous dynamics arising from the structural changes in disease, to provide new insights and potentially new targets for hitherto impenetrable neuropsychiatric disorders.

Absence of Colony Stimulation Factor-1 Receptor Results in Loss of Microglia, Disrupted Brain Development and Olfactory Deficits

PubMed Central

Etgen, Anne M.; Dobrenis, Kostantin; Pollard, Jeffrey W.

2011-01-01

The brain contains numerous mononuclear phagocytes called microglia. These cells express the transmembrane tyrosine kinase receptor for the macrophage growth factor colony stimulating factor-1 (CSF-1R). Using a CSF-1R-GFP reporter mouse strain combined with lineage defining antibody staining we show in the postnatal mouse brain that CSF-1R is expressed only in microglia and not neurons, astrocytes or glial cells. To study CSF-1R function we used mice homozygous for a null mutation in the Csflr gene. In these mice microglia are >99% depleted at embryonic day 16 and day 1 post-partum brain. At three weeks of age this microglial depletion continues in most regions of the brain although some contain clusters of rounded microglia. Despite the loss of microglia, embryonic brain development appears normal but during the post-natal period the brain architecture becomes perturbed with enlarged ventricles and regionally compressed parenchyma, phenotypes most prominent in the olfactory bulb and cortex. In the cortex there is increased neuronal density, elevated numbers of astrocytes but reduced numbers of oligodendrocytes. Csf1r nulls rarely survive to adulthood and therefore to study the role of CSF-1R in olfaction we used the viable null mutants in the Csf1 (Csf1op) gene that encodes one of the two known CSF-1R ligands. Food-finding experiments indicate that olfactory capacity is significantly impaired in the absence of CSF-1. CSF-1R is therefore required for the development of microglia, for a fully functional olfactory system and the maintenance of normal brain structure. PMID:22046273

1H-MRSI pattern perturbation in a mouse glioma: the effects of acute hyperglycemia and moderate hypothermia.

PubMed

Simões, R V; Delgado-Goñi, T; Lope-Piedrafita, S; Arús, C

2010-01-01

MR spectroscopic Imaging (MRSI), with PRESS localization, is used here to monitor the effects of acute hyperglycemia in the spectral pattern of 11 mice bearing GL261 gliomas at normothermia (36.5-37.5 degrees C) and at hypothermia (28.5-29.5 degrees C). These in vivo studies were complemented by ex vivo high resolution magic angle spinning (HR-MAS) analysis of GL261 tumor samples from 6 animals sacrificed by focused microwave irradiation, and blood glucose measurements in 12 control mice. Apparent glucose levels, monitored by in vivo MRSI in brain tumors during acute hyperglycemia, rose to an average of 1.6-fold during hypothermia (p < 0.05), while no significant changes were detected at normothermia, or in control experiments performed at euglycemia, or in normal/peritumoral brain regions. Ex vivo analysis of glioma-bearing mouse brains at hypothermia revealed higher glucose increases in distinct regions during the acute hyperglycemic challenge (up to 6.6-fold at the tumor center), in agreement with maximal in vivo blood glucose changes (5-fold). Phantom studies on taurine plus glucose containing solutions explained the differences between in vivo and ex vivo measurements. Our results also indicate brain tumor heterogeneity in the four animal tumors investigated in response to a defined metabolic challenge.

Dynamics of brain activity in motor and frontal cortical areas during music listening: a magnetoencephalographic study.

PubMed

Popescu, Mihai; Otsuka, Asuka; Ioannides, Andreas A

2004-04-01

There are formidable problems in studying how 'real' music engages the brain over wide ranges of temporal scales extending from milliseconds to a lifetime. In this work, we recorded the magnetoencephalographic signal while subjects listened to music as it unfolded over long periods of time (seconds), and we developed and applied methods to correlate the time course of the regional brain activations with the dynamic aspects of the musical sound. We showed that frontal areas generally respond with slow time constants to the music, reflecting their more integrative mode; motor-related areas showed transient-mode responses to fine temporal scale structures of the sound. The study combined novel analysis techniques designed to capture and quantify fine temporal sequencing from the authentic musical piece (characterized by a clearly defined rhythm and melodic structure) with the extraction of relevant features from the dynamics of the regional brain activations. The results demonstrated that activity in motor-related structures, specifically in lateral premotor areas, supplementary motor areas, and somatomotor areas, correlated with measures of rhythmicity derived from the music. These correlations showed distinct laterality depending on how the musical performance deviated from the strict tempo of the music score, that is, depending on the musical expression.

Comparison of multiple tau-PET measures as biomarkers in aging and Alzheimer's disease

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maass, Anne; Landau, Susan; Baker, Suzanne L.

The recent development of tau-specific positron emission tomography (PET) tracers enables in vivo quantification of regional tau pathology, one of the key lesions in Alzheimer's disease (AD). Tau PET imaging may become a useful biomarker for clinical diagnosis and tracking of disease progression but there is no consensus yet on how tau PET signal is best quantified. The goal of the current paper was to evaluate multiple whole-brain and region-specific approaches to detect clinically relevant tau PET signal. Two independent cohorts of cognitively normal adults and amyloid-positive (Aβ +) patients with mild cognitive impairment (MCI) or AD-dementia underwent [ 18F]AV-1451more » PET. Methods for tau tracer quantification included: (i) in vivo Braak staging, (ii) regional uptake in Braak composite regions, (iii) several whole-brain measures of tracer uptake, (iv) regional uptake in AD-vulnerable voxels, and (v) uptake in a priori defined regions. Receiver operating curves characterized accuracy in distinguishing Aβ - controls from AD/MCI patients and yielded tau positivity cutoffs. Clinical relevance of tau PET measures was assessed by regressions against cognition and MR imaging measures. Key tracer uptake patterns were identified by a factor analysis and voxel-wise contrasts. Braak staging, global and region-specific tau measures yielded similar diagnostic accuracies, which differed between cohorts. While all tau measures were related to amyloid and global cognition, memory and hippocampal/entorhinal volume/thickness were associated with regional tracer retention in the medial temporal lobe. Key regions of tau accumulation included medial temporal and inferior/middle temporal regions, retrosplenial cortex, and banks of the superior temporal sulcus. Finally, our data indicate that whole-brain tau PET measures might be adequate biomarkers to detect AD-related tau pathology. However, regional measures covering AD-vulnerable regions may increase sensitivity to early tau PET signal, atrophy and memory decline.« less

Construction and evaluation of quantitative small-animal PET probabilistic atlases for [¹⁸F]FDG and [¹⁸F]FECT functional mapping of the mouse brain.

PubMed

Casteels, Cindy; Vunckx, Kathleen; Aelvoet, Sarah-Ann; Baekelandt, Veerle; Bormans, Guy; Van Laere, Koen; Koole, Michel

2013-01-01

Automated voxel-based or pre-defined volume-of-interest (VOI) analysis of small-animal PET data in mice is necessary for optimal information usage as the number of available resolution elements is limited. We have mapped metabolic ([(18)F]FDG) and dopamine transporter ([(18)F]FECT) small-animal PET data onto a 3D Magnetic Resonance Microscopy (MRM) mouse brain template and aligned them in space to the Paxinos co-ordinate system. In this way, ligand-specific templates for sensitive analysis and accurate anatomical localization were created. Next, using a pre-defined VOI approach, test-retest and intersubject variability of various quantification methods were evaluated. Also, the feasibility of mouse brain statistical parametric mapping (SPM) was explored for [(18)F]FDG and [(18)F]FECT imaging of 6-hydroxydopamine-lesioned (6-OHDA) mice. Twenty-three adult C57BL6 mice were scanned with [(18)F]FDG and [(18)F]FECT. Registrations and affine spatial normalizations were performed using SPM8. [(18)F]FDG data were quantified using (1) an image-derived-input function obtained from the liver (cMRglc), using (2) standardized uptake values (SUVglc) corrected for blood glucose levels and by (3) normalizing counts to the whole-brain uptake. Parametric [(18)F]FECT binding images were constructed by reference to the cerebellum. Registration accuracy was determined using random simulated misalignments and vectorial mismatch determination. Registration accuracy was between 0.21-1.11 mm. Regional intersubject variabilities of cMRglc ranged from 15.4% to 19.2%, while test-retest values were between 5.0% and 13.0%. For [(18)F]FECT uptake in the caudate-putamen, these values were 13.0% and 10.3%, respectively. Regional values of cMRglc positively correlated to SUVglc measured within the 45-60 min time frame (spearman r = 0.71). Next, SPM analysis of 6-OHDA-lesioned mice showed hypometabolism in the bilateral caudate-putamen and cerebellum, and an unilateral striatal decrease in DAT availability. MRM-based small-animal PET templates facilitate accurate assessment and spatial localization of mouse brain function using VOI or voxel-based analysis. Regional intersubject- and test-retest variations indicate that for these targets accuracy comparable to humans can be achieved.

Neuroanatomic alterations and social and communication deficits in monozygotic twins discordant for autism disorder.

PubMed

Mitchell, Shanti R; Reiss, Allan L; Tatusko, Danielle H; Ikuta, Ichiro; Kazmerski, Dana B; Botti, Jo-Anna C; Burnette, Courtney P; Kates, Wendy R

2009-08-01

Investigating neuroanatomic differences in monozygotic twins who are discordant for autism can help unravel the relative contributions of genetics and environment to this pervasive developmental disorder. The authors used magnetic resonance imaging (MRI) to investigate several brain regions of interest in monozygotic twins who varied in degree of phenotypic discordance for narrowly defined autism. The subjects were 14 pairs of monozygotic twins between the ages of 5 and 14 years old and 14 singleton age- and gender-matched typically developing comparison subjects. The monozygotic twin group was a cohort of children with narrowly defined autistic deficits and their co-twins who presented with varying levels of autistic deficits. High-resolution MRIs were acquired and volumetric/area measurements obtained for the frontal lobe, amygdala, and hippocampus and subregions of the prefrontal cortex, corpus callosum, and cerebellar vermis. No neurovolumetric/area differences were found between twin pairs. Relative to typically developing comparison subjects, dorsolateral prefrontal cortex volumes and anterior areas of the corpus callosum were significantly altered in autistic twins, and volumes of the posterior vermis were altered in both autistic twins and co-twins. Intraclass correlation analysis of brain volumes between children with autism and their co-twins indicated that the degree of within-pair neuroanatomic concordance varied with brain region. In the group of subjects with narrowly defined autism only, dorsolateral prefrontal cortex, amygdala, and posterior vermis volumes were significantly associated with the severity of autism based on scores from the Autism Diagnostic Observation Schedule-Generic. These findings support previous research demonstrating alterations in the prefrontal cortex, corpus callosum, and posterior vermis in children with autism and further suggest that alterations are associated with the severity of the autism phenotype. Continued research involving twins who are concordant and discordant for autism is essential to disentangle the genetic and environmental contributions to autism.

The Emergence of Network Inefficiencies in Infants With Autism Spectrum Disorder.

PubMed

Lewis, John D; Evans, Alan C; Pruett, John R; Botteron, Kelly N; McKinstry, Robert C; Zwaigenbaum, Lonnie; Estes, Annette M; Collins, D Louis; Kostopoulos, Penelope; Gerig, Guido; Dager, Stephen R; Paterson, Sarah; Schultz, Robert T; Styner, Martin A; Hazlett, Heather C; Piven, Joseph

2017-08-01

Autism spectrum disorder (ASD) is a developmental disorder defined by behavioral features that emerge during the first years of life. Research indicates that abnormalities in brain connectivity are associated with these behavioral features. However, the inclusion of individuals past the age of onset of the defining behaviors complicates interpretation of the observed abnormalities: they may be cascade effects of earlier neuropathology and behavioral abnormalities. Our recent study of network efficiency in a cohort of 24-month-olds at high and low familial risk for ASD reduced this confound; we reported reduced network efficiencies in toddlers classified with ASD. The current study maps the emergence of these inefficiencies in the first year of life. This study uses data from 260 infants at 6 and 12 months of age, including 116 infants with longitudinal data. As in our earlier study, we use diffusion data to obtain measures of the length and strength of connections between brain regions to compute network efficiency. We assess group differences in efficiency within linear mixed-effects models determined by the Akaike information criterion. Inefficiencies in high-risk infants later classified with ASD were detected from 6 months onward in regions involved in low-level sensory processing. In addition, within the high-risk infants, these inefficiencies predicted 24-month symptom severity. These results suggest that infants with ASD, even before 6 months of age, have deficits in connectivity related to low-level processing, which contribute to a developmental cascade affecting brain organization and eventually higher-level cognitive processes and social behavior. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Effects of traumatic brain injury on a virtual reality social problem solving task and relations to cortical thickness in adolescence.

PubMed

Hanten, Gerri; Cook, Lori; Orsten, Kimberley; Chapman, Sandra B; Li, Xiaoqi; Wilde, Elisabeth A; Schnelle, Kathleen P; Levin, Harvey S

2011-02-01

Social problem solving was assessed in 28 youth ages 12-19 years (15 with moderate to severe traumatic brain injury (TBI), 13 uninjured) using a naturalistic, computerized virtual reality (VR) version of the Interpersonal Negotiations Strategy interview (Yeates, Schultz, & Selman, 1991). In each scenario, processing load condition was varied in terms of number of characters and amount of information. Adolescents viewed animated scenarios depicting social conflict in a virtual microworld environment from an avatar's viewpoint, and were questioned on four problem solving steps: defining the problem, generating solutions, selecting solutions, and evaluating the likely outcome. Scoring was based on a developmental scale in which responses were judged as impulsive, unilateral, reciprocal, or collaborative, in order of increasing score. Adolescents with TBI were significantly impaired on the summary VR-Social Problem Solving (VR-SPS) score in Condition A (2 speakers, no irrelevant information), p=0.005; in Condition B (2 speakers+irrelevant information), p=0.035; and Condition C (4 speakers+irrelevant information), p=0.008. Effect sizes (Cohen's D) were large (A=1.40, B=0.96, C=1.23). Significant group differences were strongest and most consistent for defining the problems and evaluating outcomes. The relation of task performance to cortical thickness of specific brain regions was also explored, with significant relations found with orbitofrontal regions, the frontal pole, the cuneus, and the temporal pole. Results are discussed in the context of specific cognitive and neural mechanisms underlying social problem solving deficits after childhood TBI. Copyright © 2010 Elsevier Ltd. All rights reserved.

Effects of Traumatic Brain Injury on a Virtual Reality Social Problem Solving Task and Relations to Cortical Thickness in Adolescence

PubMed Central

Hanten, Gerri; Cook, Lori; Orsten, Kimberley; Chapman, Sandra B.; Li, Xiaoqi; Wilde, Elisabeth A.; Schnelle, Kathleen P.; Levin, Harvey S.

2011-01-01

Social problem solving was assessed in 28 youth ages 12–19 years (15 with moderate to severe traumatic brain injury (TBI), 13 uninjured) using a naturalistic, computerized virtual reality (VR) version of the Interpersonal Negotiations Strategy interview (Yeates, Schultz, & Selman, 1991). In each scenario, processing load condition was varied in terms of number of characters and amount of information. Adolescents viewed animated scenarios depicting social conflict in a virtual microworld environment from an avatar’s viewpoint, and were questioned on four problem solving steps: defining the problem, generating solutions, selecting solutions, and evaluating the likely outcome. Scoring was based on a developmental scale in which responses were judged as impulsive, unilateral, reciprocal, or collaborative, in order of increasing score. Adolescents with TBI were significantly impaired on the summary VR-Social Problem Solving (VR-SPS) score in Condition A (2 speakers, no irrelevant information), p = 0.005; in Condition B (2 speakers + irrelevant information), p = 0.035; and Condition C (4 speakers + irrelevant information), p = 0.008. Effect sizes (Cohen’s d) were large (A = 1.40, B = 0.96, C = 1.23). Significant group differences were strongest and most consistent for defining the problems and evaluating outcomes. The relation of task performance to cortical thickness of specific brain regions was also explored, with significant relations found with orbitofrontal regions, the frontal pole, the cuneus, and the temporal pole. Results are discussed in the context of specific cognitive and neural mechanisms underlying social problem solving deficits after childhood TBI. PMID:21147137

"Facilitated" amino acid transport is upregulated in brain tumors.

PubMed

Miyagawa, T; Oku, T; Uehara, H; Desai, R; Beattie, B; Tjuvajev, J; Blasberg, R

1998-05-01

The goal of this study was to determine the magnitude of "facilitated" amino acid transport across tumor and brain capillaries and to evaluate whether amino acid transporter expression is "upregulated" in tumor vessels compared to capillaries in contralateral brain tissue. Aminocyclopentane carboxylic acid (ACPC), a non-metabolized [14C]-labeled amino acid, and a reference molecule for passive vascular permeability, [67Ga]-gallium-diethylenetriaminepentaacetic acid (Ga-DTPA), were used in these studies. Two experimental rat gliomas were studied (C6 and RG2). Brain tissue was rapidly processed for double label quantitative autoradiography 10 minutes after intravenous injection of ACPC and Ga-DTPA. Parametric images of blood-to-brain transport (K1ACPC and K1Ga-DTPA, microL/min/g) produced from the autoradiograms and the histology were obtained from the same tissue section. These three images were registered in an image array processor; regions of interest in tumor and contralateral brain were defined on morphologic criteria (histology) and were transferred to the autoradiographic images to obtain mean values. The facilitated component of ACPC transport (deltaK1ACPC) was calculated from the K1ACPC and K1Ga-DTPA data, and paired comparisons between tumor and contralateral brain were performed. ACPC flux, K1ACPC, across normal brain capillaries (22.6 +/- 8.1 microL/g/min) was >200-fold greater than that of Ga-DTPA (0.09 +/- 0.04 microL/g/min), and this difference was largely (approximately 90%) due to facilitated ACPC transport. Substantially higher K1ACPC values compared to corresponding K1DTPA values were also measured in C6 and RG2 gliomas. The deltaK1ACPC values for C6 glioma were more than twice that of contralateral brain cortex. K1ACPC and deltaK1ACPC values for RG2 gliomas was not significantly higher than that of contralateral cortex, although a approximately 2-fold difference in facilitated transport is obtained after normalization for differences in capillary surface area between RG2 tumors and contralateral cortex. K1ACPC, deltaK1ACPC, and K DTPA were directly related to tumor cell density, were higher in regions of "impending" necrosis, and the tumor/contralateral brain ACPC radio-activity ratios (0 to 10 minutes) were very similar to that obtained with 0 to 60 minutes experiments. These results indicate that facilitated transport of ACPC is upregulated across C6 and RG2 glioma capillaries, and that tumors can induce upregulation of amino acid transporter expression in their supporting vasculature. They also suggest that early imaging (e.g., 0 to 20 minutes) with radiolabeled amino acids in a clinical setting may be optimal for defining brain tumors.

Representation of action in occipito-temporal cortex.

PubMed

Wiggett, Alison J; Downing, Paul E

2011-07-01

A fundamental question for social cognitive neuroscience is how and where in the brain the identities and actions of others are represented. Here we present a replication and extension of a study by Kable and Chatterjee [Kable, J. W., & Chatterjee, A. Specificity of action representations in the lateral occipito-temporal cortex. Journal of Cognitive Neuroscience, 18, 1498-1517, 2006] examining the role of occipito-temporal cortex in these processes. We presented full-cue movies of actors performing whole-body actions and used fMRI to test for action- and identity-specific adaptation effects. We examined a series of functionally defined regions, including the extrastriate and fusiform body areas, the fusiform face area, the parahippocampal place area, the lateral occipital complex, the right posterior superior temporal sulcus, and motion-selective area hMT+. These regions were analyzed with both standard univariate measures as well as multivoxel pattern analyses. Additionally, we performed whole-brain tests for significant adaptation effects. We found significant action-specific adaptation in many areas, but no evidence for identity-specific adaptation. We argue that this finding could be explained by differences in the familiarity of the stimuli presented: The actions shown were familiar but the actors performing the actions were unfamiliar. However, in contrast to previous findings, we found that the action adaptation effect could not be conclusively tied to specific functionally defined regions. Instead, our results suggest that the adaptation to previously seen actions across identities is a widespread effect, evident across lateral and ventral occipito-temporal cortex.

Effects of tetrahydrocannabinol on glucose uptake in the rat brain.

PubMed

Miederer, I; Uebbing, K; Röhrich, J; Maus, S; Bausbacher, N; Krauter, K; Weyer-Elberich, V; Lutz, B; Schreckenberger, M; Urban, R

2017-05-01

Δ 9 -Tetrahydrocannabinol (THC) is the psychoactive component of the plant Cannabis sativa and acts as a partial agonist at cannabinoid type 1 and type 2 receptors in the brain. The goal of this study was to assess the effect of THC on the cerebral glucose uptake in the rat brain. 21 male Sprague Dawley rats (12-13 w) were examined and received five different doses of THC ranging from 0.01 to 1 mg/kg. For data acquisition a Focus 120 small animal PET scanner was used and 24.1-28.0 MBq of [ 18 F]-fluoro-2-deoxy-d-glucose were injected. The data were acquired for 70 min and arterial blood samples were collected throughout the scan. THC, THC-OH and THC-COOH were determined at 55 min p.i. Nine volumes of interest were defined, and the cerebral glucose uptake was calculated for each brain region. Low blood THC levels of < 1 ng/ml (injected dose: ≤ 0.01 mg/kg) corresponded to an increased glucose uptake (6-30 %), particularly in the hypothalamus (p = 0.007), while blood THC levels > 10 ng/ml (injected dose: ≥ 0.05 mg/kg) coincided with a decreased glucose uptake (-2 to -22 %), especially in the cerebellar cortex (p = 0.008). The effective concentration in this region was estimated 2.4 ng/ml. This glucose PET study showed that stimulation of CB1 receptors by THC affects the glucose uptake in the rat brain, whereby the effect of THC is regionally different and dependent on dose - an effect that may be of relevance in behavioural studies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Flibanserin stimulated partner grooming reflects brain metabolism changes in female marmosets

PubMed Central

Converse, Alexander K.; Aubert, Yves; Allers, Kelly A.; Sommer, Bernd; Abbott, David H.

2017-01-01

Introduction Female Sexual Interest and Arousal Disorder (FSIAD) is personally distressing for women. To better understand the mechanism of the candidate therapeutic, flibanserin, we determined its effects on an index of brain glucose metabolism. Aim We hypothesized that chronic treatment with flibanserin would alter metabolism in brain regions associated with serotonergic function and female sexual behavior. Methods In a crossover design, eight adult female common marmosets (Calithrix jacchus) received daily flibanserin or vehicle. After 7–12 weeks of treatment, the glucose metabolism radiotracer FDG was administered to each female immediately prior to 30 min of interaction with her male pairmate, after which females were anesthetized and imaged by PET. Whole-brain normalized images were analyzed with anatomically defined regions of interest. Whole brain voxelwise mapping was used to explore treatment effects. Correlations were examined between alterations in metabolism and pairmate social grooming. Main Outcome Measures Changes in metabolism associated with flibanserin were determined for dorsal raphe (DR), medial prefrontal cortex (mPFC), medial preoptic area of hypothalamus (mPOA), ventromedial nucleus of hypothalamus (VMH), and field CA1 of hippocampus. Results In response to chronic flibanserin, metabolism in mPOA declined, and this reduction correlated with increases in pairmate grooming. A cluster of voxels in frontal cortico-limbic regions exhibited reduced metabolism in response to flibanserin and overlapped with a voxel cluster in which reductions in metabolism correlated with increases in pairmate grooming. Finally, reductions in mPOA metabolism correlated with increases in metabolism in a cluster of voxels in somatosensory cortex. Conclusions Taken together, these results suggest that flibanserin-induced reductions in female mPOA neural activity increase intimate affiliative behavior with male pairmates. PMID:26635207

Multiple spatially related pharmacophores define small molecule inhibitors of OLIG2 in glioblastoma

PubMed Central

Chao, Ying; Babic, Ivan; Nurmemmedov, Elmar; Pastorino, Sandra; Jiang, Pengfei; Calligaris, David; Agar, Nathalie; Scadeng, Miriam; Pingle, Sandeep C.; Wrasidlo, Wolfgang; Makale, Milan T.; Kesari, Santosh

2017-01-01

Transcription factors (TFs) are a major class of protein signaling molecules that play key cellular roles in cancers such as the highly lethal brain cancer—glioblastoma (GBM). However, the development of specific TF inhibitors has proved difficult owing to expansive protein-protein interfaces and the absence of hydrophobic pockets. We uniquely defined the dimerization surface as an expansive parental pharmacophore comprised of several regional daughter pharmacophores. We targeted the OLIG2 TF which is essential for GBM survival and growth, we hypothesized that small molecules able to fit each subpharmacophore would inhibit OLIG2 activation. The most active compound was OLIG2 selective, it entered the brain, and it exhibited potent anti-GBM activity in cell-based assays and in pre-clinical mouse orthotopic models. These data suggest that (1) our multiple pharmacophore approach warrants further investigation, and (2) our most potent compounds merit detailed pharmacodynamic, biophysical, and mechanistic characterization for potential preclinical development as GBM therapeutics. PMID:26517684

Regional differences in the blood-brain-barrier of the subfornical organs of rats and ducks (Anas platyrhynchos).

PubMed

Schmid, H A

1995-01-01

Recently published electrophysiological data investigated the effect of blood borne and brain intrinsic substances on the activity of neurons in the duck subfornical organ (SFO). This study defines histologically the region in the duck SFO, where blood borne substances can possibly influence neuronal activity. Intravenous injection of Evans blue, a dye which labels brain structures devoid of a blood brain barrier (BBB), resulted in diffuse labelling of the duck SFO from the anterior commissure to the end of the organ in rostrocaudal extension. In addition, specifically labelled neurons could be observed just rostral to the diffuse Evans blue labelling and in an area dorsomedial to the large central blood vessel. The majority of the somata of these heavily stained neurons were located inside the BBB, whereas in the areas with diffuse Evans blue labelling, thus being outside the BBB, labelled cells were rarely observed. Intravenous injection of Evans blue in rats resulted similarly in diffuse labelling of the parenchyma of the medial and caudal part of the SFO, with only a few, but heavily stained cells with fusiform somata. The rostral region of the rat SFO, which is known to have a functional BBB, shows hardly any diffuse labelling, but there the majority of neurons show strong Evans blue fluorescence. It is concluded that the heavily labelled somata inside the BBB have axonal or dendritic projections to BBB-free areas, where they can take up the dye. This study gives a functional description of the extension of the SFO areas without a BBB of rats and ducks. It is concluded that blood borne agents can affect those SFO neurons which have their somata located outside the BBB as well as those located inside the BBB which have terminals projecting to BBB free regions.

Enhanced peripheral visual processing in congenitally deaf humans is supported by multiple brain regions, including primary auditory cortex.

PubMed

Scott, Gregory D; Karns, Christina M; Dow, Mark W; Stevens, Courtney; Neville, Helen J

2014-01-01

Brain reorganization associated with altered sensory experience clarifies the critical role of neuroplasticity in development. An example is enhanced peripheral visual processing associated with congenital deafness, but the neural systems supporting this have not been fully characterized. A gap in our understanding of deafness-enhanced peripheral vision is the contribution of primary auditory cortex. Previous studies of auditory cortex that use anatomical normalization across participants were limited by inter-subject variability of Heschl's gyrus. In addition to reorganized auditory cortex (cross-modal plasticity), a second gap in our understanding is the contribution of altered modality-specific cortices (visual intramodal plasticity in this case), as well as supramodal and multisensory cortices, especially when target detection is required across contrasts. Here we address these gaps by comparing fMRI signal change for peripheral vs. perifoveal visual stimulation (11-15° vs. 2-7°) in congenitally deaf and hearing participants in a blocked experimental design with two analytical approaches: a Heschl's gyrus region of interest analysis and a whole brain analysis. Our results using individually-defined primary auditory cortex (Heschl's gyrus) indicate that fMRI signal change for more peripheral stimuli was greater than perifoveal in deaf but not in hearing participants. Whole-brain analyses revealed differences between deaf and hearing participants for peripheral vs. perifoveal visual processing in extrastriate visual cortex including primary auditory cortex, MT+/V5, superior-temporal auditory, and multisensory and/or supramodal regions, such as posterior parietal cortex (PPC), frontal eye fields, anterior cingulate, and supplementary eye fields. Overall, these data demonstrate the contribution of neuroplasticity in multiple systems including primary auditory cortex, supramodal, and multisensory regions, to altered visual processing in congenitally deaf adults.

Resting-state brain activity in the motor cortex reflects task-induced activity: A multi-voxel pattern analysis.

PubMed

Kusano, Toshiki; Kurashige, Hiroki; Nambu, Isao; Moriguchi, Yoshiya; Hanakawa, Takashi; Wada, Yasuhiro; Osu, Rieko

2015-08-01

It has been suggested that resting-state brain activity reflects task-induced brain activity patterns. In this study, we examined whether neural representations of specific movements can be observed in the resting-state brain activity patterns of motor areas. First, we defined two regions of interest (ROIs) to examine brain activity associated with two different behavioral tasks. Using multi-voxel pattern analysis with regularized logistic regression, we designed a decoder to detect voxel-level neural representations corresponding to the tasks in each ROI. Next, we applied the decoder to resting-state brain activity. We found that the decoder discriminated resting-state neural activity with accuracy comparable to that associated with task-induced neural activity. The distribution of learned weighted parameters for each ROI was similar for resting-state and task-induced activities. Large weighted parameters were mainly located on conjunctive areas. Moreover, the accuracy of detection was higher than that for a decoder whose weights were randomly shuffled, indicating that the resting-state brain activity includes multi-voxel patterns similar to the neural representation for the tasks. Therefore, these results suggest that the neural representation of resting-state brain activity is more finely organized and more complex than conventionally considered.

[Cerebral metabolism and permeability of the hemato-encephalic barrier in an experimental model for brain radiotherapy].

PubMed

Cicciarello, R; Russi, E; Albiero, F; Mesiti, M; Torre, E; D'Aquino, A; Raffaele, L; Bertolani, S; D'Avella, D

1990-11-01

Whole brain irradiation (WBR) can produce acute and chronic neurological adverse effects, which are usually divided into acute, early delayed and late delayed reactions according to the time of onset. To assess the impact of WBR on brain functional parameters during the early-delayed phase, we employed the [14C]-2-deoxyglucose (2-DG) and the [14C]-alfa-aminoisobutyric (AIB) acid quantitative autoradiographic techniques to study local cerebral glucose utilization and blood-brain barrier permeability, respectively. Sprague-Dowley albino rats were exposed to conventional fractionation (200 Gy/day 5 days a week) for a total dose of 4000 Gy. Experiments were made 3 weeks after completion of the radiation exposure. In comparison with control and sham-irradiated animals, cerebral metabolic activity was diffusely decreased following irradiation. As a rule, brain areas with the highest basal metabolic rates showed the highest percentage drop in glucose utilization. Changes in blood-brain barrier function, as assessed by an increased transcapillary transport of AIB, were also demonstrated in specific brain regions. This study illustrates how moderate doses of WBR induce well-defined changes in brain metabolism and BBB function, which are possibly involved in the pathogenesis of the early-delayed radiation-induced cerebral dysfunction in humans.

Longitudinal patterns of leukoaraiosis and brain atrophy in symptomatic small vessel disease.

PubMed

Lambert, Christian; Benjamin, Philip; Zeestraten, Eva; Lawrence, Andrew J; Barrick, Thomas R; Markus, Hugh S

2016-04-01

Cerebral small vessel disease is a common condition associated with lacunar stroke, cognitive impairment and significant functional morbidity. White matter hyperintensities and brain atrophy, seen on magnetic resonance imaging, are correlated with increasing disease severity. However, how the two are related remains an open question. To better define the relationship between white matter hyperintensity growth and brain atrophy, we applied a semi-automated magnetic resonance imaging segmentation analysis pipeline to a 3-year longitudinal cohort of 99 subjects with symptomatic small vessel disease, who were followed-up for ≥1 years. Using a novel two-stage warping pipeline with tissue repair step, voxel-by-voxel rate of change maps were calculated for each tissue class (grey matter, white matter, white matter hyperintensities and lacunes) for each individual. These maps capture both the distribution of disease and spatial information showing local rates of growth and atrophy. These were analysed to answer three primary questions: first, is there a relationship between whole brain atrophy and magnetic resonance imaging markers of small vessel disease (white matter hyperintensities or lacune volume)? Second, is there regional variation within the cerebral white matter in the rate of white matter hyperintensity progression? Finally, are there regionally specific relationships between the rates of white matter hyperintensity progression and cortical grey matter atrophy? We demonstrate that the rates of white matter hyperintensity expansion and grey matter atrophy are strongly correlated (Pearson's R = -0.69, P < 1 × 10(-7)), and significant grey matter loss and whole brain atrophy occurs annually (P < 0.05). Additionally, the rate of white matter hyperintensity growth was heterogeneous, occurring more rapidly within long association fasciculi. Using voxel-based quantification (family-wise error corrected P < 0.05), we show the rate of white matter hyperintensity progression is associated with increases in cortical grey matter atrophy rates, in the medial-frontal, orbito-frontal, parietal and occipital regions. Conversely, increased rates of global grey matter atrophy are significantly associated with faster white matter hyperintensity growth in the frontal and parietal regions. Together, these results link the progression of white matter hyperintensities with increasing rates of regional grey matter atrophy, and demonstrate that grey matter atrophy is the major contributor to whole brain atrophy in symptomatic cerebral small vessel disease. These measures provide novel insights into the longitudinal pathogenesis of small vessel disease, and imply that therapies aimed at reducing progression of white matter hyperintensities via end-arteriole damage may protect against secondary brain atrophy and consequent functional morbidity. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain.

GRAPES-Grounding representations in action, perception, and emotion systems: How object properties and categories are represented in the human brain.

PubMed

Martin, Alex

2016-08-01

In this article, I discuss some of the latest functional neuroimaging findings on the organization of object concepts in the human brain. I argue that these data provide strong support for viewing concepts as the products of highly interactive neural circuits grounded in the action, perception, and emotion systems. The nodes of these circuits are defined by regions representing specific object properties (e.g., form, color, and motion) and thus are property-specific, rather than strictly modality-specific. How these circuits are modified by external and internal environmental demands, the distinction between representational content and format, and the grounding of abstract social concepts are also discussed.

Brain Response to Working Memory Over Three Years of Adolescence: Influence of Initiating Heavy Drinking

PubMed Central

Squeglia, Lindsay M.; Pulido, Carmen; Wetherill, Reagan R.; Jacobus, Joanna; Brown, Gregory G.; Tapert, Susan F.

2012-01-01

Objective: Many adolescents engage in heavy alcohol use. The aim of this study was to disentangle whether brain abnormalities seen in adolescent heavy drinkers are a consequence of heavy drinking, a preexisting risk factor for initiation of alcohol use, or both. Method: Study 1 used cross-sectional functional magnetic resonance imaging (fMRI) visual working-memory (VWM) data from 15- to 19-year-olds (20 heavy drinkers, 20 controls) to identify brain regions affected by heavy adolescent alcohol use. Study 2 used longitudinal fMRI VWM data from 12- to 16-year-olds imaged before the onset of drinking and imaged again on the same scanner approximately 3 years later. Those who had transitioned into heavy drinking (n = 20) were matched to continuous nondrinkers (n = 20) on baseline alcohol risk and developmental factors (N = 40; 80 scans). Results: Study 1 found that heavy drinkers exhibited more frontal and parietal but less occipital activation than controls, defining the regions of interest for Study 2. In Study 2, adolescents who later transitioned into heavy drinking showed less fMRI response contrast at baseline than continuous nondrinkers, which increased after the onset of heavy drinking, in frontal (1,431 μL, p = .003; η2 = .19) and parietal (810 μL, p = .005; η2 = .23) regions, as in Study 1. Lower baseline activation in the frontal and parietal regions predicted subsequent substance use, more so than commonly observed predictors of youth drinking (p < .05). Conclusions: Adolescents who initiated heavy drinking showed different brain activation before the onset of drinking, then less efficient information processing after high-dose alcohol use started. This suggests neural response patterns that could be risk factors for future substance use and also supports prior neuropsychological reports indicating that initiating heavy episodic drinking in adolescence may be followed by subtle alterations in brain functioning. PMID:22846239

Modelling the effect of electrode displacement on transcranial direct current stimulation (tDCS)

NASA Astrophysics Data System (ADS)

Ramaraju, Sriharsha; Roula, Mohammed A.; McCarthy, Peter W.

2018-02-01

Objective. Transcranial direct current stimulation (tDCS) is a neuromodulatory technique that delivers a low-intensity, direct current to cortical areas with the purpose of modulating underlying brain activity. Recent studies have reported inconsistencies in tDCS outcomes. The underlying assumption of many tDCS studies has been that replication of electrode montage equates to replicating stimulation conditions. It is possible however that anatomical difference between subjects, as well as inherent inaccuracies in montage placement, could affect current flow to targeted areas. The hypothesis that stimulation of a defined brain region will be stable under small displacements was tested. Approach. Initially, we compared the total simulated current flowing through ten specific brain areas for four commonly used tDCS montages: F3-Fp2, C3-Fp2, Fp1-F4, and P3-P4 using the software tool COMETS. The effect of a slight (~1 cm in each of four directions) anode displacement on the simulated regional current density for each of the four tDCS montages was then determined. Current flow was calculated and compared through ten segmented brain areas to determine the effect of montage type and displacement. The regional currents, as well as the localised current densities, were compared with the original electrode location, for each of these new positions. Main results. Recommendations for montages that maximise stimulation current for the ten brain regions are considered. We noted that the extent to which stimulation is affected by electrode displacement varies depending on both area and montage type. The F3-Fp2 montage was found to be the least stable with up to 38% change in average current density in the left frontal lobe while the Fp1-F4 montage was found to the most stable exhibiting only 1% change when electrodes were displaced. Significance. These results indicate that even relatively small changes in stimulation electrode placement appear to result in surprisingly large changes in current densities and distribution.

Mapping higher-order relations between brain structure and function with embedded vector representations of connectomes.

PubMed

Rosenthal, Gideon; Váša, František; Griffa, Alessandra; Hagmann, Patric; Amico, Enrico; Goñi, Joaquín; Avidan, Galia; Sporns, Olaf

2018-06-05

Connectomics generates comprehensive maps of brain networks, represented as nodes and their pairwise connections. The functional roles of nodes are defined by their direct and indirect connectivity with the rest of the network. However, the network context is not directly accessible at the level of individual nodes. Similar problems in language processing have been addressed with algorithms such as word2vec that create embeddings of words and their relations in a meaningful low-dimensional vector space. Here we apply this approach to create embedded vector representations of brain networks or connectome embeddings (CE). CE can characterize correspondence relations among brain regions, and can be used to infer links that are lacking from the original structural diffusion imaging, e.g., inter-hemispheric homotopic connections. Moreover, we construct predictive deep models of functional and structural connectivity, and simulate network-wide lesion effects using the face processing system as our application domain. We suggest that CE offers a novel approach to revealing relations between connectome structure and function.

Assessment of variability in cerebral vasculature for neuro-anatomical surgery planning in rodent brain

NASA Astrophysics Data System (ADS)

Rangarajan, J. R.; Van Kuyck, K.; Himmelreich, U.; Nuttin, B.; Maes, F.; Suetens, P.

2011-03-01

Clinical and pre-clinical studies show that deep brain stimulation (DBS) of targeted brain regions by neurosurgical techniques ameliorate psychiatric disorder such as anorexia nervosa. Neurosurgical interventions in preclinical rodent brain are mostly accomplished manually with a 2D atlas. Considering both the large number of animals subjected to stereotactic surgical experiments and the associated imaging cost, feasibility of sophisticated pre-operative imaging based surgical path planning and/or robotic guidance is limited. Here, we spatially normalize vasculature information and assess the intra-strain variability in cerebral vasculature for a neurosurgery planning. By co-registering and subsequently building a probabilistic vasculature template in a standard space, we evaluate the risk of a user defined electrode trajectory damaging a blood vessel on its path. The use of such a method may not only be confined to DBS therapy in small animals, but also could be readily applicable to a wide range of stereotactic small animal surgeries like targeted injection of contrast agents and cell labeling applications.

Optical imaging of the rat brain suggests a previously missing link between top-down and bottom-up nervous system function

PubMed Central

Greenfield, Susan A.; Badin, Antoine-Scott; Ferrati, Giovanni; Devonshire, Ian M.

2017-01-01

Abstract. Optical imaging with voltage-sensitive dyes enables the visualization of extensive yet highly transient coalitions of neurons (assemblies) operating throughout the brain on a subsecond time scale. We suggest that operating at the mesoscale level of brain organization, neuronal assemblies may provide a functional link between “bottom-up” cellular mechanisms and “top-down” cognitive ones within anatomically defined regions. We demonstrate in ex vivo rat brain slices how varying spatiotemporal dynamics of assemblies reveal differences not previously appreciated between: different stages of development in cortical versus subcortical brain areas, different sensory modalities (hearing versus vision), different classes of psychoactive drugs (anesthetics versus analgesics), different effects of anesthesia linked to hyperbaric conditions and, in vivo, depths of anesthesia. The strategy of voltage-sensitive dye imaging is therefore as powerful as it is versatile and as such can now be applied to the evaluation of neurochemical signaling systems and the screening of related new drugs, as well as to mathematical modeling and, eventually, even theories of consciousness. PMID:28573153

Safety of real-time convection-enhanced delivery of liposomes to primate brain: a long-term retrospective.

PubMed

Krauze, Michal T; Vandenberg, Scott R; Yamashita, Yoji; Saito, Ryuta; Forsayeth, John; Noble, Charles; Park, John; Bankiewicz, Krystof S

2008-04-01

Convection-enhanced delivery (CED) is gaining popularity in direct brain infusions. Our group has pioneered the use of liposomes loaded with the MRI contrast reagent as a means to track and quantitate CED in the primate brain through real-time MRI. When co-infused with therapeutic nanoparticles, these tracking liposomes provide us with unprecedented precision in the management of infusions into discrete brain regions. In order to translate real-time CED into clinical application, several important parameters must be defined. In this study, we have analyzed all our cumulative animal data to answer a number of questions as to whether real-time CED in primates depends on concentration of infusate, is reproducible, allows prediction of distribution in a given anatomic structure, and whether it has long term pathological consequences. Our retrospective analysis indicates that real-time CED is highly predictable; repeated procedures yielded identical results, and no long-term brain pathologies were found. We conclude that introduction of our technique to clinical application would enhance accuracy and patient safety when compared to current non-monitored delivery trials.

Optical imaging of the rat brain suggests a previously missing link between top-down and bottom-up nervous system function.

PubMed

Greenfield, Susan A; Badin, Antoine-Scott; Ferrati, Giovanni; Devonshire, Ian M

2017-07-01

Optical imaging with voltage-sensitive dyes enables the visualization of extensive yet highly transient coalitions of neurons (assemblies) operating throughout the brain on a subsecond time scale. We suggest that operating at the mesoscale level of brain organization, neuronal assemblies may provide a functional link between "bottom-up" cellular mechanisms and "top-down" cognitive ones within anatomically defined regions. We demonstrate in ex vivo rat brain slices how varying spatiotemporal dynamics of assemblies reveal differences not previously appreciated between: different stages of development in cortical versus subcortical brain areas, different sensory modalities (hearing versus vision), different classes of psychoactive drugs (anesthetics versus analgesics), different effects of anesthesia linked to hyperbaric conditions and, in vivo , depths of anesthesia. The strategy of voltage-sensitive dye imaging is therefore as powerful as it is versatile and as such can now be applied to the evaluation of neurochemical signaling systems and the screening of related new drugs, as well as to mathematical modeling and, eventually, even theories of consciousness.

Examination of a Method to Determine the Reference Region for Calculating the Specific Binding Ratio in Dopamine Transporter Imaging.

PubMed

Watanabe, Ayumi; Inoue, Yusuke; Asano, Yuji; Kikuchi, Kei; Miyatake, Hiroki; Tokushige, Takanobu

2017-01-01

The specific binding ratio (SBR) was first reported by Tossici-Bolt et al. for quantitative indicators for dopamine transporter (DAT) imaging. It is defined as the ratio of the specific binding concentration of the striatum to the non-specific binding concentration of the whole brain other than the striatum. The non-specific binding concentration is calculated based on the region of interest (ROI), which is set 20 mm inside the outer contour, defined by a threshold technique. Tossici-Bolt et al. used a 50% threshold, but sometimes we couldn't define the ROI of non-specific binding concentration (reference region) and calculate SBR appropriately with a 50% threshold. Therefore, we sought a new method for determining the reference region when calculating SBR. We used data from 20 patients who had undergone DAT imaging in our hospital, to calculate the non-specific binding concentration by the following methods, the threshold to define a reference region was fixed at some specific values (the fixing method) and reference region was visually optimized by an examiner at every examination (the visual optimization method). First, we assessed the reference region of each method visually, and afterward, we quantitatively compared SBR calculated based on each method. In the visual assessment, the scores of the fixing method at 30% and visual optimization method were higher than the scores of the fixing method at other values, with or without scatter correction. In the quantitative assessment, the SBR obtained by visual optimization of the reference region, based on consensus of three radiological technologists, was used as a baseline (the standard method). The values of SBR showed good agreement between the standard method and both the fixing method at 30% and the visual optimization method, with or without scatter correction. Therefore, the fixing method at 30% and the visual optimization method were equally suitable for determining the reference region.

Diffusion imaging of cerebral white matter in persons who stutter: evidence for network-level anomalies

PubMed Central

Cai, Shanqing; Tourville, Jason A.; Beal, Deryk S.; Perkell, Joseph S.; Guenther, Frank H.; Ghosh, Satrajit S.

2013-01-01

Deficits in brain white matter have been a main focus of recent neuroimaging studies on stuttering. However, no prior study has examined brain connectivity on the global level of the cerebral cortex in persons who stutter (PWS). In the current study, we analyzed the results from probabilistic tractography between regions comprising the cortical speech network. An anatomical parcellation scheme was used to define 28 speech production-related ROIs in each hemisphere. We used network-based statistic (NBS) and graph theory to analyze the connectivity patterns obtained from tractography. At the network-level, the probabilistic corticocortical connectivity from the PWS group were significantly weaker than that from persons with fluent speech (PFS). NBS analysis revealed significant components in the bilateral speech networks with negative correlations with stuttering severity. To facilitate comparison with previous studies, we also performed tract-based spatial statistics (TBSS) and regional fractional anisotropy (FA) averaging. Results from tractography, TBSS and regional FA averaging jointly highlight the importance of several regions in the left peri-Rolandic sensorimotor and premotor areas, most notably the left ventral premotor cortex (vPMC) and middle primary motor cortex, in the neuroanatomical basis of stuttering. PMID:24611042

Diffusion imaging of cerebral white matter in persons who stutter: evidence for network-level anomalies.

PubMed

Cai, Shanqing; Tourville, Jason A; Beal, Deryk S; Perkell, Joseph S; Guenther, Frank H; Ghosh, Satrajit S

2014-01-01

Deficits in brain white matter have been a main focus of recent neuroimaging studies on stuttering. However, no prior study has examined brain connectivity on the global level of the cerebral cortex in persons who stutter (PWS). In the current study, we analyzed the results from probabilistic tractography between regions comprising the cortical speech network. An anatomical parcellation scheme was used to define 28 speech production-related ROIs in each hemisphere. We used network-based statistic (NBS) and graph theory to analyze the connectivity patterns obtained from tractography. At the network-level, the probabilistic corticocortical connectivity from the PWS group were significantly weaker than that from persons with fluent speech (PFS). NBS analysis revealed significant components in the bilateral speech networks with negative correlations with stuttering severity. To facilitate comparison with previous studies, we also performed tract-based spatial statistics (TBSS) and regional fractional anisotropy (FA) averaging. Results from tractography, TBSS and regional FA averaging jointly highlight the importance of several regions in the left peri-Rolandic sensorimotor and premotor areas, most notably the left ventral premotor cortex (vPMC) and middle primary motor cortex, in the neuroanatomical basis of stuttering.

Spontaneous low frequency BOLD signal variations from resting-state fMRI are decreased in Alzheimer disease

PubMed Central

Manning, Kathryn Y.; Rajakumar, Nagalingam; Gómez, Francisco A.; Soddu, Andrea; Borrie, Michael J.

2017-01-01

Previous studies have demonstrated altered brain activity in Alzheimer's disease using task based functional MRI (fMRI), network based resting-state fMRI, and glucose metabolism from 18F fluorodeoxyglucose-PET (FDG-PET). Our goal was to define a novel indicator of neuronal activity based on a first-order textural feature of the resting state functional MRI (RS-fMRI) signal. Furthermore, we examined the association between this neuronal activity metric and glucose metabolism from 18F FDG-PET. We studied 15 normal elderly controls (NEC) and 15 probable Alzheimer disease (AD) subjects from the AD Neuroimaging Initiative. An independent component analysis was applied to the RS-fMRI, followed by template matching to identify neuronal components (NC). A regional brain activity measurement was constructed based on the variation of the RS-fMRI signal of these NC. The standardized glucose uptake values of several brain regions relative to the cerebellum (SUVR) were measured from partial volume corrected FDG-PET images. Comparing the AD and NEC groups, the mean brain activity metric was significantly lower in the accumbens, while the glucose SUVR was significantly lower in the amygdala and hippocampus. The RS-fMRI brain activity metric was positively correlated with cognitive measures and amyloid β1–42 cerebral spinal fluid levels; however, these did not remain significant following Bonferroni correction. There was a significant linear correlation between the brain activity metric and the glucose SUVR measurements. This proof of concept study demonstrates that this novel and easy to implement RS-fMRI brain activity metric can differentiate a group of healthy elderly controls from a group of people with AD. PMID:28582450

Spontaneous low frequency BOLD signal variations from resting-state fMRI are decreased in Alzheimer disease.

PubMed

Kazemifar, Samaneh; Manning, Kathryn Y; Rajakumar, Nagalingam; Gómez, Francisco A; Soddu, Andrea; Borrie, Michael J; Menon, Ravi S; Bartha, Robert

2017-01-01

Previous studies have demonstrated altered brain activity in Alzheimer's disease using task based functional MRI (fMRI), network based resting-state fMRI, and glucose metabolism from 18F fluorodeoxyglucose-PET (FDG-PET). Our goal was to define a novel indicator of neuronal activity based on a first-order textural feature of the resting state functional MRI (RS-fMRI) signal. Furthermore, we examined the association between this neuronal activity metric and glucose metabolism from 18F FDG-PET. We studied 15 normal elderly controls (NEC) and 15 probable Alzheimer disease (AD) subjects from the AD Neuroimaging Initiative. An independent component analysis was applied to the RS-fMRI, followed by template matching to identify neuronal components (NC). A regional brain activity measurement was constructed based on the variation of the RS-fMRI signal of these NC. The standardized glucose uptake values of several brain regions relative to the cerebellum (SUVR) were measured from partial volume corrected FDG-PET images. Comparing the AD and NEC groups, the mean brain activity metric was significantly lower in the accumbens, while the glucose SUVR was significantly lower in the amygdala and hippocampus. The RS-fMRI brain activity metric was positively correlated with cognitive measures and amyloid β1-42 cerebral spinal fluid levels; however, these did not remain significant following Bonferroni correction. There was a significant linear correlation between the brain activity metric and the glucose SUVR measurements. This proof of concept study demonstrates that this novel and easy to implement RS-fMRI brain activity metric can differentiate a group of healthy elderly controls from a group of people with AD.

Single cell gene expression profiling in Alzheimer's disease.

PubMed

Ginsberg, Stephen D; Che, Shaoli; Counts, Scott E; Mufson, Elliott J

2006-07-01

Development and implementation of microarray techniques to quantify expression levels of dozens to hundreds to thousands of transcripts simultaneously within select tissue samples from normal control subjects and neurodegenerative diseased brains has enabled scientists to create molecular fingerprints of vulnerable neuronal populations in Alzheimer's disease (AD) and related disorders. A goal is to sample gene expression from homogeneous cell types within a defined region without potential contamination by expression profiles of adjacent neuronal subpopulations and nonneuronal cells. The precise resolution afforded by single cell and population cell RNA analysis in combination with microarrays and real-time quantitative polymerase chain reaction (qPCR)-based analyses allows for relative gene expression level comparisons across cell types under different experimental conditions and disease progression. The ability to analyze single cells is an important distinction from global and regional assessments of mRNA expression and can be applied to optimally prepared tissues from animal models of neurodegeneration as well as postmortem human brain tissues. Gene expression analysis in postmortem AD brain regions including the hippocampal formation and neocortex reveals selectively vulnerable cell types share putative pathogenetic alterations in common classes of transcripts, for example, markers of glutamatergic neurotransmission, synaptic-related markers, protein phosphatases and kinases, and neurotrophins/neurotrophin receptors. Expression profiles of vulnerable regions and neurons may reveal important clues toward the understanding of the molecular pathogenesis of various neurological diseases and aid in identifying rational targets toward pharmacotherapeutic interventions for progressive, late-onset neurodegenerative disorders such as mild cognitive impairment (MCI) and AD.

Nonlinear analyses of interictal EEG map the brain interdependences in human focal epilepsy

NASA Astrophysics Data System (ADS)

Quyen, Michel Le Van; Martinerie, Jacques; Adam, Claude; Varela, Francisco J.

1999-03-01

The degree of interdependence between intracranial electroencephalographic (EEG) channels was investigated in epileptic patients with temporal lobe seizures during interictal (between seizures) periods. With a novel method to characterize nonlinear cross-predictability, that is, the predictability of one channel using another channel as data base, we demonstrated here a possibility to extract information on the spatio-temporal organization of interactions between multichannel recording sites. This method determines whether two channels contain common activity, and often, whether one channel contains activity induced by the activity of the other channel. In particular, the technique and the comparison with surrogate data demonstrated that transient large-scale nonlinear entrainments by the epileptogenic region can be identified, this with or without epileptic activity. Furthermore, these recurrent activities related with the epileptic foci occurred in well-defined spatio-temporal patterns. This suggests that the epileptogenic region can exhibit very subtle influences on other brain regions during an interictal period and raises the possibility that the cross-predictability analysis of interictal data may be used as a significant aid in locating epileptogenic foci.

Source space analysis of event-related dynamic reorganization of brain networks.

PubMed

Ioannides, Andreas A; Dimitriadis, Stavros I; Saridis, George A; Voultsidou, Marotesa; Poghosyan, Vahe; Liu, Lichan; Laskaris, Nikolaos A

2012-01-01

How the brain works is nowadays synonymous with how different parts of the brain work together and the derivation of mathematical descriptions for the functional connectivity patterns that can be objectively derived from data of different neuroimaging techniques. In most cases static networks are studied, often relying on resting state recordings. Here, we present a quantitative study of dynamic reconfiguration of connectivity for event-related experiments. Our motivation is the development of a methodology that can be used for personalized monitoring of brain activity. In line with this motivation, we use data with visual stimuli from a typical subject that participated in different experiments that were previously analyzed with traditional methods. The earlier studies identified well-defined changes in specific brain areas at specific latencies related to attention, properties of stimuli, and tasks demands. Using a recently introduced methodology, we track the event-related changes in network organization, at source space level, thus providing a more global and complete view of the stages of processing associated with the regional changes in activity. The results suggest the time evolving modularity as an additional brain code that is accessible with noninvasive means and hence available for personalized monitoring and clinical applications.

Virtual milgram: empathic concern or personal distress? Evidence from functional MRI and dispositional measures.

PubMed

Cheetham, Marcus; Pedroni, Andreas F; Antley, Angus; Slater, Mel; Jäncke, Lutz

2009-01-01

One motive for behaving as the agent of another's aggression appears to be anchored in as yet unelucidated mechanisms of obedience to authority. In a recent partial replication of Milgram's obedience paradigm within an immersive virtual environment, participants administered pain to a female virtual human and observed her suffering. Whether the participants' response to the latter was more akin to other-oriented empathic concern for her well-being or to a self-oriented aversive state of personal distress in response to her distress is unclear. Using the stimuli from that study, this event-related fMRI-based study analysed brain activity during observation of the victim in pain versus not in pain. This contrast revealed activation in pre-defined brain areas known to be involved in affective processing but not in those commonly associated with affect sharing (e.g., ACC and insula). We then examined whether different dimensions of dispositional empathy predict activity within the same pre-defined brain regions: While personal distress and fantasy (i.e., tendency to transpose oneself into fictional situations and characters) predicted brain activity, empathic concern and perspective taking predicted no change in neuronal response associated with pain observation. These exploratory findings suggest that there is a distinct pattern of brain activity associated with observing the pain-related behaviour of the victim within the context of this social dilemma, that this observation evoked a self-oriented aversive state of personal distress, and that the objective "reality" of pain is of secondary importance for this response. These findings provide a starting point for experimentally more rigorous investigation of obedience.

The hubs of the human connectome are generally implicated in the anatomy of brain disorders.

PubMed

Crossley, Nicolas A; Mechelli, Andrea; Scott, Jessica; Carletti, Francesco; Fox, Peter T; McGuire, Philip; Bullmore, Edward T

2014-08-01

Brain networks or 'connectomes' include a minority of highly connected hub nodes that are functionally valuable, because their topological centrality supports integrative processing and adaptive behaviours. Recent studies also suggest that hubs have higher metabolic demands and longer-distance connections than other brain regions, and therefore could be considered biologically costly. Assuming that hubs thus normally combine both high topological value and high biological cost, we predicted that pathological brain lesions would be concentrated in hub regions. To test this general hypothesis, we first identified the hubs of brain anatomical networks estimated from diffusion tensor imaging data on healthy volunteers (n = 56), and showed that computational attacks targeted on hubs disproportionally degraded the efficiency of brain networks compared to random attacks. We then prepared grey matter lesion maps, based on meta-analyses of published magnetic resonance imaging data on more than 20 000 subjects and 26 different brain disorders. Magnetic resonance imaging lesions that were common across all brain disorders were more likely to be located in hubs of the normal brain connectome (P < 10(-4), permutation test). Specifically, nine brain disorders had lesions that were significantly more likely to be located in hubs (P < 0.05, permutation test), including schizophrenia and Alzheimer's disease. Both these disorders had significantly hub-concentrated lesion distributions, although (almost completely) distinct subsets of cortical hubs were lesioned in each disorder: temporal lobe hubs specifically were associated with higher lesion probability in Alzheimer's disease, whereas in schizophrenia lesions were concentrated in both frontal and temporal cortical hubs. These results linking pathological lesions to the topological centrality of nodes in the normal diffusion tensor imaging connectome were generally replicated when hubs were defined instead by the meta-analysis of more than 1500 task-related functional neuroimaging studies of healthy volunteers to create a normative functional co-activation network. We conclude that the high cost/high value hubs of human brain networks are more likely to be anatomically abnormal than non-hubs in many (if not all) brain disorders. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain.

Improving Functional MRI Registration Using Whole-Brain Functional Correlation Tensors.

PubMed

Zhou, Yujia; Yap, Pew-Thian; Zhang, Han; Zhang, Lichi; Feng, Qianjin; Shen, Dinggang

2017-09-01

Population studies of brain function with resting-state functional magnetic resonance imaging (rs-fMRI) largely rely on the accurate inter-subject registration of functional areas. This is typically achieved through registration of the corresponding T1-weighted MR images with more structural details. However, accumulating evidence has suggested that such strategy cannot well-align functional regions which are not necessarily confined by the anatomical boundaries defined by the T1-weighted MR images. To mitigate this problem, various registration algorithms based directly on rs-fMRI data have been developed, most of which have utilized functional connectivity (FC) as features for registration. However, most of the FC-based registration methods usually extract the functional features only from the thin and highly curved cortical grey matter (GM), posing a great challenge in accurately estimating the whole-brain deformation field. In this paper, we demonstrate that the additional useful functional features can be extracted from brain regions beyond the GM, particularly, white-matter (WM) based on rs-fMRI, for improving the overall functional registration. Specifically, we quantify the local anisotropic correlation patterns of the blood oxygenation level-dependent (BOLD) signals, modeled by functional correlation tensors (FCTs), in both GM and WM. Functional registration is then performed based on multiple components of the whole-brain FCTs using a multichannel Large Deformation Diffeomorphic Metric Mapping (mLDDMM) algorithm. Experimental results show that our proposed method achieves superior functional registration performance, compared with other conventional registration methods.

Brain activities associated with gaming urge of online gaming addiction.

PubMed

Ko, Chih-Hung; Liu, Gin-Chung; Hsiao, Sigmund; Yen, Ju-Yu; Yang, Ming-Jen; Lin, Wei-Chen; Yen, Cheng-Fang; Chen, Cheng-Sheng

2009-04-01

The aim of this study was to identify the neural substrates of online gaming addiction through evaluation of the brain areas associated with the cue-induced gaming urge. Ten participants with online gaming addiction and 10 control subjects without online gaming addiction were tested. They were presented with gaming pictures and the paired mosaic pictures while undergoing functional magnetic resonance imaging (fMRI) scanning. The contrast in blood-oxygen-level dependent (BOLD) signals when viewing gaming pictures and when viewing mosaic pictures was calculated with the SPM2 software to evaluate the brain activations. Right orbitofrontal cortex, right nucleus accumbens, bilateral anterior cingulate and medial frontal cortex, right dorsolateral prefrontal cortex, and right caudate nucleus were activated in the addicted group in contrast to the control group. The activation of the region-of-interest (ROI) defined by the above brain areas was positively correlated with self-reported gaming urge and recalling of gaming experience provoked by the WOW pictures. The results demonstrate that the neural substrate of cue-induced gaming urge/craving in online gaming addiction is similar to that of the cue-induced craving in substance dependence. The above-mentioned brain regions have been reported to contribute to the craving in substance dependence, and here we show that the same areas were involved in online gaming urge/craving. Thus, the results suggest that the gaming urge/craving in online gaming addiction and craving in substance dependence might share the same neurobiological mechanism.

A method for functional network connectivity among spatially independent resting-state components in schizophrenia.

PubMed

Jafri, Madiha J; Pearlson, Godfrey D; Stevens, Michael; Calhoun, Vince D

2008-02-15

Functional connectivity of the brain has been studied by analyzing correlation differences in time courses among seed voxels or regions with other voxels of the brain in healthy individuals as well as in patients with brain disorders. The spatial extent of strongly temporally coherent brain regions co-activated during rest has also been examined using independent component analysis (ICA). However, the weaker temporal relationships among ICA component time courses, which we operationally define as a measure of functional network connectivity (FNC), have not yet been studied. In this study, we propose an approach for evaluating FNC and apply it to functional magnetic resonance imaging (fMRI) data collected from persons with schizophrenia and healthy controls. We examined the connectivity and latency among ICA component time courses to test the hypothesis that patients with schizophrenia would show increased functional connectivity and increased lag among resting state networks compared to controls. Resting state fMRI data were collected and the inter-relationships among seven selected resting state networks (identified using group ICA) were evaluated by correlating each subject's ICA time courses with one another. Patients showed higher correlation than controls among most of the dominant resting state networks. Patients also had slightly more variability in functional connectivity than controls. We present a novel approach for quantifying functional connectivity among brain networks identified with spatial ICA. Significant differences between patient and control connectivity in different networks were revealed possibly reflecting deficiencies in cortical processing in patients.

Sound Frequency Representation in the Auditory Cortex of the Common Marmoset Visualized Using Optical Intrinsic Signal Imaging

PubMed Central

Tani, Toshiki; Abe, Hiroshi; Hayami, Taku; Banno, Taku; Kitamura, Naohito; Mashiko, Hiromi

2018-01-01

Abstract Natural sound is composed of various frequencies. Although the core region of the primate auditory cortex has functionally defined sound frequency preference maps, how the map is organized in the auditory areas of the belt and parabelt regions is not well known. In this study, we investigated the functional organizations of the core, belt, and parabelt regions encompassed by the lateral sulcus and the superior temporal sulcus in the common marmoset (Callithrix jacchus). Using optical intrinsic signal imaging, we obtained evoked responses to band-pass noise stimuli in a range of sound frequencies (0.5–16 kHz) in anesthetized adult animals and visualized the preferred sound frequency map on the cortical surface. We characterized the functionally defined organization using histologically defined brain areas in the same animals. We found tonotopic representation of a set of sound frequencies (low to high) within the primary (A1), rostral (R), and rostrotemporal (RT) areas of the core region. In the belt region, the tonotopic representation existed only in the mediolateral (ML) area. This representation was symmetric with that found in A1 along the border between areas A1 and ML. The functional structure was not very clear in the anterolateral (AL) area. Low frequencies were mainly preferred in the rostrotemplatal (RTL) area, while high frequencies were preferred in the caudolateral (CL) area. There was a portion of the parabelt region that strongly responded to higher sound frequencies (>5.8 kHz) along the border between the rostral parabelt (RPB) and caudal parabelt (CPB) regions. PMID:29736410

Whole brain C-arm computed tomography parenchymal blood volume measurements

PubMed Central

Byrne, James V

2016-01-01

Introduction C-arm flat detector computed tomography (FDCT) parenchymal blood volume (PBV) imaging in the neuro-interventional suite is a new technique for which detailed whole brain measurements have not been previously reported. This study aims to create a catalogue of PBV measurements for various anatomical regions encompassing the whole brain, using a three-dimensional volume-of-interest (3D-VOI) analysis. Methods We acquired and analysed 30 C-arm FDCT datasets from 26 patients with aneurysmal subarachnoid haemorrhage (SAH), as part of a prospective study comparing C-arm computed tomography (CT) PBV with magnetic resonance perfusion-weighted imaging (MR-PWI). We calculated the PBV values for various brain regions with an automated analysis, using 58 pre-defined atlas-based 3D-VOIs encompassing the whole brain. VOIs partially or completely overlapping regions of magnetic resonance diffusion weighted imaging (MR-DWI) abnormality or magnetic resonance cerebral blood flow (MR-CBF) asymmetry were excluded from the analysis. Results Of the 30 C-arm CT PBV datasets, 14 (54%; 12 patients) had areas of restricted diffusion, the majority of which were focal. The PBV values for the cerebral cortex and cerebral white matter were 4.01 ± 0.47 (mean ± SD) and 3.01 ± 0.39 ml per 100 ml. Lobar PBV values were: frontal lobe 4.2 ± 0.8, temporal lobe 4.2 ± 0.9, parietal lobe 3.9 ± 0.7 and occipital lobe 4.3 ± 0.8 ml/100 ml. The basal ganglia and brainstem PBV values were 3.4 ± 0.7 and 4.6 ± 0.6 ml/100 ml, respectively. Conclusions Compared with the typical reference cerebral blood volume (CBV) values reported in the literature for Positron Emission Tomography (PET), the PBV values were relatively high for the white matter and relatively low for the cortical grey matter. The reported catalogue of PBV values for various brain regions would be useful to inform future studies and could be used in clinical practice, when interpreting PBV maps. PMID:26769737

Whole brain C-arm computed tomography parenchymal blood volume measurements.

PubMed

Kamran, Mudassar; Byrne, James V

2016-04-01

C-arm flat detector computed tomography (FDCT) parenchymal blood volume (PBV) imaging in the neuro-interventional suite is a new technique for which detailed whole brain measurements have not been previously reported. This study aims to create a catalogue of PBV measurements for various anatomical regions encompassing the whole brain, using a three-dimensional volume-of-interest (3D-VOI) analysis. We acquired and analysed 30 C-arm FDCT datasets from 26 patients with aneurysmal subarachnoid haemorrhage (SAH), as part of a prospective study comparing C-arm computed tomography (CT) PBV with magnetic resonance perfusion-weighted imaging (MR-PWI). We calculated the PBV values for various brain regions with an automated analysis, using 58 pre-defined atlas-based 3D-VOIs encompassing the whole brain. VOIs partially or completely overlapping regions of magnetic resonance diffusion weighted imaging (MR-DWI) abnormality or magnetic resonance cerebral blood flow (MR-CBF) asymmetry were excluded from the analysis. Of the 30 C-arm CT PBV datasets, 14 (54%; 12 patients) had areas of restricted diffusion, the majority of which were focal. The PBV values for the cerebral cortex and cerebral white matter were 4.01 ± 0.47 (mean ± SD) and 3.01 ± 0.39 ml per 100 ml. Lobar PBV values were: frontal lobe 4.2 ± 0.8, temporal lobe 4.2 ± 0.9, parietal lobe 3.9 ± 0.7 and occipital lobe 4.3 ± 0.8 ml/100 ml. The basal ganglia and brainstem PBV values were 3.4 ± 0.7 and 4.6 ± 0.6 ml/100 ml, respectively. Compared with the typical reference cerebral blood volume (CBV) values reported in the literature for Positron Emission Tomography (PET), the PBV values were relatively high for the white matter and relatively low for the cortical grey matter. The reported catalogue of PBV values for various brain regions would be useful to inform future studies and could be used in clinical practice, when interpreting PBV maps. © The Author(s) 2016.

Sparse EEG/MEG source estimation via a group lasso

PubMed Central

Lim, Michael; Ales, Justin M.; Cottereau, Benoit R.; Hastie, Trevor

2017-01-01

Non-invasive recordings of human brain activity through electroencephalography (EEG) or magnetoencelphalography (MEG) are of value for both basic science and clinical applications in sensory, cognitive, and affective neuroscience. Here we introduce a new approach to estimating the intra-cranial sources of EEG/MEG activity measured from extra-cranial sensors. The approach is based on the group lasso, a sparse-prior inverse that has been adapted to take advantage of functionally-defined regions of interest for the definition of physiologically meaningful groups within a functionally-based common space. Detailed simulations using realistic source-geometries and data from a human Visual Evoked Potential experiment demonstrate that the group-lasso method has improved performance over traditional ℓ2 minimum-norm methods. In addition, we show that pooling source estimates across subjects over functionally defined regions of interest results in improvements in the accuracy of source estimates for both the group-lasso and minimum-norm approaches. PMID:28604790

Individual differences in cortical face selectivity predict behavioral performance in face recognition

PubMed Central

Huang, Lijie; Song, Yiying; Li, Jingguang; Zhen, Zonglei; Yang, Zetian; Liu, Jia

2014-01-01

In functional magnetic resonance imaging studies, object selectivity is defined as a higher neural response to an object category than other object categories. Importantly, object selectivity is widely considered as a neural signature of a functionally-specialized area in processing its preferred object category in the human brain. However, the behavioral significance of the object selectivity remains unclear. In the present study, we used the individual differences approach to correlate participants' face selectivity in the face-selective regions with their behavioral performance in face recognition measured outside the scanner in a large sample of healthy adults. Face selectivity was defined as the z score of activation with the contrast of faces vs. non-face objects, and the face recognition ability was indexed as the normalized residual of the accuracy in recognizing previously-learned faces after regressing out that for non-face objects in an old/new memory task. We found that the participants with higher face selectivity in the fusiform face area (FFA) and the occipital face area (OFA), but not in the posterior part of the superior temporal sulcus (pSTS), possessed higher face recognition ability. Importantly, the association of face selectivity in the FFA and face recognition ability cannot be accounted for by FFA response to objects or behavioral performance in object recognition, suggesting that the association is domain-specific. Finally, the association is reliable, confirmed by the replication from another independent participant group. In sum, our finding provides empirical evidence on the validity of using object selectivity as a neural signature in defining object-selective regions in the human brain. PMID:25071513

Multiscale energy reallocation during low-frequency steady-state brain response.

PubMed

Wang, Yifeng; Chen, Wang; Ye, Liangkai; Biswal, Bharat B; Yang, Xuezhi; Zou, Qijun; Yang, Pu; Yang, Qi; Wang, Xinqi; Cui, Qian; Duan, Xujun; Liao, Wei; Chen, Huafu

2018-05-01

Traditional task-evoked brain activations are based on detection and estimation of signal change from the mean signal. By contrast, the low-frequency steady-state brain response (lfSSBR) reflects frequency-tagging activity at the fundamental frequency of the task presentation and its harmonics. Compared to the activity at these resonant frequencies, brain responses at nonresonant frequencies are largely unknown. Additionally, because the lfSSBR is defined by power change, we hypothesize using Parseval's theorem that the power change reflects brain signal variability rather than the change of mean signal. Using a face recognition task, we observed power increase at the fundamental frequency (0.05 Hz) and two harmonics (0.1 and 0.15 Hz) and power decrease within the infra-slow frequency band (<0.1 Hz), suggesting a multifrequency energy reallocation. The consistency of power and variability was demonstrated by the high correlation (r > .955) of their spatial distribution and brain-behavior relationship at all frequency bands. Additionally, the reallocation of finite energy was observed across various brain regions and frequency bands, forming a particular spatiotemporal pattern. Overall, results from this study strongly suggest that frequency-specific power and variability may measure the same underlying brain activity and that these results may shed light on different mechanisms between lfSSBR and brain activation, and spatiotemporal characteristics of energy reallocation induced by cognitive tasks. © 2018 Wiley Periodicals, Inc.

Recent technological advances in pediatric brain tumor surgery.

PubMed

Zebian, Bassel; Vergani, Francesco; Lavrador, José Pedro; Mukherjee, Soumya; Kitchen, William John; Stagno, Vita; Chamilos, Christos; Pettorini, Benedetta; Mallucci, Conor

2017-01-01

X-rays and ventriculograms were the first imaging modalities used to localize intracranial lesions including brain tumors as far back as the 1880s. Subsequent advances in preoperative radiological localization included computed tomography (CT; 1971) and MRI (1977). Since then, other imaging modalities have been developed for clinical application although none as pivotal as CT and MRI. Intraoperative technological advances include the microscope, which has allowed precise surgery under magnification and improved lighting, and the endoscope, which has improved the treatment of hydrocephalus and allowed biopsy and complete resection of intraventricular, pituitary and pineal region tumors through a minimally invasive approach. Neuronavigation, intraoperative MRI, CT and ultrasound have increased the ability of the neurosurgeon to perform safe and maximal tumor resection. This may be facilitated by the use of fluorescing agents, which help define the tumor margin, and intraoperative neurophysiological monitoring, which helps identify and protect eloquent brain.

Familiarity promotes the blurring of self and other in the neural representation of threat

PubMed Central

Beckes, Lane; Hasselmo, Karen

2013-01-01

Neurobiological investigations of empathy often support an embodied simulation account. Using functional magnetic resonance imaging (fMRI), we monitored statistical associations between brain activations indicating self-focused threat to those indicating threats to a familiar friend or an unfamiliar stranger. Results in regions such as the anterior insula, putamen and supramarginal gyrus indicate that self-focused threat activations are robustly correlated with friend-focused threat activations but not stranger-focused threat activations. These results suggest that one of the defining features of human social bonding may be increasing levels of overlap between neural representations of self and other. This article presents a novel and important methodological approach to fMRI empathy studies, which informs how differences in brain activation can be detected in such studies and how covariate approaches can provide novel and important information regarding the brain and empathy. PMID:22563005

Gray and white matter correlates of the Big Five personality traits.

PubMed

Privado, Jesús; Román, Francisco J; Saénz-Urturi, Carlota; Burgaleta, Miguel; Colom, Roberto

2017-05-04

Personality neuroscience defines the scientific study of the neurobiological basis of personality. This field assumes that individual differences in personality traits are related with structural and functional variations of the human brain. Gray and white matters are structural properties considered separately in previous research. Available findings in this regard are largely disparate. Here we analyze the relationships between gray matter (cortical thickness (CT), cortical surface area (CSA), and cortical volume) and integrity scores obtained after several white matter tracts connecting different brain regions, with individual differences in the personality traits comprised by the Five-Factor Model (extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience). These psychological and biological data were obtained from young healthy women. The main findings showed statistically significant associations between occipital CSA variations and extraversion, as well as between parietal CT variations and neuroticism. Regarding white matter integrity, openness showed positive correlations with tracts connecting posterior and anterior brain regions. Therefore, variations in discrete gray matter clusters were associated with temperamental traits (extraversion and neuroticism), whereas long-distance structural connections were related with the dimension of personality that has been associated with high-level cognitive processes (openness). Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

Regional gray matter density is associated with achievement motivation: evidence from voxel-based morphometry.

PubMed

Takeuchi, Hikaru; Taki, Yasuyuki; Nouchi, Rui; Sekiguchi, Atsushi; Kotozaki, Yuka; Miyauchi, Carlos Makoto; Yokoyama, Ryoichi; Iizuka, Kunio; Hashizume, Hiroshi; Nakagawa, Seishu; Kunitoki, Keiko; Sassa, Yuko; Kawashima, Ryuta

2014-01-01

Achievement motivation can be defined as a recurrent need to improve one's past performance. Despite previous functional imaging studies on motivation-related functional activation, the relationship between regional gray matter (rGM) morphology and achievement motivation has never been investigated. We used voxel-based morphometry and a questionnaire (achievement motivation scale) to measure individual achievement motivation and investigated the association between rGM density (rGMD) and achievement motivation [self-fulfillment achievement motivation (SFAM) and competitive achievement motivation (CAM) across the brain in healthy young adults (age 21.0 ± 1.8 years, men (n = 94), women (n = 91)]. SFAM and rGMD significantly and negatively correlated in the orbitofrontal cortex (OFC). CAM and rGMD significantly and positively correlated in the right putamen, insula, and precuneus. These results suggest that the brain areas that play central roles in externally modulated motivation (OFC and putamen) also contribute to SFAM and CAM, respectively, but in different ways. Furthermore, the brain areas in which rGMD correlated with CAM are related to cognitive processes associated with distressing emotions and social cognition, and these cognitive processes may characterize CAM.

A silicon-based microelectrode array with a microdrive for monitoring brainstem regions of freely moving rats

NASA Astrophysics Data System (ADS)

Márton, G.; Baracskay, P.; Cseri, B.; Plósz, B.; Juhász, G.; Fekete, Z.; Pongrácz, A.

2016-04-01

Objective. Exploring neural activity behind synchronization and time locking in brain circuits is one of the most important tasks in neuroscience. Our goal was to design and characterize a microelectrode array (MEA) system specifically for obtaining in vivo extracellular recordings from three deep-brain areas of freely moving rats, simultaneously. The target areas, the deep mesencephalic reticular-, pedunculopontine tegmental- and pontine reticular nuclei are related to the regulation of sleep-wake cycles. Approach. The three targeted nuclei are collinear, therefore a single-shank MEA was designed in order to contact them. The silicon-based device was equipped with 3*4 recording sites, located according to the geometry of the brain regions. Furthermore, a microdrive was developed to allow fine actuation and post-implantation relocation of the probe. The probe was attached to a rigid printed circuit board, which was fastened to the microdrive. A flexible cable was designed in order to provide not only electronic connection between the probe and the amplifier system, but sufficient freedom for the movements of the probe as well. Main results. The microdrive was stable enough to allow precise electrode targeting into the tissue via a single track. The microelectrodes on the probe were suitable for recording neural activity from the three targeted brainstem areas. Significance. The system offers a robust solution to provide long-term interface between an array of precisely defined microelectrodes and deep-brain areas of a behaving rodent. The microdrive allowed us to fine-tune the probe location and easily scan through the regions of interest.

Functional language shift to the right hemisphere in patients with language-eloquent brain tumors.

PubMed

Krieg, Sandro M; Sollmann, Nico; Hauck, Theresa; Ille, Sebastian; Foerschler, Annette; Meyer, Bernhard; Ringel, Florian

2013-01-01

Language function is mainly located within the left hemisphere of the brain, especially in right-handed subjects. However, functional MRI (fMRI) has demonstrated changes of language organization in patients with left-sided perisylvian lesions to the right hemisphere. Because intracerebral lesions can impair fMRI, this study was designed to investigate human language plasticity with a virtual lesion model using repetitive navigated transcranial magnetic stimulation (rTMS). Fifteen patients with lesions of left-sided language-eloquent brain areas and 50 healthy and purely right-handed participants underwent bilateral rTMS language mapping via an object-naming task. All patients were proven to have left-sided language function during awake surgery. The rTMS-induced language errors were categorized into 6 different error types. The error ratio (induced errors/number of stimulations) was determined for each brain region on both hemispheres. A hemispheric dominance ratio was then defined for each region as the quotient of the error ratio (left/right) of the corresponding area of both hemispheres (ratio >1 = left dominant; ratio <1 = right dominant). Patients with language-eloquent lesions showed a statistically significantly lower ratio than healthy participants concerning "all errors" and "all errors without hesitations", which indicates a higher participation of the right hemisphere in language function. Yet, there was no cortical region with pronounced difference in language dominance compared to the whole hemisphere. This is the first study that shows by means of an anatomically accurate virtual lesion model that a shift of language function to the non-dominant hemisphere can occur.

Investigating changes in brain network properties in HIV-associated neurocognitive disease (HAND) using mutual connectivity analysis (MCA)

NASA Astrophysics Data System (ADS)

Abidin, Anas Zainul; D'Souza, Adora M.; Nagarajan, Mahesh B.; Wismüller, Axel

2016-03-01

About 50% of subjects infected with HIV present deficits in cognitive domains, which are known collectively as HIV associated neurocognitive disorder (HAND). The underlying synaptodendritic damage can be captured using resting state functional MRI, as has been demonstrated by a few earlier studies. Such damage may induce topological changes of brain connectivity networks. We test this hypothesis by capturing the functional interdependence of 90 brain network nodes using a Mutual Connectivity Analysis (MCA) framework with non-linear time series modeling based on Generalized Radial Basis function (GRBF) neural networks. The network nodes are selected based on the regions defined in the Automated Anatomic Labeling (AAL) atlas. Each node is represented by the average time series of the voxels of that region. The resulting networks are then characterized using graph-theoretic measures that quantify various network topology properties at a global as well as at a local level. We tested for differences in these properties in network graphs obtained for 10 subjects (6 male and 4 female, 5 HIV+ and 5 HIV-). Global network properties captured some differences between these subject cohorts, though significant differences were seen only with the clustering coefficient measure. Local network properties, such as local efficiency and the degree of connections, captured significant differences in regions of the frontal lobe, precentral and cingulate cortex amongst a few others. These results suggest that our method can be used to effectively capture differences occurring in brain network connectivity properties revealed by resting-state functional MRI in neurological disease states, such as HAND.

Ensemble Classification of Alzheimer's Disease and Mild Cognitive Impairment Based on Complex Graph Measures from Diffusion Tensor Images

PubMed Central

Ebadi, Ashkan; Dalboni da Rocha, Josué L.; Nagaraju, Dushyanth B.; Tovar-Moll, Fernanda; Bramati, Ivanei; Coutinho, Gabriel; Sitaram, Ranganatha; Rashidi, Parisa

2017-01-01

The human brain is a complex network of interacting regions. The gray matter regions of brain are interconnected by white matter tracts, together forming one integrative complex network. In this article, we report our investigation about the potential of applying brain connectivity patterns as an aid in diagnosing Alzheimer's disease and Mild Cognitive Impairment (MCI). We performed pattern analysis of graph theoretical measures derived from Diffusion Tensor Imaging (DTI) data representing structural brain networks of 45 subjects, consisting of 15 patients of Alzheimer's disease (AD), 15 patients of MCI, and 15 healthy subjects (CT). We considered pair-wise class combinations of subjects, defining three separate classification tasks, i.e., AD-CT, AD-MCI, and CT-MCI, and used an ensemble classification module to perform the classification tasks. Our ensemble framework with feature selection shows a promising performance with classification accuracy of 83.3% for AD vs. MCI, 80% for AD vs. CT, and 70% for MCI vs. CT. Moreover, our findings suggest that AD can be related to graph measures abnormalities at Brodmann areas in the sensorimotor cortex and piriform cortex. In this way, node redundancy coefficient and load centrality in the primary motor cortex were recognized as good indicators of AD in contrast to MCI. In general, load centrality, betweenness centrality, and closeness centrality were found to be the most relevant network measures, as they were the top identified features at different nodes. The present study can be regarded as a “proof of concept” about a procedure for the classification of MRI markers between AD dementia, MCI, and normal old individuals, due to the small and not well-defined groups of AD and MCI patients. Future studies with larger samples of subjects and more sophisticated patient exclusion criteria are necessary toward the development of a more precise technique for clinical diagnosis. PMID:28293162

Brain Injured Students at My School? In My Room?

ERIC Educational Resources Information Center

Cave, Bobbin Kyte

2004-01-01

In this article, the author identifies brain injuries as defined in special education law, discusses the number of students who might be impacted, describes symptoms, and reviews successful educational interventions. Traumatic brain injuries (TBI) are defined in special education law in the Individuals with Disabilities Education Act (IDEA 1990)…

Intracranial Tumor Cell Migration and the Development of Multiple Brain Metastases in Malignant Melanoma.

PubMed

Simonsen, Trude G; Gaustad, Jon-Vidar; Rofstad, Einar K

2016-06-01

A majority of patients with melanoma brain metastases develop multiple lesions, and these patients show particularly poor prognosis. To develop improved treatment strategies, detailed insights into the biology of melanoma brain metastases, and particularly the development of multiple lesions, are needed. The purpose of this preclinical investigation was to study melanoma cell migration within the brain after cell injection into a well-defined intracerebral site. A-07, D-12, R-18, and U-25 human melanoma cells transfected with green fluorescent protein were injected stereotactically into the right cerebral hemisphere of nude mice. Moribund mice were killed and autopsied, and the brain was evaluated by fluorescence imaging or histological examination. Intracerebral inoculation of melanoma cells produced multiple lesions involving all regions of the brain, suggesting that the cells were able to migrate over substantial distances within the brain. Multiple modes of transport were identified, and all transport modes were observed in all four melanoma lines. Thus, the melanoma cells were passively transported via the flow of cerebrospinal fluid in the meninges and ventricles, they migrated actively along leptomeningeal and brain parenchymal blood vessels, and they migrated actively along the surfaces separating different brain compartments. Migration of melanoma cells after initial arrest, extravasation, and growth at a single location within the brain may contribute significantly to the development of multiple melanoma brain metastases. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Associations between the self-reported frequency of hearing chemical alarms in theater and regional brain volume in Gulf War Veterans.

PubMed

Chao, Linda L; Reeb, Rosemary; Esparza, Iva L; Abadjian, Linda R

2016-03-01

We previously reported evidence of reduced cortical gray matter (GM), white matter (WM), and hippocampal volume in Gulf War (GW) veterans with predicted exposure to low-levels of nerve agent according to the 2000 Khamisiyah plume model analysis. Because there is suggestive evidence that other nerve agent exposures may have occurred during the Gulf War, we examined the association between the self-reported frequency of hearing chemical alarms sound during deployment in the Gulf War and regional brain volume in GW veterans. Ninety consecutive GW veterans (15 female, mean age: 52±8years) participating in a VA-funded study underwent structural magnetic resonance imaging (MRI) on a 3T scanner. Freesurfer (version 5.1) was used to obtain regional measures of cortical GM, WM, hippocampal, and insula volume. Multiple linear regression was used to determine the association between the self-reported frequencies of hearing chemical alarms during the Gulf War and regional brain volume. There was an inverse association between the self-reported frequency of hearing chemical alarms sound and total cortical GM (adjusted p=0.007), even after accounting for potentially confounding demographic and clinical variables, the veterans' current health status, and other concurrent deployment-related exposures that were correlated with hearing chemical alarms. Post-hoc analyses extended the inverse relationship between the frequency of hearing chemical alarms to GM volume in the frontal (adjusted p=0.02), parietal (adjusted p=0.01), and occipital (adjusted p=0.001) lobes. In contrast, regional brain volumes were not significantly associated with predicted exposure to the Khamisiyah plume or with Gulf War Illness status defined by the Kansas or Centers for Disease Control and Prevention criteria. Many veterans reported hearing chemical alarms sound during the Gulf War. The current findings suggest that exposure to substances that triggered those chemical alarms during the Gulf War likely had adverse neuroanatomical effects. Published by Elsevier B.V.

Associations between the self-reported frequency of hearing chemical alarms in theater and regional brain volume in Gulf War Veterans

PubMed Central

Chao, Linda L.; Reeb, Rosemary; Esparza, Iva L.; Abadjian, Linda R.

2017-01-01

Background We previously reported evidence of reduced cortical gray matter (GM), white matter (WM), and hippocampal volume in Gulf War (GW) veterans with predicted exposure to low-levels of nerve agent according to the 2000 Khamisiyah plume model analysis. Because there is suggestive evidence that other nerve agent exposures may have occurred during the Gulf War, we examined the association between the self-reported frequency of hearing chemical alarms sound during deployment in the Gulf War and regional brain volume in GW veterans. Methods Ninety consecutive GW veterans (15 female, mean age: 52±8 years) participating in a VA-funded study underwent structural magnetic resonance imaging (MRI) on a 3 T scanner. Freesurfer (version 5.1) was used to obtain regional measures of cortical GM, WM, hippocampal, and insula volume. Multiple linear regression was used to determine the association between the self-reported frequencies of hearing chemical alarms during the Gulf War and regional brain volume. Results There was an inverse association between the self-reported frequency of hearing chemical alarms sound and total cortical GM (adjusted p = 0.007), even after accounting for potentially confounding demographic and clinical variables, the veterans’ current health status, and other concurrent deployment-related exposures that were correlated with hearing chemical alarms. Post-hoc analyses extended the inverse relationship between the frequency of hearing chemical alarms to GM volume in the frontal (adjusted p = 0.02), parietal (adjusted p = 0.01), and occipital (adjusted p = 0.001) lobes. In contrast, regional brain volumes were not significantly associated with predicted exposure to the Khamisiyah plume or with Gulf War Illness status defined by the Kansas or Centers for Disease Control and Prevention criteria. Conclusions Many veterans reported hearing chemical alarms sound during the Gulf War. The current findings suggest that exposure to substances that triggered those chemical alarms during the Gulf War likely had adverse neuroanatomical effects. PMID:26920621

Subjective-Objective Sleep Discrepancy Is Associated With Alterations in Regional Glucose Metabolism in Patients With Insomnia and Good Sleeper Controls.

PubMed

Kay, Daniel B; Karim, Helmet T; Soehner, Adriane M; Hasler, Brant P; James, Jeffrey A; Germain, Anne; Hall, Martica H; Franzen, Peter L; Price, Julie C; Nofzinger, Eric A; Buysse, Daniel J

2017-11-01

Sleep discrepancies are common in primary insomnia (PI) and include reports of longer sleep onset latency (SOL) than measured by polysomnography (PSG) or "negative SOL discrepancy." We hypothesized that negative SOL discrepancy in PI would be associated with higher relative glucose metabolism during nonrapid eye movement (NREM) sleep in brain networks involved in conscious awareness, including the salience, left executive control, and default mode networks. PI (n = 32) and good sleeper controls (GS; n = 30) completed [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) scans during NREM sleep, and relative regional cerebral metabolic rate for glucose (rCMRglc) was measured. Sleep discrepancy was calculated by subtracting PSG-measured SOL on the PET night from corresponding self-report values the following morning. We tested for interactions between group (PI vs. GS) and SOL discrepancy for rCMRglc during NREM sleep using both a region of interest mask and exploratory whole-brain analyses. Significant group by SOL discrepancy interactions for rCMRglc were observed in several brain regions (pcorrected < .05 for all clusters). In the PI group, more negative SOL discrepancy (self-reported > PSG-measured SOL) was associated with significantly higher relative rCMRglc in the right anterior insula and middle/posterior cingulate during NREM sleep. In GS, more positive SOL discrepancy (self-reported < PSG-measured SOL) was associated with significantly higher relative rCMRglc in the right anterior insula, left anterior cingulate cortex, and middle/posterior cingulate cortex. Although preliminary, these findings suggest regions of the brain previously shown to be involved in conscious awareness, and the perception of PSG-defined states may also be involved in the phenomena of SOL discrepancy. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

Heterogeneity of anatomic regions by MR volumetry in juvenile myoclonic epilepsy.

PubMed

Swartz, B E; Spitz, J; Vu, A L; Mandelkern, M; Su, M L

2016-10-01

To investigate brain volumes in patients with well-characterized juvenile myoclonic epilepsy (JME). We studied the MRI images of seventeen subjects with EEG and clinically defined JME and seventeen age- and sex-matched controls using voxel-based morphometry (VBM) and automated and manual volumetry. We found no significant group differences in the cortical volumes by automated techniques for all regions or for the whole brain. However, we found a larger pulvinar nucleus in JME using VBM with small volume correction and a larger thalamus with manual volumetry (P = 0.001; corrected two-tailed t-test). By analysing the individual subjects, we determined that considerable heterogeneity exists even in this highly selected group. Histograms of all JME and matched control regions' volumes showed more subjects with JME had smaller hippocampi and larger thalami (P < 0.05; chi-square). Subjects in whom the first seizure was absence were more likely to have smaller hippocampi than their matched control, while those without absences showed no differences (P < 0.05, chi-square). There is ample evidence for frontal cortical thalamic network changes in JME, but subcortical structural differences were more distinct in this group. Given the heterogeneity of brain volumes in the clinical population, further advancement in the field will require the examination of stringent genetically controlled populations. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A case study for outreach: the Auckland experience of the New Zealand Brain Bee Challenge.

PubMed

Dowie, Megan J; Nicholson, Louise F B

2011-02-01

The 3rd hosting of the Auckland region New Zealand Brain Bee Challenge was held in 2009. Designed as a neuroscience quiz for high school students, the competition provides a valuable case study for science outreach. By engaging with teenagers, the field of neuroscience presents an exciting area of science but also stimulates those in the field to promote and share their research. Neuroscience is the ideal subject to highlight and promote science to young people and the community, as the brain defines unique features such as our personality, emotions, creativity, and intelligence. Understanding brain function and, importantly, determining dysfunction is a growing area of research interest, with relevance to health care systems and government policy, especially in light of the aging population. Feedback from students and teachers indicated that they had learned something about research and the brain, were more aware of options within science including considering neuroscience as a career option, and would recommend participation in the Brain Bee Challenge to other students. A number of participants indicated it was interesting/valuable to have interaction with neuroscientists. Although there are many synergistic benefits resulting from an undertaking such as the Brain Bee Challenge, the following profile highlights the value of the interaction and promotion of research to the community.

Evaluation of the default-mode network by quantitative 15O-PET: comparative study between cerebral blood flow and oxygen consumption.

PubMed

Aoe, Jo; Watabe, Tadashi; Shimosegawa, Eku; Kato, Hiroki; Kanai, Yasukazu; Naka, Sadahiro; Matsunaga, Keiko; Isohashi, Kayako; Tatsumi, Mitsuaki; Hatazawa, Jun

2018-06-22

Resting-state functional MRI (rs-fMRI) has revealed the existence of a default-mode network (DMN) based on spontaneous oscillations of the blood oxygenation level-dependent (BOLD) signal. The BOLD signal reflects the deoxyhemoglobin concentration, which depends on the relationship between the regional cerebral blood flow (CBF) and the cerebral metabolic rate of oxygen (CMRO 2 ). However, these two factors cannot be separated in BOLD rs-fMRI. In this study, we attempted to estimate the functional correlations in the DMN by means of quantitative 15 O-labeled gases and water PET, and to compare the contribution of the CBF and CMRO 2 to the DMN. Nine healthy volunteers (5 men and 4 women; mean age, 47.0 ± 1.2 years) were studied by means of 15 O-O 2 , 15 O-CO gases and 15 O-water PET. Quantitative CBF and CMRO 2 images were generated by an autoradiographic method and transformed into MNI standardized brain template. Regions of interest were placed on normalized PET images according to the previous rs-fMRI study. For the functional correlation analysis, the intersubject Pearson's correlation coefficients (r) were calculated for all pairs in the brain regions and correlation matrices were obtained for CBF and CMRO 2 , respectively. We defined r > 0.7 as a significant positive correlation and compared the correlation matrices of CBF and CMRO 2 . Significant positive correlations (r > 0.7) were observed in 24 pairs of brain regions for the CBF and 22 pairs of brain regions for the CMRO 2 . Among them, 12 overlapping networks were observed between CBF and CMRO 2 . Correlation analysis of CBF led to the detection of more brain networks as compared to that of CMRO 2 , indicating that the CBF can capture the state of the spontaneous activity with a higher sensitivity. We estimated the functional correlations in the DMN by means of quantitative PET using 15 O-labeled gases and water. The correlation matrix derived from the CBF revealed a larger number of brain networks as compared to that derived from the CMRO 2 , indicating that contribution to the functional correlation in the DMN is higher in the blood flow more than the oxygen consumption.

Automated selection of brain regions for real-time fMRI brain-computer interfaces

NASA Astrophysics Data System (ADS)

Lührs, Michael; Sorger, Bettina; Goebel, Rainer; Esposito, Fabrizio

2017-02-01

Objective. Brain-computer interfaces (BCIs) implemented with real-time functional magnetic resonance imaging (rt-fMRI) use fMRI time-courses from predefined regions of interest (ROIs). To reach best performances, localizer experiments and on-site expert supervision are required for ROI definition. To automate this step, we developed two unsupervised computational techniques based on the general linear model (GLM) and independent component analysis (ICA) of rt-fMRI data, and compared their performances on a communication BCI. Approach. 3 T fMRI data of six volunteers were re-analyzed in simulated real-time. During a localizer run, participants performed three mental tasks following visual cues. During two communication runs, a letter-spelling display guided the subjects to freely encode letters by performing one of the mental tasks with a specific timing. GLM- and ICA-based procedures were used to decode each letter, respectively using compact ROIs and whole-brain distributed spatio-temporal patterns of fMRI activity, automatically defined from subject-specific or group-level maps. Main results. Letter-decoding performances were comparable to supervised methods. In combination with a similarity-based criterion, GLM- and ICA-based approaches successfully decoded more than 80% (average) of the letters. Subject-specific maps yielded optimal performances. Significance. Automated solutions for ROI selection may help accelerating the translation of rt-fMRI BCIs from research to clinical applications.

Using large-scale Granger causality to study changes in brain network properties in the Clinically Isolated Syndrome (CIS) stage of multiple sclerosis

NASA Astrophysics Data System (ADS)

Abidin, Anas Z.; Chockanathan, Udaysankar; DSouza, Adora M.; Inglese, Matilde; Wismüller, Axel

2017-03-01

Clinically Isolated Syndrome (CIS) is often considered to be the first neurological episode associated with Multiple sclerosis (MS). At an early stage the inflammatory demyelination occurring in the CNS can manifest as a change in neuronal metabolism, with multiple asymptomatic white matter lesions detected in clinical MRI. Such damage may induce topological changes of brain networks, which can be captured by advanced functional MRI (fMRI) analysis techniques. We test this hypothesis by capturing the effective relationships of 90 brain regions, defined in the Automated Anatomic Labeling (AAL) atlas, using a large-scale Granger Causality (lsGC) framework. The resulting networks are then characterized using graph-theoretic measures that quantify various network topology properties at a global as well as at a local level. We study for differences in these properties in network graphs obtained for 18 subjects (10 male and 8 female, 9 with CIS and 9 healthy controls). Global network properties captured trending differences with modularity and clustering coefficient (p<0.1). Additionally, local network properties, such as local efficiency and the strength of connections, captured statistically significant (p<0.01) differences in some regions of the inferior frontal and parietal lobe. We conclude that multivariate analysis of fMRI time-series can reveal interesting information about changes occurring in the brain in early stages of MS.

The Agent Brain: A Review of Non-invasive Brain Stimulation Studies on Sensing Agency.

PubMed

Crivelli, Davide; Balconi, Michela

2017-01-01

According to philosophy of mind and neuroscientific models, the sense of agency can be defined as the sense that I am the one that is generating an action and causing its effects. Such ability to sense ourselves as causal agents is critical for the definition of intentional behavior and is a primary root for human interaction skills. The present mini-review aims at discussing evidences from non-invasive brain stimulation (NIBS) studies targeting functional correlates of different aspects of agency and evidences on the way stimulation techniques affect such core feature of human subjective experience. Clinical and brain imaging studies helped in defining a neural network mediating agency-related processes, which includes the dorsolateral prefrontal cortex (dlPFC), the cingulate cortex (CC), the supplementary and pre-supplementary motor areas (SMA and pre-SMA), the posterior parietal cortex (PPC) and its inferior regions and the cerebellum. However, while the plurality of those structures mirrors the complexity of the phenomenon, their actual roles with respect to different components of the experience of agency have been primarily explored via correlational techniques, without a clear evidence about their causal significance with respect to the integration of sensorimotor information, intentionalization, and action monitoring processes. Therefore, insights into the specific causal role of different cortical structures can be specified by using NIBS techniques, in order to provide improved understanding into the bases of our ability vs. inability to properly act in complex social contexts.

Longitudinal patterns of leukoaraiosis and brain atrophy in symptomatic small vessel disease

PubMed Central

Benjamin, Philip; Zeestraten, Eva; Lawrence, Andrew J.; Barrick, Thomas R.; Markus, Hugh S.

2016-01-01

Abstract Cerebral small vessel disease is a common condition associated with lacunar stroke, cognitive impairment and significant functional morbidity. White matter hyperintensities and brain atrophy, seen on magnetic resonance imaging, are correlated with increasing disease severity. However, how the two are related remains an open question. To better define the relationship between white matter hyperintensity growth and brain atrophy, we applied a semi-automated magnetic resonance imaging segmentation analysis pipeline to a 3-year longitudinal cohort of 99 subjects with symptomatic small vessel disease, who were followed-up for ≥1 years. Using a novel two-stage warping pipeline with tissue repair step, voxel-by-voxel rate of change maps were calculated for each tissue class (grey matter, white matter, white matter hyperintensities and lacunes) for each individual. These maps capture both the distribution of disease and spatial information showing local rates of growth and atrophy. These were analysed to answer three primary questions: first, is there a relationship between whole brain atrophy and magnetic resonance imaging markers of small vessel disease (white matter hyperintensities or lacune volume)? Second, is there regional variation within the cerebral white matter in the rate of white matter hyperintensity progression? Finally, are there regionally specific relationships between the rates of white matter hyperintensity progression and cortical grey matter atrophy? We demonstrate that the rates of white matter hyperintensity expansion and grey matter atrophy are strongly correlated (Pearson’s R = −0.69, P < 1 × 10 −7 ), and significant grey matter loss and whole brain atrophy occurs annually ( P < 0.05). Additionally, the rate of white matter hyperintensity growth was heterogeneous, occurring more rapidly within long association fasciculi. Using voxel-based quantification (family-wise error corrected P < 0.05), we show the rate of white matter hyperintensity progression is associated with increases in cortical grey matter atrophy rates, in the medial-frontal, orbito-frontal, parietal and occipital regions. Conversely, increased rates of global grey matter atrophy are significantly associated with faster white matter hyperintensity growth in the frontal and parietal regions. Together, these results link the progression of white matter hyperintensities with increasing rates of regional grey matter atrophy, and demonstrate that grey matter atrophy is the major contributor to whole brain atrophy in symptomatic cerebral small vessel disease. These measures provide novel insights into the longitudinal pathogenesis of small vessel disease, and imply that therapies aimed at reducing progression of white matter hyperintensities via end-arteriole damage may protect against secondary brain atrophy and consequent functional morbidity. PMID:26936939

Functional Brain Networks Develop from a “Local to Distributed” Organization

PubMed Central

Power, Jonathan D.; Dosenbach, Nico U. F.; Church, Jessica A.; Miezin, Francis M.; Schlaggar, Bradley L.; Petersen, Steven E.

2009-01-01

The mature human brain is organized into a collection of specialized functional networks that flexibly interact to support various cognitive functions. Studies of development often attempt to identify the organizing principles that guide the maturation of these functional networks. In this report, we combine resting state functional connectivity MRI (rs-fcMRI), graph analysis, community detection, and spring-embedding visualization techniques to analyze four separate networks defined in earlier studies. As we have previously reported, we find, across development, a trend toward ‘segregation’ (a general decrease in correlation strength) between regions close in anatomical space and ‘integration’ (an increased correlation strength) between selected regions distant in space. The generalization of these earlier trends across multiple networks suggests that this is a general developmental principle for changes in functional connectivity that would extend to large-scale graph theoretic analyses of large-scale brain networks. Communities in children are predominantly arranged by anatomical proximity, while communities in adults predominantly reflect functional relationships, as defined from adult fMRI studies. In sum, over development, the organization of multiple functional networks shifts from a local anatomical emphasis in children to a more “distributed” architecture in young adults. We argue that this “local to distributed” developmental characterization has important implications for understanding the development of neural systems underlying cognition. Further, graph metrics (e.g., clustering coefficients and average path lengths) are similar in child and adult graphs, with both showing “small-world”-like properties, while community detection by modularity optimization reveals stable communities within the graphs that are clearly different between young children and young adults. These observations suggest that early school age children and adults both have relatively efficient systems that may solve similar information processing problems in divergent ways. PMID:19412534

Whole-brain spectroscopic MRI biomarkers identify infiltrating margins in glioblastoma patients

PubMed Central

Cordova, James S.; Shu, Hui-Kuo G.; Liang, Zhongxing; Gurbani, Saumya S.; Cooper, Lee A. D.; Holder, Chad A.; Olson, Jeffrey J.; Kairdolf, Brad; Schreibmann, Eduard; Neill, Stewart G.; Hadjipanayis, Constantinos G.; Shim, Hyunsuk

2016-01-01

Background The standard of care for glioblastoma (GBM) is maximal safe resection followed by radiation therapy with chemotherapy. Currently, contrast-enhanced MRI is used to define primary treatment volumes for surgery and radiation therapy. However, enhancement does not identify the tumor entirely, resulting in limited local control. Proton spectroscopic MRI (sMRI), a method reporting endogenous metabolism, may better define the tumor margin. Here, we develop a whole-brain sMRI pipeline and validate sMRI metrics with quantitative measures of tumor infiltration. Methods Whole-brain sMRI metabolite maps were coregistered with surgical planning MRI and imported into a neuronavigation system to guide tissue sampling in GBM patients receiving 5-aminolevulinic acid fluorescence-guided surgery. Samples were collected from regions with metabolic abnormalities in a biopsy-like fashion before bulk resection. Tissue fluorescence was measured ex vivo using a hand-held spectrometer. Tissue samples were immunostained for Sox2 and analyzed to quantify the density of staining cells using a novel digital pathology image analysis tool. Correlations among sMRI markers, Sox2 density, and ex vivo fluorescence were evaluated. Results Spectroscopic MRI biomarkers exhibit significant correlations with Sox2-positive cell density and ex vivo fluorescence. The choline to N-acetylaspartate ratio showed significant associations with each quantitative marker (Pearson's ρ = 0.82, P < .001 and ρ = 0.36, P < .0001, respectively). Clinically, sMRI metabolic abnormalities predated contrast enhancement at sites of tumor recurrence and exhibited an inverse relationship with progression-free survival. Conclusions As it identifies tumor infiltration and regions at high risk for recurrence, sMRI could complement conventional MRI to improve local control in GBM patients. PMID:26984746

Functional brain networks develop from a "local to distributed" organization.

PubMed

Fair, Damien A; Cohen, Alexander L; Power, Jonathan D; Dosenbach, Nico U F; Church, Jessica A; Miezin, Francis M; Schlaggar, Bradley L; Petersen, Steven E

2009-05-01

The mature human brain is organized into a collection of specialized functional networks that flexibly interact to support various cognitive functions. Studies of development often attempt to identify the organizing principles that guide the maturation of these functional networks. In this report, we combine resting state functional connectivity MRI (rs-fcMRI), graph analysis, community detection, and spring-embedding visualization techniques to analyze four separate networks defined in earlier studies. As we have previously reported, we find, across development, a trend toward 'segregation' (a general decrease in correlation strength) between regions close in anatomical space and 'integration' (an increased correlation strength) between selected regions distant in space. The generalization of these earlier trends across multiple networks suggests that this is a general developmental principle for changes in functional connectivity that would extend to large-scale graph theoretic analyses of large-scale brain networks. Communities in children are predominantly arranged by anatomical proximity, while communities in adults predominantly reflect functional relationships, as defined from adult fMRI studies. In sum, over development, the organization of multiple functional networks shifts from a local anatomical emphasis in children to a more "distributed" architecture in young adults. We argue that this "local to distributed" developmental characterization has important implications for understanding the development of neural systems underlying cognition. Further, graph metrics (e.g., clustering coefficients and average path lengths) are similar in child and adult graphs, with both showing "small-world"-like properties, while community detection by modularity optimization reveals stable communities within the graphs that are clearly different between young children and young adults. These observations suggest that early school age children and adults both have relatively efficient systems that may solve similar information processing problems in divergent ways.

Memory-Efficient Analysis of Dense Functional Connectomes.

PubMed

Loewe, Kristian; Donohue, Sarah E; Schoenfeld, Mircea A; Kruse, Rudolf; Borgelt, Christian

2016-01-01

The functioning of the human brain relies on the interplay and integration of numerous individual units within a complex network. To identify network configurations characteristic of specific cognitive tasks or mental illnesses, functional connectomes can be constructed based on the assessment of synchronous fMRI activity at separate brain sites, and then analyzed using graph-theoretical concepts. In most previous studies, relatively coarse parcellations of the brain were used to define regions as graphical nodes. Such parcellated connectomes are highly dependent on parcellation quality because regional and functional boundaries need to be relatively consistent for the results to be interpretable. In contrast, dense connectomes are not subject to this limitation, since the parcellation inherent to the data is used to define graphical nodes, also allowing for a more detailed spatial mapping of connectivity patterns. However, dense connectomes are associated with considerable computational demands in terms of both time and memory requirements. The memory required to explicitly store dense connectomes in main memory can render their analysis infeasible, especially when considering high-resolution data or analyses across multiple subjects or conditions. Here, we present an object-based matrix representation that achieves a very low memory footprint by computing matrix elements on demand instead of explicitly storing them. In doing so, memory required for a dense connectome is reduced to the amount needed to store the underlying time series data. Based on theoretical considerations and benchmarks, different matrix object implementations and additional programs (based on available Matlab functions and Matlab-based third-party software) are compared with regard to their computational efficiency. The matrix implementation based on on-demand computations has very low memory requirements, thus enabling analyses that would be otherwise infeasible to conduct due to insufficient memory. An open source software package containing the created programs is available for download.

Memory-Efficient Analysis of Dense Functional Connectomes

PubMed Central

Loewe, Kristian; Donohue, Sarah E.; Schoenfeld, Mircea A.; Kruse, Rudolf; Borgelt, Christian

2016-01-01

The functioning of the human brain relies on the interplay and integration of numerous individual units within a complex network. To identify network configurations characteristic of specific cognitive tasks or mental illnesses, functional connectomes can be constructed based on the assessment of synchronous fMRI activity at separate brain sites, and then analyzed using graph-theoretical concepts. In most previous studies, relatively coarse parcellations of the brain were used to define regions as graphical nodes. Such parcellated connectomes are highly dependent on parcellation quality because regional and functional boundaries need to be relatively consistent for the results to be interpretable. In contrast, dense connectomes are not subject to this limitation, since the parcellation inherent to the data is used to define graphical nodes, also allowing for a more detailed spatial mapping of connectivity patterns. However, dense connectomes are associated with considerable computational demands in terms of both time and memory requirements. The memory required to explicitly store dense connectomes in main memory can render their analysis infeasible, especially when considering high-resolution data or analyses across multiple subjects or conditions. Here, we present an object-based matrix representation that achieves a very low memory footprint by computing matrix elements on demand instead of explicitly storing them. In doing so, memory required for a dense connectome is reduced to the amount needed to store the underlying time series data. Based on theoretical considerations and benchmarks, different matrix object implementations and additional programs (based on available Matlab functions and Matlab-based third-party software) are compared with regard to their computational efficiency. The matrix implementation based on on-demand computations has very low memory requirements, thus enabling analyses that would be otherwise infeasible to conduct due to insufficient memory. An open source software package containing the created programs is available for download. PMID:27965565

Stress and Fear Extinction

PubMed Central

Maren, Stephen; Holmes, Andrew

2016-01-01

Stress has a critical role in the development and expression of many psychiatric disorders, and is a defining feature of posttraumatic stress disorder (PTSD). Stress also limits the efficacy of behavioral therapies aimed at limiting pathological fear, such as exposure therapy. Here we examine emerging evidence that stress impairs recovery from trauma by impairing fear extinction, a form of learning thought to underlie the suppression of trauma-related fear memories. We describe the major structural and functional abnormalities in brain regions that are particularly vulnerable to stress, including the amygdala, prefrontal cortex, and hippocampus, which may underlie stress-induced impairments in extinction. We also discuss some of the stress-induced neurochemical and molecular alterations in these brain regions that are associated with extinction deficits, and the potential for targeting these changes to prevent or reverse impaired extinction. A better understanding of the neurobiological basis of stress effects on extinction promises to yield novel approaches to improving therapeutic outcomes for PTSD and other anxiety and trauma-related disorders. PMID:26105142

Decoding the neural mechanisms of human tool use

PubMed Central

Gallivan, Jason P; McLean, D Adam; Valyear, Kenneth F; Culham, Jody C

2013-01-01

Sophisticated tool use is a defining characteristic of the primate species but how is it supported by the brain, particularly the human brain? Here we show, using functional MRI and pattern classification methods, that tool use is subserved by multiple distributed action-centred neural representations that are both shared with and distinct from those of the hand. In areas of frontoparietal cortex we found a common representation for planned hand- and tool-related actions. In contrast, in parietal and occipitotemporal regions implicated in hand actions and body perception we found that coding remained selectively linked to upcoming actions of the hand whereas in parietal and occipitotemporal regions implicated in tool-related processing the coding remained selectively linked to upcoming actions of the tool. The highly specialized and hierarchical nature of this coding suggests that hand- and tool-related actions are represented separately at earlier levels of sensorimotor processing before becoming integrated in frontoparietal cortex. DOI: http://dx.doi.org/10.7554/eLife.00425.001 PMID:23741616

Molecular regionalization of the developing amphioxus neural tube challenges major partitions of the vertebrate brain.

PubMed

Albuixech-Crespo, Beatriz; López-Blanch, Laura; Burguera, Demian; Maeso, Ignacio; Sánchez-Arrones, Luisa; Moreno-Bravo, Juan Antonio; Somorjai, Ildiko; Pascual-Anaya, Juan; Puelles, Eduardo; Bovolenta, Paola; Garcia-Fernàndez, Jordi; Puelles, Luis; Irimia, Manuel; Ferran, José Luis

2017-04-01

All vertebrate brains develop following a common Bauplan defined by anteroposterior (AP) and dorsoventral (DV) subdivisions, characterized by largely conserved differential expression of gene markers. However, it is still unclear how this Bauplan originated during evolution. We studied the relative expression of 48 genes with key roles in vertebrate neural patterning in a representative amphioxus embryonic stage. Unlike nonchordates, amphioxus develops its central nervous system (CNS) from a neural plate that is homologous to that of vertebrates, allowing direct topological comparisons. The resulting genoarchitectonic model revealed that the amphioxus incipient neural tube is unexpectedly complex, consisting of several AP and DV molecular partitions. Strikingly, comparison with vertebrates indicates that the vertebrate thalamus, pretectum, and midbrain domains jointly correspond to a single amphioxus region, which we termed Di-Mesencephalic primordium (DiMes). This suggests that these domains have a common developmental and evolutionary origin, as supported by functional experiments manipulating secondary organizers in zebrafish and mice.

Molecular regionalization of the developing amphioxus neural tube challenges major partitions of the vertebrate brain

PubMed Central

Albuixech-Crespo, Beatriz; Maeso, Ignacio; Sánchez-Arrones, Luisa; Moreno-Bravo, Juan Antonio; Somorjai, Ildiko; Pascual-Anaya, Juan; Puelles, Eduardo; Bovolenta, Paola; Garcia-Fernàndez, Jordi; Puelles, Luis; Ferran, José Luis

2017-01-01

All vertebrate brains develop following a common Bauplan defined by anteroposterior (AP) and dorsoventral (DV) subdivisions, characterized by largely conserved differential expression of gene markers. However, it is still unclear how this Bauplan originated during evolution. We studied the relative expression of 48 genes with key roles in vertebrate neural patterning in a representative amphioxus embryonic stage. Unlike nonchordates, amphioxus develops its central nervous system (CNS) from a neural plate that is homologous to that of vertebrates, allowing direct topological comparisons. The resulting genoarchitectonic model revealed that the amphioxus incipient neural tube is unexpectedly complex, consisting of several AP and DV molecular partitions. Strikingly, comparison with vertebrates indicates that the vertebrate thalamus, pretectum, and midbrain domains jointly correspond to a single amphioxus region, which we termed Di-Mesencephalic primordium (DiMes). This suggests that these domains have a common developmental and evolutionary origin, as supported by functional experiments manipulating secondary organizers in zebrafish and mice. PMID:28422959

Brain Perfusion In Asphyxiated Newborns Treated with Therapeutic Hypothermia

PubMed Central

Wintermark, Pia; Hansen, Anne; Gregas, Matthew C.; Soul, Janet; Labrecque, Michelle; Robertson, Richard L.; Warfield, Simon K.

2012-01-01

Background and Purpose Induced hypothermia is thought to work partly by mitigating reperfusion injury in asphyxiated term newborns. The purpose of this study is to assess brain perfusion in the first week of life in these newborns. Patients and Methods In this prospective cohort study, magnetic resonance imaging (MRI) and perfusion imaging by arterial spin labeling (ASL-PI) was used to assess brain perfusion in these newborns. We measured regional cerebral blood flow values on 1–2 MRIs obtained during the first week of life and compared them to values obtained in control term newborns. The same or later MRI scans were obtained to define the extent of brain injury. Results Eighteen asphyxiated and four control term newborns were enrolled; eleven asphyxiated newborns were treated with hypothermia. Those developing brain injury despite being treated with induced hypothermia usually displayed hypoperfusion on day of life (DOL) 1, and then hyperperfusion on DOL 2–3 in brain areas subsequently exhibiting injury. Asphyxiated newborns not treated with hypothermia who developed brain injury also displayed hyperperfusion on DOL 1–6 in brain areas displaying injury. Conclusions Our data show that ASL-PI may be useful for identifying asphyxiated newborns at risk of developing brain injury, whether or not hypothermia is administered. Since hypothermia for 72 hours may not prevent brain injury when hyperperfusion is found early in the course of neonatal hypoxic-ischemic encephalopathy, such newborns may be candidates for adjustments in their hypothermia therapy or for adjunctive neuroprotective therapies. PMID:21979494

GRAPES—Grounding representations in action, perception, and emotion systems: How object properties and categories are represented in the human brain

PubMed Central

Martin, Alex

2016-01-01

In this article, I discuss some of the latest functional neuroimaging findings on the organization of object concepts in the human brain. I argue that these data provide strong support for viewing concepts as the products of highly interactive neural circuits grounded in the action, perception, and emotion systems. The nodes of these circuits are defined by regions representing specific object properties (e.g., form, color, and motion) and thus are property-specific, rather than strictly modality-specific. How these circuits are modified by external and internal environmental demands, the distinction between representational content and format, and the grounding of abstract social concepts are also discussed. PMID:25968087

Enc1 expression in the chick telencephalon at intermediate and late stages of development.

PubMed

García-Calero, Elena; Puelles, Luis

2009-12-10

In this work we studied the regional expression pattern of the Enc1 gene in the chick embryo telencephalon at intermediate and late stages of development, bearing on architectonic groupings and boundaries of current interest. In general, the Enc1 signal shows a markedly heterogeneous areal pattern of expression throughout the telencephalon; this corroborates data on new pallial and subpallial structures defined recently in the stereotaxic chick brain atlas of Puelles et al. (2007. The chick brain in stereotaxic coodinates. San Diego, CA: Academic Press). For example: a periventricular/central domain is Enc1-negative in the ventral pallium or nidopallium; core and shell nuclei appear in the mesopallium; the redefined caudodorsolateral area shows a characteristic pattern; the limits of the densocellular hyperpallium in the dorsal pallium are illuminated; and the postulated entorhinal cortex area is distinct at the posterior telencephalic pole. Interestingly, Enc1 transcripts are distinctly present in the piriform cortex at the surface of the ventral pallium throughout its longitudinal extent, as well as in the most rostral part of the lateral pallium, implying a layout of this cortex more similar to the situation in mammals than was assumed previously. Separate corticoid superficial strata are labeled by the Enc1 probe in the lateral and dorsal pallial regions. In the subpallium, the expression of Enc1 agrees with the new radial subdivisions defined by Puelles et al. (2007).

A Putative Multiple-Demand System in the Macaque Brain.

PubMed

Mitchell, Daniel J; Bell, Andrew H; Buckley, Mark J; Mitchell, Anna S; Sallet, Jerome; Duncan, John

2016-08-17

In humans, cognitively demanding tasks of many types recruit common frontoparietal brain areas. Pervasive activation of this "multiple-demand" (MD) network suggests a core function in supporting goal-oriented behavior. A similar network might therefore be predicted in nonhuman primates that readily perform similar tasks after training. However, an MD network in nonhuman primates has not been described. Single-cell recordings from macaque frontal and parietal cortex show some similar properties to human MD fMRI responses (e.g., adaptive coding of task-relevant information). Invasive recordings, however, come from limited prespecified locations, so they do not delineate a macaque homolog of the MD system and their positioning could benefit from knowledge of where MD foci lie. Challenges of scanning behaving animals mean that few macaque fMRI studies specifically contrast levels of cognitive demand, so we sought to identify a macaque counterpart to the human MD system using fMRI connectivity in 35 rhesus macaques. Putative macaque MD regions, mapped from frontoparietal MD regions defined in humans, were found to be functionally connected under anesthesia. To further refine these regions, an iterative process was used to maximize their connectivity cross-validated across animals. Finally, whole-brain connectivity analyses identified voxels that were robustly connected to MD regions, revealing seven clusters across frontoparietal and insular cortex comparable to human MD regions and one unexpected cluster in the lateral fissure. The proposed macaque MD regions can be used to guide future electrophysiological investigation of MD neural coding and in task-based fMRI to test predictions of similar functional properties to human MD cortex. In humans, a frontoparietal "multiple-demand" (MD) brain network is recruited during a wide range of cognitively demanding tasks. Because this suggests a fundamental function, one might expect a similar network to exist in nonhuman primates, but this remains controversial. Here, we sought to identify a macaque counterpart to the human MD system using fMRI connectivity. Putative macaque MD regions were functionally connected under anesthesia and were further refined by iterative optimization. The result is a network including lateral frontal, dorsomedial frontal, and insular and inferior parietal regions closely similar to the human counterpart. The proposed macaque MD regions can be useful in guiding electrophysiological recordings or in task-based fMRI to test predictions of similar functional properties to human MD cortex. Copyright © 2016 Mitchell et al.

Clinical NOE 13C MRS for neuropsychiatric disorders of the frontal lobe

NASA Astrophysics Data System (ADS)

Sailasuta, Napapon; Robertson, Larry W.; Harris, Kent C.; Gropman, Andrea L.; Allen, Peter S.; Ross, Brian D.

2008-12-01

In this communication, a scheme is described whereby in vivo 13C MRS can safely be performed in the frontal lobe, a human brain region hitherto precluded on grounds of SAR, but important in being the seat of impaired cognitive function in many neuropsychiatric and developmental disorders. By combining two well known features of 13C NMR—the use of low power NOE and the focus on 13C carbon atoms which are only minimally coupled to protons, we are able to overcome the obstacle of SAR and develop means of monitoring the 13C fluxes of critically important metabolic pathways in frontal brain structures of normal volunteers and patients. Using a combination of low-power WALTZ decoupling, variants of random noise for nuclear overhauser effect enhancement it was possible to reduce power deposition to 20% of the advised maximum specific absorption rate (SAR). In model solutions 13C signal enhancement achieved with this scheme were comparable to that obtained with WALTZ-4. In human brain, the low power procedure effectively determined glutamine, glutamate and bicarbonate in the posterior parietal brain after [1- 13C] glucose infusion. The same 13C enriched metabolites were defined in frontal brain of human volunteers after administration of [1- 13C] acetate, a recognized probe of glial metabolism. Time courses of incorporation of 13C into cerebral glutamate, glutamine and bicarbonate were constructed. The results suggest efficacy for measurement of in vivo cerebral metabolic rates of the glutamate-glutamine and tricarboxylic acid cycles in 20 min MR scans in previously inaccessible brain regions in humans at 1.5T. We predict these will be clinically useful biomarkers in many human neuropsychiatric and genetic conditions.

A computational study of whole-brain connectivity in resting state and task fMRI

PubMed Central

Goparaju, Balaji; Rana, Kunjan D.; Calabro, Finnegan J.; Vaina, Lucia Maria

2014-01-01

Background We compared the functional brain connectivity produced during resting-state in which subjects were not actively engaged in a task with that produced while they actively performed a visual motion task (task-state). Material/Methods In this paper we employed graph-theoretical measures and network statistics in novel ways to compare, in the same group of human subjects, functional brain connectivity during resting-state fMRI with brain connectivity during performance of a high level visual task. We performed a whole-brain connectivity analysis to compare network statistics in resting and task states among anatomically defined Brodmann areas to investigate how brain networks spanning the cortex changed when subjects were engaged in task performance. Results In the resting state, we found strong connectivity among the posterior cingulate cortex (PCC), precuneus, medial prefrontal cortex (MPFC), lateral parietal cortex, and hippocampal formation, consistent with previous reports of the default mode network (DMN). The connections among these areas were strengthened while subjects actively performed an event-related visual motion task, indicating a continued and strong engagement of the DMN during task processing. Regional measures such as degree (number of connections) and betweenness centrality (number of shortest paths), showed that task performance induces stronger inter-regional connections, leading to a denser processing network, but that this does not imply a more efficient system as shown by the integration measures such as path length and global efficiency, and from global measures such as small-worldness. Conclusions In spite of the maintenance of connectivity and the “hub-like” behavior of areas, our results suggest that the network paths may be rerouted when performing the task condition. PMID:24947491

Robust estimation of fractal measures for characterizing the structural complexity of the human brain: optimization and reproducibility

PubMed Central

Goñi, Joaquín; Sporns, Olaf; Cheng, Hu; Aznárez-Sanado, Maite; Wang, Yang; Josa, Santiago; Arrondo, Gonzalo; Mathews, Vincent P; Hummer, Tom A; Kronenberger, William G; Avena-Koenigsberger, Andrea; Saykin, Andrew J.; Pastor, María A.

2013-01-01

High-resolution isotropic three-dimensional reconstructions of human brain gray and white matter structures can be characterized to quantify aspects of their shape, volume and topological complexity. In particular, methods based on fractal analysis have been applied in neuroimaging studies to quantify the structural complexity of the brain in both healthy and impaired conditions. The usefulness of such measures for characterizing individual differences in brain structure critically depends on their within-subject reproducibility in order to allow the robust detection of between-subject differences. This study analyzes key analytic parameters of three fractal-based methods that rely on the box-counting algorithm with the aim to maximize within-subject reproducibility of the fractal characterizations of different brain objects, including the pial surface, the cortical ribbon volume, the white matter volume and the grey matter/white matter boundary. Two separate datasets originating from different imaging centers were analyzed, comprising, 50 subjects with three and 24 subjects with four successive scanning sessions per subject, respectively. The reproducibility of fractal measures was statistically assessed by computing their intra-class correlations. Results reveal differences between different fractal estimators and allow the identification of several parameters that are critical for high reproducibility. Highest reproducibility with intra-class correlations in the range of 0.9–0.95 is achieved with the correlation dimension. Further analyses of the fractal dimensions of parcellated cortical and subcortical gray matter regions suggest robustly estimated and region-specific patterns of individual variability. These results are valuable for defining appropriate parameter configurations when studying changes in fractal descriptors of human brain structure, for instance in studies of neurological diseases that do not allow repeated measurements or for disease-course longitudinal studies. PMID:23831414

Processing demands upon cognitive, linguistic, and articulatory functions promote grey matter plasticity in the adult multilingual brain: Insights from simultaneous interpreters.

PubMed

Elmer, Stefan; Hänggi, Jürgen; Jäncke, Lutz

2014-05-01

Until now, considerable effort has been made to determine structural brain characteristics related to exceptional multilingual skills. However, at least one important question has not yet been satisfactorily addressed in the previous literature, namely whether and to which extent the processing demands upon cognitive, linguistic, and articulatory functions may promote grey matter plasticity in the adult multilingual brain. Based on the premise that simultaneous interpretation is a highly demanding linguistic task that places strong demands on executive and articulatory functions, here we compared grey matter volumes between professional simultaneous interpreters (SI) and multilingual control subjects. Thereby, we focused on a specific set of a-priori defined bilateral brain regions that have previously been shown to support neurocognitional aspects of language control and linguistic functions in the multilingual brain. These regions are the cingulate gyrus, caudate nucleus, frontal operculum (pars triangularis and opercularis), inferior parietal lobe (IPL) (supramarginal and angular gyrus), and the insula. As a main result, we found reduced grey matter volumes in professional SI, compared to multilingual controls, in the left middle-anterior cingulate gyrus, bilateral pars triangularis, left pars opercularis, bilateral middle part of the insula, and in the left supramarginal gyrus (SMG). Interestingly, grey matter volume in left pars triangularis, right pars opercularis, middle-anterior cingulate gyrus, and in the bilateral caudate nucleus was negatively correlated with the cumulative number of interpreting hours. Hence, we provide first evidence for an expertise-related grey matter architecture that may reflect a composite of brain characteristics that were still present before interpreting training and training-related changes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Genetic and environmental influences on structural variability of the brain in pediatric twin: deformation based morphometry.

PubMed

Yoon, Uicheul; Perusse, Daniel; Lee, Jong-Min; Evans, Alan C

2011-04-08

Twin studies are one of the most powerful study designs for estimating the relative contribution of genetic and environmental influences on phenotypic variation inhuman brain morphology. In this study, we applied deformation based morphometry, a technique that provides a voxel-wise index of local tissue growth or atrophy relative to a template brain, combined with univariate ACE model, to investigate the genetic and environmental effects on the human brain structural variations in a cohort of homogeneously aged healthy pediatric twins. In addition, anatomical regions of interest (ROIs) were defined in order to explore global and regional genetic effects. ROI results showed that the influence of genetic factors on cerebrum (h(2)=0.70), total gray matter (0.67), and total white matter (0.73) volumes were significant. In particular, structural variability of left-side lobar volumes showed a significant heritability. Several subcortical structures such as putamen (h(ROI)(2)=0.79/0.77(L/R),h(MAX)(2)=0.82/0.79) and globus pallidus (0.81/0.76, 0.88/0.82) were also significantly heritable in both voxel-wise and ROI-based results. In the voxel-wise results, lateral parts of right cerebellum (c(2)=0.68) and the posterior portion of the corpus callosum (0.63) were rather environmentally determined, but it failed to reach statistical significance. Pediatric twin studies are important because they can discriminate several influences on developmental brain trajectories and identify relationships between gene and behavior. Several brain structures showed significant genetic effects and might therefore serve as biological markers for inherited traits, or as targets for genetic linkage and association studies. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Brain microstructural development at near-term age in very-low-birth-weight preterm infants: An atlas-based diffusion imaging study

PubMed Central

Rose, Jessica; Vassar, Rachel; Cahill-Rowley, Katelyn; Guzman, Ximena Stecher; Stevenson, David K.; Barnea-Goraly, Naama

2014-01-01

At near-term age the brain undergoes rapid growth and development. Abnormalities identified during this period have been recognized as potential predictors of neurodevelopment in children born preterm. This study used diffusion tensor imaging (DTI) to examine white matter (WM) microstructure in very-low-birth-weight (VLBW) preterm infants to better understand regional WM developmental trajectories at near-term age. DTI scans were analyzed in a cross-sectional sample of 45 VLBW preterm infants (BW ≤ 1500 g, GA ≤ 32 weeks) within a cohort of 102 neonates admitted to the NICU and recruited to participate prior to standard-of-care MRI, from 2010 to 2011, 66/102 also had DTI. For inclusion in this analysis, 45 infants had DTI, no evidence of brain abnormality on MRI, and were scanned at PMA ≤40 weeks (34.7–38.6). White matter microstructure was analyzed in 19 subcortical regions defined by DiffeoMap neonatal brain atlas, using threshold values of trace b0.006 mm2 s−1 and FA >0.15. Regional fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated and temporal–spatial trajectories of development were examined in relation to PMA and brain region location. Posterior regions within the corona radiata (CR), corpus callosum (CC), and internal capsule (IC) demonstrated significantly higher mean FA values compared to anterior regions. Posterior regions of the CR and IC demonstrated significantly lower RD values compared to anterior regions. Centrally located projection fibers demonstrated higher mean FA and lower RD values than peripheral regions including the posterior limb of the internal capsule (PLIC), cerebral peduncle, retrolenticular part of the IC, posterior thalamic radiation, and sagittal stratum. Centrally located association fibers of the external capsule had higher FA and lower RD than the more peripherally-located superior longitudinal fasciculus (SLF). A significant relationship between PMA-at-scan and FA, MD, and RD was demonstrated by a majority of regions, the strongest correlations were observed in the anterior limb of the internal capsule, a region undergoing early stages of myelination at near-term age, in which FA increased (r = .433, p = .003) and MD (r = –.545, p = .000) and RD (r = –.540, p = .000) decreased with PMA-at-scan. No correlation with PMA-at-scan was observed in the CC or SLF, regions that myelinate later in infancy. Regional patterns of higher FA and lower RD were observed at this near-term age, suggestive of more advanced microstructural development in posterior compared to anterior regions within the CR, CC, and IC and in central compared to peripheral WM structures. Evidence of region-specific rates of microstructural development was observed. Temporal–spatial patterns of WM microstructure development at near-term age have important implications for interpretation of near-term DTI and for identification of aberrations in typical developmental trajectories that may signal future impairment. PMID:24091089

Brain microstructural development at near-term age in very-low-birth-weight preterm infants: an atlas-based diffusion imaging study.

PubMed

Rose, Jessica; Vassar, Rachel; Cahill-Rowley, Katelyn; Guzman, Ximena Stecher; Stevenson, David K; Barnea-Goraly, Naama

2014-02-01

At near-term age the brain undergoes rapid growth and development. Abnormalities identified during this period have been recognized as potential predictors of neurodevelopment in children born preterm. This study used diffusion tensor imaging (DTI) to examine white matter (WM) microstructure in very-low-birth-weight (VLBW) preterm infants to better understand regional WM developmental trajectories at near-term age. DTI scans were analyzed in a cross-sectional sample of 45 VLBW preterm infants (BW≤1500g, GA≤32weeks) within a cohort of 102 neonates admitted to the NICU and recruited to participate prior to standard-of-care MRI, from 2010 to 2011, 66/102 also had DTI. For inclusion in this analysis, 45 infants had DTI, no evidence of brain abnormality on MRI, and were scanned at PMA ≤40weeks (34.7-38.6). White matter microstructure was analyzed in 19 subcortical regions defined by DiffeoMap neonatal brain atlas, using threshold values of trace <0.006mm(2)s(-1) and FA >0.15. Regional fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated and temporal-spatial trajectories of development were examined in relation to PMA and brain region location. Posterior regions within the corona radiata (CR), corpus callosum (CC), and internal capsule (IC) demonstrated significantly higher mean FA values compared to anterior regions. Posterior regions of the CR and IC demonstrated significantly lower RD values compared to anterior regions. Centrally located projection fibers demonstrated higher mean FA and lower RD values than peripheral regions including the posterior limb of the internal capsule (PLIC), cerebral peduncle, retrolenticular part of the IC, posterior thalamic radiation, and sagittal stratum. Centrally located association fibers of the external capsule had higher FA and lower RD than the more peripherally-located superior longitudinal fasciculus (SLF). A significant relationship between PMA-at-scan and FA, MD, and RD was demonstrated by a majority of regions, the strongest correlations were observed in the anterior limb of the internal capsule, a region undergoing early stages of myelination at near-term age, in which FA increased (r=.433, p=.003) and MD (r=-.545, p=.000) and RD (r=-.540, p=.000) decreased with PMA-at-scan. No correlation with PMA-at-scan was observed in the CC or SLF, regions that myelinate later in infancy. Regional patterns of higher FA and lower RD were observed at this near-term age, suggestive of more advanced microstructural development in posterior compared to anterior regions within the CR, CC, and IC and in central compared to peripheral WM structures. Evidence of region-specific rates of microstructural development was observed. Temporal-spatial patterns of WM microstructure development at near-term age have important implications for interpretation of near-term DTI and for identification of aberrations in typical developmental trajectories that may signal future impairment. © 2013.

Defining an Analytic Framework to Evaluate Quantitative MRI Markers of Traumatic Axonal Injury: Preliminary Results in a Mouse Closed Head Injury Model

PubMed Central

Sadeghi, N.; Namjoshi, D.; Irfanoglu, M. O.; Wellington, C.; Diaz-Arrastia, R.

2017-01-01

Diffuse axonal injury (DAI) is a hallmark of traumatic brain injury (TBI) pathology. Recently, the Closed Head Injury Model of Engineered Rotational Acceleration (CHIMERA) was developed to generate an experimental model of DAI in a mouse. The characterization of DAI using diffusion tensor magnetic resonance imaging (MRI; diffusion tensor imaging, DTI) may provide a useful set of outcome measures for preclinical and clinical studies. The objective of this study was to identify the complex neurobiological underpinnings of DTI features following DAI using a comprehensive and quantitative evaluation of DTI and histopathology in the CHIMERA mouse model. A consistent neuroanatomical pattern of pathology in specific white matter tracts was identified across ex vivo DTI maps and photomicrographs of histology. These observations were confirmed by voxelwise and regional analysis of DTI maps, demonstrating reduced fractional anisotropy (FA) in distinct regions such as the optic tract. Similar regions were identified by quantitative histology and exhibited axonal damage as well as robust gliosis. Additional analysis using a machine-learning algorithm was performed to identify regions and metrics important for injury classification in a manner free from potential user bias. This analysis found that diffusion metrics were able to identify injured brains almost with the same degree of accuracy as the histology metrics. Good agreement between regions detected as abnormal by histology and MRI was also found. The findings of this work elucidate the complexity of cellular changes that give rise to imaging abnormalities and provide a comprehensive and quantitative evaluation of the relative importance of DTI and histological measures to detect brain injury. PMID:28966972

Decoding complex flow-field patterns in visual working memory.

PubMed

Christophel, Thomas B; Haynes, John-Dylan

2014-05-01

There has been a long history of research on visual working memory. Whereas early studies have focused on the role of lateral prefrontal cortex in the storage of sensory information, this has been challenged by research in humans that has directly assessed the encoding of perceptual contents, pointing towards a role of visual and parietal regions during storage. In a previous study we used pattern classification to investigate the storage of complex visual color patterns across delay periods. This revealed coding of such contents in early visual and parietal brain regions. Here we aim to investigate whether the involvement of visual and parietal cortex is also observable for other types of complex, visuo-spatial pattern stimuli. Specifically, we used a combination of fMRI and multivariate classification to investigate the retention of complex flow-field stimuli defined by the spatial patterning of motion trajectories of random dots. Subjects were trained to memorize the precise spatial layout of these stimuli and to retain this information during an extended delay. We used a multivariate decoding approach to identify brain regions where spatial patterns of activity encoded the memorized stimuli. Content-specific memory signals were observable in motion sensitive visual area MT+ and in posterior parietal cortex that might encode spatial information in a modality independent manner. Interestingly, we also found information about the memorized visual stimulus in somatosensory cortex, suggesting a potential crossmodal contribution to memory. Our findings thus indicate that working memory storage of visual percepts might be distributed across unimodal, multimodal and even crossmodal brain regions. Copyright © 2014 Elsevier Inc. All rights reserved.

Virtual Milgram: Empathic Concern or Personal Distress? Evidence from Functional MRI and Dispositional Measures

PubMed Central

Cheetham, Marcus; Pedroni, Andreas F.; Antley, Angus; Slater, Mel; Jäncke, Lutz

2009-01-01

One motive for behaving as the agent of another's aggression appears to be anchored in as yet unelucidated mechanisms of obedience to authority. In a recent partial replication of Milgram's obedience paradigm within an immersive virtual environment, participants administered pain to a female virtual human and observed her suffering. Whether the participants’ response to the latter was more akin to other-oriented empathic concern for her well-being or to a self-oriented aversive state of personal distress in response to her distress is unclear. Using the stimuli from that study, this event-related fMRI-based study analysed brain activity during observation of the victim in pain versus not in pain. This contrast revealed activation in pre-defined brain areas known to be involved in affective processing but not in those commonly associated with affect sharing (e.g., ACC and insula). We then examined whether different dimensions of dispositional empathy predict activity within the same pre-defined brain regions: While personal distress and fantasy (i.e., tendency to transpose oneself into fictional situations and characters) predicted brain activity, empathic concern and perspective taking predicted no change in neuronal response associated with pain observation. These exploratory findings suggest that there is a distinct pattern of brain activity associated with observing the pain-related behaviour of the victim within the context of this social dilemma, that this observation evoked a self-oriented aversive state of personal distress, and that the objective “reality” of pain is of secondary importance for this response. These findings provide a starting point for experimentally more rigorous investigation of obedience. PMID:19876407

NeuroNames: an ontology for the BrainInfo portal to neuroscience on the web.

PubMed

Bowden, Douglas M; Song, Evan; Kosheleva, Julia; Dubach, Mark F

2012-01-01

BrainInfo ( http://braininfo.org ) is a growing portal to neuroscientific information on the Web. It is indexed by NeuroNames, an ontology designed to compensate for ambiguities in neuroanatomical nomenclature. The 20-year old ontology continues to evolve toward the ideal of recognizing all names of neuroanatomical entities and accommodating all structural concepts about which neuroscientists communicate, including multiple concepts of entities for which neuroanatomists have yet to determine the best or 'true' conceptualization. To make the definitions of structural concepts unambiguous and terminologically consistent we created a 'default vocabulary' of unique structure names selected from existing terminology. We selected standard names by criteria designed to maximize practicality for use in verbal communication as well as computerized knowledge management. The ontology of NeuroNames accommodates synonyms and homonyms of the standard terms in many languages. It defines complex structures as models composed of primary structures, which are defined in unambiguous operational terms. NeuroNames currently relates more than 16,000 names in eight languages to some 2,500 neuroanatomical concepts. The ontology is maintained in a relational database with three core tables: Names, Concepts and Models. BrainInfo uses NeuroNames to index information by structure, to interpret users' queries and to clarify terminology on remote web pages. NeuroNames is a resource vocabulary of the NLM's Unified Medical Language System (UMLS, 2011) and the basis for the brain regions component of NIFSTD (NeuroLex, 2011). The current version has been downloaded to hundreds of laboratories for indexing data and linking to BrainInfo, which attracts some 400 visitors/day, downloading 2,000 pages/day.

Brain lactate responses during visual stimulation in fasting and hyperglycemic subjects: a proton magnetic resonance spectroscopy study at 1.5 Tesla.

PubMed

Maddock, Richard J; Buonocore, Michael H; Lavoie, Shawn P; Copeland, Linda E; Kile, Shawn J; Richards, Anne L; Ryan, John M

2006-11-22

Proton magnetic resonance spectroscopy ((1)H-MRS) studies showing increased lactate during neural activation support a broader role for lactate in brain energy metabolism than was traditionally recognized. Proton MRS measures of brain lactate responses have been used to study regional brain metabolism in clinical populations. This study examined whether variations in blood glucose influence the lactate response to visual stimulation in the visual cortex. Six subjects were scanned twice, receiving either saline or 21% glucose intravenously. Using (1)H-MRS at 1.5 Tesla with a long echo time (TE=288 ms), the lactate doublet was visible at 1.32 ppm in the visual cortex of all subjects. Lactate increased significantly from resting to visual stimulation. Hyperglycemia had no effect on this increase. The order of the slice-selective gradients for defining the spectroscopy voxel had a pronounced effect on the extent of contamination by signal originating outside the voxel. The results of this preliminary study demonstrate a method for observing a consistent activity-stimulated increase in brain lactate at 1.5 T and show that variations in blood glucose across the normal range have little effect on this response.

Defining Optimal Brain Health in Adults: A Presidential Advisory From the American Heart Association/American Stroke Association.

PubMed

Gorelick, Philip B; Furie, Karen L; Iadecola, Costantino; Smith, Eric E; Waddy, Salina P; Lloyd-Jones, Donald M; Bae, Hee-Joon; Bauman, Mary Ann; Dichgans, Martin; Duncan, Pamela W; Girgus, Meighan; Howard, Virginia J; Lazar, Ronald M; Seshadri, Sudha; Testai, Fernando D; van Gaal, Stephen; Yaffe, Kristine; Wasiak, Hank; Zerna, Charlotte

2017-10-01

Cognitive function is an important component of aging and predicts quality of life, functional independence, and risk of institutionalization. Advances in our understanding of the role of cardiovascular risks have shown them to be closely associated with cognitive impairment and dementia. Because many cardiovascular risks are modifiable, it may be possible to maintain brain health and to prevent dementia in later life. The purpose of this American Heart Association (AHA)/American Stroke Association presidential advisory is to provide an initial definition of optimal brain health in adults and guidance on how to maintain brain health. We identify metrics to define optimal brain health in adults based on inclusion of factors that could be measured, monitored, and modified. From these practical considerations, we identified 7 metrics to define optimal brain health in adults that originated from AHA's Life's Simple 7: 4 ideal health behaviors (nonsmoking, physical activity at goal levels, healthy diet consistent with current guideline levels, and body mass index <25 kg/m 2 ) and 3 ideal health factors (untreated blood pressure <120/<80 mm Hg, untreated total cholesterol <200 mg/dL, and fasting blood glucose <100 mg/dL). In addition, in relation to maintenance of cognitive health, we recommend following previously published guidance from the AHA/American Stroke Association, Institute of Medicine, and Alzheimer's Association that incorporates control of cardiovascular risks and suggest social engagement and other related strategies. We define optimal brain health but recognize that the truly ideal circumstance may be uncommon because there is a continuum of brain health as demonstrated by AHA's Life's Simple 7. Therefore, there is opportunity to improve brain health through primordial prevention and other interventions. Furthermore, although cardiovascular risks align well with brain health, we acknowledge that other factors differing from those related to cardiovascular health may drive cognitive health. Defining optimal brain health in adults and its maintenance is consistent with the AHA's Strategic Impact Goal to improve cardiovascular health of all Americans by 20% and to reduce deaths resulting from cardiovascular disease and stroke by 20% by the year 2020. This work in defining optimal brain health in adults serves to provide the AHA/American Stroke Association with a foundation for a new strategic direction going forward in cardiovascular health promotion and disease prevention. © 2017 American Heart Association, Inc.

Defining Optimal Brain Health in Adults

PubMed Central

Gorelick, Philip B.; Furie, Karen L.; Iadecola, Costantino; Smith, Eric E.; Waddy, Salina P.; Lloyd-Jones, Donald M.; Bae, Hee-Joon; Bauman, Mary Ann; Dichgans, Martin; Duncan, Pamela W.; Girgus, Meighan; Howard, Virginia J.; Lazar, Ronald M.; Seshadri, Sudha; Testai, Fernando D.; van Gaal, Stephen; Yaffe, Kristine; Wasiak, Hank; Zerna, Charlotte

2017-01-01

Cognitive function is an important component of aging and predicts quality of life, functional independence, and risk of institutionalization. Advances in our understanding of the role of cardiovascular risks have shown them to be closely associated with cognitive impairment and dementia. Because many cardiovascular risks are modifiable, it may be possible to maintain brain health and to prevent dementia in later life. The purpose of this American Heart Association (AHA)/American Stroke Association presidential advisory is to provide an initial definition of optimal brain health in adults and guidance on how to maintain brain health. We identify metrics to define optimal brain health in adults based on inclusion of factors that could be measured, monitored, and modified. From these practical considerations, we identified 7 metrics to define optimal brain health in adults that originated from AHA’s Life’s Simple 7: 4 ideal health behaviors (nonsmoking, physical activity at goal levels, healthy diet consistent with current guideline levels, and body mass index <25 kg/m2) and 3 ideal health factors (untreated blood pressure <120/<80 mm Hg, untreated total cholesterol <200 mg/dL, and fasting blood glucose <100 mg/dL). In addition, in relation to maintenance of cognitive health, we recommend following previously published guidance from the AHA/American Stroke Association, Institute of Medicine, and Alzheimer’s Association that incorporates control of cardiovascular risks and suggest social engagement and other related strategies. We define optimal brain health but recognize that the truly ideal circumstance may be uncommon because there is a continuum of brain health as demonstrated by AHA’s Life’s Simple 7. Therefore, there is opportunity to improve brain health through primordial prevention and other interventions. Furthermore, although cardiovascular risks align well with brain health, we acknowledge that other factors differing from those related to cardiovascular health may drive cognitive health. Defining optimal brain health in adults and its maintenance is consistent with the AHA’s Strategic Impact Goal to improve cardiovascular health of all Americans by 20% and to reduce deaths resulting from cardiovascular disease and stroke by 20% by the year 2020. This work in defining optimal brain health in adults serves to provide the AHA/American Stroke Association with a foundation for a new strategic direction going forward in cardiovascular health promotion and disease prevention. PMID:28883125

Improving resolution of dynamic communities in human brain networks through targeted node removal

PubMed Central

Turner, Benjamin O.; Miller, Michael B.; Carlson, Jean M.

2017-01-01

Current approaches to dynamic community detection in complex networks can fail to identify multi-scale community structure, or to resolve key features of community dynamics. We propose a targeted node removal technique to improve the resolution of community detection. Using synthetic oscillator networks with well-defined “ground truth” communities, we quantify the community detection performance of a common modularity maximization algorithm. We show that the performance of the algorithm on communities of a given size deteriorates when these communities are embedded in multi-scale networks with communities of different sizes, compared to the performance in a single-scale network. We demonstrate that targeted node removal during community detection improves performance on multi-scale networks, particularly when removing the most functionally cohesive nodes. Applying this approach to network neuroscience, we compare dynamic functional brain networks derived from fMRI data taken during both repetitive single-task and varied multi-task experiments. After the removal of regions in visual cortex, the most coherent functional brain area during the tasks, community detection is better able to resolve known functional brain systems into communities. In addition, node removal enables the algorithm to distinguish clear differences in brain network dynamics between these experiments, revealing task-switching behavior that was not identified with the visual regions present in the network. These results indicate that targeted node removal can improve spatial and temporal resolution in community detection, and they demonstrate a promising approach for comparison of network dynamics between neuroscientific data sets with different resolution parameters. PMID:29261662

Lack of sex effect on brain activity during a visuomotor response task: functional MR imaging study.

PubMed

Mikhelashvili-Browner, Nina; Yousem, David M; Wu, Colin; Kraut, Michael A; Vaughan, Christina L; Oguz, Kader Karli; Calhoun, Vince D

2003-03-01

As more individuals are enrolled in clinical functional MR imaging (fMRI) studies, an understanding of how sex may influence fMRI-measured brain activation is critical. We used fixed- and random-effects models to study the influence of sex on fMRI patterns of brain activation during a simple visuomotor reaction time task in the group of 26 age-matched men and women. We evaluated the right visual, left visual, left primary motor, left supplementary motor, and left anterior cingulate areas. Volumes of activations did not significantly differ between the groups in any defined regions. Analysis of variance failed to show any significant correlations between sex and volumes of brain activation in any location studied. Mean percentage signal-intensity changes for all locations were similar between men and women. A two-way t test of brain activation in men and women, performed as a part of random-effects modeling, showed no significant difference at any site. Our results suggest that sex seems to have little influence on fMRI brain activation when we compared performance on the simple reaction-time task. The need to control for sex effects is not critical in the analysis of this task with fMRI.

Brain mechanisms of successful recognition through retrieval of semantic context.

PubMed

Flegal, Kristin E; Marín-Gutiérrez, Alejandro; Ragland, J Daniel; Ranganath, Charan

2014-08-01

Episodic memory is associated with the encoding and retrieval of context information and with a subjective sense of reexperiencing past events. The neural correlates of episodic retrieval have been extensively studied using fMRI, leading to the identification of a "general recollection network" including medial temporal, parietal, and prefrontal regions. However, in these studies, it is difficult to disentangle the effects of context retrieval from recollection. In this study, we used fMRI to determine the extent to which the recruitment of regions in the recollection network is contingent on context reinstatement. Participants were scanned during a cued recognition test for target words from encoded sentences. Studied target words were preceded by either a cue word studied in the same sentence (thus congruent with encoding context) or a cue word studied in a different sentence (thus incongruent with encoding context). Converging fMRI results from independently defined ROIs and whole-brain analysis showed regional specificity in the recollection network. Activity in hippocampus and parahippocampal cortex was specifically increased during successful retrieval following congruent context cues, whereas parietal and prefrontal components of the general recollection network were associated with confident retrieval irrespective of contextual congruency. Our findings implicate medial temporal regions in the retrieval of semantic context, contributing to, but dissociable from, recollective experience.

The Representation of Object-Directed Action and Function Knowledge in the Human Brain

PubMed Central

Chen, Quanjing; Garcea, Frank E.; Mahon, Bradford Z.

2016-01-01

The appropriate use of everyday objects requires the integration of action and function knowledge. Previous research suggests that action knowledge is represented in frontoparietal areas while function knowledge is represented in temporal lobe regions. Here we used multivoxel pattern analysis to investigate the representation of object-directed action and function knowledge while participants executed pantomimes of familiar tool actions. A novel approach for decoding object knowledge was used in which classifiers were trained on one pair of objects and then tested on a distinct pair; this permitted a measurement of classification accuracy over and above object-specific information. Region of interest (ROI) analyses showed that object-directed actions could be decoded in tool-preferring regions of both parietal and temporal cortex, while no independently defined tool-preferring ROI showed successful decoding of object function. However, a whole-brain searchlight analysis revealed that while frontoparietal motor and peri-motor regions are engaged in the representation of object-directed actions, medial temporal lobe areas in the left hemisphere are involved in the representation of function knowledge. These results indicate that both action and function knowledge are represented in a topographically coherent manner that is amenable to study with multivariate approaches, and that the left medial temporal cortex represents knowledge of object function. PMID:25595179

Association between sociability and diffusion tensor imaging in BALB/cJ mice.

PubMed

Kim, Sungheon; Pickup, Stephen; Fairless, Andrew H; Ittyerah, Ranjit; Dow, Holly C; Abel, Ted; Brodkin, Edward S; Poptani, Harish

2012-01-01

The purpose of this study was to use high-resolution diffusion tensor imaging (DTI) to investigate the association between DTI metrics and sociability in BALB/c inbred mice. The sociability of prepubescent (30-day-old) BALB/cJ mice was operationally defined as the time that the mice spent sniffing a stimulus mouse in a social choice test. High-resolution ex vivo DTI data on 12 BALB/cJ mouse brains were acquired using a 9.4-T vertical-bore magnet. Regression analysis was conducted to investigate the association between DTI metrics and sociability. Significant positive regression (p < 0.001) between social sniffing time and fractional anisotropy was found in 10 regions located in the thalamic nuclei, zona incerta/substantia nigra, visual/orbital/somatosensory cortices and entorhinal cortex. In addition, significant negative regression (p < 0.001) between social sniffing time and mean diffusivity was found in five areas located in the sensory cortex, motor cortex, external capsule and amygdaloid region. In all regions showing significant regression with either the mean diffusivity or fractional anisotropy, the tertiary eigenvalue correlated negatively with the social sniffing time. This study demonstrates the feasibility of using DTI to detect brain regions associated with sociability in a mouse model system. Copyright © 2011 John Wiley & Sons, Ltd.

Information processing architecture of functionally defined clusters in the macaque cortex.

PubMed

Shen, Kelly; Bezgin, Gleb; Hutchison, R Matthew; Gati, Joseph S; Menon, Ravi S; Everling, Stefan; McIntosh, Anthony R

2012-11-28

Computational and empirical neuroimaging studies have suggested that the anatomical connections between brain regions primarily constrain their functional interactions. Given that the large-scale organization of functional networks is determined by the temporal relationships between brain regions, the structural limitations may extend to the global characteristics of functional networks. Here, we explored the extent to which the functional network community structure is determined by the underlying anatomical architecture. We directly compared macaque (Macaca fascicularis) functional connectivity (FC) assessed using spontaneous blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI) to directed anatomical connectivity derived from macaque axonal tract tracing studies. Consistent with previous reports, FC increased with increasing strength of anatomical connection, and FC was also present between regions that had no direct anatomical connection. We observed moderate similarity between the FC of each region and its anatomical connectivity. Notably, anatomical connectivity patterns, as described by structural motifs, were different within and across functional modules: partitioning of the functional network was supported by dense bidirectional anatomical connections within clusters and unidirectional connections between clusters. Together, our data directly demonstrate that the FC patterns observed in resting-state BOLD-fMRI are dictated by the underlying neuroanatomical architecture. Importantly, we show how this architecture contributes to the global organizational principles of both functional specialization and integration.

Is synaptic loss a unique hallmark of Alzheimer's disease?

PubMed Central

Scheff, Stephen W.; Neltner, Janna H.; Nelson, Peter T.

2014-01-01

Synapses may represent a key nidus for dementia including Alzheimer's disease (AD) pathogenesis. Here we review published studies and present new ideas related to the question of the specificity of synapse loss in AD. Currently, AD is defined by the regional presence of neuritic plaques and neurofibrillary tangles in the brain. The severity of involvement by those pathological hallmarks tends to correlate both with antemortem cognitive status, and also with synapse loss in multiple brain areas. Recent studies from large autopsy series have led to a new standard of excellence with regard to clinical–pathological correlation and to improved comprehension of the numerous brain diseases of the elderly. These studies have provided evidence that it is the rule rather than the exception for brains of aged individuals to demonstrate pathologies (often multiple) other than AD plaques and tangles. For many of these comorbid pathologies, the extent of synapse loss is imperfectly understood but could be substantial. These findings indicate that synapse loss is probably not a hallmark specific to AD but rather a change common to many diseases associated with dementia. PMID:24412275

Brain Modularity Mediates the Relation between Task Complexity and Performance

NASA Astrophysics Data System (ADS)

Ye, Fengdan; Yue, Qiuhai; Martin, Randi; Fischer-Baum, Simon; Ramos-Nuã+/-Ez, Aurora; Deem, Michael

Recent work in cognitive neuroscience has focused on analyzing the brain as a network, rather than a collection of independent regions. Prior studies taking this approach have found that individual differences in the degree of modularity of the brain network relate to performance on cognitive tasks. However, inconsistent results concerning the direction of this relationship have been obtained, with some tasks showing better performance as modularity increases, and other tasks showing worse performance. A recent theoretical model suggests that these inconsistencies may be explained on the grounds that high-modularity networks favor performance on simple tasks whereas low-modularity networks favor performance on complex tasks. The current study tests these predictions by relating modularity from resting-state fMRI to performance on a set of behavioral tasks. Complex and simple tasks were defined on the basis of whether they drew on executive attention. Consistent with predictions, we found a negative correlation between individuals' modularity and their performance on the complex tasks but a positive correlation with performance on the simple tasks. The results presented here provide a framework for linking measures of whole brain organization to cognitive processing.

Insulin Resistance as a Link between Amyloid-Beta and Tau Pathologies in Alzheimer’s Disease

PubMed Central

Mullins, Roger J.; Diehl, Thomas C.; Chia, Chee W.; Kapogiannis, Dimitrios

2017-01-01

Current hypotheses and theories regarding the pathogenesis of Alzheimer’s disease (AD) heavily implicate brain insulin resistance (IR) as a key factor. Despite the many well-validated metrics for systemic IR, the absence of biomarkers for brain-specific IR represents a translational gap that has hindered its study in living humans. In our lab, we have been working to develop biomarkers that reflect the common mechanisms of brain IR and AD that may be used to follow their engagement by experimental treatments. We present two promising biomarkers for brain IR in AD: insulin cascade mediators probed in extracellular vesicles (EVs) enriched for neuronal origin, and two-dimensional magnetic resonance spectroscopy (MRS) measures of brain glucose. As further evidence for a fundamental link between brain IR and AD, we provide a novel analysis demonstrating the close spatial correlation between brain expression of genes implicated in IR (using Allen Human Brain Atlas data) and tau and beta-amyloid pathologies. We proceed to propose the bold hypotheses that baseline differences in the metabolic reliance on glycolysis, and the expression of glucose transporters (GLUT) and insulin signaling genes determine the vulnerability of different brain regions to Tau and/or Amyloid beta (Aβ) pathology, and that IR is a critical link between these two pathologies that define AD. Lastly, we provide an overview of ongoing clinical trials that target IR as an angle to treat AD, and suggest how biomarkers may be used to evaluate treatment efficacy and target engagement. PMID:28515688

High Spatial Resolution Imaging Mass Spectrometry of Human Optic Nerve Lipids and Proteins

NASA Astrophysics Data System (ADS)

Anderson, David M. G.; Spraggins, Jeffrey M.; Rose, Kristie L.; Schey, Kevin L.

2015-06-01

The human optic nerve carries signals from the retina to the visual cortex of the brain. Each optic nerve is comprised of approximately one million nerve fibers that are organized into bundles of 800-1200 fibers surrounded by connective tissue and supportive glial cells. Damage to the optic nerve contributes to a number of blinding diseases including: glaucoma, neuromyelitis optica, optic neuritis, and neurofibromatosis; however, the molecular mechanisms of optic nerve damage and death are incompletely understood. Herein we present high spatial resolution MALDI imaging mass spectrometry (IMS) analysis of lipids and proteins to define the molecular anatomy of the human optic nerve. The localization of a number of lipids was observed in discrete anatomical regions corresponding to myelinated and unmyelinated nerve regions as well as to supporting connective tissue, glial cells, and blood vessels. A protein fragment from vimentin, a known intermediate filament marker for astrocytes, was observed surrounding nerved fiber bundles in the lamina cribrosa region. S100B was also found in supporting glial cell regions in the prelaminar region, and the hemoglobin alpha subunit was observed in blood vessel areas. The molecular anatomy of the optic nerve defined by MALDI IMS provides a firm foundation to study biochemical changes in blinding human diseases.

Functional Language Shift to the Right Hemisphere in Patients with Language-Eloquent Brain Tumors

PubMed Central

Krieg, Sandro M.; Sollmann, Nico; Hauck, Theresa; Ille, Sebastian; Foerschler, Annette; Meyer, Bernhard; Ringel, Florian

2013-01-01

Objectives Language function is mainly located within the left hemisphere of the brain, especially in right-handed subjects. However, functional MRI (fMRI) has demonstrated changes of language organization in patients with left-sided perisylvian lesions to the right hemisphere. Because intracerebral lesions can impair fMRI, this study was designed to investigate human language plasticity with a virtual lesion model using repetitive navigated transcranial magnetic stimulation (rTMS). Experimental design Fifteen patients with lesions of left-sided language-eloquent brain areas and 50 healthy and purely right-handed participants underwent bilateral rTMS language mapping via an object-naming task. All patients were proven to have left-sided language function during awake surgery. The rTMS-induced language errors were categorized into 6 different error types. The error ratio (induced errors/number of stimulations) was determined for each brain region on both hemispheres. A hemispheric dominance ratio was then defined for each region as the quotient of the error ratio (left/right) of the corresponding area of both hemispheres (ratio >1  =  left dominant; ratio <1  =  right dominant). Results Patients with language-eloquent lesions showed a statistically significantly lower ratio than healthy participants concerning “all errors” and “all errors without hesitations”, which indicates a higher participation of the right hemisphere in language function. Yet, there was no cortical region with pronounced difference in language dominance compared to the whole hemisphere. Conclusions This is the first study that shows by means of an anatomically accurate virtual lesion model that a shift of language function to the non-dominant hemisphere can occur. PMID:24069410

Neural connectivity of the anterior body of the fornix in the human brain: diffusion tensor imaging study.

PubMed

Jang, Sung Ho; Kwon, Hyeok Gyu

2014-01-24

A few studies have reported on the neural connectivity of the fornix in the human brain, however, little is known about the neural connectivity of the anterior body of the fornix. In this study, we used diffusion tensor imaging in investigation of the neural connectivity of the anterior body of the fornix in normal subjects. Forty healthy subjects were recruited for this study. A seed region of interest was placed on the anterior body of the fornix using the FMRIB Software Library. Connectivity was defined as the incidence of connection between the anterior body of the fornix and any neural structure of the brain at the threshold of 5, 25, and 50 streamlines. In all subjects, the anterior body of the fornix showed 100% connectivity to the anterior commissure and hypothalamus at thresholds of 5, 25, and 50. On the other hand, regarding the thresholds of 5, 25, and 50, the anterior body of the fornix showed connectivity to the septal forebrain region (53.8, 23.8, and 15.0%), frontal lobe via anterior commissure (41.3,12.5, and 10.0%), medial temporal lobe (85.0,66.3, and 62.5%), lateral temporal lobe (75.0, 56.3, and 35.0%), occipital lobe (21.3, 5.0, and 1.3%), frontal lobe via septum pellucidum (28.8, 13.8, and 8.8%), tegmentum of midbrain (7.5, 5.0, and 0%), tectum of midbrain (2.5,0, and 0%), and tegmentum of pons (5.0,0, and 0%). The anterior body of the fornix showed high connectivity with the anterior commissure and hypothalamus, and brain areas relevant to cholinergic nuclei (the septal forebrain region and brainstem) and memory function (the medial temporal lobe). Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Relationship between neuronal network architecture and naming performance in temporal lobe epilepsy: A connectome based approach using machine learning.

PubMed

Munsell, B C; Wu, G; Fridriksson, J; Thayer, K; Mofrad, N; Desisto, N; Shen, D; Bonilha, L

2017-09-09

Impaired confrontation naming is a common symptom of temporal lobe epilepsy (TLE). The neurobiological mechanisms underlying this impairment are poorly understood but may indicate a structural disorganization of broadly distributed neuronal networks that support naming ability. Importantly, naming is frequently impaired in other neurological disorders and by contrasting the neuronal structures supporting naming in TLE with other diseases, it will become possible to elucidate the common systems supporting naming. We aimed to evaluate the neuronal networks that support naming in TLE by using a machine learning algorithm intended to predict naming performance in subjects with medication refractory TLE using only the structural brain connectome reconstructed from diffusion tensor imaging. A connectome-based prediction framework was developed using network properties from anatomically defined brain regions across the entire brain, which were used in a multi-task machine learning algorithm followed by support vector regression. Nodal eigenvector centrality, a measure of regional network integration, predicted approximately 60% of the variance in naming. The nodes with the highest regression weight were bilaterally distributed among perilimbic sub-networks involving mainly the medial and lateral temporal lobe regions. In the context of emerging evidence regarding the role of large structural networks that support language processing, our results suggest intact naming relies on the integration of sub-networks, as opposed to being dependent on isolated brain areas. In the case of TLE, these sub-networks may be disproportionately indicative naming processes that are dependent semantic integration from memory and lexical retrieval, as opposed to multi-modal perception or motor speech production. Copyright © 2017. Published by Elsevier Inc.

Low-frequency connectivity is associated with mild traumatic brain injury.

PubMed

Dunkley, B T; Da Costa, L; Bethune, A; Jetly, R; Pang, E W; Taylor, M J; Doesburg, S M

2015-01-01

Mild traumatic brain injury (mTBI) occurs from a closed-head impact. Often referred to as concussion, about 20% of cases complain of secondary psychological sequelae, such as disorders of attention and memory. Known as post-concussive symptoms (PCS), these problems can severely disrupt the patient's quality of life. Changes in local spectral power, particularly low-frequency amplitude increases and/or peak alpha slowing have been reported in mTBI, but large-scale connectivity metrics based on inter-regional amplitude correlations relevant for integration and segregation in functional brain networks, and their association with disorders in cognition and behaviour, remain relatively unexplored. Here, we used non-invasive neuroimaging with magnetoencephalography to examine functional connectivity in a resting-state protocol in a group with mTBI (n = 20), and a control group (n = 21). We observed a trend for atypical slow-wave power changes in subcortical, temporal and parietal regions in mTBI, as well as significant long-range increases in amplitude envelope correlations among deep-source, temporal, and frontal regions in the delta, theta, and alpha bands. Subsequently, we conducted an exploratory analysis of patterns of connectivity most associated with variability in secondary symptoms of mTBI, including inattention, anxiety, and depression. Differential patterns of altered resting state neurophysiological network connectivity were found across frequency bands. This indicated that multiple network and frequency specific alterations in large scale brain connectivity may contribute to overlapping cognitive sequelae in mTBI. In conclusion, we show that local spectral power content can be supplemented with measures of correlations in amplitude to define general networks that are atypical in mTBI, and suggest that certain cognitive difficulties are mediated by disturbances in a variety of alterations in network interactions which are differentially expressed across canonical neurophysiological frequency ranges.

Relating Inter-Individual Differences in Verbal Creative Thinking to Cerebral Structures: An Optimal Voxel-Based Morphometry Study

PubMed Central

Zhu, Feifei; Zhang, Qinglin; Qiu, Jiang

2013-01-01

Creativity can be defined the capacity of an individual to produce something original and useful. An important measurable component of creativity is divergent thinking. Despite existing studies on creativity-related cerebral structural basis, no study has used a large sample to investigate the relationship between individual verbal creativity and regional gray matter volumes (GMVs) and white matter volumes (WMVs). In the present work, optimal voxel-based morphometry (VBM) was employed to identify the structure that correlates verbal creativity (measured by the verbal form of Torrance Tests of Creative Thinking) across the brain in young healthy subjects. Verbal creativity was found to be significantly positively correlated with regional GMV in the left inferior frontal gyrus (IFG), which is believed to be responsible for language production and comprehension, new semantic representation, and memory retrieval, and in the right IFG, which may involve inhibitory control and attention switching. A relationship between verbal creativity and regional WMV in the left and right IFG was also observed. Overall, a highly verbal creative individual with superior verbal skills may demonstrate a greater computational efficiency in the brain areas involved in high-level cognitive processes including language production, semantic representation and cognitive control. PMID:24223921

Random Forest Segregation of Drug Responses May Define Regions of Biological Significance.

PubMed

Bukhari, Qasim; Borsook, David; Rudin, Markus; Becerra, Lino

2016-01-01

The ability to assess brain responses in unsupervised manner based on fMRI measure has remained a challenge. Here we have applied the Random Forest (RF) method to detect differences in the pharmacological MRI (phMRI) response in rats to treatment with an analgesic drug (buprenorphine) as compared to control (saline). Three groups of animals were studied: two groups treated with different doses of the opioid buprenorphine, low (LD), and high dose (HD), and one receiving saline. PhMRI responses were evaluated in 45 brain regions and RF analysis was applied to allocate rats to the individual treatment groups. RF analysis was able to identify drug effects based on differential phMRI responses in the hippocampus, amygdala, nucleus accumbens, superior colliculus, and the lateral and posterior thalamus for drug vs. saline. These structures have high levels of mu opioid receptors. In addition these regions are involved in aversive signaling, which is inhibited by mu opioids. The results demonstrate that buprenorphine mediated phMRI responses comprise characteristic features that allow a supervised differentiation from placebo treated rats as well as the proper allocation to the respective drug dose group using the RF method, a method that has been successfully applied in clinical studies.

Relating inter-individual differences in verbal creative thinking to cerebral structures: an optimal voxel-based morphometry study.

PubMed

Zhu, Feifei; Zhang, Qinglin; Qiu, Jiang

2013-01-01

Creativity can be defined the capacity of an individual to produce something original and useful. An important measurable component of creativity is divergent thinking. Despite existing studies on creativity-related cerebral structural basis, no study has used a large sample to investigate the relationship between individual verbal creativity and regional gray matter volumes (GMVs) and white matter volumes (WMVs). In the present work, optimal voxel-based morphometry (VBM) was employed to identify the structure that correlates verbal creativity (measured by the verbal form of Torrance Tests of Creative Thinking) across the brain in young healthy subjects. Verbal creativity was found to be significantly positively correlated with regional GMV in the left inferior frontal gyrus (IFG), which is believed to be responsible for language production and comprehension, new semantic representation, and memory retrieval, and in the right IFG, which may involve inhibitory control and attention switching. A relationship between verbal creativity and regional WMV in the left and right IFG was also observed. Overall, a highly verbal creative individual with superior verbal skills may demonstrate a greater computational efficiency in the brain areas involved in high-level cognitive processes including language production, semantic representation and cognitive control.

Brain mechanisms of successful recognition through retrieval of semantic context

PubMed Central

Flegal, Kristin E.; Marín-Gutiérrez, Alejandro; Ragland, J. Daniel; Ranganath, Charan

2017-01-01

Episodic memory is associated with the encoding and retrieval of context information, and with a subjective sense of re-experiencing past events. The neural correlates of episodic retrieval have been extensively studied using fMRI, leading to the identification of a “general recollection network” including medial temporal, parietal, and prefrontal regions. However, in these studies, it is difficult to disentangle the effects of context retrieval from recollection. In the present study, we used functional magnetic resonance imaging (fMRI) to determine the extent to which the recruitment of regions in the recollection network is contingent on context reinstatement. Participants were scanned during a cued recognition test for target words from encoded sentences. Studied target words were preceded by either a cue word studied in the same sentence (thus congruent with encoding context), or a cue word studied in a different sentence (thus incongruent with encoding context). Converging fMRI results from independently-defined regions of interest and whole-brain analysis showed regional specificity in the recollection network. Activity in hippocampus and parahippocampal cortex was specifically increased during successful retrieval following congruent context cues, whereas parietal and prefrontal components of the general recollection network were associated with confident retrieval irrespective of contextual congruency. Our findings implicate medial temporal regions in the retrieval of semantic context, contributing to, but dissociable from, recollective experience. PMID:24564467

An EEG Finger-Print of fMRI deep regional activation.

PubMed

Meir-Hasson, Yehudit; Kinreich, Sivan; Podlipsky, Ilana; Hendler, Talma; Intrator, Nathan

2014-11-15

This work introduces a general framework for producing an EEG Finger-Print (EFP) which can be used to predict specific brain activity as measured by fMRI at a given deep region. This new approach allows for improved EEG spatial resolution based on simultaneous fMRI activity measurements. Advanced signal processing and machine learning methods were applied on EEG data acquired simultaneously with fMRI during relaxation training guided by on-line continuous feedback on changing alpha/theta EEG measure. We focused on demonstrating improved EEG prediction of activation in sub-cortical regions such as the amygdala. Our analysis shows that a ridge regression model that is based on time/frequency representation of EEG data from a single electrode, can predict the amygdala related activity significantly better than a traditional theta/alpha activity sampled from the best electrode and about 1/3 of the times, significantly better than a linear combination of frequencies with a pre-defined delay. The far-reaching goal of our approach is to be able to reduce the need for fMRI scanning for probing specific sub-cortical regions such as the amygdala as the basis for brain-training procedures. On the other hand, activity in those regions can be characterized with higher temporal resolution than is obtained by fMRI alone thus revealing additional information about their processing mode. Copyright © 2013 Elsevier Inc. All rights reserved.

Characterization and classification of zebrafish brain morphology mutants

PubMed Central

Lowery, Laura Anne; De Rienzo, Gianluca; Gutzman, Jennifer H.; Sive, Hazel

2010-01-01

The mechanisms by which the vertebrate brain achieves its three-dimensional structure are clearly complex, requiring the functions of many genes. Using the zebrafish as a model, we have begun to define genes required for brain morphogenesis, including brain ventricle formation, by studying 16 mutants previously identified as having embryonic brain morphology defects. We report the phenotypic characterization of these mutants at several time-points, using brain ventricle dye injection, imaging, and immunohistochemistry with neuronal markers. Most of these mutants display early phenotypes, affecting initial brain shaping, while others show later phenotypes, affecting brain ventricle expansion. In the early phenotype group, we further define four phenotypic classes and corresponding functions required for brain morphogenesis. Although we did not use known genotypes for this classification, basing it solely on phenotypes, many mutants with defects in functionally related genes clustered in a single class. In particular, class 1 mutants show midline separation defects, corresponding to epithelial junction defects; class 2 mutants show reduced brain ventricle size; class 3 mutants show midbrain-hindbrain abnormalities, corresponding to basement membrane defects; and class 4 mutants show absence of ventricle lumen inflation, corresponding to defective ion pumping. Later brain ventricle expansion requires the extracellular matrix, cardiovascular circulation, and transcription/splicing-dependent events. We suggest that these mutants define processes likely to be used during brain morphogenesis throughout the vertebrates. PMID:19051268

Brain size and visual environment predict species differences in paper wasp sensory processing brain regions (hymenoptera: vespidae, polistinae).

PubMed

O'Donnell, Sean; Clifford, Marie R; DeLeon, Sara; Papa, Christopher; Zahedi, Nazaneen; Bulova, Susan J

2013-01-01

The mosaic brain evolution hypothesis predicts that the relative volumes of functionally distinct brain regions will vary independently and correlate with species' ecology. Paper wasp species (Hymenoptera: Vespidae, Polistinae) differ in light exposure: they construct open versus enclosed nests and one genus (Apoica) is nocturnal. We asked whether light environments were related to species differences in the size of antennal and optic processing brain tissues. Paper wasp brains have anatomically distinct peripheral and central regions that process antennal and optic sensory inputs. We measured the volumes of 4 sensory processing brain regions in paper wasp species from 13 Neotropical genera including open and enclosed nesters, and diurnal and nocturnal species. Species differed in sensory region volumes, but there was no evidence for trade-offs among sensory modalities. All sensory region volumes correlated with brain size. However, peripheral optic processing investment increased with brain size at a higher rate than peripheral antennal processing investment. Our data suggest that mosaic and concerted (size-constrained) brain evolution are not exclusive alternatives. When brain regions increase with brain size at different rates, these distinct allometries can allow for differential investment among sensory modalities. As predicted by mosaic evolution, species ecology was associated with some aspects of brain region investment. Nest architecture variation was not associated with brain investment differences, but the nocturnal genus Apoica had the largest antennal:optic volume ratio in its peripheral sensory lobes. Investment in central processing tissues was not related to nocturnality, a pattern also noted in mammals. The plasticity of neural connections in central regions may accommodate evolutionary shifts in input from the periphery with relatively minor changes in volume. © 2013 S. Karger AG, Basel.

Higher levels of trait emotional awareness are associated with more efficient global information integration throughout the brain: A graph-theoretic analysis of resting state functional connectivity.

PubMed

Smith, Ryan; Sanova, Anna; Alkozei, Anna; Lane, Richard D; Killgore, William D S

2018-06-21

Previous studies have suggested that trait differences in emotional awareness (tEA) are clinically relevant, and associated with differences in neural structure/function. While multiple leading theories suggest that conscious awareness requires widespread information integration across the brain, no study has yet tested the hypothesis that higher tEA corresponds to more efficient brain-wide information exchange. Twenty-six healthy volunteers (13 female) underwent a resting state functional magnetic resonance imaging scan, and completed the Levels of Emotional Awareness Scale (LEAS; a measure of tEA) and the Wechsler Abbreviated Scale of Intelligence (WASI-II; a measure of general intelligence [IQ]). Using a whole-brain (functionally defined) region-of-interest (ROI) atlas, we computed several graph theory metrics to assess the efficiency of brain-wide information exchange. After statistically controlling for differences in age, gender, and IQ, we first observed a significant relationship between higher LEAS scores and greater average degree (i.e., overall whole-brain network density). When controlling for average degree, we found that higher LEAS scores were also associated with shorter average path lengths across the collective network of all included ROIs. These results jointly suggest that individuals with higher tEA display more efficient global information exchange throughout the brain. This is consistent with the idea that conscious awareness requires global accessibility of represented information.

Structural Brain Connectivity Constrains within-a-Day Variability of Direct Functional Connectivity

PubMed Central

Park, Bumhee; Eo, Jinseok; Park, Hae-Jeong

2017-01-01

The idea that structural white matter connectivity constrains functional connectivity (interactions among brain regions) has widely been explored in studies of brain networks; studies have mostly focused on the “average” strength of functional connectivity. The question of how structural connectivity constrains the “variability” of functional connectivity remains unresolved. In this study, we investigated the variability of resting state functional connectivity that was acquired every 3 h within a single day from 12 participants (eight time sessions within a 24-h period, 165 scans per session). Three different types of functional connectivity (functional connectivity based on Pearson correlation, direct functional connectivity based on partial correlation, and the pseudo functional connectivity produced by their difference) were estimated from resting state functional magnetic resonance imaging data along with structural connectivity defined using fiber tractography of diffusion tensor imaging. Those types of functional connectivity were evaluated with regard to properties of structural connectivity (fiber streamline counts and lengths) and types of structural connectivity such as intra-/inter-hemispheric edges and topological edge types in the rich club organization. We observed that the structural connectivity constrained the variability of direct functional connectivity more than pseudo-functional connectivity and that the constraints depended strongly on structural connectivity types. The structural constraints were greater for intra-hemispheric and heterologous inter-hemispheric edges than homologous inter-hemispheric edges, and feeder and local edges than rich club edges in the rich club architecture. While each edge was highly variable, the multivariate patterns of edge involvement, especially the direct functional connectivity patterns among the rich club brain regions, showed low variability over time. This study suggests that structural connectivity not only constrains the strength of functional connectivity, but also the within-a-day variability of functional connectivity and connectivity patterns, particularly the direct functional connectivity among brain regions. PMID:28848416

DCE-MRI defined subvolumes of a brain metastatic lesion by principle component analysis and fuzzy-c-means clustering for response assessment of radiation therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farjam, Reza; Tsien, Christina I.; Lawrence, Theodore S.

Purpose: To develop a pharmacokinetic modelfree framework to analyze the dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data for assessment of response of brain metastases to radiation therapy. Methods: Twenty patients with 45 analyzable brain metastases had MRI scans prior to whole brain radiation therapy (WBRT) and at the end of the 2-week therapy. The volumetric DCE images covering the whole brain were acquired on a 3T scanner with approximately 5 s temporal resolution and a total scan time of about 3 min. DCE curves from all voxels of the 45 brain metastases were normalized and then temporally aligned. Amore » DCE matrix that is constructed from the aligned DCE curves of all voxels of the 45 lesions obtained prior to WBRT is processed by principal component analysis to generate the principal components (PCs). Then, the projection coefficient maps prior to and at the end of WBRT are created for each lesion. Next, a pattern recognition technique, based upon fuzzy-c-means clustering, is used to delineate the tumor subvolumes relating to the value of the significant projection coefficients. The relationship between changes in different tumor subvolumes and treatment response was evaluated to differentiate responsive from stable and progressive tumors. Performance of the PC-defined tumor subvolume was also evaluated by receiver operating characteristic (ROC) analysis in prediction of nonresponsive lesions and compared with physiological-defined tumor subvolumes. Results: The projection coefficient maps of the first three PCs contain almost all response-related information in DCE curves of brain metastases. The first projection coefficient, related to the area under DCE curves, is the major component to determine response while the third one has a complimentary role. In ROC analysis, the area under curve of 0.88 ± 0.05 and 0.86 ± 0.06 were achieved for the PC-defined and physiological-defined tumor subvolume in response assessment. Conclusions: The PC-defined subvolume of a brain metastasis could predict tumor response to therapy similar to the physiological-defined one, while the former is determined more rapidly for clinical decision-making support.« less

DCE-MRI defined subvolumes of a brain metastatic lesion by principle component analysis and fuzzy-c-means clustering for response assessment of radiation therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farjam, Reza; Tsien, Christina I.; Lawrence, Theodore S.

2014-01-15

Purpose: To develop a pharmacokinetic modelfree framework to analyze the dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data for assessment of response of brain metastases to radiation therapy. Methods: Twenty patients with 45 analyzable brain metastases had MRI scans prior to whole brain radiation therapy (WBRT) and at the end of the 2-week therapy. The volumetric DCE images covering the whole brain were acquired on a 3T scanner with approximately 5 s temporal resolution and a total scan time of about 3 min. DCE curves from all voxels of the 45 brain metastases were normalized and then temporally aligned. Amore » DCE matrix that is constructed from the aligned DCE curves of all voxels of the 45 lesions obtained prior to WBRT is processed by principal component analysis to generate the principal components (PCs). Then, the projection coefficient maps prior to and at the end of WBRT are created for each lesion. Next, a pattern recognition technique, based upon fuzzy-c-means clustering, is used to delineate the tumor subvolumes relating to the value of the significant projection coefficients. The relationship between changes in different tumor subvolumes and treatment response was evaluated to differentiate responsive from stable and progressive tumors. Performance of the PC-defined tumor subvolume was also evaluated by receiver operating characteristic (ROC) analysis in prediction of nonresponsive lesions and compared with physiological-defined tumor subvolumes. Results: The projection coefficient maps of the first three PCs contain almost all response-related information in DCE curves of brain metastases. The first projection coefficient, related to the area under DCE curves, is the major component to determine response while the third one has a complimentary role. In ROC analysis, the area under curve of 0.88 ± 0.05 and 0.86 ± 0.06 were achieved for the PC-defined and physiological-defined tumor subvolume in response assessment. Conclusions: The PC-defined subvolume of a brain metastasis could predict tumor response to therapy similar to the physiological-defined one, while the former is determined more rapidly for clinical decision-making support.« less

Functional (dissociative) retrograde amnesia.

PubMed

Markowitsch, H J; Staniloiu, A

2016-01-01

Retrograde amnesia is described as condition which can occur after direct brain damage, but which occurs more frequently as a result of a psychiatric illness. In order to understand the amnesic condition, content-based divisions of memory are defined. The measurement of retrograde memory is discussed and the dichotomy between "organic" and "psychogenic" retrograde amnesia is questioned. Briefly, brain damage-related etiologies of retrograde amnesia are mentioned. The major portion of the review is devoted to dissociative amnesia (also named psychogenic or functional amnesia) and to the discussion of an overlap between psychogenic and "brain organic" forms of amnesia. The "inability of access hypothesis" is proposed to account for most of both the organic and psychogenic (dissociative) patients with primarily retrograde amnesia. Questions such as why recovery from retrograde amnesia can occur in retrograde (dissociative) amnesia, and why long-term new learning of episodic-autobiographic episodes is possible, are addressed. It is concluded that research on retrograde amnesia research is still in its infancy, as the neural correlates of memory storage are still unknown. It is argued that the recollection of episodic-autobiographic episodes most likely involves frontotemporal regions of the right hemisphere, a region which appears to be hypometabolic in patients with dissociative amnesia. © 2016 Elsevier B.V. All rights reserved.

The relationship between spatial configuration and functional connectivity of brain regions

PubMed Central

Woolrich, Mark W; Glasser, Matthew F; Robinson, Emma C; Beckmann, Christian F; Van Essen, David C

2018-01-01

Brain connectivity is often considered in terms of the communication between functionally distinct brain regions. Many studies have investigated the extent to which patterns of coupling strength between multiple neural populations relates to behaviour. For example, studies have used ‘functional connectivity fingerprints’ to characterise individuals' brain activity. Here, we investigate the extent to which the exact spatial arrangement of cortical regions interacts with measures of brain connectivity. We find that the shape and exact location of brain regions interact strongly with the modelling of brain connectivity, and present evidence that the spatial arrangement of functional regions is strongly predictive of non-imaging measures of behaviour and lifestyle. We believe that, in many cases, cross-subject variations in the spatial configuration of functional brain regions are being interpreted as changes in functional connectivity. Therefore, a better understanding of these effects is important when interpreting the relationship between functional imaging data and cognitive traits. PMID:29451491

Category representations in the brain are both discretely localized and widely distributed.

PubMed

Shehzad, Zarrar; McCarthy, Gregory

2018-06-01

Whether category information is discretely localized or represented widely in the brain remains a contentious issue. Initial functional MRI studies supported the localizationist perspective that category information is represented in discrete brain regions. More recent fMRI studies using machine learning pattern classification techniques provide evidence for widespread distributed representations. However, these latter studies have not typically accounted for shared information. Here, we find strong support for distributed representations when brain regions are considered separately. However, localized representations are revealed by using analytical methods that separate unique from shared information among brain regions. The distributed nature of shared information and the localized nature of unique information suggest that brain connectivity may encourage spreading of information but category-specific computations are carried out in distinct domain-specific regions. NEW & NOTEWORTHY Whether visual category information is localized in unique domain-specific brain regions or distributed in many domain-general brain regions is hotly contested. We resolve this debate by using multivariate analyses to parse functional MRI signals from different brain regions into unique and shared variance. Our findings support elements of both models and show information is initially localized and then shared among other regions leading to distributed representations being observed.

Weight Perturbation Alters Leptin Signal Transduction in a Region-Specific Manner throughout the Brain

PubMed Central

Morabito, Michael V.; Ravussin, Yann; Mueller, Bridget R.; Skowronski, Alicja A.; Watanabe, Kazuhisa; Foo, Kylie S.; Lee, Samuel X.; Lehmann, Anders; Hjorth, Stephan; Zeltser, Lori M.; LeDuc, Charles A.; Leibel, Rudolph L.

2017-01-01

Diet-induced obesity (DIO) resulting from consumption of a high fat diet (HFD) attenuates normal neuronal responses to leptin and may contribute to the metabolic defense of an acquired higher body weight in humans; the molecular bases for the persistence of this defense are unknown. We measured the responses of 23 brain regions to exogenous leptin in 4 different groups of weight- and/or diet-perturbed mice. Responses to leptin were assessed by quantifying pSTAT3 levels in brain nuclei 30 minutes following 3 mg/kg intraperitoneal leptin. HFD attenuated leptin sensing throughout the brain, but weight loss did not restore central leptin signaling to control levels in several brain regions important in energy homeostasis, including the arcuate and dorsomedial hypothalamic nuclei. Effects of diet on leptin signaling varied by brain region, with results dependent on the method of weight loss (restriction of calories of HFD, ad lib intake of standard mouse chow). High fat diet attenuates leptin signaling throughout the brain, but some brain regions maintain their ability to sense leptin. Weight loss restores leptin sensing to some degree in most (but not all) brain regions, while other brain regions display hypersensitivity to leptin following weight loss. Normal leptin sensing was restored in several brain regions, with the pattern of restoration dependent on the method of weight loss. PMID:28107353

The Role of Intrinsic Brain Functional Connectivity in Vulnerability and Resilience to Bipolar Disorder.

PubMed

Doucet, Gaelle E; Bassett, Danielle S; Yao, Nailin; Glahn, David C; Frangou, Sophia

2017-12-01

Bipolar disorder is a heritable disorder characterized by mood dysregulation associated with brain functional dysconnectivity. Previous research has focused on the detection of risk- and disease-associated dysconnectivity in individuals with bipolar disorder and their first-degree relatives. The present study seeks to identify adaptive brain connectivity features associated with resilience, defined here as avoidance of illness or delayed illness onset in unaffected siblings of patients with bipolar disorder. Graph theoretical methods were used to examine global and regional brain network topology in head-motion-corrected resting-state functional MRI data acquired from 78 patients with bipolar disorder, 64 unaffected siblings, and 41 healthy volunteers. Global network properties were preserved in patients and their siblings while both groups showed reductions in the cohesiveness of the sensorimotor network. In the patient group, these sensorimotor network abnormalities were coupled with reduced integration of core default mode network regions in the ventromedial cortex and hippocampus. Conversely, integration of the default mode network was increased in the sibling group compared with both the patient group and the healthy volunteer group. The authors found that trait-related vulnerability to bipolar disorder was associated with reduced resting-state cohesiveness of the sensorimotor network in patients with bipolar disorder. However, integration of the default mode network emerged as a key feature differentiating disease expression and resilience between the patients and their siblings. This is indicative of the presence of neural mechanisms that may promote resilience, or at least delay illness onset.

Cognitive Flexibility through Metastable Neural Dynamics Is Disrupted by Damage to the Structural Connectome.

PubMed

Hellyer, Peter J; Scott, Gregory; Shanahan, Murray; Sharp, David J; Leech, Robert

2015-06-17

Current theory proposes that healthy neural dynamics operate in a metastable regime, where brain regions interact to simultaneously maximize integration and segregation. Metastability may confer important behavioral properties, such as cognitive flexibility. It is increasingly recognized that neural dynamics are constrained by the underlying structural connections between brain regions. An important challenge is, therefore, to relate structural connectivity, neural dynamics, and behavior. Traumatic brain injury (TBI) is a pre-eminent structural disconnection disorder whereby traumatic axonal injury damages large-scale connectivity, producing characteristic cognitive impairments, including slowed information processing speed and reduced cognitive flexibility, that may be a result of disrupted metastable dynamics. Therefore, TBI provides an experimental and theoretical model to examine how metastable dynamics relate to structural connectivity and cognition. Here, we use complementary empirical and computational approaches to investigate how metastability arises from the healthy structural connectome and relates to cognitive performance. We found reduced metastability in large-scale neural dynamics after TBI, measured with resting-state functional MRI. This reduction in metastability was associated with damage to the connectome, measured using diffusion MRI. Furthermore, decreased metastability was associated with reduced cognitive flexibility and information processing. A computational model, defined by empirically derived connectivity data, demonstrates how behaviorally relevant changes in neural dynamics result from structural disconnection. Our findings suggest how metastable dynamics are important for normal brain function and contingent on the structure of the human connectome. Copyright © 2015 the authors 0270-6474/15/359050-14$15.00/0.

Effects of outcome on the covariance between risk level and brain activity in adolescents with internet gaming disorder.

PubMed

Qi, Xin; Yang, Yongxin; Dai, Shouping; Gao, Peihong; Du, Xin; Zhang, Yang; Du, Guijin; Li, Xiaodong; Zhang, Quan

2016-01-01

Individuals with internet gaming disorder (IGD) often have impaired risky decision-making abilities, and IGD-related functional changes have been observed during neuroimaging studies of decision-making tasks. However, it is still unclear how feedback (outcomes of decision-making) affects the subsequent risky decision-making in individuals with IGD. In this study, twenty-four adolescents with IGD and 24 healthy controls (HCs) were recruited and underwent functional magnetic resonance imaging while performing the balloon analog risk task (BART) to evaluate the effects of prior outcomes on brain activity during subsequent risky decision-making in adolescents with IGD. The covariance between risk level and activation of the bilateral ventral medial prefrontal cortex, left inferior frontal cortex, right ventral striatum (VS), left hippocampus/parahippocampus, right inferior occipital gyrus/fusiform gyrus and right inferior temporal gyrus demonstrated interaction effects of group by outcome ( P  < 0.05, AlphaSim correction). The regions with interactive effects were defined as ROI, and ROI-based intergroup comparisons showed that the covariance between risk level and brain activation was significantly greater in adolescents with IGD compared with HCs after a negative outcome occurred ( P  < 0.05). Our results indicated that negative outcomes affected the covariance between risk level and activation of the brain regions related to value estimation (prefrontal cortex), anticipation of rewards (VS), and emotional-related learning (hippocampus/parahippocampus), which may be one of the underlying neural mechanisms of disadvantageous risky decision-making in adolescents with IGD.

A Method for Functional Network Connectivity Among Spatially Independent Resting-State Components in Schizophrenia

PubMed Central

Jafri, Madiha J; Pearlson, Godfrey D; Stevens, Michael; Calhoun, Vince D

2011-01-01

Functional connectivity of the brain has been studied by analyzing correlation differences in time courses among seed voxels or regions with other voxels of the brain in patients versus controls. The spatial extent of strongly temporally coherent brain regions co-activated during rest has also been examined using independent component analysis (ICA). However, the weaker temporal relationships among ICA component time courses, which we operationally define as a measure of functional network connectivity (FNC), have not yet been studied. In this study, we propose an approach for evaluating FNC and apply it to functional magnetic resonance imaging (fMRI) data collected from persons with schizophrenia and healthy controls. We examined the connectivity and latency among ICA component time courses to test the hypothesis that patients with schizophrenia would show increased functional connectivity and increased lag among resting state networks compared to controls. Resting state fMRI data were collected and the inter-relationships among seven selected resting state networks (identified using group ICA) were evaluated by correlating each subject’s ICA time courses with one another. Patients showed higher correlation than controls among most of the dominant resting state networks. Patients also had slightly more variability in functional connectivity than controls. We present a novel approach for quantifying functional connectivity among brain networks identified with spatial ICA. Significant differences between patient and control connectivity in different networks were revealed possibly reflecting deficiencies in cortical processing in patients. PMID:18082428

Advanced MR Imaging of the Human Nucleus Accumbens--Additional Guiding Tool for Deep Brain Stimulation.

PubMed

Lucas-Neto, Lia; Reimão, Sofia; Oliveira, Edson; Rainha-Campos, Alexandre; Sousa, João; Nunes, Rita G; Gonçalves-Ferreira, António; Campos, Jorge G

2015-07-01

The human nucleus accumbens (Acc) has become a target for deep brain stimulation (DBS) in some neuropsychiatric disorders. Nonetheless, even with the most recent advances in neuroimaging it remains difficult to accurately delineate the Acc and closely related subcortical structures, by conventional MRI sequences. It is our purpose to perform a MRI study of the human Acc and to determine whether there are reliable anatomical landmarks that enable the precise location and identification of the nucleus and its core/shell division. For the Acc identification and delineation, based on anatomical landmarks, T1WI, T1IR and STIR 3T-MR images were acquired in 10 healthy volunteers. Additionally, 32-direction DTI was obtained for Acc segmentation. Seed masks for the Acc were generated with FreeSurfer and probabilistic tractography was performed using FSL. The probability of connectivity between the seed voxels and distinct brain areas was determined and subjected to k-means clustering analysis, defining 2 different regions. With conventional T1WI, the Acc borders are better defined through its surrounding anatomical structures. The DTI color-coded vector maps and IR sequences add further detail in the Acc identification and delineation. Additionally, using probabilistic tractography it is possible to segment the Acc into a core and shell division and establish its structural connectivity with different brain areas. Advanced MRI techniques allow in vivo delineation and segmentation of the human Acc and represent an additional guiding tool in the precise and safe target definition for DBS. © 2015 International Neuromodulation Society.

Automatic corpus callosum segmentation for standardized MR brain scanning

NASA Astrophysics Data System (ADS)

Xu, Qing; Chen, Hong; Zhang, Li; Novak, Carol L.

2007-03-01

Magnetic Resonance (MR) brain scanning is often planned manually with the goal of aligning the imaging plane with key anatomic landmarks. The planning is time-consuming and subject to inter- and intra- operator variability. An automatic and standardized planning of brain scans is highly useful for clinical applications, and for maximum utility should work on patients of all ages. In this study, we propose a method for fully automatic planning that utilizes the landmarks from two orthogonal images to define the geometry of the third scanning plane. The corpus callosum (CC) is segmented in sagittal images by an active shape model (ASM), and the result is further improved by weighting the boundary movement with confidence scores and incorporating region based refinement. Based on the extracted contour of the CC, several important landmarks are located and then combined with landmarks from the coronal or transverse plane to define the geometry of the third plane. Our automatic method is tested on 54 MR images from 24 patients and 3 healthy volunteers, with ages ranging from 4 months to 70 years old. The average accuracy with respect to two manually labeled points on the CC is 3.54 mm and 4.19 mm, and differed by an average of 2.48 degrees from the orientation of the line connecting them, demonstrating that our method is sufficiently accurate for clinical use.

Topological Organization of Functional Brain Networks in Healthy Children: Differences in Relation to Age, Sex, and Intelligence

PubMed Central

Wu, Kai; Taki, Yasuyuki; Sato, Kazunori; Hashizume, Hiroshi; Sassa, Yuko; Takeuchi, Hikaru; Thyreau, Benjamin; He, Yong; Evans, Alan C.; Li, Xiaobo; Kawashima, Ryuta; Fukuda, Hiroshi

2013-01-01

Recent studies have demonstrated developmental changes of functional brain networks derived from functional connectivity using graph theoretical analysis, which has been rapidly translated to studies of brain network organization. However, little is known about sex- and IQ-related differences in the topological organization of functional brain networks during development. In this study, resting-state fMRI (rs-fMRI) was used to map the functional brain networks in 51 healthy children. We then investigated the effects of age, sex, and IQ on economic small-world properties and regional nodal properties of the functional brain networks. At a global level of whole networks, we found significant age-related increases in the small-worldness and local efficiency, significant higher values of the global efficiency in boys compared with girls, and no significant IQ-related difference. Age-related increases in the regional nodal properties were found predominately in the frontal brain regions, whereas the parietal, temporal, and occipital brain regions showed age-related decreases. Significant sex-related differences in the regional nodal properties were found in various brain regions, primarily related to the default mode, language, and vision systems. Positive correlations between IQ and the regional nodal properties were found in several brain regions related to the attention system, whereas negative correlations were found in various brain regions primarily involved in the default mode, emotion, and language systems. Together, our findings of the network topology of the functional brain networks in healthy children and its relationship with age, sex, and IQ bring new insights into the understanding of brain maturation and cognitive development during childhood and adolescence. PMID:23390528

Topological organization of functional brain networks in healthy children: differences in relation to age, sex, and intelligence.

PubMed

Wu, Kai; Taki, Yasuyuki; Sato, Kazunori; Hashizume, Hiroshi; Sassa, Yuko; Takeuchi, Hikaru; Thyreau, Benjamin; He, Yong; Evans, Alan C; Li, Xiaobo; Kawashima, Ryuta; Fukuda, Hiroshi

2013-01-01

Recent studies have demonstrated developmental changes of functional brain networks derived from functional connectivity using graph theoretical analysis, which has been rapidly translated to studies of brain network organization. However, little is known about sex- and IQ-related differences in the topological organization of functional brain networks during development. In this study, resting-state fMRI (rs-fMRI) was used to map the functional brain networks in 51 healthy children. We then investigated the effects of age, sex, and IQ on economic small-world properties and regional nodal properties of the functional brain networks. At a global level of whole networks, we found significant age-related increases in the small-worldness and local efficiency, significant higher values of the global efficiency in boys compared with girls, and no significant IQ-related difference. Age-related increases in the regional nodal properties were found predominately in the frontal brain regions, whereas the parietal, temporal, and occipital brain regions showed age-related decreases. Significant sex-related differences in the regional nodal properties were found in various brain regions, primarily related to the default mode, language, and vision systems. Positive correlations between IQ and the regional nodal properties were found in several brain regions related to the attention system, whereas negative correlations were found in various brain regions primarily involved in the default mode, emotion, and language systems. Together, our findings of the network topology of the functional brain networks in healthy children and its relationship with age, sex, and IQ bring new insights into the understanding of brain maturation and cognitive development during childhood and adolescence.

Functional connectivity constrains the category-related organization of human ventral occipitotemporal cortex

PubMed Central

Stevens, W. Dale; Tessler, Michael Henry; Peng, Cynthia S.; Martin, Alex

2015-01-01

One of the most robust and oft-replicated findings in cognitive neuroscience is that several spatially distinct, functionally dissociable ventral occipitotemporal cortex (VOTC) regions respond preferentially to different categories of concrete entities. However, the determinants of this category-related organization remain to be fully determined. One recent proposal is that privileged connectivity of these VOTC regions with other regions that store and/or process category-relevant properties may be a major contributing factor. To test this hypothesis, we used a multi-category functional MRI localizer to individually define category-related brain regions of interest (ROIs) in a large group of subjects (n=33). We then used these ROIs in resting-state functional connectivity MRI analyses to explore spontaneous functional connectivity among these regions. We demonstrate that during rest, distinct category-preferential VOTC regions show differentially stronger functional connectivity with other regions that have congruent category-preference, as defined by the functional localizer. Importantly, a ‘tool’-preferential region in the left medial fusiform gyrus showed differentially stronger functional connectivity with other left lateralized cortical regions associated with perceiving and knowing about common tools – posterior middle temporal gyrus (involved in perception of non-biological motion), lateral parietal cortex (critical for reaching, grasping, manipulating), and ventral premotor cortex (involved in storing/executing motor programs) – relative to other category-related regions in VOTC of both the right and left hemisphere. Our findings support the claim that privileged connectivity with other cortical regions that store and/or process category-relevant properties constrains the category-related organization of VOTC. PMID:25704493

Functional Connectivity of Multiple Brain Regions Required for the Consolidation of Social Recognition Memory.

PubMed

Tanimizu, Toshiyuki; Kenney, Justin W; Okano, Emiko; Kadoma, Kazune; Frankland, Paul W; Kida, Satoshi

2017-04-12

Social recognition memory is an essential and basic component of social behavior that is used to discriminate familiar and novel animals/humans. Previous studies have shown the importance of several brain regions for social recognition memories; however, the mechanisms underlying the consolidation of social recognition memory at the molecular and anatomic levels remain unknown. Here, we show a brain network necessary for the generation of social recognition memory in mice. A mouse genetic study showed that cAMP-responsive element-binding protein (CREB)-mediated transcription is required for the formation of social recognition memory. Importantly, significant inductions of the CREB target immediate-early genes c-fos and Arc were observed in the hippocampus (CA1 and CA3 regions), medial prefrontal cortex (mPFC), anterior cingulate cortex (ACC), and amygdala (basolateral region) when social recognition memory was generated. Pharmacological experiments using a microinfusion of the protein synthesis inhibitor anisomycin showed that protein synthesis in these brain regions is required for the consolidation of social recognition memory. These findings suggested that social recognition memory is consolidated through the activation of CREB-mediated gene expression in the hippocampus/mPFC/ACC/amygdala. Network analyses suggested that these four brain regions show functional connectivity with other brain regions and, more importantly, that the hippocampus functions as a hub to integrate brain networks and generate social recognition memory, whereas the ACC and amygdala are important for coordinating brain activity when social interaction is initiated by connecting with other brain regions. We have found that a brain network composed of the hippocampus/mPFC/ACC/amygdala is required for the consolidation of social recognition memory. SIGNIFICANCE STATEMENT Here, we identify brain networks composed of multiple brain regions for the consolidation of social recognition memory. We found that social recognition memory is consolidated through CREB-meditated gene expression in the hippocampus, medial prefrontal cortex, anterior cingulate cortex (ACC), and amygdala. Importantly, network analyses based on c-fos expression suggest that functional connectivity of these four brain regions with other brain regions is increased with time spent in social investigation toward the generation of brain networks to consolidate social recognition memory. Furthermore, our findings suggest that hippocampus functions as a hub to integrate brain networks and generate social recognition memory, whereas ACC and amygdala are important for coordinating brain activity when social interaction is initiated by connecting with other brain regions. Copyright © 2017 the authors 0270-6474/17/374103-14$15.00/0.

MDD diagnosis based on partial-brain functional connection network

NASA Astrophysics Data System (ADS)

Yan, Gaoliang; Hu, Hailong; Zhao, Xiang; Zhang, Lin; Qu, Zehui; Li, Yantao

2018-04-01

Artificial intelligence (AI) is a hotspot in computer science research nowadays. To apply AI technology in all industries has been the developing direction for researchers. Major depressive disorder (MDD) is a common disease of serious mental disorders. The World Health Organization (WHO) reports that MDD is projected to become the second most common cause of death and disability by 2020. At present, the way of MDD diagnosis is single. Applying AI technology to MDD diagnosis and pathophysiological research will speed up the MDD research and improve the efficiency of MDD diagnosis. In this study, we select the higher degree of brain network functional connectivity by statistical methods. And our experiments show that the average accuracy of Logistic Regression (LR) classifier using feature filtering reaches 88.48%. Compared with other classification methods, both the efficiency and accuracy of this method are improved, which will greatly improve the process of MDD diagnose. In these experiments, we also define the brain regions associated with MDD, which plays a vital role in MDD pathophysiological research.

The zinc paradigm for metalloneurochemistry.

PubMed

Barr, Chelsea A; Burdette, Shawn C

2017-05-09

Neurotransmission and sensory perception are shaped through metal ion-protein interactions in various brain regions. The term "metalloneurochemistry" defines the unique field of bioinorganic chemistry focusing on these processes, and zinc has been the leading target of metalloneurochemists in the almost 15 years since the definition was introduced. Zinc in the hippocampus interacts with receptors that dictate ion flow and neurotransmitter release. Understanding the intricacies of these interactions is crucial to uncovering the role that zinc plays in learning and memory. Based on receptor similarities and zinc-enriched neurons (ZENs) in areas of the brain responsible for sensory perception, such as the olfactory bulb (OB), and dorsal cochlear nucleus (DCN), zinc participates in odor and sound perception. Development and improvement of methods which allow for precise detection and immediate manipulation of zinc ions in neuronal cells and in brain slices will be critical in uncovering the synaptic action of zinc and, more broadly, the bioinorganic chemistry of cognition. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

Genomic connectivity networks based on the BrainSpan atlas of the developing human brain

NASA Astrophysics Data System (ADS)

Mahfouz, Ahmed; Ziats, Mark N.; Rennert, Owen M.; Lelieveldt, Boudewijn P. F.; Reinders, Marcel J. T.

2014-03-01

The human brain comprises systems of networks that span the molecular, cellular, anatomic and functional levels. Molecular studies of the developing brain have focused on elucidating networks among gene products that may drive cellular brain development by functioning together in biological pathways. On the other hand, studies of the brain connectome attempt to determine how anatomically distinct brain regions are connected to each other, either anatomically (diffusion tensor imaging) or functionally (functional MRI and EEG), and how they change over development. A global examination of the relationship between gene expression and connectivity in the developing human brain is necessary to understand how the genetic signature of different brain regions instructs connections to other regions. Furthermore, analyzing the development of connectivity networks based on the spatio-temporal dynamics of gene expression provides a new insight into the effect of neurodevelopmental disease genes on brain networks. In this work, we construct connectivity networks between brain regions based on the similarity of their gene expression signature, termed "Genomic Connectivity Networks" (GCNs). Genomic connectivity networks were constructed using data from the BrainSpan Transcriptional Atlas of the Developing Human Brain. Our goal was to understand how the genetic signatures of anatomically distinct brain regions relate to each other across development. We assessed the neurodevelopmental changes in connectivity patterns of brain regions when networks were constructed with genes implicated in the neurodevelopmental disorder autism (autism spectrum disorder; ASD). Using graph theory metrics to characterize the GCNs, we show that ASD-GCNs are relatively less connected later in development with the cerebellum showing a very distinct expression of ASD-associated genes compared to other brain regions.

Histogram analysis of ADC in brain tumor patients

NASA Astrophysics Data System (ADS)

Banerjee, Debrup; Wang, Jihong; Li, Jiang

2011-03-01

At various stage of progression, most brain tumors are not homogenous. In this presentation, we retrospectively studied the distribution of ADC values inside tumor volume during the course of tumor treatment and progression for a selective group of patients who underwent an anti-VEGF trial. Complete MRI studies were obtained for this selected group of patients including pre- and multiple follow-up, post-treatment imaging studies. In each MRI imaging study, multiple scan series were obtained as a standard protocol which includes T1, T2, T1-post contrast, FLAIR and DTI derived images (ADC, FA etc.) for each visit. All scan series (T1, T2, FLAIR, post-contrast T1) were registered to the corresponding DTI scan at patient's first visit. Conventionally, hyper-intensity regions on T1-post contrast images are believed to represent the core tumor region while regions highlighted by FLAIR may overestimate tumor size. Thus we annotated tumor regions on the T1-post contrast scans and ADC intensity values for pixels were extracted inside tumor regions as defined on T1-post scans. We fit a mixture Gaussian (MG) model for the extracted pixels using the Expectation-Maximization (EM) algorithm, which produced a set of parameters (mean, various and mixture coefficients) for the MG model. This procedure was performed for each visits resulting in a series of GM parameters. We studied the parameters fitted for ADC and see if they can be used as indicators for tumor progression. Additionally, we studied the ADC characteristics in the peri-tumoral region as identified by hyper-intensity on FLAIR scans. The results show that ADC histogram analysis of the tumor region supports the two compartment model that suggests the low ADC value subregion corresponding to densely packed cancer cell while the higher ADC value region corresponding to a mixture of viable and necrotic cells with superimposed edema. Careful studies of the composition and relative volume of the two compartments in tumor region may provide some insights in the early assessment of tumor response to therapy for recurrence brain cancer patients.

Age-related differences in memory-encoding fMRI responses after accounting for decline in vascular reactivity

PubMed Central

Liu, Peiying; Hebrank, Andrew C.; Rodrigue, Karen M.; Kennedy, Kristen M.; Section, Jarren; Park, Denise C.; Lu, Hanzhang

2013-01-01

BOLD fMRI has provided a wealth of information about the aging brain. A common finding is that posterior regions of the brain manifest an age-related decrease in activation while the anterior regions show an age-related increase. Several neurocognitive models have been proposed to interpret these findings. However, one issue that has not been sufficiently considered to date is that the BOLD signal is based on vascular responses secondary to neural activity. Thus the above findings could be in part due to a vascular change, especially in view of the expected decline of vascular health with age. In the present study, we aim to examine age-related differences in memory-encoding fMRI response in the context of vascular aging. One hundred and thirty healthy subjects ranging from 20 to 89 years old underwent a scene-viewing fMRI task and, in the same session, cerebrovascular reactivity (CVR) was measured in each subject using a CO2-inhalation task. Without accounting for the influence of vascular changes, the task-activated fMRI signal showed the typical age-related decrease in visual cortex and medial temporal lobe (MTL), but manifested an increase in the right inferior frontal gyrus (IFG). In the same individuals, an age-related CVR reduction was observed in all of these regions. We then used a previously proposed normalization approach to calculate a CVR-corrected fMRI signal, which was defined as the uncorrected signal divided by CVR. Based on the CVR-corrected fMRI signal, an age-related increase is now seen in both the left and right side of IFG; and no brain regions showed a signal decrease with age. We additionally used a model-based approach to examine the fMRI data in the context of CVR, which again suggested an age-related change in the two frontal regions, but not in the visual and MTL regions. PMID:23624491

Aberrant Intrinsic Activity and Connectivity in Cognitively Normal Parkinson's Disease.

PubMed

Harrington, Deborah L; Shen, Qian; Castillo, Gabriel N; Filoteo, J Vincent; Litvan, Irene; Takahashi, Colleen; French, Chelsea

2017-01-01

Disturbances in intrinsic activity during resting-state functional MRI (rsfMRI) are common in Parkinson's disease (PD), but have largely been studied in a priori defined subnetworks. The cognitive significance of abnormal intrinsic activity is also poorly understood, as are abnormalities that precede the onset of mild cognitive impairment. To address these limitations, we leveraged three different analytic approaches to identify disturbances in rsfMRI metrics in 31 cognitively normal PD patients (PD-CN) and 30 healthy adults. Subjects were screened for mild cognitive impairment using the Movement Disorders Society Task Force Level II criteria. Whole-brain data-driven analytic approaches first analyzed the amplitude of low-frequency intrinsic fluctuations (ALFF) and regional homogeneity (ReHo), a measure of local connectivity amongst functionally similar regions. We then examined if regional disturbances in these metrics altered functional connectivity with other brain regions. We also investigated if abnormal rsfMRI metrics in PD-CN were related to brain atrophy and executive, visual organization, and episodic memory functioning. The results revealed abnormally increased and decreased ALFF and ReHo in PD-CN patients within the default mode network (posterior cingulate, inferior parietal cortex, parahippocampus, entorhinal cortex), sensorimotor cortex (primary motor, pre/post-central gyrus), basal ganglia (putamen, caudate), and posterior cerebellar lobule VII, which mediates cognition. For default mode network regions, we also observed a compound profile of altered ALFF and ReHo. Most regional disturbances in ALFF and ReHo were associated with strengthened long-range interactions in PD-CN, notably with regions in different networks. Stronger long-range functional connectivity in PD-CN was also partly expanded to connections that were outside the networks of the control group. Abnormally increased activity and functional connectivity appeared to have a pathological, rather than compensatory influence on cognitive abilities tested in this study. Receiver operating curve analyses demonstrated excellent sensitivity (≥90%) of rsfMRI variables in distinguishing patients from controls, but poor accuracy for brain volume and cognitive variables. Altogether these results provide new insights into the topology, cognitive relevance, and sensitivity of aberrant intrinsic activity and connectivity that precedes clinically significant cognitive impairment. Longitudinal studies are needed to determine if these neurocognitive associations presage the development of future mild cognitive impairment or dementia.

Causal Inference for fMRI Time Series Data with Systematic Errors of Measurement in a Balanced On/Off Study of Social Evaluative Threat.

PubMed

Sobel, Michael E; Lindquist, Martin A

2014-07-01

Functional magnetic resonance imaging (fMRI) has facilitated major advances in understanding human brain function. Neuroscientists are interested in using fMRI to study the effects of external stimuli on brain activity and causal relationships among brain regions, but have not stated what is meant by causation or defined the effects they purport to estimate. Building on Rubin's causal model, we construct a framework for causal inference using blood oxygenation level dependent (BOLD) fMRI time series data. In the usual statistical literature on causal inference, potential outcomes, assumed to be measured without systematic error, are used to define unit and average causal effects. However, in general the potential BOLD responses are measured with stimulus dependent systematic error. Thus we define unit and average causal effects that are free of systematic error. In contrast to the usual case of a randomized experiment where adjustment for intermediate outcomes leads to biased estimates of treatment effects (Rosenbaum, 1984), here the failure to adjust for task dependent systematic error leads to biased estimates. We therefore adjust for systematic error using measured "noise covariates" , using a linear mixed model to estimate the effects and the systematic error. Our results are important for neuroscientists, who typically do not adjust for systematic error. They should also prove useful to researchers in other areas where responses are measured with error and in fields where large amounts of data are collected on relatively few subjects. To illustrate our approach, we re-analyze data from a social evaluative threat task, comparing the findings with results that ignore systematic error.

Machine Learning Classification Combining Multiple Features of A Hyper-Network of fMRI Data in Alzheimer's Disease

PubMed Central

Guo, Hao; Zhang, Fan; Chen, Junjie; Xu, Yong; Xiang, Jie

2017-01-01

Exploring functional interactions among various brain regions is helpful for understanding the pathological underpinnings of neurological disorders. Brain networks provide an important representation of those functional interactions, and thus are widely applied in the diagnosis and classification of neurodegenerative diseases. Many mental disorders involve a sharp decline in cognitive ability as a major symptom, which can be caused by abnormal connectivity patterns among several brain regions. However, conventional functional connectivity networks are usually constructed based on pairwise correlations among different brain regions. This approach ignores higher-order relationships, and cannot effectively characterize the high-order interactions of many brain regions working together. Recent neuroscience research suggests that higher-order relationships between brain regions are important for brain network analysis. Hyper-networks have been proposed that can effectively represent the interactions among brain regions. However, this method extracts the local properties of brain regions as features, but ignores the global topology information, which affects the evaluation of network topology and reduces the performance of the classifier. This problem can be compensated by a subgraph feature-based method, but it is not sensitive to change in a single brain region. Considering that both of these feature extraction methods result in the loss of information, we propose a novel machine learning classification method that combines multiple features of a hyper-network based on functional magnetic resonance imaging in Alzheimer's disease. The method combines the brain region features and subgraph features, and then uses a multi-kernel SVM for classification. This retains not only the global topological information, but also the sensitivity to change in a single brain region. To certify the proposed method, 28 normal control subjects and 38 Alzheimer's disease patients were selected to participate in an experiment. The proposed method achieved satisfactory classification accuracy, with an average of 91.60%. The abnormal brain regions included the bilateral precuneus, right parahippocampal gyrus\\hippocampus, right posterior cingulate gyrus, and other regions that are known to be important in Alzheimer's disease. Machine learning classification combining multiple features of a hyper-network of functional magnetic resonance imaging data in Alzheimer's disease obtains better classification performance. PMID:29209156

Neurons derived from different brain regions are inherently different in vitro: a novel multiregional brain-on-a-chip.

PubMed

Dauth, Stephanie; Maoz, Ben M; Sheehy, Sean P; Hemphill, Matthew A; Murty, Tara; Macedonia, Mary Kate; Greer, Angie M; Budnik, Bogdan; Parker, Kevin Kit

2017-03-01

Brain in vitro models are critically important to developing our understanding of basic nervous system cellular physiology, potential neurotoxic effects of chemicals, and specific cellular mechanisms of many disease states. In this study, we sought to address key shortcomings of current brain in vitro models: the scarcity of comparative data for cells originating from distinct brain regions and the lack of multiregional brain in vitro models. We demonstrated that rat neurons from different brain regions exhibit unique profiles regarding their cell composition, protein expression, metabolism, and electrical activity in vitro. In vivo, the brain is unique in its structural and functional organization, and the interactions and communication between different brain areas are essential components of proper brain function. This fact and the observation that neurons from different areas of the brain exhibit unique behaviors in vitro underline the importance of establishing multiregional brain in vitro models. Therefore, we here developed a multiregional brain-on-a-chip and observed a reduction of overall firing activity, as well as altered amounts of astrocytes and specific neuronal cell types compared with separately cultured neurons. Furthermore, this multiregional model was used to study the effects of phencyclidine, a drug known to induce schizophrenia-like symptoms in vivo, on individual brain areas separately while monitoring downstream effects on interconnected regions. Overall, this work provides a comparison of cells from different brain regions in vitro and introduces a multiregional brain-on-a-chip that enables the development of unique disease models incorporating essential in vivo features. NEW & NOTEWORTHY Due to the scarcity of comparative data for cells from different brain regions in vitro, we demonstrated that neurons isolated from distinct brain areas exhibit unique behaviors in vitro. Moreover, in vivo proper brain function is dependent on the connection and communication of several brain regions, underlining the importance of developing multiregional brain in vitro models. We introduced a novel brain-on-a-chip model, implementing essential in vivo features, such as different brain areas and their functional connections. Copyright © 2017 the American Physiological Society.

Neurons derived from different brain regions are inherently different in vitro: a novel multiregional brain-on-a-chip

PubMed Central

Dauth, Stephanie; Maoz, Ben M.; Sheehy, Sean P.; Hemphill, Matthew A.; Murty, Tara; Macedonia, Mary Kate; Greer, Angie M.; Budnik, Bogdan

2017-01-01

Brain in vitro models are critically important to developing our understanding of basic nervous system cellular physiology, potential neurotoxic effects of chemicals, and specific cellular mechanisms of many disease states. In this study, we sought to address key shortcomings of current brain in vitro models: the scarcity of comparative data for cells originating from distinct brain regions and the lack of multiregional brain in vitro models. We demonstrated that rat neurons from different brain regions exhibit unique profiles regarding their cell composition, protein expression, metabolism, and electrical activity in vitro. In vivo, the brain is unique in its structural and functional organization, and the interactions and communication between different brain areas are essential components of proper brain function. This fact and the observation that neurons from different areas of the brain exhibit unique behaviors in vitro underline the importance of establishing multiregional brain in vitro models. Therefore, we here developed a multiregional brain-on-a-chip and observed a reduction of overall firing activity, as well as altered amounts of astrocytes and specific neuronal cell types compared with separately cultured neurons. Furthermore, this multiregional model was used to study the effects of phencyclidine, a drug known to induce schizophrenia-like symptoms in vivo, on individual brain areas separately while monitoring downstream effects on interconnected regions. Overall, this work provides a comparison of cells from different brain regions in vitro and introduces a multiregional brain-on-a-chip that enables the development of unique disease models incorporating essential in vivo features. NEW & NOTEWORTHY Due to the scarcity of comparative data for cells from different brain regions in vitro, we demonstrated that neurons isolated from distinct brain areas exhibit unique behaviors in vitro. Moreover, in vivo proper brain function is dependent on the connection and communication of several brain regions, underlining the importance of developing multiregional brain in vitro models. We introduced a novel brain-on-a-chip model, implementing essential in vivo features, such as different brain areas and their functional connections. PMID:28031399

Childhood abuse and reduced cortical thickness in brain regions involved in emotional processing.

PubMed

Gold, Andrea L; Sheridan, Margaret A; Peverill, Matthew; Busso, Daniel S; Lambert, Hilary K; Alves, Sonia; Pine, Daniel S; McLaughlin, Katie A

2016-10-01

Alterations in gray matter development represent a potential pathway through which childhood abuse is associated with psychopathology. Several prior studies find reduced volume and thickness of prefrontal (PFC) and temporal cortex regions in abused compared with nonabused adolescents, although most prior research is based on adults and volume-based measures. This study tests the hypothesis that child abuse, independent of parental education, predicts reduced cortical thickness in prefrontal and temporal cortices as well as reduced gray mater volume (GMV) in subcortical regions during adolescence. Structural MRI scans were obtained from 21 adolescents exposed to physical and/or sexual abuse and 37 nonabused adolescents (ages 13-20). Abuse was operationalized using dichotomous and continuous measures. We examined associations between abuse and brain structure in several a priori-defined regions, controlling for parental education, age, sex, race, and total brain volume for subcortical GMV. Significance was evaluated at p < .05 with a false discovery rate correction. Child abuse exposure and severity were associated with reduced thickness in ventromedial prefrontal cortex (PFC), right lateral orbitofrontal cortex, right inferior frontal gyrus, bilateral parahippocampal gyrus (PHG), left temporal pole, and bilateral inferior, right middle, and right superior temporal gyri. Neither abuse measure predicted cortical surface area or subcortical GMV. Bilateral PHG thickness was inversely related to externalizing symptoms. Child abuse, an experience characterized by a high degree of threat, is associated with reduced cortical thickness in ventromedial and ventrolateral PFC and medial and lateral temporal cortex in adolescence. Reduced PHG thickness may be a mediator linking abuse with externalizing psychopathology, although prospective research is needed to evaluate this possibility. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

A multiparametric evaluation of regional brain damage in patients with primary progressive multiple sclerosis.

PubMed

Ceccarelli, Antonia; Rocca, Maria A; Valsasina, Paola; Rodegher, Mariaemma; Pagani, Elisabetta; Falini, Andrea; Comi, Giancarlo; Filippi, Massimo

2009-09-01

The purpose of this study is to define the topographical distribution of gray matter (GM) and white matter (WM) damage in patients with primary progressive multiple sclerosis (PPMS), using a multiparametric MR-based approach. Using a 3 Tesla scanner, dual-echo, 3D fast-field echo (FFE), and diffusion tensor (DT) MRI scans were acquired from 18 PPMS patients and 17 matched healthy volunteers. An optimized voxel-based (VB) analysis was used to investigate the patterns of regional GM density changes and to quantify GM and WM diffusivity alterations of the entire brain. In PPMS patients, GM atrophy was found in the thalami and the right insula, while mean diffusivity (MD) changes involved several cortical-subcortical structures in all cerebral lobes and the cerebellum. An overlap between decreased WM fractional anisotropy (FA) and increased WM MD was found in the corpus callosum, the cingulate gyrus, the left short temporal fibers, the right short frontal fibers, the optic radiations, and the middle cerebellar peduncles. Selective MD increase, not associated with FA decrease, was found in the internal capsules, the corticospinal tracts, the superior longitudinal fasciculi, the fronto-occipital fasciculi, and the right cerebral peduncle. A discrepancy was found between regional WM diffusivity changes and focal lesions because several areas had DT MRI abnormalities but did not harbor T2-visible lesions. Our study allowed to detect tissue damage in brain areas associated with motor and cognitive functions, which are known to be impaired in PPMS patients. Combining regional measures derived from different MR modalities may be a valuable tool to improve our understanding of PPMS pathophysiology. 2009 Wiley-Liss, Inc.

Zic-Proteins Are Repressors of Dopaminergic Forebrain Fate in Mice and C. elegans.

PubMed

Tiveron, Marie-Catherine; Beclin, Christophe; Murgan, Sabrina; Wild, Stefan; Angelova, Alexandra; Marc, Julie; Coré, Nathalie; de Chevigny, Antoine; Herrera, Eloisa; Bosio, Andreas; Bertrand, Vincent; Cremer, Harold

2017-11-01

In the postnatal forebrain regionalized neural stem cells along the ventricular walls produce olfactory bulb (OB) interneurons with varying neurotransmitter phenotypes and positions. To understand the molecular basis of this region-specific variability we analyzed gene expression in the postnatal dorsal and lateral lineages in mice of both sexes from stem cells to neurons. We show that both lineages maintain transcription factor signatures of their embryonic site of origin, the pallium and subpallium. However, additional factors, including Zic1 and Zic2, are postnatally expressed in the dorsal stem cell compartment and maintained in the lineage that generates calretinin-positive GABAergic neurons for the OB. Functionally, we show that Zic1 and Zic2 induce the generation of calretinin-positive neurons while suppressing dopaminergic fate in the postnatal dorsal lineage. We investigated the evolutionary conservation of the dopaminergic repressor function of Zic proteins and show that it is already present in C. elegans SIGNIFICANCE STATEMENT The vertebrate brain generates thousands of different neuron types. In this work we investigate the molecular mechanisms underlying this variability. Using a genomics approach we identify the transcription factor signatures of defined neural stem cells and neuron populations. Based thereon we show that two related transcription factors, Zic1 and Zic2, are essential to control the balance between two defined neuron types in the postnatal brain. We show that this mechanism is conserved in evolutionary very distant species. Copyright © 2017 the authors 0270-6474/17/3710611-13$15.00/0.

The relationship between spatial configuration and functional connectivity of brain regions.

PubMed

Bijsterbosch, Janine Diane; Woolrich, Mark W; Glasser, Matthew F; Robinson, Emma C; Beckmann, Christian F; Van Essen, David C; Harrison, Samuel J; Smith, Stephen M

2018-02-16

Brain connectivity is often considered in terms of the communication between functionally distinct brain regions. Many studies have investigated the extent to which patterns of coupling strength between multiple neural populations relates to behaviour. For example, studies have used 'functional connectivity fingerprints' to characterise individuals' brain activity. Here, we investigate the extent to which the exact spatial arrangement of cortical regions interacts with measures of brain connectivity. We find that the shape and exact location of brain regions interact strongly with the modelling of brain connectivity, and present evidence that the spatial arrangement of functional regions is strongly predictive of non-imaging measures of behaviour and lifestyle. We believe that, in many cases, cross-subject variations in the spatial configuration of functional brain regions are being interpreted as changes in functional connectivity. Therefore, a better understanding of these effects is important when interpreting the relationship between functional imaging data and cognitive traits. © 2018, Bijsterbosch et al.

Expanding the spectrum of neuronal pathology in multiple system atrophy

PubMed Central

Cykowski, Matthew D.; Coon, Elizabeth A.; Powell, Suzanne Z.; Jenkins, Sarah M.; Benarroch, Eduardo E.; Low, Phillip A.; Schmeichel, Ann M.

2015-01-01

Multiple system atrophy is a sporadic alpha-synucleinopathy that typically affects patients in their sixth decade of life and beyond. The defining clinical features of the disease include progressive autonomic failure, parkinsonism, and cerebellar ataxia leading to significant disability. Pathologically, multiple system atrophy is characterized by glial cytoplasmic inclusions containing filamentous alpha-synuclein. Neuronal inclusions also have been reported but remain less well defined. This study aimed to further define the spectrum of neuronal pathology in 35 patients with multiple system atrophy (20 male, 15 female; mean age at death 64.7 years; median disease duration 6.5 years, range 2.2 to 15.6 years). The morphologic type, topography, and frequencies of neuronal inclusions, including globular cytoplasmic (Lewy body-like) neuronal inclusions, were determined across a wide spectrum of brain regions. A correlation matrix of pathologic severity also was calculated between distinct anatomic regions of involvement (striatum, substantia nigra, olivary and pontine nuclei, hippocampus, forebrain and thalamus, anterior cingulate and neocortex, and white matter of cerebrum, cerebellum, and corpus callosum). The major finding was the identification of widespread neuronal inclusions in the majority of patients, not only in typical disease-associated regions (striatum, substantia nigra), but also within anterior cingulate cortex, amygdala, entorhinal cortex, basal forebrain and hypothalamus. Neuronal inclusion pathology appeared to follow a hierarchy of region-specific susceptibility, independent of the clinical phenotype, and the severity of pathology was duration-dependent. Neuronal inclusions also were identified in regions not previously implicated in the disease, such as within cerebellar roof nuclei. Lewy body-like inclusions in multiple system atrophy followed the stepwise anatomic progression of Lewy body-spectrum disease inclusion pathology in 25.7% of patients with multiple system atrophy, including a patient with visual hallucinations. Further, the presence of Lewy body-like inclusions in neocortex, but not hippocampal alpha-synuclein pathology, was associated with cognitive impairment (P = 0.002). However, several cases had the presence of isolated Lewy body-like inclusions at atypical sites (e.g. thalamus, deep cerebellar nuclei) that are not typical for Lewy body-spectrum disease. Finally, interregional correlations (rho ≥ 0.6) in pathologic glial and neuronal lesion burden suggest shared mechanisms of disease progression between both discrete anatomic regions (e.g. basal forebrain and hippocampus) and cell types (neuronal and glial inclusions in frontal cortex and white matter, respectively). These findings suggest that in addition to glial inclusions, neuronal pathology plays an important role in the developmental and progression of multiple system atrophy. See Halliday (doi:10.1093/brain/awv151) for a scientific commentary on this article. PMID:25981961

Aberrant Global and Regional Topological Organization of the Fractional Anisotropy-weighted Brain Structural Networks in Major Depressive Disorder

PubMed Central

Chen, Jian-Huai; Yao, Zhi-Jian; Qin, Jiao-Long; Yan, Rui; Hua, Ling-Ling; Lu, Qing

2016-01-01

Background: Most previous neuroimaging studies have focused on the structural and functional abnormalities of local brain regions in major depressive disorder (MDD). Moreover, the exactly topological organization of networks underlying MDD remains unclear. This study examined the aberrant global and regional topological patterns of the brain white matter networks in MDD patients. Methods: The diffusion tensor imaging data were obtained from 27 patients with MDD and 40 healthy controls. The brain fractional anisotropy-weighted structural networks were constructed, and the global network and regional nodal metrics of the networks were explored by the complex network theory. Results: Compared with the healthy controls, the brain structural network of MDD patients showed an intact small-world topology, but significantly abnormal global network topological organization and regional nodal characteristic of the network in MDD were found. Our findings also indicated that the brain structural networks in MDD patients become a less strongly integrated network with a reduced central role of some key brain regions. Conclusions: All these resulted in a less optimal topological organization of networks underlying MDD patients, including an impaired capability of local information processing, reduced centrality of some brain regions and limited capacity to integrate information across different regions. Thus, these global network and regional node-level aberrations might contribute to understanding the pathogenesis of MDD from the view of the brain network. PMID:26960371

A viscoelastic analysis of the P56 mouse brain under large-deformation dynamic indentation.

PubMed

MacManus, David B; Pierrat, Baptiste; Murphy, Jeremiah G; Gilchrist, Michael D

2017-01-15

The brain is a complex organ made up of many different functional and structural regions consisting of different types of cells such as neurons and glia, as well as complex anatomical geometries. It is hypothesized that the different regions of the brain exhibit significantly different mechanical properties which may be attributed to the diversity of cells within individual brain regions. The regional viscoelastic properties of P56 mouse brain tissue, up to 70μm displacement, are presented and discussed in the context of traumatic brain injury, particularly how the different regions of the brain respond to mechanical loads. Force-relaxation data obtained from micro-indentation measurements were fit to both linear and quasi-linear viscoelastic models to determine the time and frequency domain viscoelastic response of the pons, cortex, medulla oblongata, cerebellum, and thalamus. The damping ratio of each region was also determined. Each region was found to have a unique mechanical response to the applied displacement, with the pons and thalamus exhibiting the largest and smallest force-response, respectively. All brain regions appear to have an optimal frequency for the dissipation of energies which lies between 1 and 10Hz. We present the first mechanical characterization of the viscoelastic response for different regions of mouse brain. Force-relaxation tests are performed under large strain dynamic micro-indentation, and viscoelastic models are used subsequently, providing time-dependent mechanical properties of brain tissue under loading conditions comparable to what is experienced in TBI. The unique mechanical properties of different brain regions are highlighted, with substantial variations in the viscoelastic properties and damping ratio of each region. Cortex and pons were the stiffest regions, while the thalamus and medulla were most compliant. The cerebellum and thalamus had highest damping ratio values and those of the medulla were lowest. The reported material parameters can be implemented into finite element computer models of the mouse to investigate the effects of trauma on individual brain regions. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Synergistic Roles of Antibody and Interferon in Noncytolytic Clearance of Sindbis Virus from Different Regions of the Central Nervous System▿

PubMed Central

Burdeinick-Kerr, Rebeca; Wind, Jennifer; Griffin, Diane E.

2007-01-01

Sindbis virus (SINV) is an alphavirus that causes infection of neurons and encephalomyelitis in adult immunocompetent mice. Recovery can occur without apparent neurological damage. To better define the factors facilitating noncytolytic clearance of SINV in different regions of the central nervous system (CNS) and the roles of innate and adaptive immune responses at different times during infection, we have characterized SINV infection and clearance in the brain, brain stem, and spinal cords of severe combined immunodeficiency (SCID) and C57BL/6 (wild-type [WT]) mice and mice deficient in beta interferon (IFN-β) (BKO), antibody (μMT), IFN-γ (GKO), IFN-γ receptor (GRKO), and both antibody and IFN-γ (μMT/GKO). WT mice cleared infectious virus by day 8, while SCID mice had persistent virus replication at all sites. For 3 days after infection, BKO mice had higher titers at all sites than WT mice, despite similar IFN-α production, but cleared virus similarly. GKO and GRKO mice cleared infectious virus from all sites by days 8 to 10 and, like WT mice, displayed transient reactivation at 12 to 22 days. μMT mice did not clear virus from the brain, and clearance from the brain stem and lumbar spinal cord was delayed, followed by reactivation. Eighty-one days after infection, μMT/GKO mice had not cleared virus from any site, but titers were lower than for SCID mice. These studies show that IFN-β is independently important for early control of CNS virus replication, that antiviral antibody is critical for clearance from the brain, and that both antibody and IFN-γ contribute to prevention of reactivation after initial clearance. PMID:17376910

Global and regional annual brain volume loss rates in physiological aging.

PubMed

Schippling, Sven; Ostwaldt, Ann-Christin; Suppa, Per; Spies, Lothar; Manogaran, Praveena; Gocke, Carola; Huppertz, Hans-Jürgen; Opfer, Roland

2017-03-01

The objective is to estimate average global and regional percentage brain volume loss per year (BVL/year) of the physiologically ageing brain. Two independent, cross-sectional single scanner cohorts of healthy subjects were included. The first cohort (n = 248) was acquired at the Medical Prevention Center (MPCH) in Hamburg, Germany. The second cohort (n = 316) was taken from the Open Access Series of Imaging Studies (OASIS). Brain parenchyma (BP), grey matter (GM), white matter (WM), corpus callosum (CC), and thalamus volumes were calculated. A non-parametric technique was applied to fit the resulting age-volume data. For each age, the BVL/year was derived from the age-volume curves. The resulting BVL/year curves were compared between the two cohorts. For the MPCH cohort, the BVL/year curve of the BP was an increasing function starting from 0.20% at the age of 35 years increasing to 0.52% at 70 years (corresponding values for GM ranged from 0.32 to 0.55%, WM from 0.02 to 0.47%, CC from 0.07 to 0.48%, and thalamus from 0.25 to 0.54%). Mean absolute difference between BVL/year trajectories across the age range of 35-70 years was 0.02% for BP, 0.04% for GM, 0.04% for WM, 0.11% for CC, and 0.02% for the thalamus. Physiological BVL/year rates were remarkably consistent between the two cohorts and independent from the scanner applied. Average BVL/year was clearly age and compartment dependent. These results need to be taken into account when defining cut-off values for pathological annual brain volume loss in disease models, such as multiple sclerosis.

Important considerations in lesion-symptom mapping: Illustrations from studies of word comprehension.

PubMed

Shahid, Hinna; Sebastian, Rajani; Schnur, Tatiana T; Hanayik, Taylor; Wright, Amy; Tippett, Donna C; Fridriksson, Julius; Rorden, Chris; Hillis, Argye E

2017-06-01

Lesion-symptom mapping is an important method of identifying networks of brain regions critical for functions. However, results might be influenced substantially by the imaging modality and timing of assessment. We tested the hypothesis that brain regions found to be associated with acute language deficits depend on (1) timing of behavioral measurement, (2) imaging sequences utilized to define the "lesion" (structural abnormality only or structural plus perfusion abnormality), and (3) power of the study. We studied 191 individuals with acute left hemisphere stroke with MRI and language testing to identify areas critical for spoken word comprehension. We use the data from this study to examine the potential impact of these three variables on lesion-symptom mapping. We found that only the combination of structural and perfusion imaging within 48 h of onset identified areas where more abnormal voxels was associated with more severe acute deficits, after controlling for lesion volume and multiple comparisons. The critical area identified with this methodology was the left posterior superior temporal gyrus, consistent with other methods that have identified an important role of this area in spoken word comprehension. Results have implications for interpretation of other lesion-symptom mapping studies, as well as for understanding areas critical for auditory word comprehension in the healthy brain. We propose that lesion-symptom mapping at the acute stage of stroke addresses a different sort of question about brain-behavior relationships than lesion-symptom mapping at the chronic stage, but that timing of behavioral measurement and imaging modalities should be considered in either case. Hum Brain Mapp 38:2990-3000, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Structural covariance networks are coupled to expression of genes enriched in supragranular layers of the human cortex.

PubMed

Romero-Garcia, Rafael; Whitaker, Kirstie J; Váša, František; Seidlitz, Jakob; Shinn, Maxwell; Fonagy, Peter; Dolan, Raymond J; Jones, Peter B; Goodyer, Ian M; Bullmore, Edward T; Vértes, Petra E

2018-05-01

Complex network topology is characteristic of many biological systems, including anatomical and functional brain networks (connectomes). Here, we first constructed a structural covariance network from MRI measures of cortical thickness on 296 healthy volunteers, aged 14-24 years. Next, we designed a new algorithm for matching sample locations from the Allen Brain Atlas to the nodes of the SCN. Subsequently we used this to define, transcriptomic brain networks by estimating gene co-expression between pairs of cortical regions. Finally, we explored the hypothesis that transcriptional networks and structural MRI connectomes are coupled. A transcriptional brain network (TBN) and a structural covariance network (SCN) were correlated across connection weights and showed qualitatively similar complex topological properties: assortativity, small-worldness, modularity, and a rich-club. In both networks, the weight of an edge was inversely related to the anatomical (Euclidean) distance between regions. There were differences between networks in degree and distance distributions: the transcriptional network had a less fat-tailed degree distribution and a less positively skewed distance distribution than the SCN. However, cortical areas connected to each other within modules of the SCN had significantly higher levels of whole genome co-expression than expected by chance. Nodes connected in the SCN had especially high levels of expression and co-expression of a human supragranular enriched (HSE) gene set that has been specifically located to supragranular layers of human cerebral cortex and is known to be important for large-scale, long-distance cortico-cortical connectivity. This coupling of brain transcriptome and connectome topologies was largely but not entirely accounted for by the common constraint of physical distance on both networks. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Network-Level Analysis of Cortical Thickness of the Epileptic Brain

PubMed Central

Raj, A; Mueller, S.G; Young, K; Laxer, K.D.; Weiner, M

2010-01-01

Temporal lobe epilepsy (TLE) characterized by an epileptogenic focus in the medial temporal lobe is the most common form of focal epilepsy. However, the seizures are not confined to the temporal lobe but can spread to other, anatomically connected brain regions where they can cause similar structural abnormalities as observed in the focus. The aim of this study was to derive whole brain networks from volumetric data and obtain network-centric measures which can capture cortical thinning characteristic for TLE and can be used for classifying a given MRI into TLE or normal, and to obtain additional summary statistics which relate to the extent and spread of the disease. T1 weighted whole brain images were acquired on a 4T magnet in 13 patients with TLE with mesial temporal lobe sclerosis (TLE-MTS), 14 patients with TLE with normal MRI (TLE-no) and 30 controls. Mean cortical thickness and curvature measurements were obtained using the Freesurfer software. These values were used to derive a graph, or network, for each subject. The nodes of the graph are brain regions, and edges represent disease progression paths. We show how to obtain summary statistics like mean, median and variance defined for these networks and to perform exploratory analyses like correlation and classification. Our results indicate that the proposed network approach can improve accuracy of classifying subjects into 2 groups (control and TLE), from 78% for non-network classifiers to 93% using the proposed approach. We also obtain network “peakiness” values using statistical measures like entropy and complexity - this appears to be a good characterizer of the disease, and may have utility in surgical planning. PMID:20553893

Altered resting state neuromotor connectivity in men with chronic prostatitis/chronic pelvic pain syndrome: A MAPP

PubMed Central

Kutch, Jason J.; Yani, Moheb S.; Asavasopon, Skulpan; Kirages, Daniel J.; Rana, Manku; Cosand, Louise; Labus, Jennifer S.; Kilpatrick, Lisa A.; Ashe-McNalley, Cody; Farmer, Melissa A.; Johnson, Kevin A.; Ness, Timothy J.; Deutsch, Georg; Harris, Richard E.; Apkarian, A. Vania; Clauw, Daniel J.; Mackey, Sean C.; Mullins, Chris; Mayer, Emeran A.

2015-01-01

Brain network activity associated with altered motor control in individuals with chronic pain is not well understood. Chronic Prostatitis/Chronic Pelvic Pain Syndrome (CP/CPPS) is a debilitating condition in which previous studies have revealed altered resting pelvic floor muscle activity in men with CP/CPPS compared to healthy controls. We hypothesized that the brain networks controlling pelvic floor muscles would also show altered resting state function in men with CP/CPPS. Here we describe the results of the first test of this hypothesis focusing on the motor cortical regions, termed pelvic-motor, that can directly activate pelvic floor muscles. A group of men with CP/CPPS (N = 28), as well as group of age-matched healthy male controls (N = 27), had resting state functional magnetic resonance imaging scans as part of the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Research Network study. Brain maps of the functional connectivity of pelvic-motor were compared between groups. A significant group difference was observed in the functional connectivity between pelvic-motor and the right posterior insula. The effect size of this group difference was among the largest effect sizes in functional connectivity between all pairs of 165 anatomically-defined subregions of the brain. Interestingly, many of the atlas region pairs with large effect sizes also involved other subregions of the insular cortices. We conclude that functional connectivity between motor cortex and the posterior insula may be among the most important markers of altered brain function in men with CP/CPPS, and may represent changes in the integration of viscerosensory and motor processing. PMID:26106574

Patterns of cell death in the perinatal mouse forebrain.

PubMed

Mosley, Morgan; Shah, Charisma; Morse, Kiriana A; Miloro, Stephen A; Holmes, Melissa M; Ahern, Todd H; Forger, Nancy G

2017-01-01

The importance of cell death in brain development has long been appreciated, but many basic questions remain, such as what initiates or terminates the cell death period. One obstacle has been the lack of quantitative data defining exactly when cell death occurs. We recently created a "cell death atlas," using the detection of activated caspase-3 (AC3) to quantify apoptosis in the postnatal mouse ventral forebrain and hypothalamus, and found that the highest rates of cell death were seen at the earliest postnatal ages in most regions. Here we have extended these analyses to prenatal ages and additional brain regions. We quantified cell death in 16 forebrain regions across nine perinatal ages from embryonic day (E) 17 to postnatal day (P) 11 and found that cell death peaks just after birth in most regions. We found greater cell death in several regions in offspring delivered vaginally on the day of parturition compared with those of the same postconception age but still in utero at the time of collection. We also found massive cell death in the oriens layer of the hippocampus on P1 and in regions surrounding the anterior crossing of the corpus callosum on E18 as well as the persistence of large numbers of cells in those regions in adult mice lacking the pro-death Bax gene. Together these findings suggest that birth may be an important trigger of neuronal cell death and identify transient cell groups that may undergo wholesale elimination perinatally. J. Comp. Neurol. 525:47-64, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Communication of brain network core connections altered in behavioral variant frontotemporal dementia but possibly preserved in early-onset Alzheimer's disease

NASA Astrophysics Data System (ADS)

Daianu, Madelaine; Jahanshad, Neda; Mendez, Mario F.; Bartzokis, George; Jimenez, Elvira E.; Thompson, Paul M.

2015-03-01

Diffusion imaging and brain connectivity analyses can assess white matter deterioration in the brain, revealing the underlying patterns of how brain structure declines. Fiber tractography methods can infer neural pathways and connectivity patterns, yielding sensitive mathematical metrics of network integrity. Here, we analyzed 1.5-Tesla wholebrain diffusion-weighted images from 64 participants - 15 patients with behavioral variant frontotemporal dementia (bvFTD), 19 with early-onset Alzheimer's disease (EOAD), and 30 healthy elderly controls. Using whole-brain tractography, we reconstructed structural brain connectivity networks to map connections between cortical regions. We evaluated the brain's networks focusing on the most highly central and connected regions, also known as hubs, in each diagnostic group - specifically the "high-cost" structural backbone used in global and regional communication. The high-cost backbone of the brain, predicted by fiber density and minimally short pathways between brain regions, accounted for 81-92% of the overall brain communication metric in all diagnostic groups. Furthermore, we found that the set of pathways interconnecting high-cost and high-capacity regions of the brain's communication network are globally and regionally altered in bvFTD, compared to healthy participants; however, the overall organization of the high-cost and high-capacity networks were relatively preserved in EOAD participants, relative to controls. Disruption of the major central hubs that transfer information between brain regions may impair neural communication and functional integrity in characteristic ways typical of each subtype of dementia.

A Response to the Legitimacy of Brain Death in Islam.

PubMed

Rady, Mohamed Y; Verheijde, Joseph L

2016-08-01

Brain death is a novel construct of death for the procurement of transplantable organs. Many authoritative Islamic organizations and governments have endorsed brain death as true death for organ donation. Many commentators have reiterated the misconception that the Quranic text does not define death. We respond by clarifying: (1) the Quran does define death as biologic disintegration and clearly distinguishes it from the dying process, (2) brain death belongs scientifically within the spectrum of neurologic disorders of consciousness and should not be confused with death, and (3) religious and legal discord about brain death has grown in jurisdictions worldwide. We urge for public transparency and truthfulness about brain death and the accommodation and respect of religious objection to the determination of death by neurologic criteria.

MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images

PubMed Central

Varando, Gherardo; Benavides-Piccione, Ruth; Muñoz, Alberto; Kastanauskaite, Asta; Bielza, Concha; Larrañaga, Pedro; DeFelipe, Javier

2018-01-01

The development of 3D visualization and reconstruction methods to analyse microscopic structures at different levels of resolutions is of great importance to define brain microorganization and connectivity. MultiMap is a new tool that allows the visualization, 3D segmentation and quantification of fluorescent structures selectively in the neuropil from large stacks of confocal microscopy images. The major contribution of this tool is the posibility to easily navigate and create regions of interest of any shape and size within a large brain area that will be automatically 3D segmented and quantified to determine the density of puncta in the neuropil. As a proof of concept, we focused on the analysis of glutamatergic and GABAergic presynaptic axon terminals in the mouse hippocampal region to demonstrate its use as a tool to provide putative excitatory and inhibitory synaptic maps. The segmentation and quantification method has been validated over expert labeled images of the mouse hippocampus and over two benchmark datasets, obtaining comparable results to the expert detections. PMID:29875639

MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images.

PubMed

Varando, Gherardo; Benavides-Piccione, Ruth; Muñoz, Alberto; Kastanauskaite, Asta; Bielza, Concha; Larrañaga, Pedro; DeFelipe, Javier

2018-01-01

The development of 3D visualization and reconstruction methods to analyse microscopic structures at different levels of resolutions is of great importance to define brain microorganization and connectivity. MultiMap is a new tool that allows the visualization, 3D segmentation and quantification of fluorescent structures selectively in the neuropil from large stacks of confocal microscopy images. The major contribution of this tool is the posibility to easily navigate and create regions of interest of any shape and size within a large brain area that will be automatically 3D segmented and quantified to determine the density of puncta in the neuropil. As a proof of concept, we focused on the analysis of glutamatergic and GABAergic presynaptic axon terminals in the mouse hippocampal region to demonstrate its use as a tool to provide putative excitatory and inhibitory synaptic maps. The segmentation and quantification method has been validated over expert labeled images of the mouse hippocampus and over two benchmark datasets, obtaining comparable results to the expert detections.

Metacognitive impairment in active cocaine use disorder is associated with individual differences in brain structure

PubMed Central

Moeller, Scott J.; Fleming, Stephen M.; Gan, Gabriela; Zilverstand, Anna; Malaker, Pias; Uquillas, Federico d’Oleire; Schneider, Kristin E.; Preston-Campbell, Rebecca; Parvaz, Muhammad A.; Maloney, Thomas; Alia-Klein, Nelly; Goldstein, Rita Z.

2016-01-01

Dysfunctional self-awareness has been posited as a key feature of drug addiction, contributing to compromised control over addictive behaviors. In the present investigation, we showed that, compared with healthy controls (n=13) and even individuals with remitted cocaine use disorder (n=14), individuals with active cocaine use disorder (n=8) exhibited deficits in basic metacognition, defined as a weaker link between objective performance and self-reported confidence of performance on a visuo-perceptual accuracy task. This metacognitive deficit was accompanied by gray matter volume decreases, also most pronounced in individuals with active cocaine use disorder, in the rostral anterior cingulate cortex, a region necessary for this function in health. Our results thus provide a direct unbiased measurement – not relying on long-term memory or multifaceted choice behavior – of metacognition deficits in drug addiction, which are further mapped onto structural deficits in a brain region that subserves metacognitive accuracy in health and self-awareness in drug addiction. Impairments of metacognition could provide a basic mechanism underlying the higher-order self-awareness deficits in addiction, particularly among recent, active users. PMID:26948669

Physiological Imaging-Defined, Response-Driven Subvolumes of a Tumor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farjam, Reza; Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Tsien, Christina I.

2013-04-01

Purpose: To develop an image analysis framework to delineate the physiological imaging-defined subvolumes of a tumor in relating to treatment response and outcome. Methods and Materials: Our proposed approach delineates the subvolumes of a tumor based on its heterogeneous distributions of physiological imaging parameters. The method assigns each voxel a probabilistic membership function belonging to the physiological parameter classes defined in a sample of tumors, and then calculates the related subvolumes in each tumor. We applied our approach to regional cerebral blood volume (rCBV) and Gd-DTPA transfer constant (K{sup trans}) images of patients who had brain metastases and were treatedmore » by whole-brain radiation therapy (WBRT). A total of 45 lesions were included in the analysis. Changes in the rCBV (or K{sup trans})–defined subvolumes of the tumors from pre-RT to 2 weeks after the start of WBRT (2W) were evaluated for differentiation of responsive, stable, and progressive tumors using the Mann-Whitney U test. Performance of the newly developed metrics for predicting tumor response to WBRT was evaluated by receiver operating characteristic (ROC) curve analysis. Results: The percentage decrease in the high-CBV-defined subvolumes of the tumors from pre-RT to 2W was significantly greater in the group of responsive tumors than in the group of stable and progressive tumors (P<.007). The change in the high-CBV-defined subvolumes of the tumors from pre-RT to 2W was a predictor for post-RT response significantly better than change in the gross tumor volume observed during the same time interval (P=.012), suggesting that the physiological change occurs before the volumetric change. Also, K{sup trans} did not add significant discriminatory information for assessing response with respect to rCBV. Conclusion: The physiological imaging-defined subvolumes of the tumors delineated by our method could be candidates for boost target, for which further development and evaluation is warranted.« less

Comprehensive Review on Magnetic Resonance Imaging in Alzheimer's Disease.

PubMed

Dona, Olga; Thompson, Jeff; Druchok, Cheryl

2016-01-01

Alzheimer's disease (AD) is the most common cause of dementia in the elderly. However, definitive diagnosis of AD is only achievable postmortem and currently relies on clinical neurological evaluation. Magnetic resonance imaging (MRI) can evaluate brain changes typical of AD, including brain atrophy, presence of amyloid β (Aβ) plaques, and functional and biochemical abnormalities. Structural MRI (sMRI) has historically been used to assess the inherent brain atrophy present in AD. However, new techniques have recently emerged that have refined sMRI into a more precise tool to quantify the thickness and volume of AD-sensitive cerebral structures. Aβ plaques, a defining pathology of AD, are widely believed to contribute to the progressive cognitive decline in AD, but accurate assessment is only possible on autopsy. In vivo MRI of plaques, although currently limited to mouse models of AD, is a very promising technique. Measuring changes in activation and connectivity in AD-specific regions of the brain can be performed with functional MRI (fMRI). To help distinguish AD from diseases with similar symptoms, magnetic resonance spectroscopy (MRS) can be used to look for differing metabolite concentrations in vivo. Together, these MR techniques, evaluating various brain changes typical of AD, may help to provide a more definitive diagnosis and ease the assessment of the disease over time, noninvasively.

Tools for neuroanatomy and neurogenetics in Drosophila

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pfeiffer, Barret D.; Jenett, Arnim; Hammonds, Ann S.

2008-08-11

We demonstrate the feasibility of generating thousands of transgenic Drosophila melanogaster lines in which the expression of an exogenous gene is reproducibly directed to distinct small subsets of cells in the adult brain. We expect the expression patterns produced by the collection of 5,000 lines that we are currently generating to encompass all neurons in the brain in a variety of intersecting patterns. Overlapping 3-kb DNA fragments from the flanking noncoding and intronic regions of genes thought to have patterned expression in the adult brain were inserted into a defined genomic location by site-specific recombination. These fragments were then assayedmore » for their ability to function as transcriptional enhancers in conjunction with a synthetic core promoter designed to work with a wide variety of enhancer types. An analysis of 44 fragments from four genes found that >80% drive expression patterns in the brain; the observed patterns were, on average, comprised of <100 cells. Our results suggest that the D. melanogaster genome contains >50,000 enhancers and that multiple enhancers drive distinct subsets of expression of a gene in each tissue and developmental stage. We expect that these lines will be valuable tools for neuroanatomy as well as for the elucidation of neuronal circuits and information flow in the fly brain.« less

Novel Intrinsic Ignition Method Measuring Local-Global Integration Characterizes Wakefulness and Deep Sleep

PubMed Central

Tagliazucchi, Enzo; Sanjuán, Ana

2017-01-01

Abstract A precise definition of a brain state has proven elusive. Here, we introduce the novel local-global concept of intrinsic ignition characterizing the dynamical complexity of different brain states. Naturally occurring intrinsic ignition events reflect the capability of a given brain area to propagate neuronal activity to other regions, giving rise to different levels of integration. The ignitory capability of brain regions is computed by the elicited level of integration for each intrinsic ignition event in each brain region, averaged over all events. This intrinsic ignition method is shown to clearly distinguish human neuroimaging data of two fundamental brain states (wakefulness and deep sleep). Importantly, whole-brain computational modelling of this data shows that at the optimal working point is found where there is maximal variability of the intrinsic ignition across brain regions. Thus, combining whole brain models with intrinsic ignition can provide novel insights into underlying mechanisms of brain states. PMID:28966977

Novel Intrinsic Ignition Method Measuring Local-Global Integration Characterizes Wakefulness and Deep Sleep.

PubMed

Deco, Gustavo; Tagliazucchi, Enzo; Laufs, Helmut; Sanjuán, Ana; Kringelbach, Morten L

2017-01-01

A precise definition of a brain state has proven elusive. Here, we introduce the novel local-global concept of intrinsic ignition characterizing the dynamical complexity of different brain states. Naturally occurring intrinsic ignition events reflect the capability of a given brain area to propagate neuronal activity to other regions, giving rise to different levels of integration. The ignitory capability of brain regions is computed by the elicited level of integration for each intrinsic ignition event in each brain region, averaged over all events. This intrinsic ignition method is shown to clearly distinguish human neuroimaging data of two fundamental brain states (wakefulness and deep sleep). Importantly, whole-brain computational modelling of this data shows that at the optimal working point is found where there is maximal variability of the intrinsic ignition across brain regions. Thus, combining whole brain models with intrinsic ignition can provide novel insights into underlying mechanisms of brain states.

Prediction of Blood-Brain Barrier Disruption and Intracerebral Hemorrhagic Infarction Using Arterial Spin-Labeling Magnetic Resonance Imaging.

PubMed

Niibo, Takeya; Ohta, Hajime; Miyata, Shirou; Ikushima, Ichiro; Yonenaga, Kazuchika; Takeshima, Hideo

2017-01-01

Arterial spin-labeling magnetic resonance imaging is sensitive for detecting hyperemic lesions (HLs) in patients with acute ischemic stroke. We evaluated whether HLs could predict blood-brain barrier (BBB) disruption and hemorrhagic transformation (HT) in acute ischemic stroke patients. In a retrospective study, arterial spin-labeling was performed within 6 hours of symptom onset before revascularization treatment in 25 patients with anterior circulation large vessel occlusion on baseline magnetic resonance angiography. All patients underwent angiographic procedures intended for endovascular therapy and a noncontrast computed tomography scan immediately after treatment. BBB disruption was defined as a hyperdense lesion present on the posttreatment computed tomography scan. A subacute magnetic resonance imaging or computed tomography scan was performed during the subacute phase to assess HTs. The relationship between HLs and BBB disruption and HT was examined using the Alberta Stroke Program Early Computed Tomography Score locations in the symptomatic hemispheres. A HL was defined as a region where CBF relative ≥1.4 (CBF relative =CBF HL /CBF contralateral ). HLs, BBB disruption, and HT were found in 9, 15, and 15 patients, respectively. Compared with the patients without HLs, the patients with HLs had a higher incidence of both BBB disruption (100% versus 37.5%; P=0.003) and HT (100% versus 37.5%; P=0.003). Based on the Alberta Stroke Program Early Computed Tomography Score locations, 21 regions of interests displayed HLs. Compared with the regions of interests without HLs, the regions of interests with HLs had a higher incidence of both BBB disruption (42.8% versus 3.9%; P<0.001) and HT (85.7% versus 7.8%; P<0.001). HLs detected on pretreatment arterial spin-labeling maps may enable the prediction and localization of subsequent BBB disruption and HT. © 2016 American Heart Association, Inc.

Asymmetric right/left encoding of emotions in the human subthalamic nucleus

PubMed Central

Eitan, Renana; Shamir, Reuben R.; Linetsky, Eduard; Rosenbluh, Ovadya; Moshel, Shay; Ben-Hur, Tamir; Bergman, Hagai; Israel, Zvi

2013-01-01

Emotional processing is lateralized to the non-dominant brain hemisphere. However, there is no clear spatial model for lateralization of emotional domains in the basal ganglia. The subthalamic nucleus (STN), an input structure in the basal ganglia network, plays a major role in the pathophysiology of Parkinson's disease (PD). This role is probably not limited only to the motor deficits of PD, but may also span the emotional and cognitive deficits commonly observed in PD patients. Beta oscillations (12–30 Hz), the electrophysiological signature of PD, are restricted to the dorsolateral part of the STN that corresponds to the anatomically defined sensorimotor STN. The more medial, more anterior and more ventral parts of the STN are thought to correspond to the anatomically defined limbic and associative territories of the STN. Surprisingly, little is known about the electrophysiological properties of the non-motor domains of the STN, nor about electrophysiological differences between right and left STNs. In this study, microelectrodes were utilized to record the STN spontaneous spiking activity and responses to vocal non-verbal emotional stimuli during deep brain stimulation (DBS) surgeries in human PD patients. The oscillation properties of the STN neurons were used to map the dorsal oscillatory and the ventral non-oscillatory regions of the STN. Emotive auditory stimulation evoked activity in the ventral non-oscillatory region of the right STN. These responses were not observed in the left ventral STN or in the dorsal regions of either the right or left STN. Therefore, our results suggest that the ventral non-oscillatory regions are asymmetrically associated with non-motor functions, with the right ventral STN associated with emotional processing. These results suggest that DBS of the right ventral STN may be associated with beneficial or adverse emotional effects observed in PD patients and may relieve mental symptoms in other neurological and psychiatric diseases. PMID:24194703

Brain Connectivity and Visual Attention

PubMed Central

Parks, Emily L.

2013-01-01

Abstract Emerging hypotheses suggest that efficient cognitive functioning requires the integration of separate, but interconnected cortical networks in the brain. Although task-related measures of brain activity suggest that a frontoparietal network is associated with the control of attention, little is known regarding how components within this distributed network act together or with other networks to achieve various attentional functions. This review considers both functional and structural studies of brain connectivity, as complemented by behavioral and task-related neuroimaging data. These studies show converging results: The frontal and parietal cortical regions are active together, over time, and identifiable frontoparietal networks are active in relation to specific task demands. However, the spontaneous, low-frequency fluctuations of brain activity that occur in the resting state, without specific task demands, also exhibit patterns of connectivity that closely resemble the task-related, frontoparietal attention networks. Both task-related and resting-state networks exhibit consistent relations to behavioral measures of attention. Further, anatomical structure, particularly white matter pathways as defined by diffusion tensor imaging, places constraints on intrinsic functional connectivity. Lastly, connectivity analyses applied to investigate cognitive differences across individuals in both healthy and diseased states suggest that disconnection of attentional networks is linked to deficits in cognitive functioning, and in extreme cases, to disorders of attention. Thus, comprehensive theories of visual attention and their clinical translation depend on the continued integration of behavioral, task-related neuroimaging, and brain connectivity measures. PMID:23597177

Nicotine and the adolescent brain

PubMed Central

Yuan, Menglu; Cross, Sarah J; Loughlin, Sandra E; Leslie, Frances M

2015-01-01

Adolescence encompasses a sensitive developmental period of enhanced clinical vulnerability to nicotine, tobacco, and e-cigarettes. While there are sociocultural influences, data at preclinical and clinical levels indicate that this adolescent sensitivity has strong neurobiological underpinnings. Although definitions of adolescence vary, the hallmark of this period is a profound reorganization of brain regions necessary for mature cognitive and executive function, working memory, reward processing, emotional regulation, and motivated behavior. Regulating critical facets of brain maturation are nicotinic acetylcholine receptors (nAChRs). However, perturbations of cholinergic systems during this time with nicotine, via tobacco or e-cigarettes, have unique consequences on adolescent development. In this review, we highlight recent clinical and preclinical data examining the adolescent brain's distinct neurobiology and unique sensitivity to nicotine. First, we discuss what defines adolescence before reviewing normative structural and neurochemical alterations that persist until early adulthood, with an emphasis on dopaminergic systems. We review how acute exposure to nicotine impacts brain development and how drug responses differ from those seen in adults. Finally, we discuss the persistent alterations in neuronal signaling and cognitive function that result from chronic nicotine exposure, while highlighting a low dose, semi-chronic exposure paradigm that may better model adolescent tobacco use. We argue that nicotine exposure, increasingly occurring as a result of e-cigarette use, may induce epigenetic changes that sensitize the brain to other drugs and prime it for future substance abuse. PMID:26018031

COMPLEXITY AND HETEROGENEITY: WHAT DRIVES THE EVER-CHANGING BRAIN IN HUNTINGTONS DISEASE?

PubMed Central

Rosas, H. Diana; Salat, David H; Lee, Stephanie Y; Zaleta, Alexandra K; Hevelone, Nathanael; Hersch, Steven M.

2008-01-01

Significant advances are being made in our understanding of basic pathophyiological and biochemical mechanisms that cause HuntingtonÕs disease (HD). There is increasing reason to believe that pathologic alterations occur in the brain for years before symptoms manifest. The “classic” hallmark of neuropathology in HD is selective neurodegeneration in which vulnerable populations of neurons degenerate while less vulnerable populations are spared. While, the earliest and most striking neuropathologic changes have been found in the neostriatum, neuronal loss has been identified in many other regions of the brain. We report topologically selective, early, and progressive changes in the cortex, striatum, extra-striatal brain structures and white matter throughout the spectrum of disease. Our growing understanding of HD underscores the reality that points to the complexity of HD. A single, well-defined genetic mutation causes a cascade of events whose final result is an aggregate insult of the homeostatic process. We explore possible explanations for the selective vulnerability of the brain in HD. The ultimate goal in HD is to develop disease-modifying therapies that will prevent the onset of clinical symptoms in those individuals who are at risk and slow the progression of symptoms in those individuals already affected with symptoms. Understanding changes in brain morphometry and their relationship to clinical symptoms may provide important new and important insights into basic pathophysiological mechanisms at play in the disease. PMID:19076442

Tracking the Reorganization of Module Structure in Time-Varying Weighted Brain Functional Connectivity Networks.

PubMed

Schmidt, Christoph; Piper, Diana; Pester, Britta; Mierau, Andreas; Witte, Herbert

2018-05-01

Identification of module structure in brain functional networks is a promising way to obtain novel insights into neural information processing, as modules correspond to delineated brain regions in which interactions are strongly increased. Tracking of network modules in time-varying brain functional networks is not yet commonly considered in neuroscience despite its potential for gaining an understanding of the time evolution of functional interaction patterns and associated changing degrees of functional segregation and integration. We introduce a general computational framework for extracting consensus partitions from defined time windows in sequences of weighted directed edge-complete networks and show how the temporal reorganization of the module structure can be tracked and visualized. Part of the framework is a new approach for computing edge weight thresholds for individual networks based on multiobjective optimization of module structure quality criteria as well as an approach for matching modules across time steps. By testing our framework using synthetic network sequences and applying it to brain functional networks computed from electroencephalographic recordings of healthy subjects that were exposed to a major balance perturbation, we demonstrate the framework's potential for gaining meaningful insights into dynamic brain function in the form of evolving network modules. The precise chronology of the neural processing inferred with our framework and its interpretation helps to improve the currently incomplete understanding of the cortical contribution for the compensation of such balance perturbations.

Synthetic event-related potentials: a computational bridge between neurolinguistic models and experiments.

PubMed

Barrès, Victor; Simons, Arthur; Arbib, Michael

2013-01-01

Our previous work developed Synthetic Brain Imaging to link neural and schema network models of cognition and behavior to PET and fMRI studies of brain function. We here extend this approach to Synthetic Event-Related Potentials (Synthetic ERP). Although the method is of general applicability, we focus on ERP correlates of language processing in the human brain. The method has two components: Phase 1: To generate cortical electro-magnetic source activity from neural or schema network models; and Phase 2: To generate known neurolinguistic ERP data (ERP scalp voltage topographies and waveforms) from putative cortical source distributions and activities within a realistic anatomical model of the human brain and head. To illustrate the challenges of Phase 2 of the methodology, spatiotemporal information from Friederici's 2002 model of auditory language comprehension was used to define cortical regions and time courses of activation for implementation within a forward model of ERP data. The cortical regions from the 2002 model were modeled using atlas-based masks overlaid on the MNI high definition single subject cortical mesh. The electromagnetic contribution of each region was modeled using current dipoles whose position and orientation were constrained by the cortical geometry. In linking neural network computation via EEG forward modeling to empirical results in neurolinguistics, we emphasize the need for neural network models to link their architecture to geometrically sound models of the cortical surface, and the need for conceptual models to refine and adopt brain-atlas based approaches to allow precise brain anchoring of their modules. The detailed analysis of Phase 2 sets the stage for a brief introduction to Phase 1 of the program, including the case for a schema-theoretic approach to language production and perception presented in detail elsewhere. Unlike Dynamic Causal Modeling (DCM) and Bojak's mean field model, Synthetic ERP builds on models of networks that mediate the relation between the brain's inputs, outputs, and internal states in executing a specific task. The neural networks used for Synthetic ERP must include neuroanatomically realistic placement and orientation of the cortical pyramidal neurons. These constraints pose exciting challenges for future work in neural network modeling that is applicable to systems and cognitive neuroscience. Copyright © 2012 Elsevier Ltd. All rights reserved.

Emerging Trends in the Management of Brain Metastases from Non-small Cell Lung Cancer.

PubMed

Churilla, Thomas M; Weiss, Stephanie E

2018-05-07

To summarize current approaches in the management of brain metastases from non-small cell lung cancer (NSCLC). Local treatment has evolved from whole-brain radiotherapy (WBRT) to increasing use of stereotactic radiosurgery (SRS) alone for patients with limited (1-4) brain metastases. Trials have established post-operative SRS as an alternative to adjuvant WBRT following resection of brain metastases. Second-generation TKIs for ALK rearranged NSCLC have demonstrated improved CNS penetration and activity. Current brain metastasis trials are focused on reducing cognitive toxicity: hippocampal sparing WBRT, SRS for 5-15 metastases, pre-operative SRS, and use of systemic targeted agents or immunotherapy. The role for radiotherapy in the management of brain metastases is becoming better defined with local treatment shifting from WBRT to SRS alone for limited brain metastases and post-operative SRS for resected metastases. Further trials are warranted to define the optimal integration of newer systemic agents with local therapies.

Regional brain volumetry and brain function in severely brain-injured patients.

PubMed

Annen, Jitka; Frasso, Gianluca; Crone, Julia Sophia; Heine, Lizette; Di Perri, Carol; Martial, Charlotte; Cassol, Helena; Demertzi, Athena; Naccache, Lionel; Laureys, Steven

2018-04-01

The relationship between residual brain tissue in patients with disorders of consciousness (DOC) and the clinical condition is unclear. This observational study aimed to quantify gray (GM) and white matter (WM) atrophy in states of (altered) consciousness. Structural T1-weighted magnetic resonance images were processed for 102 severely brain-injured and 52 healthy subjects. Regional brain volume was quantified for 158 (sub)cortical regions using Freesurfer. The relationship between regional brain volume and clinical characteristics of patients with DOC and conscious brain-injured patients was assessed using a linear mixed-effects model. Classification of patients with unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS) using regional volumetric information was performed and compared to classification using cerebral glucose uptake from fluorodeoxyglucose positron emission tomography. For validation, the T1-based classifier was tested on independent datasets. Patients were characterized by smaller regional brain volumes than healthy subjects. Atrophy occurred faster in UWS compared to MCS (GM) and conscious (GM and WM) patients. Classification was successful (misclassification with leave-one-out cross-validation between 2% and 13%) and generalized to the independent data set with an area under the receiver operator curve of 79% (95% confidence interval [CI; 67-91.5]) for GM and 70% (95% CI [55.6-85.4]) for WM. Brain volumetry at the single-subject level reveals that regions in the default mode network and subcortical gray matter regions, as well as white matter regions involved in long range connectivity, are most important to distinguish levels of consciousness. Our findings suggest that changes of brain structure provide information in addition to the assessment of functional neuroimaging and thus should be evaluated as well. Ann Neurol 2018;83:842-853. © 2018 American Neurological Association.

Two-photon NADH imaging exposes boundaries of oxygen diffusion in cortical vascular supply regions

PubMed Central

Kasischke, Karl A; Lambert, Elton M; Panepento, Ben; Sun, Anita; Gelbard, Harris A; Burgess, Robert W; Foster, Thomas H; Nedergaard, Maiken

2011-01-01

Oxygen transport imposes a possible constraint on the brain's ability to sustain variable metabolic demands, but oxygen diffusion in the cerebral cortex has not yet been observed directly. We show that concurrent two-photon fluorescence imaging of endogenous nicotinamide adenine dinucleotide (NADH) and the cortical microcirculation exposes well-defined boundaries of tissue oxygen diffusion in the mouse cortex. The NADH fluorescence increases rapidly over a narrow, very low pO2 range with a p50 of 3.4±0.6 mm Hg, thereby establishing a nearly binary reporter of significant, metabolically limiting hypoxia. The transient cortical tissue boundaries of NADH fluorescence exhibit remarkably delineated geometrical patterns, which define the limits of tissue oxygen diffusion from the cortical microcirculation and bear a striking resemblance to the ideal Krogh tissue cylinder. The visualization of microvessels and their regional contribution to oxygen delivery establishes penetrating arterioles as major oxygen sources in addition to the capillary network and confirms the existence of cortical oxygen fields with steep microregional oxygen gradients. Thus, two-photon NADH imaging can be applied to expose vascular supply regions and to localize functionally relevant microregional cortical hypoxia with micrometer spatial resolution. PMID:20859293

Two-photon NADH imaging exposes boundaries of oxygen diffusion in cortical vascular supply regions.

PubMed

Kasischke, Karl A; Lambert, Elton M; Panepento, Ben; Sun, Anita; Gelbard, Harris A; Burgess, Robert W; Foster, Thomas H; Nedergaard, Maiken

2011-01-01

Oxygen transport imposes a possible constraint on the brain's ability to sustain variable metabolic demands, but oxygen diffusion in the cerebral cortex has not yet been observed directly. We show that concurrent two-photon fluorescence imaging of endogenous nicotinamide adenine dinucleotide (NADH) and the cortical microcirculation exposes well-defined boundaries of tissue oxygen diffusion in the mouse cortex. The NADH fluorescence increases rapidly over a narrow, very low pO(2) range with a p(50) of 3.4 ± 0.6 mm Hg, thereby establishing a nearly binary reporter of significant, metabolically limiting hypoxia. The transient cortical tissue boundaries of NADH fluorescence exhibit remarkably delineated geometrical patterns, which define the limits of tissue oxygen diffusion from the cortical microcirculation and bear a striking resemblance to the ideal Krogh tissue cylinder. The visualization of microvessels and their regional contribution to oxygen delivery establishes penetrating arterioles as major oxygen sources in addition to the capillary network and confirms the existence of cortical oxygen fields with steep microregional oxygen gradients. Thus, two-photon NADH imaging can be applied to expose vascular supply regions and to localize functionally relevant microregional cortical hypoxia with micrometer spatial resolution.

EXACT DOSE X-IRRADIATION OF VARIOUS REGIONS OF THE HEAD AND VISUAL SENSATIONS--X-RAY LOCATION METHOD OF STUDY OF THE REACTIVITY OF THE CENTRAL NERVOUS SYSTEM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gurtovoi, G.K.; Burdianskaya, E.O.

1960-01-01

The primary substrate excited by threshold doses of x radiation of the normal human eye causes perception of a light flash in the retinal region. The threshold dose for the retina is about 1 mr; the threshold absorbed dose is about 1 mrad. Persons with a removed eyeball, on irradiation of the operated region with a frontal x-ray beam, perceive a flash of light at definite doses of radiation. Six persons taking part in an experiment saw a flash at doses of 17 to 150 mr (different observers saw flash at different doses) and did not see flash at dosesmore » of 5 to 90 mr. The cause of x-ray phosphene on frontal irradiation of the region of the removed eye with threshold doses is neither the reactivity of the optic nerve stump, the reactivity of the parts of the brain irradiated, nor the sensitivity of the skin receptors. In the cases considered, the cause of x-ray phosphene was irradiation of the retina of the nomnal eye by scattered x rays. The averaged coefficient of scatter was about 2%. On irradiation of the occiptal regions of the brain in subjects with normal eyes at a dose of about 150 mr, one subject perceived a flash of light. In this case, the absorbed dose for the occipital regions of the brain was about 40 mrad. The reason for this phenomenon must be explored. Stimulation of the cerebral formations (after atrophic changes in the visual tract and cortex) by x radia tion with a dose of up to 3 r, did not cause visual sensations. With the disposition of the beam, the absorbed dose for the chiasma was about 1 rad and for the occipital regions about 0.2 rad. In the study of threshold visual sensation and their causes on x irradiation of various regions of the head, it is important to apply defined doses of radiation. Scatter of the x rays in the head must be taken into consideration. (auth)« less

Brain region distribution and patterns of bioaccumulative perfluoroalkyl carboxylates and sulfonates in east greenland polar bears (Ursus maritimus).

PubMed

Greaves, Alana K; Letcher, Robert J; Sonne, Christian; Dietz, Rune

2013-03-01

The present study investigated the comparative accumulation of perfluoroalkyl acids (PFAAs) in eight brain regions of polar bears (Ursus maritimus, n = 19) collected in 2006 from Scoresby Sound, East Greenland. The PFAAs studied were perfluoroalkyl carboxylates (PFCAs, C(6) -C(15) chain lengths) and sulfonates (C(4) , C(6) , C(8) , and C(10) chain lengths) as well as selected precursors including perfluorooctane sulfonamide. On a wet-weight basis, blood-brain barrier transport of PFAAs occurred for all brain regions, although inner regions of the brain closer to incoming blood flow (pons/medulla, thalamus, and hypothalamus) contained consistently higher PFAA concentrations compared to outer brain regions (cerebellum, striatum, and frontal, occipital, and temporal cortices). For pons/medulla, thalamus, and hypothalamus, the most concentrated PFAAs were perfluorooctane sulfonate (PFOS), ranging from 47 to 58 ng/g wet weight, and perfluorotridecanoic acid, ranging from 43 to 49 ng/g wet weight. However, PFOS and the longer-chain PFCAs (C(10) -C(15) ) were significantly (p < 0.002) positively correlated with lipid content for all brain regions. Lipid-normalized PFOS and PFCA (C(10) -C(15) ) concentrations were not significantly (p > 0.05) different among brain regions. The burden of the sum of PFCAs, perfluoroalkyl sulfonates, and perfluorooctane sulfonamide in the brain (average mass, 392 g) was estimated to be 46 µg. The present study demonstrates that both PFCAs and perfluoroalkyl sulfonates cross the blood-brain barrier in polar bears and that wet-weight concentrations are brain region-specific. Copyright © 2012 SETAC.

The Representation of Object-Directed Action and Function Knowledge in the Human Brain.

PubMed

Chen, Quanjing; Garcea, Frank E; Mahon, Bradford Z

2016-04-01

The appropriate use of everyday objects requires the integration of action and function knowledge. Previous research suggests that action knowledge is represented in frontoparietal areas while function knowledge is represented in temporal lobe regions. Here we used multivoxel pattern analysis to investigate the representation of object-directed action and function knowledge while participants executed pantomimes of familiar tool actions. A novel approach for decoding object knowledge was used in which classifiers were trained on one pair of objects and then tested on a distinct pair; this permitted a measurement of classification accuracy over and above object-specific information. Region of interest (ROI) analyses showed that object-directed actions could be decoded in tool-preferring regions of both parietal and temporal cortex, while no independently defined tool-preferring ROI showed successful decoding of object function. However, a whole-brain searchlight analysis revealed that while frontoparietal motor and peri-motor regions are engaged in the representation of object-directed actions, medial temporal lobe areas in the left hemisphere are involved in the representation of function knowledge. These results indicate that both action and function knowledge are represented in a topographically coherent manner that is amenable to study with multivariate approaches, and that the left medial temporal cortex represents knowledge of object function. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Functional brain microstate predicts the outcome in a visuospatial working memory task.

PubMed

Muthukrishnan, Suriya-Prakash; Ahuja, Navdeep; Mehta, Nalin; Sharma, Ratna

2016-11-01

Humans have limited capacity of processing just up to 4 integrated items of information in the working memory. Thus, it is inevitable to commit more errors when challenged with high memory loads. However, the neural mechanisms that determine the accuracy of response at high memory loads still remain unclear. High temporal resolution of Electroencephalography (EEG) technique makes it the best tool to resolve the temporal dynamics of brain networks. EEG-defined microstate is the quasi-stable scalp electrical potential topography that represents the momentary functional state of brain. Thus, it has been possible to assess the information processing currently performed by the brain using EEG microstate analysis. We hypothesize that the EEG microstate preceding the trial could determine its outcome in a visuospatial working memory (VSWM) task. Twenty-four healthy participants performed a high memory load VSWM task, while their brain activity was recorded using EEG. Four microstate maps were found to represent the functional brain state prior to the trials in the VSWM task. One pre-trial microstate map was found to determine the accuracy of subsequent behavioural response. The intracranial generators of the pre-trial microstate map that determined the response accuracy were localized to the visuospatial processing areas at bilateral occipital, right temporal and limbic cortices. Our results imply that the behavioural outcome in a VSWM task could be determined by the intensity of activation of memory representations in the visuospatial processing brain regions prior to the trial. Copyright © 2016 Elsevier B.V. All rights reserved.

Marijuana and cannabinoid regulation of brain reward circuits.

PubMed

Lupica, Carl R; Riegel, Arthur C; Hoffman, Alexander F

2004-09-01

The reward circuitry of the brain consists of neurons that synaptically connect a wide variety of nuclei. Of these brain regions, the ventral tegmental area (VTA) and the nucleus accumbens (NAc) play central roles in the processing of rewarding environmental stimuli and in drug addiction. The psychoactive properties of marijuana are mediated by the active constituent, Delta(9)-THC, interacting primarily with CB1 cannabinoid receptors in a large number of brain areas. However, it is the activation of these receptors located within the central brain reward circuits that is thought to play an important role in sustaining the self-administration of marijuana in humans, and in mediating the anxiolytic and pleasurable effects of the drug. Here we describe the cellular circuitry of the VTA and the NAc, define the sites within these areas at which cannabinoids alter synaptic processes, and discuss the relevance of these actions to the regulation of reinforcement and reward. In addition, we compare the effects of Delta(9)-THC with those of other commonly abused drugs on these reward circuits, and we discuss the roles that endogenous cannabinoids may play within these brain pathways, and their possible involvement in regulating ongoing brain function, independently of marijuana consumption. We conclude that, whereas Delta(9)-THC alters the activity of these central reward pathways in a manner that is consistent with other abused drugs, the cellular mechanism through which this occurs is likely different, relying upon the combined regulation of several afferent pathways to the VTA.

Regional infant brain development: an MRI-based morphometric analysis in 3 to 13 month olds.

PubMed

Choe, Myong-Sun; Ortiz-Mantilla, Silvia; Makris, Nikos; Gregas, Matt; Bacic, Janine; Haehn, Daniel; Kennedy, David; Pienaar, Rudolph; Caviness, Verne S; Benasich, April A; Grant, P Ellen

2013-09-01

Elucidation of infant brain development is a critically important goal given the enduring impact of these early processes on various domains including later cognition and language. Although infants' whole-brain growth rates have long been available, regional growth rates have not been reported systematically. Accordingly, relatively less is known about the dynamics and organization of typically developing infant brains. Here we report global and regional volumetric growth of cerebrum, cerebellum, and brainstem with gender dimorphism, in 33 cross-sectional scans, over 3 to 13 months, using T1-weighted 3-dimensional spoiled gradient echo images and detailed semi-automated brain segmentation. Except for the midbrain and lateral ventricles, all absolute volumes of brain regions showed significant growth, with 6 different patterns of volumetric change. When normalized to the whole brain, the regional increase was characterized by 5 differential patterns. The putamen, cerebellar hemispheres, and total cerebellum were the only regions that showed positive growth in the normalized brain. Our results show region-specific patterns of volumetric change and contribute to the systematic understanding of infant brain development. This study greatly expands our knowledge of normal development and in future may provide a basis for identifying early deviation above and beyond normative variation that might signal higher risk for neurological disorders.

Regional Infant Brain Development: An MRI-Based Morphometric Analysis in 3 to 13 Month Olds

PubMed Central

Choe, Myong-sun; Ortiz-Mantilla, Silvia; Makris, Nikos; Gregas, Matt; Bacic, Janine; Haehn, Daniel; Kennedy, David; Pienaar, Rudolph; Caviness, Verne S.; Benasich, April A.; Grant, P. Ellen

2013-01-01

Elucidation of infant brain development is a critically important goal given the enduring impact of these early processes on various domains including later cognition and language. Although infants’ whole-brain growth rates have long been available, regional growth rates have not been reported systematically. Accordingly, relatively less is known about the dynamics and organization of typically developing infant brains. Here we report global and regional volumetric growth of cerebrum, cerebellum, and brainstem with gender dimorphism, in 33 cross-sectional scans, over 3 to 13 months, using T1-weighted 3-dimensional spoiled gradient echo images and detailed semi-automated brain segmentation. Except for the midbrain and lateral ventricles, all absolute volumes of brain regions showed significant growth, with 6 different patterns of volumetric change. When normalized to the whole brain, the regional increase was characterized by 5 differential patterns. The putamen, cerebellar hemispheres, and total cerebellum were the only regions that showed positive growth in the normalized brain. Our results show region-specific patterns of volumetric change and contribute to the systematic understanding of infant brain development. This study greatly expands our knowledge of normal development and in future may provide a basis for identifying early deviation above and beyond normative variation that might signal higher risk for neurological disorders. PMID:22772652

Carnosine reverses the aging-induced down regulation of brain regional serotonergic system.

PubMed

Banerjee, Soumyabrata; Ghosh, Tushar K; Poddar, Mrinal K

2015-12-01

The purpose of the present investigation was to study the role of carnosine, an endogenous dipeptide biomolecule, on brain regional (cerebral cortex, hippocampus, hypothalamus and pons-medulla) serotonergic system during aging. Results showed an aging-induced brain region specific significant (a) increase in Trp (except cerebral cortex) and their 5-HIAA steady state level with an increase in their 5-HIAA accumulation and declination, (b) decrease in their both 5-HT steady state level and 5-HT accumulation (except cerebral cortex). A significant decrease in brain regional 5-HT/Trp ratio (except cerebral cortex) and increase in 5-HIAA/5-HT ratio were also observed during aging. Carnosine at lower dosages (0.5-1.0μg/Kg/day, i.t. for 21 consecutive days) didn't produce any significant response in any of the brain regions, but higher dosages (2.0-2.5μg/Kg/day, i.t. for 21 consecutive days) showed a significant response on those aging-induced brain regional serotonergic parameters. The treatment with carnosine (2.0μg/Kg/day, i.t. for 21 consecutive days), attenuated these brain regional aging-induced serotonergic parameters and restored towards their basal levels that observed in 4 months young control rats. These results suggest that carnosine attenuates and restores the aging-induced brain regional down regulation of serotonergic system towards that observed in young rats' brain regions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Fatigue: Is it all neurochemistry?

PubMed

Meeusen, Romain; Roelands, Bart

2018-02-01

Fatigue during exercise can be approached from different angles. Peripheral fatigue is usually described as an impairment located in the muscle and characterized by a metabolic end point, while central fatigue is defined as a failure of the central nervous system to adequately drive the muscle. The aim of the present narrative review paper is to look at the mechanisms involved in the occurrence of fatigue during prolonged exercise, predominantly from a brain neurochemical point of view. From studies in rodents it is clear that exercise increases the release of several neurotransmitters in different brain regions, and that the onset of fatigue can be manipulated when dopaminergic influx in the preoptic and anterior hypothalamus is increased, interfering with thermoregulation. This is however not as straightforward in humans, in which most studies manipulating brain neurotransmission failed to change the onset of fatigue in normal ambient temperatures. When the ambient temperature was increased, dopaminergic and combined dopaminergic and noradrenergic reuptake inhibition appeared to override a safety switch, allowing subjects to push harder and become much warmer, without changing their perception. In general, we can conclude that brain neurochemistry is clearly involved in the complex regulation of fatigue, but many other mediators also play a role.

The usefulness of sLORETA in evaluating the effect of high-dose ARA-C on brain connectivity in patients with acute myeloid leukemia: an exploratory study

PubMed Central

Zarabla, Alessia; Ungania, Sara; Cacciatore, Alessandra; Maialetti, Andrea; Petreri, Gianluca; Mengarelli, Andrea; Spadea, Antonio; Marchesi, Francesco; Renzi, Daniela; Gumenyuk, Svitlana; Strigari, Lidia; Maschio, Marta

2017-01-01

Summary Cytosine arabinoside (Ara-C) is one of the key drugs for treating acute myeloid leukemia (AML). High intravenous doses may produce a number of central nervous system (CNS) toxicities and contribute to modifications in brain functional connectivity. sLORETA is a software used for localizing brain electrical activity and functional connectivity. The aim of this study was to apply sLORETA in the evaluation of possible effects of Ara-C on brain connectivity in patients with AML without CNS involvement. We studied eight patients with AML; four were administered standard doses of Ara-C while the other four received high doses. sLORETA was computed from computerized EEG data before treatment and after six months of treatment. Three regions of interest, corresponding to specific combinations of Brodmann areas, were defined. In the patients receiving high-dose Ara-C, a statistically significant reduction in functional connectivity was observed in the frontoparietal network, which literature data suggest is involved in attentional processes. Our data highlight the possibility of using novel techniques to study potential CNS toxicity of cancer therapy.

Deep brain optical measurements of cell type-specific neural activity in behaving mice.

PubMed

Cui, Guohong; Jun, Sang Beom; Jin, Xin; Luo, Guoxiang; Pham, Michael D; Lovinger, David M; Vogel, Steven S; Costa, Rui M

2014-01-01

Recent advances in genetically encoded fluorescent sensors enable the monitoring of cellular events from genetically defined groups of neurons in vivo. In this protocol, we describe how to use a time-correlated single-photon counting (TCSPC)-based fiber optics system to measure the intensity, emission spectra and lifetime of fluorescent biosensors expressed in deep brain structures in freely moving mice. When combined with Cre-dependent selective expression of genetically encoded Ca(2+) indicators (GECIs), this system can be used to measure the average neural activity from a specific population of cells in mice performing complex behavioral tasks. As an example, we used viral expression of GCaMPs in striatal projection neurons (SPNs) and recorded the fluorescence changes associated with calcium spikes from mice performing a lever-pressing operant task. The whole procedure, consisting of virus injection, behavior training and optical recording, takes 3-4 weeks to complete. With minor adaptations, this protocol can also be applied to recording cellular events from other cell types in deep brain regions, such as dopaminergic neurons in the ventral tegmental area. The simultaneously recorded fluorescence signals and behavior events can be used to explore the relationship between the neural activity of specific brain circuits and behavior.

Age-Related Effects and Sex Differences in Gray Matter Density, Volume, Mass, and Cortical Thickness from Childhood to Young Adulthood.

PubMed

Gennatas, Efstathios D; Avants, Brian B; Wolf, Daniel H; Satterthwaite, Theodore D; Ruparel, Kosha; Ciric, Rastko; Hakonarson, Hakon; Gur, Raquel E; Gur, Ruben C

2017-05-17

Developmental structural neuroimaging studies in humans have long described decreases in gray matter volume (GMV) and cortical thickness (CT) during adolescence. Gray matter density (GMD), a measure often assumed to be highly related to volume, has not been systematically investigated in development. We used T1 imaging data collected on the Philadelphia Neurodevelopmental Cohort to study age-related effects and sex differences in four regional gray matter measures in 1189 youths ranging in age from 8 to 23 years. Custom T1 segmentation and a novel high-resolution gray matter parcellation were used to extract GMD, GMV, gray matter mass (GMM; defined as GMD × GMV), and CT from 1625 brain regions. Nonlinear models revealed that each modality exhibits unique age-related effects and sex differences. While GMV and CT generally decrease with age, GMD increases and shows the strongest age-related effects, while GMM shows a slight decline overall. Females have lower GMV but higher GMD than males throughout the brain. Our findings suggest that GMD is a prime phenotype for the assessment of brain development and likely cognition and that periadolescent gray matter loss may be less pronounced than previously thought. This work highlights the need for combined quantitative histological MRI studies. SIGNIFICANCE STATEMENT This study demonstrates that different MRI-derived gray matter measures show distinct age and sex effects and should not be considered equivalent but complementary. It is shown for the first time that gray matter density increases from childhood to young adulthood, in contrast with gray matter volume and cortical thickness, and that females, who are known to have lower gray matter volume than males, have higher density throughout the brain. A custom preprocessing pipeline and a novel high-resolution parcellation were created to analyze brain scans of 1189 youths collected as part of the Philadelphia Neurodevelopmental Cohort. A clear understanding of normal structural brain development is essential for the examination of brain-behavior relationships, the study of brain disease, and, ultimately, clinical applications of neuroimaging. Copyright © 2017 the authors 0270-6474/17/375065-09$15.00/0.

The effect of face inversion for neurons inside and outside fMRI-defined face-selective cortical regions

PubMed Central

Van Belle, Goedele; Vanduffel, Wim; Rossion, Bruno; Vogels, Rufin

2014-01-01

It is widely believed that face processing in the primate brain occurs in a network of category-selective cortical regions. Combined functional MRI (fMRI)-single-cell recording studies in macaques have identified high concentrations of neurons that respond more to faces than objects within face-selective patches. However, cells with a preference for faces over objects are also found scattered throughout inferior temporal (IT) cortex, raising the question whether face-selective cells inside and outside of the face patches differ functionally. Here, we compare the properties of face-selective cells inside and outside of face-selective patches in the IT cortex by means of an image manipulation that reliably disrupts behavior toward face processing: inversion. We recorded IT neurons from two fMRI-defined face-patches (ML and AL) and a region outside of the face patches (herein labeled OUT) during upright and inverted face stimulation. Overall, turning faces upside down reduced the firing rate of face-selective cells. However, there were differences among the recording regions. First, the reduced neuronal response for inverted faces was independent of stimulus position, relative to fixation, in the face-selective patches (ML and AL) only. Additionally, the effect of inversion for face-selective cells in ML, but not those in AL or OUT, was impervious to whether the neurons were initially searched for using upright or inverted stimuli. Collectively, these results show that face-selective cells differ in their functional characteristics depending on their anatomicofunctional location, suggesting that upright faces are preferably coded by face-selective cells inside but not outside of the fMRI-defined face-selective regions of the posterior IT cortex. PMID:25520434

Opportunistic Neurologic Infections in Patients with Acquired Immunodeficiency Syndrome (AIDS).

PubMed

Albarillo, Fritzie; O'Keefe, Paul

2016-01-01

Infections of the central nervous system (CNS) in individuals with human immunodeficiency virus (HIV) remain a substantial cause of morbidity and mortality despite the introduction of highly active antiretroviral therapy (HAART) especially in the resource-limited regions of the world. Diagnosis of these infections may be challenging because findings on cerebrospinal fluid (CSF) analysis and brain imaging are nonspecific. While brain biopsy provides a definitive diagnosis, it is an invasive procedure associated with a relatively low mortality rate, thus less invasive modalities have been studied in recent years. Diagnosis, therefore, can be established based on a combination of a compatible clinical syndrome, radiologic and CSF findings, and understanding of the role of HIV in these infections. The most common CNS opportunistic infections are AIDS-defining conditions; thus, treatment of these infections in combination with HAART has greatly improved survival.

Age- and brain region-dependent α-synuclein oligomerization is attributed to alterations in intrinsic enzymes regulating α-synuclein phosphorylation in aging monkey brains.

PubMed

Chen, Min; Yang, Weiwei; Li, Xin; Li, Xuran; Wang, Peng; Yue, Feng; Yang, Hui; Chan, Piu; Yu, Shun

2016-02-23

We previously reported that the levels of α-syn oligomers, which play pivotal pathogenic roles in age-related Parkinson's disease (PD) and dementia with Lewy bodies, increase heterogeneously in the aging brain. Here, we show that exogenous α-syn incubated with brain extracts from older cynomolgus monkeys and in Lewy body pathology (LBP)-susceptible brain regions (striatum and hippocampus) forms higher amounts of phosphorylated and oligomeric α-syn than that in extracts from younger monkeys and LBP-insusceptible brain regions (cerebellum and occipital cortex). The increased α-syn phosphorylation and oligomerization in the brain extracts from older monkeys and in LBP-susceptible brain regions were associated with higher levels of polo-like kinase 2 (PLK2), an enzyme promoting α-syn phosphorylation, and lower activity of protein phosphatase 2A (PP2A), an enzyme inhibiting α-syn phosphorylation, in these brain extracts. Further, the extent of the age- and brain-dependent increase in α-syn phosphorylation and oligomerization was reduced by inhibition of PLK2 and activation of PP2A. Inversely, phosphorylated α-syn oligomers reduced the activity of PP2A and showed potent cytotoxicity. In addition, the activity of GCase and the levels of ceramide, a product of GCase shown to activate PP2A, were lower in brain extracts from older monkeys and in LBP-susceptible brain regions. Our results suggest a role for altered intrinsic metabolic enzymes in age- and brain region-dependent α-syn oligomerization in aging brains.

Brain function in carriers of a genome-wide supported bipolar disorder variant.

PubMed

Erk, Susanne; Meyer-Lindenberg, Andreas; Schnell, Knut; Opitz von Boberfeld, Carola; Esslinger, Christine; Kirsch, Peter; Grimm, Oliver; Arnold, Claudia; Haddad, Leila; Witt, Stephanie H; Cichon, Sven; Nöthen, Markus M; Rietschel, Marcella; Walter, Henrik

2010-08-01

The neural abnormalities underlying genetic risk for bipolar disorder, a severe, common, and highly heritable psychiatric condition, are largely unknown. An opportunity to define these mechanisms is provided by the recent discovery, through genome-wide association, of a single-nucleotide polymorphism (rs1006737) strongly associated with bipolar disorder within the CACNA1C gene, encoding the alpha subunit of the L-type voltage-dependent calcium channel Ca(v)1.2. To determine whether the genetic risk associated with rs1006737 is mediated through hippocampal function. Functional magnetic resonance imaging study. University hospital. A total of 110 healthy volunteers of both sexes and of German descent in the Hardy-Weinberg equilibrium for rs1006737. Blood oxygen level-dependent signal during an episodic memory task and behavioral and psychopathological measures. Using an intermediate phenotype approach, we show that healthy carriers of the CACNA1C risk variant exhibit a pronounced reduction of bilateral hippocampal activation during episodic memory recall and diminished functional coupling between left and right hippocampal regions. Furthermore, risk allele carriers exhibit activation deficits of the subgenual anterior cingulate cortex, a region repeatedly associated with affective disorders and the mediation of adaptive stress-related responses. The relevance of these findings for affective disorders is supported by significantly higher psychopathology scores for depression, anxiety, obsessive-compulsive thoughts, interpersonal sensitivity, and neuroticism in risk allele carriers, correlating negatively with the observed regional brain activation. Our data demonstrate that rs1006737 or genetic variants in linkage disequilibrium with it are functional in the human brain and provide a neurogenetic risk mechanism for bipolar disorder backed by genome-wide evidence.

The use of stable xenon-enhanced computed tomographic studies of cerebral blood flow to define changes in cerebral carbon dioxide vasoresponsivity caused by a severe head injury.

PubMed

Marion, D W; Bouma, G J

1991-12-01

Previous studies using the xenon-133 cerebral blood flow (CBF) method have documented the impairment of CO2 vasoresponsivity after a severe head injury, but only global values can be obtained reliably with this technique. We studied CO2 vasoresponsivity using the stable xenon-enhanced computed tomographic CBF method, which provided information about well-defined cortical regions and deep brain structures not available with the xenon-133 method. In 17 patients with admission Glasgow Coma Scale scores of 8 or less, hemispheric CO2 vasoresponsivity ranged from 1.3 to 8.5% per mm Hg change in partial CO2 pressure. Lobar, cerebellar, basal ganglia, and brain stem CO2 vasoresponsivity frequently varied from the mean global value by more than 25%. In all but one patient, local CO2 vasoresponsivity in one or more of these areas differed from the mean global value by more than 50%. The greatest variability occurred in patients with acute subdural hematomas and diffuse (bihemispheric) injuries. This variability in CO2 vasoresponsivity has important implications for the effective and safe management of intracranial hypertension that frequently accompanies severe head injury.

The VALiDATe29 MRI Based Multi-Channel Atlas of the Squirrel Monkey Brain.

PubMed

Schilling, Kurt G; Gao, Yurui; Stepniewska, Iwona; Wu, Tung-Lin; Wang, Feng; Landman, Bennett A; Gore, John C; Chen, Li Min; Anderson, Adam W

2017-10-01

We describe the development of the first digital atlas of the normal squirrel monkey brain and present the resulting product, VALiDATe29. The VALiDATe29 atlas is based on multiple types of magnetic resonance imaging (MRI) contrast acquired on 29 squirrel monkeys, and is created using unbiased, nonlinear registration techniques, resulting in a population-averaged stereotaxic coordinate system. The atlas consists of multiple anatomical templates (proton density, T1, and T2* weighted), diffusion MRI templates (fractional anisotropy and mean diffusivity), and ex vivo templates (fractional anisotropy and a structural MRI). In addition, the templates are combined with histologically defined cortical labels, and diffusion tractography defined white matter labels. The combination of intensity templates and image segmentations make this atlas suitable for the fundamental atlas applications of spatial normalization and label propagation. Together, this atlas facilitates 3D anatomical localization and region of interest delineation, and enables comparisons of experimental data across different subjects or across different experimental conditions. This article describes the atlas creation and its contents, and demonstrates the use of the VALiDATe29 atlas in typical applications. The atlas is freely available to the scientific community.

Artistic creativity and dementia.

PubMed

Miller, Zachary A; Miller, Bruce L

2013-01-01

Artistic ability and creativity are defining characteristics of human behavior. Behavioral neurology, as a specialty, believes that even the most complex behaviors can be modeled and understood as the summation of smaller cognitive functions. Literature from individuals with specific brain lesions has helped to map out these smaller regions of cognitive abilities. More recently, models based on neurodegenerative conditions, especially from the frontotemporal dementias, have allowed for greater nuanced investigations into the various functional anatomies necessary for artistic behavior and possibly the underlying networks that promote creativity. © 2013 Elsevier B.V. All rights reserved.

Assessing Relevance of External Cognitive Measures.

PubMed

Cairó, Osvaldo

2017-01-01

The arrival of modern brain imaging technologies has provided new opportunities for examining the biological essence of human intelligence as well as the relationship between brain size and cognition. Thanks to these advances, we can now state that the relationship between brain size and intelligence has never been well understood. This view is supported by findings showing that cognition is correlated more with brain tissues than sheer brain size. The complexity of cellular and molecular organization of neural connections actually determines the computational capacity of the brain. In this review article, we determine that while genotypes are responsible for defining the theoretical limits of intelligence, what is primarily responsible for determining whether those limits are reached or exceeded is experience (environmental influence). Therefore, we contend that the gene-environment interplay defines the intelligent quotient of an individual.

Intrinsic network activity in tinnitus investigated using functional MRI

PubMed Central

Leaver, Amber M.; Turesky, Ted K.; Seydell-Greenwald, Anna; Morgan, Susan; Kim, Hung J.; Rauschecker, Josef P.

2016-01-01

Tinnitus is an increasingly common disorder in which patients experience phantom auditory sensations, usually ringing or buzzing in the ear. Tinnitus pathophysiology has been repeatedly shown to involve both auditory and non-auditory brain structures, making network-level studies of tinnitus critical. In this magnetic resonance imaging (MRI) study, we used two resting-state functional connectivity (RSFC) approaches to better understand functional network disturbances in tinnitus. First, we demonstrated tinnitus-related reductions in RSFC between specific brain regions and resting-state networks (RSNs), defined by independent components analysis (ICA) and chosen for their overlap with structures known to be affected in tinnitus. Then, we restricted ICA to data from tinnitus patients, and identified one RSN not apparent in control data. This tinnitus RSN included auditory-sensory regions like inferior colliculus and medial Heschl’s gyrus, as well as classically non-auditory regions like the mediodorsal nucleus of the thalamus, striatum, lateral prefrontal and orbitofrontal cortex. Notably, patients’ reported tinnitus loudness was positively correlated with RSFC between the mediodorsal nucleus and the tinnitus RSN, indicating that this network may underlie the auditory-sensory experience of tinnitus. These data support the idea that tinnitus involves network dysfunction, and further stress the importance of communication between auditory-sensory and fronto-striatal circuits in tinnitus pathophysiology. PMID:27091485

Random Forest Segregation of Drug Responses May Define Regions of Biological Significance

PubMed Central

Bukhari, Qasim; Borsook, David; Rudin, Markus; Becerra, Lino

2016-01-01

The ability to assess brain responses in unsupervised manner based on fMRI measure has remained a challenge. Here we have applied the Random Forest (RF) method to detect differences in the pharmacological MRI (phMRI) response in rats to treatment with an analgesic drug (buprenorphine) as compared to control (saline). Three groups of animals were studied: two groups treated with different doses of the opioid buprenorphine, low (LD), and high dose (HD), and one receiving saline. PhMRI responses were evaluated in 45 brain regions and RF analysis was applied to allocate rats to the individual treatment groups. RF analysis was able to identify drug effects based on differential phMRI responses in the hippocampus, amygdala, nucleus accumbens, superior colliculus, and the lateral and posterior thalamus for drug vs. saline. These structures have high levels of mu opioid receptors. In addition these regions are involved in aversive signaling, which is inhibited by mu opioids. The results demonstrate that buprenorphine mediated phMRI responses comprise characteristic features that allow a supervised differentiation from placebo treated rats as well as the proper allocation to the respective drug dose group using the RF method, a method that has been successfully applied in clinical studies. PMID:27014046

An Active Contour Model Based on Adaptive Threshold for Extraction of Cerebral Vascular Structures.

PubMed

Wang, Jiaxin; Zhao, Shifeng; Liu, Zifeng; Tian, Yun; Duan, Fuqing; Pan, Yutong

2016-01-01

Cerebral vessel segmentation is essential and helpful for the clinical diagnosis and the related research. However, automatic segmentation of brain vessels remains challenging because of the variable vessel shape and high complex of vessel geometry. This study proposes a new active contour model (ACM) implemented by the level-set method for segmenting vessels from TOF-MRA data. The energy function of the new model, combining both region intensity and boundary information, is composed of two region terms, one boundary term and one penalty term. The global threshold representing the lower gray boundary of the target object by maximum intensity projection (MIP) is defined in the first-region term, and it is used to guide the segmentation of the thick vessels. In the second term, a dynamic intensity threshold is employed to extract the tiny vessels. The boundary term is used to drive the contours to evolve towards the boundaries with high gradients. The penalty term is used to avoid reinitialization of the level-set function. Experimental results on 10 clinical brain data sets demonstrate that our method is not only able to achieve better Dice Similarity Coefficient than the global threshold based method and localized hybrid level-set method but also able to extract whole cerebral vessel trees, including the thin vessels.

Cerebral Perfusion Is Perturbed by Preterm Birth and Brain Injury.

PubMed

Mahdi, E S; Bouyssi-Kobar, M; Jacobs, M B; Murnick, J; Chang, T; Limperopoulos, C

2018-05-10

Early disturbances in systemic and cerebral hemodynamics are thought to mediate prematurity-related brain injury. However, the extent to which CBF is perturbed by preterm birth is unknown. Our aim was to compare global and regional CBF in preterm infants with and without brain injury on conventional MR imaging using arterial spin-labeling during the third trimester of ex utero life and to examine the relationship between clinical risk factors and CBF. We prospectively enrolled preterm infants younger than 32 weeks' gestational age and <1500 g and performed arterial spin-labeling MR imaging studies. Global and regional CBF in the cerebral cortex, thalami, pons, and cerebellum was quantified. Preterm infants were stratified into those with and without structural brain injury. We further categorized preterm infants by brain injury severity: moderate-severe and mild. We studied 78 preterm infants: 31 without brain injury and 47 with brain injury (29 with mild and 18 with moderate-severe injury). Global CBF showed a borderline significant increase with increasing gestational age at birth ( P = .05) and trended lower in preterm infants with brain injury ( P = .07). Similarly, regional CBF was significantly lower in the right thalamus and midpons ( P < .05) and trended lower in the midtemporal, left thalamus, and anterior vermis regions ( P < .1) in preterm infants with brain injury. Regional CBF in preterm infants with moderate-severe brain injury trended lower in the midpons, right cerebellar hemisphere, and dentate nuclei compared with mild brain injury ( P < .1). In addition, a significant, lower regional CBF was associated with ventilation, sepsis, and cesarean delivery ( P < .05). We report early disturbances in global and regional CBF in preterm infants following brain injury. Regional cerebral perfusion alterations were evident in the thalamus and pons, suggesting regional vulnerability of the developing cerebro-cerebellar circuitry. © 2018 by American Journal of Neuroradiology.

The power of using functional fMRI on small rodents to study brain pharmacology and disease

PubMed Central

Jonckers, Elisabeth; Shah, Disha; Hamaide, Julie; Verhoye, Marleen; Van der Linden, Annemie

2015-01-01

Functional magnetic resonance imaging (fMRI) is an excellent tool to study the effect of pharmacological modulations on brain function in a non-invasive and longitudinal manner. We introduce several blood oxygenation level dependent (BOLD) fMRI techniques, including resting state (rsfMRI), stimulus-evoked (st-fMRI), and pharmacological MRI (phMRI). Respectively, these techniques permit the assessment of functional connectivity during rest as well as brain activation triggered by sensory stimulation and/or a pharmacological challenge. The first part of this review describes the physiological basis of BOLD fMRI and the hemodynamic response on which the MRI contrast is based. Specific emphasis goes to possible effects of anesthesia and the animal’s physiological conditions on neural activity and the hemodynamic response. The second part of this review describes applications of the aforementioned techniques in pharmacologically induced, as well as in traumatic and transgenic disease models and illustrates how multiple fMRI methods can be applied successfully to evaluate different aspects of a specific disorder. For example, fMRI techniques can be used to pinpoint the neural substrate of a disease beyond previously defined hypothesis-driven regions-of-interest. In addition, fMRI techniques allow one to dissect how specific modifications (e.g., treatment, lesion etc.) modulate the functioning of specific brain areas (st-fMRI, phMRI) and how functional connectivity (rsfMRI) between several brain regions is affected, both in acute and extended time frames. Furthermore, fMRI techniques can be used to assess/explore the efficacy of novel treatments in depth, both in fundamental research as well as in preclinical settings. In conclusion, by describing several exemplary studies, we aim to highlight the advantages of functional MRI in exploring the acute and long-term effects of pharmacological substances and/or pathology on brain functioning along with several methodological considerations. PMID:26539115

At the centennial of Michaelis and Menten, competing Michaelis-Menten steps explain effect of GLP-1 on blood-brain transfer and metabolism of glucose.

PubMed

Gejl, Michael; Rungby, Jørgen; Brock, Birgitte; Gjedde, Albert

2014-08-01

Glucagon-like peptide-1 (GLP-1) is a potent insulinotropic incretin hormone with both pancreatic and extrapancreatic effects. Studies of GLP-1 reveal significant effects in regions of brain tissue that regulate appetite and satiety. GLP-1 mimetics are used for the treatment of type 2 diabetes mellitus. GLP-1 interacts with peripheral functions in which the autonomic nervous system plays an important role, and emerging pre-clinical findings indicate a potential neuroprotective role of the peptide, for example in models of stroke and in neurodegenerative disorders. A century ago, Leonor Michaelis and Maud Menten described the steady-state enzyme kinetics that still apply to the multiple receptors, transporters and enzymes that define the biochemical reactions of the brain, including the glucose-dependent impact of GLP-1 on blood-brain glucose transfer and metabolism. This MiniReview examines the potential of GLP-1 as a molecule of interest for the understanding of brain energy metabolism and with reference to the impact on brain metabolism related to appetite and satiety regulation, stroke and neurodegenerative disorders. These effects can be understood only by reference to the original formulation of the Michaelis-Menten equation as applied to a chain of kinetically controlled steps. Indeed, the effects of GLP-1 receptor activation on blood-brain glucose transfer and brain metabolism of glucose depend on the glucose concentration and relative affinities of the steps both in vitro and in vivo, as in the pancreas. © 2014 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society).

A reliability study on brain activation during active and passive arm movements supported by an MRI-compatible robot.

PubMed

Estévez, Natalia; Yu, Ningbo; Brügger, Mike; Villiger, Michael; Hepp-Reymond, Marie-Claude; Riener, Robert; Kollias, Spyros

2014-11-01

In neurorehabilitation, longitudinal assessment of arm movement related brain function in patients with motor disability is challenging due to variability in task performance. MRI-compatible robots monitor and control task performance, yielding more reliable evaluation of brain function over time. The main goals of the present study were first to define the brain network activated while performing active and passive elbow movements with an MRI-compatible arm robot (MaRIA) in healthy subjects, and second to test the reproducibility of this activation over time. For the fMRI analysis two models were compared. In model 1 movement onset and duration were included, whereas in model 2 force and range of motion were added to the analysis. Reliability of brain activation was tested with several statistical approaches applied on individual and group activation maps and on summary statistics. The activated network included mainly the primary motor cortex, primary and secondary somatosensory cortex, superior and inferior parietal cortex, medial and lateral premotor regions, and subcortical structures. Reliability analyses revealed robust activation for active movements with both fMRI models and all the statistical methods used. Imposed passive movements also elicited mainly robust brain activation for individual and group activation maps, and reliability was improved by including additional force and range of motion using model 2. These findings demonstrate that the use of robotic devices, such as MaRIA, can be useful to reliably assess arm movement related brain activation in longitudinal studies and may contribute in studies evaluating therapies and brain plasticity following injury in the nervous system.

A statistical approach for segregating cognitive task stages from multivariate fMRI BOLD time series.

PubMed

Demanuele, Charmaine; Bähner, Florian; Plichta, Michael M; Kirsch, Peter; Tost, Heike; Meyer-Lindenberg, Andreas; Durstewitz, Daniel

2015-01-01

Multivariate pattern analysis can reveal new information from neuroimaging data to illuminate human cognition and its disturbances. Here, we develop a methodological approach, based on multivariate statistical/machine learning and time series analysis, to discern cognitive processing stages from functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) time series. We apply this method to data recorded from a group of healthy adults whilst performing a virtual reality version of the delayed win-shift radial arm maze (RAM) task. This task has been frequently used to study working memory and decision making in rodents. Using linear classifiers and multivariate test statistics in conjunction with time series bootstraps, we show that different cognitive stages of the task, as defined by the experimenter, namely, the encoding/retrieval, choice, reward and delay stages, can be statistically discriminated from the BOLD time series in brain areas relevant for decision making and working memory. Discrimination of these task stages was significantly reduced during poor behavioral performance in dorsolateral prefrontal cortex (DLPFC), but not in the primary visual cortex (V1). Experimenter-defined dissection of time series into class labels based on task structure was confirmed by an unsupervised, bottom-up approach based on Hidden Markov Models. Furthermore, we show that different groupings of recorded time points into cognitive event classes can be used to test hypotheses about the specific cognitive role of a given brain region during task execution. We found that whilst the DLPFC strongly differentiated between task stages associated with different memory loads, but not between different visual-spatial aspects, the reverse was true for V1. Our methodology illustrates how different aspects of cognitive information processing during one and the same task can be separated and attributed to specific brain regions based on information contained in multivariate patterns of voxel activity.

An Examination of Dynamic Gene Expression Changes in the Mouse Brain During Pregnancy and the Postpartum Period.

PubMed

Ray, Surjyendu; Tzeng, Ruei-Ying; DiCarlo, Lisa M; Bundy, Joseph L; Vied, Cynthia; Tyson, Gary; Nowakowski, Richard; Arbeitman, Michelle N

2015-11-23

The developmental transition to motherhood requires gene expression changes that alter the brain to drive the female to perform maternal behaviors. We broadly examined the global transcriptional response in the mouse maternal brain, by examining four brain regions: hypothalamus, hippocampus, neocortex, and cerebellum, in virgin females, two pregnancy time points, and three postpartum time points. We find that overall there are hundreds of differentially expressed genes, but each brain region and time point shows a unique molecular signature, with only 49 genes differentially expressed in all four regions. Interestingly, a set of "early-response genes" is repressed in all brain regions during pregnancy and postpartum stages. Several genes previously implicated in underlying postpartum depression change expression. This study serves as an atlas of gene expression changes in the maternal brain, with the results demonstrating that pregnancy, parturition, and postpartum maternal experience substantially impact diverse brain regions. Copyright © 2016 Ray et al.

Reduced gray matter volume in the anterior cingulate, orbitofrontal cortex and thalamus as a function of mild depressive symptoms: a voxel-based morphometric analysis.

PubMed

Webb, C A; Weber, M; Mundy, E A; Killgore, W D S

2014-10-01

Studies investigating structural brain abnormalities in depression have typically employed a categorical rather than dimensional approach to depression [i.e., comparing subjects with Diagnostic and Statistical Manual of Mental Disorders (DSM)-defined major depressive disorder (MDD) v. healthy controls]. The National Institute of Mental Health, through their Research Domain Criteria initiative, has encouraged a dimensional approach to the study of psychopathology as opposed to an over-reliance on categorical (e.g., DSM-based) diagnostic approaches. Moreover, subthreshold levels of depressive symptoms (i.e., severity levels below DSM criteria) have been found to be associated with a range of negative outcomes, yet have been relatively neglected in neuroimaging research. To examine the extent to which depressive symptoms--even at subclinical levels--are linearly related to gray matter volume reductions in theoretically important brain regions, we employed whole-brain voxel-based morphometry in a sample of 54 participants. The severity of mild depressive symptoms, even in a subclinical population, was associated with reduced gray matter volume in the orbitofrontal cortex, anterior cingulate, thalamus, superior temporal gyrus/temporal pole and superior frontal gyrus. A conjunction analysis revealed concordance across two separate measures of depression. Reduced gray matter volume in theoretically important brain regions can be observed even in a sample that does not meet DSM criteria for MDD, but who nevertheless report relatively elevated levels of depressive symptoms. Overall, these findings highlight the need for additional research using dimensional conceptual and analytic approaches, as well as further investigation of subclinical populations.

Regional brain glucose metabolism in patients with brain tumors before and after radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, G.J.; Volkow, N.D.; Lau, Y.H.

1994-05-01

This study was performed to measure regional glucose metabolism in nonaffected brain regions of patients with primary or metastatic brain tumors. Seven female and four male patients (mean age 51.5{plus_minus}14.0 years old) were compared with eleven age and sex matched normal subjects. None of the patients had hydrocephalus and/or increased intracranial pressure. Brain glucose metabolism was measured using FDG-PET scan. Five of the patients were reevaluated one week after receiving radiation treatment (RT) to the brain. Patients were on Decadron and/or Dilantin at the time of both scan. PET images were analyzed with a template of 115 nonoverlapping regions ofmore » interest and then grouped into eight gray matter regions on each hemisphere. Brain regions with tumors and edema shown in MR imaging were excluded. Z scores were used to compare individual patients` regional values with those of normal subjects. The number of regional values with Z scores of less than - 3.0 were considered abnormal and were quantified. The mean global glucose metabolic rate (mean of all regions) in nonaffected brain regions of patients was significantly lower than that of normal controls (32.1{plus_minus}9.0 versus 44.8{plus_minus}6.3 {mu}mol/100g/min, p<0.001). Analyses of individual subjects revealed that none of the controls and 8 of the 11 patients had at least one abnormal region. In these 8 patients the regions which were abnormal were most frequently localized in right (n=5) and left occipital (n=6) and right orbital frontal cortex (n=7) whereas the basal ganglia was not affected. Five of the patients who had repeated scans following RT showed decrements in tumor metabolism (41{plus_minus}20.5%) and a significant increase in whole brain metabolism (8.6{plus_minus}5.3%, p<0.001). The improvement in whole brain metabolism after RT suggests that the brain metabolic decrements in the patients were related to the presence of tumoral tissue and not just a medication effect.« less

Partial covariance based functional connectivity computation using Ledoit-Wolf covariance regularization.

PubMed

Brier, Matthew R; Mitra, Anish; McCarthy, John E; Ances, Beau M; Snyder, Abraham Z

2015-11-01

Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a complicated covariance structure. Partial covariance assesses the unique variance shared between two brain regions excluding any widely shared variance, hence is appropriate for the analysis of multivariate fMRI datasets. However, calculation of partial covariance requires inversion of the covariance matrix, which, in most functional connectivity studies, is not invertible owing to rank deficiency. Here we apply Ledoit-Wolf shrinkage (L2 regularization) to invert the high dimensional BOLD covariance matrix. We investigate the network organization and brain-state dependence of partial covariance-based functional connectivity. Although RSNs are conventionally defined in terms of shared variance, removal of widely shared variance, surprisingly, improved the separation of RSNs in a spring embedded graphical model. This result suggests that pair-wise unique shared variance plays a heretofore unrecognized role in RSN covariance organization. In addition, application of partial correlation to fMRI data acquired in the eyes open vs. eyes closed states revealed focal changes in uniquely shared variance between the thalamus and visual cortices. This result suggests that partial correlation of resting state BOLD time series reflect functional processes in addition to structural connectivity. Copyright © 2015 Elsevier Inc. All rights reserved.

Quantitative analysis of diffusion tensor orientation: theoretical framework.

PubMed

Wu, Yu-Chien; Field, Aaron S; Chung, Moo K; Badie, Benham; Alexander, Andrew L

2004-11-01

Diffusion-tensor MRI (DT-MRI) yields information about the magnitude, anisotropy, and orientation of water diffusion of brain tissues. Although white matter tractography and eigenvector color maps provide visually appealing displays of white matter tract organization, they do not easily lend themselves to quantitative and statistical analysis. In this study, a set of visual and quantitative tools for the investigation of tensor orientations in the human brain was developed. Visual tools included rose diagrams, which are spherical coordinate histograms of the major eigenvector directions, and 3D scatterplots of the major eigenvector angles. A scatter matrix of major eigenvector directions was used to describe the distribution of major eigenvectors in a defined anatomic region. A measure of eigenvector dispersion was developed to describe the degree of eigenvector coherence in the selected region. These tools were used to evaluate directional organization and the interhemispheric symmetry of DT-MRI data in five healthy human brains and two patients with infiltrative diseases of the white matter tracts. In normal anatomical white matter tracts, a high degree of directional coherence and interhemispheric symmetry was observed. The infiltrative diseases appeared to alter the eigenvector properties of affected white matter tracts, showing decreased eigenvector coherence and interhemispheric symmetry. This novel approach distills the rich, 3D information available from the diffusion tensor into a form that lends itself to quantitative analysis and statistical hypothesis testing. (c) 2004 Wiley-Liss, Inc.

Partial covariance based functional connectivity computation using Ledoit-Wolf covariance regularization

PubMed Central

Brier, Matthew R.; Mitra, Anish; McCarthy, John E.; Ances, Beau M.; Snyder, Abraham Z.

2015-01-01

Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a complicated covariance structure. Partial covariance assesses the unique variance shared between two brain regions excluding any widely shared variance, hence is appropriate for the analysis of multivariate fMRI datasets. However, calculation of partial covariance requires inversion of the covariance matrix, which, in most functional connectivity studies, is not invertible owing to rank deficiency. Here we apply Ledoit-Wolf shrinkage (L2 regularization) to invert the high dimensional BOLD covariance matrix. We investigate the network organization and brain-state dependence of partial covariance-based functional connectivity. Although RSNs are conventionally defined in terms of shared variance, removal of widely shared variance, surprisingly, improved the separation of RSNs in a spring embedded graphical model. This result suggests that pair-wise unique shared variance plays a heretofore unrecognized role in RSN covariance organization. In addition, application of partial correlation to fMRI data acquired in the eyes open vs. eyes closed states revealed focal changes in uniquely shared variance between the thalamus and visual cortices. This result suggests that partial correlation of resting state BOLD time series reflect functional processes in addition to structural connectivity. PMID:26208872

Changes in Brain Activation Associated with Spontaneous Improvization and Figural Creativity After Design-Thinking-Based Training: A Longitudinal fMRI Study.

PubMed

Saggar, Manish; Quintin, Eve-Marie; Bott, Nicholas T; Kienitz, Eliza; Chien, Yin-Hsuan; Hong, Daniel W-C; Liu, Ning; Royalty, Adam; Hawthorne, Grace; Reiss, Allan L

2017-07-01

Creativity is widely recognized as an essential skill for entrepreneurial success and adaptation to daily-life demands. However, we know little about the neural changes associated with creative capacity enhancement. For the first time, using a prospective, randomized control design, we examined longitudinal changes in brain activity associated with participating in a five-week design-thinking-based Creative Capacity Building Program (CCBP), when compared with Language Capacity Building Program (LCBP). Creativity, an elusive and multifaceted construct, is loosely defined as an ability to produce useful/appropriate and novel outcomes. Here, we focus on one of the facets of creative thinking-spontaneous improvization. Participants were assessed pre- and post-intervention for spontaneous improvization skills using a game-like figural Pictionary-based fMRI task. Whole-brain group-by-time interaction revealed reduced task-related activity in CCBP participants (compared with LCBP participants) after training in the right dorsolateral prefrontal cortex, anterior/paracingulate gyrus, supplementary motor area, and parietal regions. Further, greater cerebellar-cerebral connectivity was observed in CCBP participants at post-intervention when compared with LCBP participants. In sum, our results suggest that improvization-based creative capacity enhancement is associated with reduced engagement of executive functioning regions and increased involvement of spontaneous implicit processing. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Brain regions involved in observing and trying to interpret dog behaviour.

PubMed

Desmet, Charlotte; van der Wiel, Alko; Brass, Marcel

2017-01-01

Humans and dogs have interacted for millennia. As a result, humans (and especially dog owners) sometimes try to interpret dog behaviour. While there is extensive research on the brain regions that are involved in mentalizing about other peoples' behaviour, surprisingly little is known of whether we use these same brain regions to mentalize about animal behaviour. In this fMRI study we investigate whether brain regions involved in mentalizing about human behaviour are also engaged when observing dog behaviour. Here we show that these brain regions are more engaged when observing dog behaviour that is difficult to interpret compared to dog behaviour that is easy to interpret. Interestingly, these results were not only obtained when participants were instructed to infer reasons for the behaviour but also when they passively viewed the behaviour, indicating that these brain regions are activated by spontaneous mentalizing processes.

Brain regions involved in observing and trying to interpret dog behaviour

PubMed Central

Desmet, Charlotte; van der Wiel, Alko; Brass, Marcel

2017-01-01

Humans and dogs have interacted for millennia. As a result, humans (and especially dog owners) sometimes try to interpret dog behaviour. While there is extensive research on the brain regions that are involved in mentalizing about other peoples’ behaviour, surprisingly little is known of whether we use these same brain regions to mentalize about animal behaviour. In this fMRI study we investigate whether brain regions involved in mentalizing about human behaviour are also engaged when observing dog behaviour. Here we show that these brain regions are more engaged when observing dog behaviour that is difficult to interpret compared to dog behaviour that is easy to interpret. Interestingly, these results were not only obtained when participants were instructed to infer reasons for the behaviour but also when they passively viewed the behaviour, indicating that these brain regions are activated by spontaneous mentalizing processes. PMID:28931030

On Expression Patterns and Developmental Origin of Human Brain Regions.

PubMed

Kirsch, Lior; Chechik, Gal

2016-08-01

Anatomical substructures of the human brain have characteristic cell-types, connectivity and local circuitry, which are reflected in area-specific transcriptome signatures, but the principles governing area-specific transcription and their relation to brain development are still being studied. In adult rodents, areal transcriptome patterns agree with the embryonic origin of brain regions, but the processes and genes that preserve an embryonic signature in regional expression profiles were not quantified. Furthermore, it is not clear how embryonic-origin signatures of adult-brain expression interplay with changes in expression patterns during development. Here we first quantify which genes have regional expression-patterns related to the developmental origin of brain regions, using genome-wide mRNA expression from post-mortem adult human brains. We find that almost all human genes (92%) exhibit an expression pattern that agrees with developmental brain-region ontology, but that this agreement changes at multiple phases during development. Agreement is particularly strong in neuron-specific genes, but also in genes that are not spatially correlated with neuron-specific or glia-specific markers. Surprisingly, agreement is also stronger in early-evolved genes. We further find that pairs of similar genes having high agreement to developmental region ontology tend to be more strongly correlated or anti-correlated, and that the strength of spatial correlation changes more strongly in gene pairs with stronger embryonic signatures. These results suggest that transcription regulation of most genes in the adult human brain is spatially tuned in a way that changes through life, but in agreement with development-determined brain regions.

On Expression Patterns and Developmental Origin of Human Brain Regions

PubMed Central

Kirsch, Lior; Chechik, Gal

2016-01-01

Anatomical substructures of the human brain have characteristic cell-types, connectivity and local circuitry, which are reflected in area-specific transcriptome signatures, but the principles governing area-specific transcription and their relation to brain development are still being studied. In adult rodents, areal transcriptome patterns agree with the embryonic origin of brain regions, but the processes and genes that preserve an embryonic signature in regional expression profiles were not quantified. Furthermore, it is not clear how embryonic-origin signatures of adult-brain expression interplay with changes in expression patterns during development. Here we first quantify which genes have regional expression-patterns related to the developmental origin of brain regions, using genome-wide mRNA expression from post-mortem adult human brains. We find that almost all human genes (92%) exhibit an expression pattern that agrees with developmental brain-region ontology, but that this agreement changes at multiple phases during development. Agreement is particularly strong in neuron-specific genes, but also in genes that are not spatially correlated with neuron-specific or glia-specific markers. Surprisingly, agreement is also stronger in early-evolved genes. We further find that pairs of similar genes having high agreement to developmental region ontology tend to be more strongly correlated or anti-correlated, and that the strength of spatial correlation changes more strongly in gene pairs with stronger embryonic signatures. These results suggest that transcription regulation of most genes in the adult human brain is spatially tuned in a way that changes through life, but in agreement with development-determined brain regions. PMID:27564987

Computation of reliable textural indices from multimodal brain MRI: suggestions based on a study of patients with diffuse intrinsic pontine glioma

NASA Astrophysics Data System (ADS)

Goya-Outi, Jessica; Orlhac, Fanny; Calmon, Raphael; Alentorn, Agusti; Nioche, Christophe; Philippe, Cathy; Puget, Stéphanie; Boddaert, Nathalie; Buvat, Irène; Grill, Jacques; Frouin, Vincent; Frouin, Frederique

2018-05-01

Few methodological studies regarding widely used textural indices robustness in MRI have been reported. In this context, this study aims to propose some rules to compute reliable textural indices from multimodal 3D brain MRI. Diagnosis and post-biopsy MR scans including T1, post-contrast T1, T2 and FLAIR images from thirty children with diffuse intrinsic pontine glioma (DIPG) were considered. The hybrid white stripe method was adapted to standardize MR intensities. Sixty textural indices were then computed for each modality in different regions of interest (ROI), including tumor and white matter (WM). Three types of intensity binning were compared : constant bin width and relative bounds; constant number of bins and relative bounds; constant number of bins and absolute bounds. The impact of the volume of the region was also tested within the WM. First, the mean Hellinger distance between patient-based intensity distributions decreased by a factor greater than 10 in WM and greater than 2.5 in gray matter after standardization. Regarding the binning strategy, the ranking of patients was highly correlated for 188/240 features when comparing with , but for only 20 when comparing with , and nine when comparing with . Furthermore, when using or texture indices reflected tumor heterogeneity as assessed visually by experts. Last, 41 features presented statistically significant differences between contralateral WM regions when ROI size slightly varies across patients, and none when using ROI of the same size. For regions with similar size, 224 features were significantly different between WM and tumor. Valuable information from texture indices can be biased by methodological choices. Recommendations are to standardize intensities in MR brain volumes, to use intensity binning with constant bin width, and to define regions with the same volumes to get reliable textural indices.

Regional brain network organization distinguishes the combined and inattentive subtypes of Attention Deficit Hyperactivity Disorder.

PubMed

Saad, Jacqueline F; Griffiths, Kristi R; Kohn, Michael R; Clarke, Simon; Williams, Leanne M; Korgaonkar, Mayuresh S

2017-01-01

Attention Deficit Hyperactivity Disorder (ADHD) is characterized clinically by hyperactive/impulsive and/or inattentive symptoms which determine diagnostic subtypes as Predominantly Hyperactive-Impulsive (ADHD-HI), Predominantly Inattentive (ADHD-I), and Combined (ADHD-C). Neuroanatomically though we do not yet know if these clinical subtypes reflect distinct aberrations in underlying brain organization. We imaged 34 ADHD participants defined using DSM-IV criteria as ADHD-I ( n  = 16) or as ADHD-C ( n  = 18) and 28 matched typically developing controls, aged 8-17 years, using high-resolution T1 MRI. To quantify neuroanatomical organization we used graph theoretical analysis to assess properties of structural covariance between ADHD subtypes and controls (global network measures: path length, clustering coefficient, and regional network measures: nodal degree). As a context for interpreting network organization differences, we also quantified gray matter volume using voxel-based morphometry. Each ADHD subtype was distinguished by a different organizational profile of the degree to which specific regions were anatomically connected with other regions (i.e., in "nodal degree"). For ADHD-I (compared to both ADHD-C and controls) the nodal degree was higher in the hippocampus. ADHD-I also had a higher nodal degree in the supramarginal gyrus, calcarine sulcus, and superior occipital cortex compared to ADHD-C and in the amygdala compared to controls. By contrast, the nodal degree was higher in the cerebellum for ADHD-C compared to ADHD-I and in the anterior cingulate, middle frontal gyrus and putamen compared to controls. ADHD-C also had reduced nodal degree in the rolandic operculum and middle temporal pole compared to controls. These regional profiles were observed in the context of no differences in gray matter volume or global network organization. Our results suggest that the clinical distinction between the Inattentive and Combined subtypes of ADHD may also be reflected in distinct aberrations in underlying brain organization.

Association of GSK3beta polymorphisms with brain structural changes in major depressive disorder.

PubMed

Inkster, Becky; Nichols, Thomas E; Saemann, Philipp G; Auer, Dorothee P; Holsboer, Florian; Muglia, Pierandrea; Matthews, Paul M

2009-07-01

Indirect evidence suggests that the glycogen synthase kinase-3beta (GSK3beta) gene might be implicated in major depressive disorder (MDD). We evaluated 15 GSK3beta single-nucleotide polymorphisms (SNPs) to test for associations with regional gray matter (GM) volume differences in patients with recurrent MDD. We then used the defined regions of interest based on significant associations to test for MDD x genotype interactions by including a matched control group without any psychiatric disorder, including MDD. General linear model with nonstationary cluster-based inference. Munich, Germany. Patients with recurrent MDD (n = 134) and age-, sex-, and ethnicity-matched healthy controls (n = 143). Associations between GSK3beta polymorphisms and regional GM volume differences. Variation in GM volume was associated with GSK3beta polymorphisms; the most significant associations were found for rs6438552, a putative functional intronic SNP that showed 3 significant GM clusters in the right and left superior temporal gyri and the right hippocampus (P < .001, P = .02, and P = .02, respectively, corrected for multiple comparisons across the whole brain). Similar results were obtained with rs12630592, an SNP in high linkage disequilibrium. A significant SNP x MDD status interaction was observed for the effect on GM volumes in the right hippocampus and superior temporal gyri (P < .001 and P = .01, corrected, respectively). The GSK3beta gene may have a role in determining regional GM volume differences of the right hippocampus and bilateral superior temporal gyri. The association between genotype and brain structure was specific to the patients with MDD, suggesting that GSK3beta genotypes might interact with MDD status. We speculate that this is a consequence of regional neocortical, glial, or neuronal growth or survival. In considering core cognitive features of MDD, the association of GSK3beta polymorphisms with structural variation in the temporal lobe and hippocampus is of particular interest in the context of other evidence for structural and functional abnormalities in the hippocampi of patients with MDD.

Alcohol-Binding Sites in Distinct Brain Proteins: The Quest for Atomic Level Resolution

PubMed Central

Howard, Rebecca J.; Slesinger, Paul A.; Davies, Daryl L.; Das, Joydip; Trudell, James R.; Harris, R. Adron

2011-01-01

Defining the sites of action of ethanol on brain proteins is a major prerequisite to understanding the molecular pharmacology of this drug. The main barrier to reaching an atomic-level understanding of alcohol action is the low potency of alcohols, ethanol in particular, which is a reflection of transient, low-affinity interactions with their targets. These mechanisms are difficult or impossible to study with traditional techniques such as radioligand binding or spectroscopy. However, there has been considerable recent progress in combining X-ray crystallography, structural modeling, and site-directed mutagenesis to define the sites and mechanisms of action of ethanol and related alcohols on key brain proteins. We review such insights for several diverse classes of proteins including inwardly rectifying potassium, transient receptor potential, and neurotransmit-ter-gated ion channels, as well as protein kinase C epsilon. Some common themes are beginning to emerge from these proteins, including hydrogen bonding of the hydroxyl group and van der Waals interactions of the methylene groups of ethanol with specific amino acid residues. The resulting binding energy is proposed to facilitate or stabilize low-energy state transitions in the bound proteins, allowing ethanol to act as a “molecular lubricant” for protein function. We discuss evidence for characteristic, discrete alcohol-binding sites on protein targets, as well as evidence that binding to some proteins is better characterized by an interaction region that can accommodate multiple molecules of ethanol. PMID:21676006

Transgenic Mouse Lines Subdivide External Segment of the Globus Pallidus (GPe) Neurons and Reveal Distinct GPe Output Pathways

PubMed Central

Mastro, Kevin J.; Bouchard, Rachel S.; Holt, Hiromi A. K.

2014-01-01

Cell-type diversity in the brain enables the assembly of complex neural circuits, whose organization and patterns of activity give rise to brain function. However, the identification of distinct neuronal populations within a given brain region is often complicated by a lack of objective criteria to distinguish one neuronal population from another. In the external segment of the globus pallidus (GPe), neuronal populations have been defined using molecular, anatomical, and electrophysiological criteria, but these classification schemes are often not generalizable across preparations and lack consistency even within the same preparation. Here, we present a novel use of existing transgenic mouse lines, Lim homeobox 6 (Lhx6)–Cre and parvalbumin (PV)–Cre, to define genetically distinct cell populations in the GPe that differ molecularly, anatomically, and electrophysiologically. Lhx6–GPe neurons, which do not express PV, are concentrated in the medial portion of the GPe. They have lower spontaneous firing rates, narrower dynamic ranges, and make stronger projections to the striatum and substantia nigra pars compacta compared with PV–GPe neurons. In contrast, PV–GPe neurons are more concentrated in the lateral portions of the GPe. They have narrower action potentials, deeper afterhyperpolarizations, and make stronger projections to the subthalamic nucleus and parafascicular nucleus of the thalamus. These electrophysiological and anatomical differences suggest that Lhx6–GPe and PV–GPe neurons participate in different circuits with the potential to contribute to different aspects of motor function and dysfunction in disease. PMID:24501350

Investigation of brain structure in the 1-month infant.

PubMed

Dean, Douglas C; Planalp, E M; Wooten, W; Schmidt, C K; Kecskemeti, S R; Frye, C; Schmidt, N L; Goldsmith, H H; Alexander, A L; Davidson, R J

2018-05-01

The developing brain undergoes systematic changes that occur at successive stages of maturation. Deviations from the typical neurodevelopmental trajectory are hypothesized to underlie many early childhood disorders; thus, characterizing the earliest patterns of normative brain development is essential. Recent neuroimaging research provides insight into brain structure during late childhood and adolescence; however, few studies have examined the infant brain, particularly in infants under 3 months of age. Using high-resolution structural MRI, we measured subcortical gray and white matter brain volumes in a cohort (N = 143) of 1-month infants and examined characteristics of these volumetric measures throughout this early period of neurodevelopment. We show that brain volumes undergo age-related changes during the first month of life, with the corresponding patterns of regional asymmetry and sexual dimorphism. Specifically, males have larger total brain volume and volumes differ by sex in regionally specific brain regions, after correcting for total brain volume. Consistent with findings from studies of later childhood and adolescence, subcortical regions appear more rightward asymmetric. Neither sex differences nor regional asymmetries changed with gestation-corrected age. Our results complement a growing body of work investigating the earliest neurobiological changes associated with development and suggest that asymmetry and sexual dimorphism are present at birth.

Carnosine: effect on aging-induced increase in brain regional monoamine oxidase-A activity.

PubMed

Banerjee, Soumyabrata; Poddar, Mrinal K

2015-03-01

Aging is a natural biological process associated with several neurological disorders along with the biochemical changes in brain. Aim of the present investigation is to study the effect of carnosine (0.5-2.5μg/kg/day, i.t. for 21 consecutive days) on aging-induced changes in brain regional (cerebral cortex, hippocampus, hypothalamus and pons-medulla) mitochondrial monoamine oxidase-A (MAO-A) activity with its kinetic parameters. The results of the present study are: (1) The brain regional mitochondrial MAO-A activity and their kinetic parameters (except in Km of pons-medulla) were significantly increased with the increase of age (4-24 months), (2) Aging-induced increase of brain regional MAO-A activity including its Vmax were attenuated with higher dosages of carnosine (1.0-2.5μg/kg/day) and restored toward the activity that observed in young, though its lower dosage (0.5μg/kg/day) were ineffective in these brain regional MAO-A activity, (3) Carnosine at higher dosage in young rats, unlike aged rats significantly inhibited all the brain regional MAO-A activity by reducing their only Vmax excepting cerebral cortex, where Km was also significantly enhanced. These results suggest that carnosine attenuated the aging-induced increase of brain regional MAO-A activity by attenuating its kinetic parameters and restored toward the results of MAO-A activity that observed in corresponding brain regions of young rats. Copyright © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Regional differences in brain glucose metabolism determined by imaging mass spectrometry.

PubMed

Kleinridders, André; Ferris, Heather A; Reyzer, Michelle L; Rath, Michaela; Soto, Marion; Manier, M Lisa; Spraggins, Jeffrey; Yang, Zhihong; Stanton, Robert C; Caprioli, Richard M; Kahn, C Ronald

2018-06-01

Glucose is the major energy substrate of the brain and crucial for normal brain function. In diabetes, the brain is subject to episodes of hypo- and hyperglycemia resulting in acute outcomes ranging from confusion to seizures, while chronic metabolic dysregulation puts patients at increased risk for depression and Alzheimer's disease. In the present study, we aimed to determine how glucose is metabolized in different regions of the brain using imaging mass spectrometry (IMS). To examine the relative abundance of glucose and other metabolites in the brain, mouse brain sections were subjected to imaging mass spectrometry at a resolution of 100 μm. This was correlated with immunohistochemistry, qPCR, western blotting and enzyme assays of dissected brain regions to determine the relative contributions of the glycolytic and pentose phosphate pathways to regional glucose metabolism. In brain, there are significant regional differences in glucose metabolism, with low levels of hexose bisphosphate (a glycolytic intermediate) and high levels of the pentose phosphate pathway (PPP) enzyme glucose-6-phosphate dehydrogenase (G6PD) and PPP metabolite hexose phosphate in thalamus compared to cortex. The ratio of ATP to ADP is significantly higher in white matter tracts, such as corpus callosum, compared to less myelinated areas. While the brain is able to maintain normal ratios of hexose phosphate, hexose bisphosphate, ATP, and ADP during fasting, fasting causes a large increase in cortical and hippocampal lactate. These data demonstrate the importance of direct measurement of metabolic intermediates to determine regional differences in brain glucose metabolism and illustrate the strength of imaging mass spectrometry for investigating the impact of changing metabolic states on brain function at a regional level with high resolution. Copyright © 2018 The Authors. Published by Elsevier GmbH.. All rights reserved.

Regional flux analysis for discovering and quantifying anatomical changes: An application to the brain morphometry in Alzheimer's disease.

PubMed

Lorenzi, M; Ayache, N; Pennec, X

2015-07-15

In this study we introduce the regional flux analysis, a novel approach to deformation based morphometry based on the Helmholtz decomposition of deformations parameterized by stationary velocity fields. We use the scalar pressure map associated to the irrotational component of the deformation to discover the critical regions of volume change. These regions are used to consistently quantify the associated measure of volume change by the probabilistic integration of the flux of the longitudinal deformations across the boundaries. The presented framework unifies voxel-based and regional approaches, and robustly describes the volume changes at both group-wise and subject-specific level as a spatial process governed by consistently defined regions. Our experiments on the large cohorts of the ADNI dataset show that the regional flux analysis is a powerful and flexible instrument for the study of Alzheimer's disease in a wide range of scenarios: cross-sectional deformation based morphometry, longitudinal discovery and quantification of group-wise volume changes, and statistically powered and robust quantification of hippocampal and ventricular atrophy. Copyright © 2015 Elsevier Inc. All rights reserved.

Multi-modality safety assessment of blood-brain barrier opening using focused ultrasound and definity microbubbles: a short-term study.

PubMed

Baseri, Babak; Choi, James J; Tung, Yao-Sheng; Konofagou, Elisa E

2010-09-01

As a potentially viable method of brain drug delivery, the safety profile of blood-brain barrier (BBB) opening using focused ultrasound (FUS) and ultrasound contrast agents (UCA) needs to be established. In this study, we provide a short-term (30-min or 5-h survival) histological assessment of murine brains undergoing FUS-induced BBB opening. Forty-nine mice were intravenously injected with Definity microbubbles (0.05 microL/kg) and sonicated under the following parameters: frequency of 1.525 MHz, pulse length of 20 ms, pulse repetition frequency of 10 Hz, peak rarefactional acoustic pressures of 0.15-0.98 MPa and two 30-s sonication intervals with an intermittent 30-s delay. The BBB opening threshold was found to be 0.15-0.3 MPa based on fluorescence and magnetic resonance imaging of systemically injected tracers. Analysis of three histological measures in hematoxylin and eosin-stained sections revealed the safest acoustic pressure to be within the range of 0.3-0.46 MPa in all examined time periods post sonication. Across different pressure amplitudes, only the samples 30 min post opening showed significant difference (p < 0.05) in the average number of distinct damaged sites, microvacuolated sites, dark neurons and sites with extravasated erythrocytes. Enhanced fluorescence around severed microvessels was also noted and found to be associated with the largest tissue effects, whereas mildly diffuse BBB opening with uniform fluorescence in the parenchyma was associated with no or mild tissue injury. Region-specific areas of the sonicated brain (thalamus, hippocampal fissure, dentate gyrus and CA3 area of hippocampus) exhibited variation in fluorescence intensity based on the position, orientation and size of affected vessels. The results of this short-term histological analysis demonstrated the feasibility of a safe FUS-UCA-induced BBB opening under a specific set of sonication parameters and provided new insights on the mechanism of BBB opening.

Identification of a set of genes showing regionally enriched expression in the mouse brain

PubMed Central

D'Souza, Cletus A; Chopra, Vikramjit; Varhol, Richard; Xie, Yuan-Yun; Bohacec, Slavita; Zhao, Yongjun; Lee, Lisa LC; Bilenky, Mikhail; Portales-Casamar, Elodie; He, An; Wasserman, Wyeth W; Goldowitz, Daniel; Marra, Marco A; Holt, Robert A; Simpson, Elizabeth M; Jones, Steven JM

2008-01-01

Background The Pleiades Promoter Project aims to improve gene therapy by designing human mini-promoters (< 4 kb) that drive gene expression in specific brain regions or cell-types of therapeutic interest. Our goal was to first identify genes displaying regionally enriched expression in the mouse brain so that promoters designed from orthologous human genes can then be tested to drive reporter expression in a similar pattern in the mouse brain. Results We have utilized LongSAGE to identify regionally enriched transcripts in the adult mouse brain. As supplemental strategies, we also performed a meta-analysis of published literature and inspected the Allen Brain Atlas in situ hybridization data. From a set of approximately 30,000 mouse genes, 237 were identified as showing specific or enriched expression in 30 target regions of the mouse brain. GO term over-representation among these genes revealed co-involvement in various aspects of central nervous system development and physiology. Conclusion Using a multi-faceted expression validation approach, we have identified mouse genes whose human orthologs are good candidates for design of mini-promoters. These mouse genes represent molecular markers in several discrete brain regions/cell-types, which could potentially provide a mechanistic explanation of unique functions performed by each region. This set of markers may also serve as a resource for further studies of gene regulatory elements influencing brain expression. PMID:18625066

Identification of a set of genes showing regionally enriched expression in the mouse brain.

PubMed

D'Souza, Cletus A; Chopra, Vikramjit; Varhol, Richard; Xie, Yuan-Yun; Bohacec, Slavita; Zhao, Yongjun; Lee, Lisa L C; Bilenky, Mikhail; Portales-Casamar, Elodie; He, An; Wasserman, Wyeth W; Goldowitz, Daniel; Marra, Marco A; Holt, Robert A; Simpson, Elizabeth M; Jones, Steven J M

2008-07-14

The Pleiades Promoter Project aims to improve gene therapy by designing human mini-promoters (< 4 kb) that drive gene expression in specific brain regions or cell-types of therapeutic interest. Our goal was to first identify genes displaying regionally enriched expression in the mouse brain so that promoters designed from orthologous human genes can then be tested to drive reporter expression in a similar pattern in the mouse brain. We have utilized LongSAGE to identify regionally enriched transcripts in the adult mouse brain. As supplemental strategies, we also performed a meta-analysis of published literature and inspected the Allen Brain Atlas in situ hybridization data. From a set of approximately 30,000 mouse genes, 237 were identified as showing specific or enriched expression in 30 target regions of the mouse brain. GO term over-representation among these genes revealed co-involvement in various aspects of central nervous system development and physiology. Using a multi-faceted expression validation approach, we have identified mouse genes whose human orthologs are good candidates for design of mini-promoters. These mouse genes represent molecular markers in several discrete brain regions/cell-types, which could potentially provide a mechanistic explanation of unique functions performed by each region. This set of markers may also serve as a resource for further studies of gene regulatory elements influencing brain expression.

Down syndrome's brain dynamics: analysis of fractality in resting state.

PubMed

Hemmati, Sahel; Ahmadlou, Mehran; Gharib, Masoud; Vameghi, Roshanak; Sajedi, Firoozeh

2013-08-01

To the best knowledge of the authors there is no study on nonlinear brain dynamics of down syndrome (DS) patients, whereas brain is a highly complex and nonlinear system. In this study, fractal dimension of EEG, as a key characteristic of brain dynamics, showing irregularity and complexity of brain dynamics, was used for evaluation of the dynamical changes in the DS brain. The results showed higher fractality of the DS brain in almost all regions compared to the normal brain, which indicates less centrality and higher irregular or random functioning of the DS brain regions. Also, laterality analysis of the frontal lobe showed that the normal brain had a right frontal laterality of complexity whereas the DS brain had an inverse pattern (left frontal laterality). Furthermore, the high accuracy of 95.8 % obtained by enhanced probabilistic neural network classifier showed the potential of nonlinear dynamic analysis of the brain for diagnosis of DS patients. Moreover, the results showed that the higher EEG fractality in DS is associated with the higher fractality in the low frequencies (delta and theta), in broad regions of the brain, and the high frequencies (beta and gamma), majorly in the frontal regions.

The mean-variance relationship reveals two possible strategies for dynamic brain connectivity analysis in fMRI.

PubMed

Thompson, William H; Fransson, Peter

2015-01-01

When studying brain connectivity using fMRI, signal intensity time-series are typically correlated with each other in time to compute estimates of the degree of interaction between different brain regions and/or networks. In the static connectivity case, the problem of defining which connections that should be considered significant in the analysis can be addressed in a rather straightforward manner by a statistical thresholding that is based on the magnitude of the correlation coefficients. More recently, interest has come to focus on the dynamical aspects of brain connectivity and the problem of deciding which brain connections that are to be considered relevant in the context of dynamical changes in connectivity provides further options. Since we, in the dynamical case, are interested in changes in connectivity over time, the variance of the correlation time-series becomes a relevant parameter. In this study, we discuss the relationship between the mean and variance of brain connectivity time-series and show that by studying the relation between them, two conceptually different strategies to analyze dynamic functional brain connectivity become available. Using resting-state fMRI data from a cohort of 46 subjects, we show that the mean of fMRI connectivity time-series scales negatively with its variance. This finding leads to the suggestion that magnitude- versus variance-based thresholding strategies will induce different results in studies of dynamic functional brain connectivity. Our assertion is exemplified by showing that the magnitude-based strategy is more sensitive to within-resting-state network (RSN) connectivity compared to between-RSN connectivity whereas the opposite holds true for a variance-based analysis strategy. The implications of our findings for dynamical functional brain connectivity studies are discussed.

Intelligence is associated with the modular structure of intrinsic brain networks.

PubMed

Hilger, Kirsten; Ekman, Matthias; Fiebach, Christian J; Basten, Ulrike

2017-11-22

General intelligence is a psychological construct that captures in a single metric the overall level of behavioural and cognitive performance in an individual. While previous research has attempted to localise intelligence in circumscribed brain regions, more recent work focuses on functional interactions between regions. However, even though brain networks are characterised by substantial modularity, it is unclear whether and how the brain's modular organisation is associated with general intelligence. Modelling subject-specific brain network graphs from functional MRI resting-state data (N = 309), we found that intelligence was not associated with global modularity features (e.g., number or size of modules) or the whole-brain proportions of different node types (e.g., connector hubs or provincial hubs). In contrast, we observed characteristic associations between intelligence and node-specific measures of within- and between-module connectivity, particularly in frontal and parietal brain regions that have previously been linked to intelligence. We propose that the connectivity profile of these regions may shape intelligence-relevant aspects of information processing. Our data demonstrate that not only region-specific differences in brain structure and function, but also the network-topological embedding of fronto-parietal as well as other cortical and subcortical brain regions is related to individual differences in higher cognitive abilities, i.e., intelligence.

Analyzing and Assessing Brain Structure with Graph Connectivity Measures

DTIC Science & Technology

2014-05-09

structural brain networks, i.e. determining which regions of the brain are physically connected. Meanwhile, functional MRI ( fMRI ) yields an image of...produced by fMRI is a map of which parts are of the brain are active and which are not at a given time. In creating functional networks, regions of...the brain which often activitate together, i.e., often show up on fMRI as deoxygenated regions together, are considered connected. DTI allows the

Understanding brain networks and brain organization

PubMed Central

Pessoa, Luiz

2014-01-01

What is the relationship between brain and behavior? The answer to this question necessitates characterizing the mapping between structure and function. The aim of this paper is to discuss broad issues surrounding the link between structure and function in the brain that will motivate a network perspective to understanding this question. As others in the past, I argue that a network perspective should supplant the common strategy of understanding the brain in terms of individual regions. Whereas this perspective is needed for a fuller characterization of the mind-brain, it should not be viewed as panacea. For one, the challenges posed by the many-to-many mapping between regions and functions is not dissolved by the network perspective. Although the problem is ameliorated, one should not anticipate a one-to-one mapping when the network approach is adopted. Furthermore, decomposition of the brain network in terms of meaningful clusters of regions, such as the ones generated by community-finding algorithms, does not by itself reveal “true” subnetworks. Given the hierarchical and multi-relational relationship between regions, multiple decompositions will offer different “slices” of a broader landscape of networks within the brain. Finally, I described how the function of brain regions can be characterized in a multidimensional manner via the idea of diversity profiles. The concept can also be used to describe the way different brain regions participate in networks. PMID:24819881

Brain Region-Specific Activity Patterns after Recent or Remote Memory Retrieval of Auditory Conditioned Fear

ERIC Educational Resources Information Center

Kwon, Jeong-Tae; Jhang, Jinho; Kim, Hyung-Su; Lee, Sujin; Han, Jin-Hee

2012-01-01

Memory is thought to be sparsely encoded throughout multiple brain regions forming unique memory trace. Although evidence has established that the amygdala is a key brain site for memory storage and retrieval of auditory conditioned fear memory, it remains elusive whether the auditory brain regions may be involved in fear memory storage or…

Structural connectivity asymmetry in the neonatal brain.

PubMed

Ratnarajah, Nagulan; Rifkin-Graboi, Anne; Fortier, Marielle V; Chong, Yap Seng; Kwek, Kenneth; Saw, Seang-Mei; Godfrey, Keith M; Gluckman, Peter D; Meaney, Michael J; Qiu, Anqi

2013-07-15

Asymmetry of the neonatal brain is not yet understood at the level of structural connectivity. We utilized DTI deterministic tractography and structural network analysis based on graph theory to determine the pattern of structural connectivity asymmetry in 124 normal neonates. We tracted white matter axonal pathways characterizing interregional connections among brain regions and inferred asymmetry in left and right anatomical network properties. Our findings revealed that in neonates, small-world characteristics were exhibited, but did not differ between the two hemispheres, suggesting that neighboring brain regions connect tightly with each other, and that one region is only a few paths away from any other region within each hemisphere. Moreover, the neonatal brain showed greater structural efficiency in the left hemisphere than that in the right. In neonates, brain regions involved in motor, language, and memory functions play crucial roles in efficient communication in the left hemisphere, while brain regions involved in emotional processes play crucial roles in efficient communication in the right hemisphere. These findings suggest that even at birth, the topology of each cerebral hemisphere is organized in an efficient and compact manner that maps onto asymmetric functional specializations seen in adults, implying lateralized brain functions in infancy. Copyright © 2013 Elsevier Inc. All rights reserved.

The solution structure of omega-Aga-IVB, a P-type calcium channel antagonist from venom of the funnel web spider, Agelenopsis aperta.

PubMed

Reily, M D; Thanabal, V; Adams, M E

1995-02-01

The 48 amino acid peptides omega-Aga-IVA and omega-Aga-IVB are the first agents known to specifically block P-type calcium channels in mammalian brain, thus complementing the existing suite of pharmacological tools used for characterizing calcium channels. These peptides provide a new set of probes for studies aimed at elucidating the structural basis underlying the subtype specificity of calcium channel antagonists. We used 288 NMR-derived constraints in a protocol combining distance geometry and molecular dynamics employing the program DGII, followed by energy minimization with Discover to derive the three-dimensional structure of omega-Aga-IVB. The toxin consists of a well-defined core region, comprising seven solvent-shielded residues and a well-defined triple-stranded beta-sheet. Four loop regions have average backbone rms deviations between 0.38 and 1.31 A, two of which are well-defined type-II beta-turns. Other structural features include disordered C- and N-termini and several conserved basic amino acids that are clustered on one face of the molecule. The reported structure suggests a possible surface for interaction with the channel. This surface contains amino acids that are identical to those of another known P-type calcium channel antagonist, omega-Aga-IVA, and is rich in basic residues that may have a role in binding to the anionic sites in the extracellular regions of the calcium channel.

Assessing Relevance of External Cognitive Measures

PubMed Central

Cairó, Osvaldo

2017-01-01

The arrival of modern brain imaging technologies has provided new opportunities for examining the biological essence of human intelligence as well as the relationship between brain size and cognition. Thanks to these advances, we can now state that the relationship between brain size and intelligence has never been well understood. This view is supported by findings showing that cognition is correlated more with brain tissues than sheer brain size. The complexity of cellular and molecular organization of neural connections actually determines the computational capacity of the brain. In this review article, we determine that while genotypes are responsible for defining the theoretical limits of intelligence, what is primarily responsible for determining whether those limits are reached or exceeded is experience (environmental influence). Therefore, we contend that the gene-environment interplay defines the intelligent quotient of an individual. PMID:28270753

Relation between brain architecture and mathematical ability in children: a DBM study.

PubMed

Han, Zhaoying; Davis, Nicole; Fuchs, Lynn; Anderson, Adam W; Gore, John C; Dawant, Benoit M

2013-12-01

Population-based studies indicate that between 5 and 9 percent of US children exhibit significant deficits in mathematical reasoning, yet little is understood about the brain morphological features related to mathematical performances. In this work, deformation-based morphometry (DBM) analyses have been performed on magnetic resonance images of the brains of 79 third graders to investigate whether there is a correlation between brain morphological features and mathematical proficiency. Group comparison was also performed between Math Difficulties (MD-worst math performers) and Normal Controls (NC), where each subgroup consists of 20 age and gender matched subjects. DBM analysis is based on the analysis of the deformation fields generated by non-rigid registration algorithms, which warp the individual volumes to a common space. To evaluate the effect of registration algorithms on DBM results, five nonrigid registration algorithms have been used: (1) the Adaptive Bases Algorithm (ABA); (2) the Image Registration Toolkit (IRTK); (3) the FSL Nonlinear Image Registration Tool; (4) the Automatic Registration Tool (ART); and (5) the normalization algorithm available in SPM8. The deformation field magnitude (DFM) was used to measure the displacement at each voxel, and the Jacobian determinant (JAC) was used to quantify local volumetric changes. Results show there are no statistically significant volumetric differences between the NC and the MD groups using JAC. However, DBM analysis using DFM found statistically significant anatomical variations between the two groups around the left occipital-temporal cortex, left orbital-frontal cortex, and right insular cortex. Regions of agreement between at least two algorithms based on voxel-wise analysis were used to define Regions of Interest (ROIs) to perform an ROI-based correlation analysis on all 79 volumes. Correlations between average DFM values and standard mathematical scores over these regions were found to be significant. We also found that the choice of registration algorithm has an impact on DBM-based results, so we recommend using more than one algorithm when conducting DBM studies. To the best of our knowledge, this is the first study that uses DBM to investigate brain anatomical features related to mathematical performance in a relatively large population of children. © 2013.

Characterization of a normal control group: are they healthy?

PubMed

Aine, C J; Sanfratello, L; Adair, J C; Knoefel, J E; Qualls, C; Lundy, S L; Caprihan, A; Stone, D; Stephen, J M

2014-01-01

We examined the health of a control group (18-81years) in our aging study, which is similar to control groups used in other neuroimaging studies. The current study was motivated by our previous results showing that one third of the elder control group had moderate to severe white matter hyperintensities and/or cortical volume loss which correlated with poor performance on memory tasks. Therefore, we predicted that cardiovascular risk factors (e.g., hypertension, high cholesterol) within the control group would account for significant variance on working memory task performance. Fifty-five participants completed 4 verbal and spatial working memory tasks, neuropsychological exams, diffusion tensor imaging (DTI), and blood tests to assess vascular risk. In addition to using a repeated measures ANOVA design, a cluster analysis was applied to the vascular risk measures as a data reduction step to characterize relationships between conjoint risk factors. The cluster groupings were used to predict working memory performance. The results show that higher levels of systolic blood pressure were associated with: 1) poor spatial working memory accuracy; and 2) lower fractional anisotropy (FA) values in multiple brain regions. In contrast, higher levels of total cholesterol corresponded with increased accuracy in verbal working memory. An association between lower FA values and higher cholesterol levels were identified in different brain regions from those associated with systolic blood pressure. The conjoint risk analysis revealed that Risk Cluster Group 3 (the group with the greatest number of risk factors) displayed: 1) the poorest performance on the spatial working memory tasks; 2) the longest reaction times across both spatial and verbal memory tasks; and 3) the lowest FA values across widespread brain regions. Our results confirm that a considerable range of vascular risk factors are present in a typical control group, even in younger individuals, which have robust effects on brain anatomy and function. These results present a new challenge to neuroimaging studies both for defining a cohort from which to characterize 'normative' brain circuitry and for establishing a control group to compare with other clinical populations. © 2013.

Detection by voxel-wise statistical analysis of significant changes in regional cerebral glucose uptake in an APP/PS1 transgenic mouse model of Alzheimer's disease.

PubMed

Dubois, Albertine; Hérard, Anne-Sophie; Delatour, Benoît; Hantraye, Philippe; Bonvento, Gilles; Dhenain, Marc; Delzescaux, Thierry

2010-06-01

Biomarkers and technologies similar to those used in humans are essential for the follow-up of Alzheimer's disease (AD) animal models, particularly for the clarification of mechanisms and the screening and validation of new candidate treatments. In humans, changes in brain metabolism can be detected by 1-deoxy-2-[(18)F] fluoro-D-glucose PET (FDG-PET) and assessed in a user-independent manner with dedicated software, such as Statistical Parametric Mapping (SPM). FDG-PET can be carried out in small animals, but its resolution is low as compared to the size of rodent brain structures. In mouse models of AD, changes in cerebral glucose utilization are usually detected by [(14)C]-2-deoxyglucose (2DG) autoradiography, but this requires prior manual outlining of regions of interest (ROI) on selected sections. Here, we evaluate the feasibility of applying the SPM method to 3D autoradiographic data sets mapping brain metabolic activity in a transgenic mouse model of AD. We report the preliminary results obtained with 4 APP/PS1 (64+/-1 weeks) and 3 PS1 (65+/-2 weeks) mice. We also describe new procedures for the acquisition and use of "blockface" photographs and provide the first demonstration of their value for the 3D reconstruction and spatial normalization of post mortem mouse brain volumes. Despite this limited sample size, our results appear to be meaningful, consistent, and more comprehensive than findings from previously published studies based on conventional ROI-based methods. The establishment of statistical significance at the voxel level, rather than with a user-defined ROI, makes it possible to detect more reliably subtle differences in geometrically complex regions, such as the hippocampus. Our approach is generic and could be easily applied to other biomarkers and extended to other species and applications. Copyright 2010 Elsevier Inc. All rights reserved.

Altered interregional molecular associations of the serotonin transporter in attention deficit/hyperactivity disorder assessed with PET.

PubMed

Vanicek, Thomas; Kutzelnigg, Alexandra; Philippe, Cecile; Sigurdardottir, Helen L; James, Gregory M; Hahn, Andreas; Kranz, Georg S; Höflich, Anna; Kautzky, Alexander; Traub-Weidinger, Tatjana; Hacker, Marcus; Wadsak, Wolfgang; Mitterhauser, Markus; Kasper, Siegfried; Lanzenberger, Rupert

2017-02-01

Altered serotonergic neurotransmission has been found to cause impulsive and aggressive behavior, as well as increased motor activity, all exemplifying key symptoms of ADHD. The main objectives of this positron emission tomography (PET) study were to investigate the serotonin transporter binding potential (SERT BP ND ) in patients with ADHD and to assess associations of SERT BP ND between the brain regions. 25 medication-free patients with ADHD (age ± SD; 32.39 ± 10.15; 10 females) without any psychiatric comorbidity and 25 age and sex matched healthy control subjects (33.74 ± 10.20) were measured once with PET and the highly selective and specific radioligand [ 11 C]DASB. SERT BP ND maps in nine a priori defined ROIs exhibiting high SERT binding were compared between groups by means of a linear mixed model. Finally, adopted from structural and functional connectivity analyses, we performed correlational analyses using regional SERT binding potentials to examine molecular interregional associations between all selected ROIs. We observed significant differences in the interregional correlations between the precuneus and the hippocampus in patients with ADHD compared to healthy controls, using SERT BP ND of the investigated ROIs (P < 0.05; Bonferroni corrected). When correlating SERT BP ND and age in the ADHD and the healthy control group, we confirmed an age-related decline in brain SERT binding in the thalamus and insula (R 2  = 0.284, R 2  = 0.167, Ps < 0.05; Bonferroni corrected). The results show significantly different interregional molecular associations of the SERT expression for the precuneus with hippocampus in patients with ADHD, indicating presumably altered functional coupling. Altered interregional coupling between brain regions might be a sensitive approach to demonstrate functional and molecular alterations in psychiatric conditions. Hum Brain Mapp 38:792-802, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Neonatal Pain-Related Stress Predicts Cortical Thickness at Age 7 Years in Children Born Very Preterm

PubMed Central

Ranger, Manon; Chau, Cecil M. Y.; Garg, Amanmeet; Woodward, Todd S.; Beg, Mirza Faisal; Bjornson, Bruce; Poskitt, Kenneth; Fitzpatrick, Kevin; Synnes, Anne R.; Miller, Steven P.; Grunau, Ruth E.

2013-01-01

Background Altered brain development is evident in children born very preterm (24–32 weeks gestational age), including reduction in gray and white matter volumes, and thinner cortex, from infancy to adolescence compared to term-born peers. However, many questions remain regarding the etiology. Infants born very preterm are exposed to repeated procedural pain-related stress during a period of very rapid brain development. In this vulnerable population, we have previously found that neonatal pain-related stress is associated with atypical brain development from birth to term-equivalent age. Our present aim was to evaluate whether neonatal pain-related stress (adjusted for clinical confounders of prematurity) is associated with altered cortical thickness in very preterm children at school age. Methods 42 right-handed children born very preterm (24–32 weeks gestational age) followed longitudinally from birth underwent 3-D T1 MRI neuroimaging at mean age 7.9 yrs. Children with severe brain injury and major motor/sensory/cognitive impairment were excluded. Regional cortical thickness was calculated using custom developed software utilizing FreeSurfer segmentation data. The association between neonatal pain-related stress (defined as the number of skin-breaking procedures) accounting for clinical confounders (gestational age, illness severity, infection, mechanical ventilation, surgeries, and morphine exposure), was examined in relation to cortical thickness using constrained principal component analysis followed by generalized linear modeling. Results After correcting for multiple comparisons and adjusting for neonatal clinical factors, greater neonatal pain-related stress was associated with significantly thinner cortex in 21/66 cerebral regions (p-values ranged from 0.00001 to 0.014), predominately in the frontal and parietal lobes. Conclusions In very preterm children without major sensory, motor or cognitive impairments, neonatal pain-related stress appears to be associated with thinner cortex in multiple regions at school age, independent of other neonatal risk factors. PMID:24204657

Differential effect of Amyloid Beta on the Cytochrome P450 epoxygenase activity in rat brain

PubMed Central

Sarkar, Pallabi; Narayanan, Jayashree; Harder, David R.

2011-01-01

One of the prominent features of Alzheimer's disease is the excessive accumulation of the protein amyloid beta (Aβ) in certain areas of the brain leading to neurodegeneration. Aβ is cytotoxic and disrupts several cytoprotective pathways. Recent literature has demonstrated that certain cytochrome P450 (CYP) products are neuroprotective, including epoxide metabolites of arachidonic acid (AA), epoxyeicosatrienoic acids (EETs). The action of Aβ with respect to regionally produced EETs in the brain has yet to be defined. Epoxygenases metabolize AA into 4 regioisomers of EETs (14,15 -, 11,12-, 8,9- and 5,6-EET). EETs are rapidly degraded into dihydroxyeicosatrienoic acids (DiHETEs) by soluble epoxide hydrolase (sEH). To determine the effect of Aβ on the epoxygenase activity in different regions of the brain, microsomes were prepared from the cerebrum and cerebellum of adult Sprague-Dawley rats and incubated with 1 and 10 μM Aβ for 30 minutes after which epoxygenase activity assay was performed. Mass spectrometry indicated that incubation with Aβ reduced 14,15-EET production by 30% as compared to vehicle in the cerebrum, but not in the cerebellum. When we separated the cerebrum into cortex and hippocampus, significant decrease in the production of total EETs and DiHETEs were seen in presence of Aβ (81% and 74%) in the cortex. Moreover, 11, 12-EET production was decreased to ∼70% of vehicle in both cortex and hippocampus. Epoxygenase activity in the cultured astrocytes and neurons also showed reduction in total EET and DiHETE production (to 80% and ∼70% of vehicle respectively) in presence of Aβ. Altogether, our data suggest that Aβ reduces epoxygenase activity differentially in a region-specific and cell-specific manner. The reduction of cytoprotective EETs by Aβ in the cerebrum may make it more prone to degeneration than the cerebellum. Further understanding of these interactions will improve our ability to protect against the pathology of Alzheimer's disease. PMID:21843605

Dynamic functional brain networks involved in simple visual discrimination learning.

PubMed

Fidalgo, Camino; Conejo, Nélida María; González-Pardo, Héctor; Arias, Jorge Luis

2014-10-01

Visual discrimination tasks have been widely used to evaluate many types of learning and memory processes. However, little is known about the brain regions involved at different stages of visual discrimination learning. We used cytochrome c oxidase histochemistry to evaluate changes in regional brain oxidative metabolism during visual discrimination learning in a water-T maze at different time points during training. As compared with control groups, the results of the present study reveal the gradual activation of cortical (prefrontal and temporal cortices) and subcortical brain regions (including the striatum and the hippocampus) associated to the mastery of a simple visual discrimination task. On the other hand, the brain regions involved and their functional interactions changed progressively over days of training. Regions associated with novelty, emotion, visuo-spatial orientation and motor aspects of the behavioral task seem to be relevant during the earlier phase of training, whereas a brain network comprising the prefrontal cortex was found along the whole learning process. This study highlights the relevance of functional interactions among brain regions to investigate learning and memory processes. Copyright © 2014 Elsevier Inc. All rights reserved.

Coherent activity between brain regions that code for value is linked to the malleability of human behavior

PubMed Central

Cooper, Nicole; Bassett, Danielle S.; Falk, Emily B.

2017-01-01

Brain activity in medial prefrontal cortex (MPFC) during exposure to persuasive messages can predict health behavior change. This brain-behavior relationship has been linked to areas of MPFC previously associated with self-related processing; however, the mechanism underlying this relationship is unclear. We explore two components of self-related processing – self-reflection and subjective valuation – and examine coherent activity between relevant networks of brain regions during exposure to health messages encouraging exercise and discouraging sedentary behaviors. We find that objectively logged reductions in sedentary behavior in the following month are linked to functional connectivity within brain regions associated with positive valuation, but not within regions associated with self-reflection on personality traits. Furthermore, functional connectivity between valuation regions contributes additional information compared to average brain activation within single brain regions. These data support an account in which MPFC integrates the value of messages to the self during persuasive health messaging and speak to broader questions of how humans make decisions about how to behave. PMID:28240271

Structural connectome topology relates to regional BOLD signal dynamics in the mouse brain

NASA Astrophysics Data System (ADS)

Sethi, Sarab S.; Zerbi, Valerio; Wenderoth, Nicole; Fornito, Alex; Fulcher, Ben D.

2017-04-01

Brain dynamics are thought to unfold on a network determined by the pattern of axonal connections linking pairs of neuronal elements; the so-called connectome. Prior work has indicated that structural brain connectivity constrains pairwise correlations of brain dynamics ("functional connectivity"), but it is not known whether inter-regional axonal connectivity is related to the intrinsic dynamics of individual brain areas. Here we investigate this relationship using a weighted, directed mesoscale mouse connectome from the Allen Mouse Brain Connectivity Atlas and resting state functional MRI (rs-fMRI) time-series data measured in 184 brain regions in eighteen anesthetized mice. For each brain region, we measured degree, betweenness, and clustering coefficient from weighted and unweighted, and directed and undirected versions of the connectome. We then characterized the univariate rs-fMRI dynamics in each brain region by computing 6930 time-series properties using the time-series analysis toolbox, hctsa. After correcting for regional volume variations, strong and robust correlations between structural connectivity properties and rs-fMRI dynamics were found only when edge weights were accounted for, and were associated with variations in the autocorrelation properties of the rs-fMRI signal. The strongest relationships were found for weighted in-degree, which was positively correlated to the autocorrelation of fMRI time series at time lag τ = 34 s (partial Spearman correlation ρ = 0.58 ), as well as a range of related measures such as relative high frequency power (f > 0.4 Hz: ρ = - 0.43 ). Our results indicate that the topology of inter-regional axonal connections of the mouse brain is closely related to intrinsic, spontaneous dynamics such that regions with a greater aggregate strength of incoming projections display longer timescales of activity fluctuations.

Defining traumatic brain injury in children and youth using international classification of diseases version 10 codes: a systematic review protocol.

PubMed

Chan, Vincy; Thurairajah, Pravheen; Colantonio, Angela

2013-11-13

Although healthcare administrative data are commonly used for traumatic brain injury research, there is currently no consensus or consistency on using the International Classification of Diseases version 10 codes to define traumatic brain injury among children and youth. This protocol is for a systematic review of the literature to explore the range of International Classification of Diseases version 10 codes that are used to define traumatic brain injury in this population. The databases MEDLINE, MEDLINE In-Process, Embase, PsychINFO, CINAHL, SPORTDiscus, and Cochrane Database of Systematic Reviews will be systematically searched. Grey literature will be searched using Grey Matters and Google. Reference lists of included articles will also be searched. Articles will be screened using predefined inclusion and exclusion criteria and all full-text articles that meet the predefined inclusion criteria will be included for analysis. The study selection process and reasons for exclusion at the full-text level will be presented using a PRISMA study flow diagram. Information on the data source of included studies, year and location of study, age of study population, range of incidence, and study purpose will be abstracted into a separate table and synthesized for analysis. All International Classification of Diseases version 10 codes will be listed in tables and the codes that are used to define concussion, acquired traumatic brain injury, head injury, or head trauma will be identified. The identification of the optimal International Classification of Diseases version 10 codes to define this population in administrative data is crucial, as it has implications for policy, resource allocation, planning of healthcare services, and prevention strategies. It also allows for comparisons across countries and studies. This protocol is for a review that identifies the range and most common diagnoses used to conduct surveillance for traumatic brain injury in children and youth. This is an important first step in reaching an appropriate definition using International Classification of Diseases version 10 codes and can inform future work on reaching consensus on the codes to define traumatic brain injury for this vulnerable population.

Age-and Brain Region-Specific Differences in Mitochondrial ...

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Mitochondria are central regulators of energy homeostasis and play a pivotal role in mechanisms of cellular senescence. The objective of the present study was to evaluate mitochondrial bio­-energetic parameters in five brain regions [brainstem (BS), frontal cortex (FC), cerebellum (CER), striatum (STR), hippocampus (HIP)] of four diverse age groups [1 Month (young), 4 Month (adult), 12 Month (middle-aged), 24 Month (old age)] to understand age-related differences in selected brain regions and their contribution to age-related chemical sensitivity. Mitochondrial bioenergetics parameters and enzyme activity were measured under identical conditions across multiple age groups and brain regions in Brown Norway rats (n = 5). The results indicate age- and brain region-specific patterns in mitochondrial functional endpoints. For example, an age-specific decline in ATP synthesis (State 111 respiration) was observed in BS and HIP. Similarly, the maximal respiratory capacities (State V1 and V2) showed age-specific declines in all brain regions examined (young > adult > middle-aged > old age). Amongst all regions, HIP had the greatest change in mitochondrial bioenergetics, showing declines in the 4, 12 and 24 Month age groups. Activities of mitochondrial pyruvate dehydrogenase complex (PDHC) and electron transport chain (ETC) complexes I, II, and IV enzymes were also age- and brain-region specific. In general changes associated with age were more pronounced, with

Defining Functional Areas in Individual Human Brains using Resting Functional Connectivity MRI

PubMed Central

Cohen, Alexander L.; Fair, Damien A.; Dosenbach, Nico U.F.; Miezin, Francis M.; Dierker, Donna; Van Essen, David C.; Schlaggar, Bradley L.; Petersen, Steven E.

2009-01-01

The cerebral cortex is anatomically organized at many physical scales starting at the level of single neurons and extending up to functional systems. Current functional magnetic resonance imaging (fMRI) studies often focus at the level of areas, networks, and systems. Except in restricted domains, (e.g. topographically-organized sensory regions), it is difficult to determine area boundaries in the human brain using fMRI. The ability to delineate functional areas non-invasively would enhance the quality of many experimental analyses allowing more accurate across-subject comparisons of independently identified functional areas. Correlations in spontaneous BOLD activity, often referred to as resting state functional connectivity (rs-fcMRI), are especially promising as a way to accurately localize differences in patterns of correlated activity across large expanses of cortex. In the current report, we applied a novel set of image analysis tools to explore the utility of rs-fcMRI for defining wide-ranging functional area boundaries. We find that rs-fcMRI patterns show sharp transitions in correlation patterns and that these putative areal boundaries can be reliably detected in individual subjects as well as in group data. Additionally, combining surface-based analysis techniques with image processing algorithms allows automated mapping of putative areal boundaries across large expanses of cortex without the need for prior information about a region’s function or topography. Our approach reliably produces maps of bounded regions appropriate in size and number for putative functional areas. These findings will hopefully stimulate further methodological refinements and validations. PMID:18367410

The Role Of Basal Forebrain Cholinergic Neurons In Fear and Extinction Memory

PubMed Central

Knox, Dayan

2016-01-01

Cholinergic input to the neocortex, dorsal hippocampus (dHipp), and basolateral amygdala (BLA) is critical for neural function and synaptic plasticity in these brain regions. Synaptic plasticity in the neocortex, dHipp, ventral Hipp (vHipp), and BLA has also been implicated in fear and extinction memory. This finding raises the possibility that basal forebrain (BF) cholinergic neurons, the predominant source of acetylcholine in these brain regions, have an important role in mediating fear and extinction memory. While empirical studies support this hypothesis, there are interesting inconsistencies among these studies that raise questions about how best to define the role of BF cholinergic neurons in fear and extinction memory. Nucleus basalis magnocellularis (NBM) cholinergic neurons that project to the BLA are critical for fear memory and contextual fear extinction memory. NBM cholinergic neurons that project to the neocortex are critical for cued and contextual fear conditioned suppression, but are not critical for fear memory in other behavioral paradigms and in the inhibitory avoidance paradigm may even inhibit contextual fear memory formation. Medial septum and diagonal band of Broca cholinergic neurons are critical for contextual fear memory and acquisition of cued fear extinction. Thus, even though the results of previous studies suggest BF cholinergic neurons modulate fear and extinction memory, inconsistent findings among these studies necessitates more research to better define the neural circuits and molecular processes through which BF cholinergic neurons modulate fear and extinction memory. Furthermore, studies determining if BF cholinergic neurons can be manipulated in such a manner so as to treat excessive fear in anxiety disorders are needed. PMID:27264248

Specific Connectivity and Unique Molecular Identity of MET Receptor Tyrosine Kinase Expressing Serotonergic Neurons in the Caudal Dorsal Raphe Nuclei.

PubMed

Kast, Ryan J; Wu, Hsiao-Huei; Williams, Piper; Gaspar, Patricia; Levitt, Pat

2017-05-17

Molecular characterization of neurons across brain regions has revealed new taxonomies for understanding functional diversity even among classically defined neuronal populations. Neuronal diversity has become evident within the brain serotonin (5-HT) system, which is far more complex than previously appreciated. However, until now it has been difficult to define subpopulations of 5-HT neurons based on molecular phenotypes. We demonstrate that the MET receptor tyrosine kinase (MET) is specifically expressed in a subset of 5-HT neurons within the caudal part of the dorsal raphe nuclei (DRC) that is encompassed by the classic B6 serotonin cell group. Mapping from embryonic day 16 through adulthood reveals that MET is expressed almost exclusively in the DRC as a condensed, paired nucleus, with an additional sparse set of MET+ neurons scattered within the median raphe. Retrograde tracing experiments reveal that MET-expressing 5-HT neurons provide substantial serotonergic input to the ventricular/subventricular region that contains forebrain stem cells, but do not innervate the dorsal hippocampus or entorhinal cortex. Conditional anterograde tracing experiments show that 5-HT neurons in the DRC/B6 target additional forebrain structures such as the medial and lateral septum and the ventral hippocampus. Molecular neuroanatomical analysis identifies 14 genes that are enriched in DRC neurons, including 4 neurotransmitter/neuropeptide receptors and 2 potassium channels. These analyses will lead to future studies determining the specific roles that 5-HT MET+ neurons contribute to the broader set of functions regulated by the serotonergic system.

A review of MRI findings in schizophrenia

PubMed Central

Shenton, Martha E.; Dickey, Chandlee C.; Frumin, Melissa; McCarley, Robert W.

2009-01-01

After more than 100 years of research, the neuropathology of schizophrenia remains unknown and this is despite the fact that both Kraepelin (1919/1971: Kraepelin,E., 1919/1971. Dementia praecox. Churchill Livingston Inc., New York) and Bleuler (1911/1950: Bleuler, E., 1911/1950. Dementia praecox or the group of schizophrenias. International Universities Press, New York), who first described ‘dementia praecox’ and the ‘ schizophrenias’, were convinced that schizophrenia would ultimately be linked to an organic brain disorder. Alzheimer (1897: Alzheimer, A., 1897. Beitrage zur pathologischen anatomie der hirnrinde und zur anatomischen grundlage einiger psychosen. Monatsschrift fur Psychiarie und Neurologie. 2, 82–120) was the first to investigate the neuropathology of schizophrenia, though he went on to study more tractable brain diseases. The results of subsequent neuropathological studies were disappointing because of conflicting findings. Research interest thus waned and did not flourish again until 1976, following the pivotal computer assisted tomography (CT) finding of lateral ventricular enlargement in schizophrenia by Johnstone and colleagues. Since that time significant progress has been made in brain imaging, particularly with the advent of magnetic resonance imaging (MRI), beginning with the first MRI study of schizophrenia by Smith and coworkers in 1984 (Smith, R.C., Calderon, M., Ravichandran, G.K., et al. (1984). Nuclear magnetic resonance in schizophrenia: A preliminary study. Psychiatry Res. 12, 137–147). MR in vivo imaging of the brain now confirms brain abnormalities in schizophrenia. The 193 peer reviewed MRI studies reported in the current review span the period from 1988 to August, 2000. This 12 year period has witnessed a burgeoning of MRI studies and has led to more definitive findings of brain abnormalities in schizophrenia than any other time period in the history of schizophrenia research. Such progress in defining the neuropathology of schizophrenia is largely due to advances in in vivo MRI techniques. These advances have now led to the identification of a number of brain abnormalities in schizophrenia. Some of these abnormalities confirm earlier post-mortem findings, and most are small and subtle, rather than large, thus necessitating more advanced and accurate measurement tools. These findings include ventricular enlargement (80% of studies reviewed) and third ventricle enlargement (73% of studies reviewed). There is also preferential involvement of medial temporal lobe structures (74% of studies reviewed), which include the amygdala, hippocampus, and parahippocampal gyrus, and neocortical temporal lobe regions (superior temporal gyrus) (100% of studies reviewed). When gray and white matter of superior temporal gyrus was combined, 67% of studies reported abnormalities. There was also moderate evidence for frontal lobe abnormalities (59% of studies reviewed), particularly prefrontal gray matter and orbitofrontal regions. Similarly, there was moderate evidence for parietal lobe abnormalities (60% of studies reviewed), particularly of the inferior parietal lobule which includes both supramarginal and angular gyri. Additionally, there was strong to moderate evidence for subcortical abnormalities (i.e. cavum septi pellucidi—92% of studies reviewed, basal ganglia—68% of studies reviewed, corpus callosum—63% of studies reviewed, and thalamus—42% of studies reviewed), but more equivocal evidence for cerebellar abnormalities (31% of studies reviewed). The timing of such abnormalities has not yet been determined, although many are evident when a patient first becomes symptomatic. There is, however, also evidence that a subset of brain abnormalities may change over the course of the illness. The most parsimonious explanation is that some brain abnormalities are neurodevelopmental in origin but unfold later in development, thus setting the stage for the development of the symptoms of schizophrenia. Or there may be additional factors, such as stress or neurotoxicity, that occur during adolescence or early adulthood and are necessary for the development of schizophrenia, and may be associated with neurodegenerative changes. Importantly, as several different brain regions are involved in the neuropathology of schizophrenia, new models need to be developed and tested that explain neural circuitry abnormalities effecting brain regions not necessarily structurally proximal to each other but nonetheless functionally interrelated. Future studies will likely benefit from: (1) studying more homogeneous patient groups so that the relationship between MRI findings and clinical symptoms become more meaningful; (2) studying at risk populations such as family members of patients diagnosed with schizophrenia and subjects diagnosed with schizotypal personality disorder in order to define which abnormalities are specific to schizophrenia spectrum disorders, which are the result of epiphenomena such as medication effects and chronic institutionalization, and which are needed for the development of frank psychosis; (3) examining shape differences not detectable from measuring volume alone; (4) applying newer methods such as diffusion tensor imaging to investigate abnormalities in brain connectivity and white matter fiber tracts; and, (5) using methods that analyze brain function (fMRI) and structure simultaneously. PMID:11343862

Early fever after trauma: Does it matter?

PubMed

Hinson, Holly E; Rowell, Susan; Morris, Cynthia; Lin, Amber L; Schreiber, Martin A

2018-01-01

Fever is strongly associated with poor outcome after traumatic brain injury (TBI). We hypothesized that early fever is a direct result of brain injury and thus would be more common in TBI than in patients without brain injury and associated with inflammation. We prospectively enrolled patients with major trauma with and without TBI from a busy Level I trauma center intensive care unit (ICU). Patients were assigned to one of four groups based on their presenting Head Abbreviated Injury Severity Scale scores: multiple injuries: head Abbreviated Injury Scale (AIS) score greater than 2, one other region greater than 2; isolated head: head AIS score greater than 2, all other regions less than 3; isolated body: one region greater than 2, excluding head/face; minor injury: no region with AIS greater than 2. Early fever was defined as at least one recorded temperature greater than 38.3°C in the first 48 hours after admission. Outcome measures included neurologic deterioration, length of stay in the ICU, hospital mortality, discharge Glasgow Outcome Scale-Extended, and plasma levels of seven key cytokines at admission and 24 hours (exploratory). Two hundred sixty-eight patients were enrolled, including subjects with multiple injuries (n = 59), isolated head (n = 97), isolated body (n = 100), and minor trauma (n = 12). The incidence of fever was similar in all groups irrespective of injury (11-24%). In all groups, there was a significant association between the presence of early fever and death in the hospital (6-18% vs. 0-3%), as well as longer median ICU stays (3-7 days vs. 2-3 days). Fever was significantly associated with elevated IL-6 at admission (50.7 pg/dL vs. 16.9 pg/dL, p = 0.0067) and at 24 hours (83.1 pg/dL vs. 17.1 pg/dL, p = 0.0025) in the isolated head injury group. Contrary to our hypothesis, early fever was not more common in patients with brain injury, though fever was associated with longer ICU stays and death in all groups. Additionally, fever was associated with elevated IL-6 levels in isolated head injury. Prognostic and Epidemiological study, level III.

Abnormal brain functional connectivity leads to impaired mood and cognition in hyperthyroidism: a resting-state functional MRI study

PubMed Central

Li, Ling; Zhi, Mengmeng; Hou, Zhenghua; Zhang, Yuqun; Yue, Yingying; Yuan, Yonggui

2017-01-01

Patients with hyperthyroidism frequently have neuropsychiatric complaints such as lack of concentration, poor memory, depression, anxiety, nervousness, and irritability, suggesting brain dysfunction. However, the underlying process of these symptoms remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI), we depicted the altered graph theoretical metric degree centrality (DC) and seed-based resting-state functional connectivity (FC) in 33 hyperthyroid patients relative to 33 healthy controls. The peak points of significantly altered DC between the two groups were defined as the seed regions to calculate FC to the whole brain. Then, partial correlation analyses were performed between abnormal DC, FC and neuropsychological performances, as well as some clinical indexes. The decreased intrinsic functional connectivity in the posterior lobe of cerebellum (PLC) and medial frontal gyrus (MeFG), as well as the abnormal seed-based FC anchored in default mode network (DMN), attention network, visual network and cognitive network in this study, possibly constitutes the latent mechanism for emotional and cognitive changes in hyperthyroidism, including anxiety and impaired processing speed. PMID:28009983

Minimally invasive multimode optical fiber microendoscope for deep brain fluorescence imaging

PubMed Central

Ohayon, Shay; Caravaca-Aguirre, Antonio; Piestun, Rafael; DiCarlo, James J.

2018-01-01

A major open challenge in neuroscience is the ability to measure and perturb neural activity in vivo from well defined neural sub-populations at cellular resolution anywhere in the brain. However, limitations posed by scattering and absorption prohibit non-invasive multi-photon approaches for deep (>2mm) structures, while gradient refractive index (GRIN) endoscopes are relatively thick and can cause significant damage upon insertion. Here, we present a novel micro-endoscope design to image neural activity at arbitrary depths via an ultra-thin multi-mode optical fiber (MMF) probe that has 5–10X thinner diameter than commercially available micro-endoscopes. We demonstrate micron-scale resolution, multi-spectral and volumetric imaging. In contrast to previous approaches, we show that this method has an improved acquisition speed that is sufficient to capture rapid neuronal dynamics in-vivo in rodents expressing a genetically encoded calcium indicator (GCaMP). Our results emphasize the potential of this technology in neuroscience applications and open up possibilities for cellular resolution imaging in previously unreachable brain regions. PMID:29675297

Spatial organization of astrocytes in ferret visual cortex

PubMed Central

López‐Hidalgo, Mónica; Hoover, Walter B.

2016-01-01

ABSTRACT Astrocytes form an intricate partnership with neural circuits to influence numerous cellular and synaptic processes. One prominent organizational feature of astrocytes is the “tiling” of the brain with non‐overlapping territories. There are some documented species and brain region–specific astrocyte specializations, but the extent of astrocyte diversity and circuit specificity are still unknown. We quantitatively defined the rules that govern the spatial arrangement of astrocyte somata and territory overlap in ferret visual cortex using a combination of in vivo two‐photon imaging, morphological reconstruction, immunostaining, and model simulations. We found that ferret astrocytes share, on average, half of their territory with other astrocytes. However, a specific class of astrocytes, abundant in thalamo‐recipient cortical layers (“kissing” astrocytes), overlap markedly less. Together, these results demonstrate novel features of astrocyte organization indicating that different classes of astrocytes are arranged in a circuit‐specific manner and that tiling does not apply universally across brain regions and species. J. Comp. Neurol. 524:3561–3576, 2016. © 2016 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc. PMID:27072916

White matter pathways and social cognition.

PubMed

Wang, Yin; Metoki, Athanasia; Alm, Kylie H; Olson, Ingrid R

2018-04-20

There is a growing consensus that social cognition and behavior emerge from interactions across distributed regions of the "social brain". Researchers have traditionally focused their attention on functional response properties of these gray matter networks and neglected the vital role of white matter connections in establishing such networks and their functions. In this article, we conduct a comprehensive review of prior research on structural connectivity in social neuroscience and highlight the importance of this literature in clarifying brain mechanisms of social cognition. We pay particular attention to three key social processes: face processing, embodied cognition, and theory of mind, and their respective underlying neural networks. To fully identify and characterize the anatomical architecture of these networks, we further implement probabilistic tractography on a large sample of diffusion-weighted imaging data. The combination of an in-depth literature review and the empirical investigation gives us an unprecedented, well-defined landscape of white matter pathways underlying major social brain networks. Finally, we discuss current problems in the field, outline suggestions for best practice in diffusion-imaging data collection and analysis, and offer new directions for future research. Copyright © 2018 Elsevier Ltd. All rights reserved.

Abnormal brain functional connectivity leads to impaired mood and cognition in hyperthyroidism: a resting-state functional MRI study.

PubMed

Li, Ling; Zhi, Mengmeng; Hou, Zhenghua; Zhang, Yuqun; Yue, Yingying; Yuan, Yonggui

2017-01-24

Patients with hyperthyroidism frequently have neuropsychiatric complaints such as lack of concentration, poor memory, depression, anxiety, nervousness, and irritability, suggesting brain dysfunction. However, the underlying process of these symptoms remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI), we depicted the altered graph theoretical metric degree centrality (DC) and seed-based resting-state functional connectivity (FC) in 33 hyperthyroid patients relative to 33 healthy controls. The peak points of significantly altered DC between the two groups were defined as the seed regions to calculate FC to the whole brain. Then, partial correlation analyses were performed between abnormal DC, FC and neuropsychological performances, as well as some clinical indexes. The decreased intrinsic functional connectivity in the posterior lobe of cerebellum (PLC) and medial frontal gyrus (MeFG), as well as the abnormal seed-based FC anchored in default mode network (DMN), attention network, visual network and cognitive network in this study, possibly constitutes the latent mechanism for emotional and cognitive changes in hyperthyroidism, including anxiety and impaired processing speed.

The resonant system: Linking brain-body-environment in sport performance☆.

PubMed

Teques, Pedro; Araújo, Duarte; Seifert, Ludovic; Del Campo, Vicente L; Davids, Keith

2017-01-01

The ecological dynamics approach offers new insights to understand how athlete nervous systems are embedded within the body-environment system in sport. Cognitive neuroscience focuses on the neural bases of athlete behaviors in terms of perceptual, cognitive, and motor functions defined within specific brain structures. Here, we discuss some limitations of this traditional perspective, addressing how athletes functionally adapt perception and action to the dynamics of complex performance environments by continuously perceiving information to regulate goal-directed actions. We examine how recent neurophysiological evidence of functioning in diverse cortical and subcortical regions appears more compatible with an ecological dynamics perspective, than traditional views in cognitive neuroscience. We propose how athlete behaviors in sports may be related to the tuning of resonant mechanisms indicating that perception is a dynamic process involving the whole body of the athlete. We emphasize the important role of metastable dynamics in the brain-body-environment system facilitating continuous interactions with a landscape of affordances (opportunities for action) in a performance environment. We discuss implications of these ideas for performance preparation and practice design in sport. © 2017 Elsevier B.V. All rights reserved.

Expression of Tau Pathology-Related Proteins in Different Brain Regions: A Molecular Basis of Tau Pathogenesis.

PubMed

Hu, Wen; Wu, Feng; Zhang, Yanchong; Gong, Cheng-Xin; Iqbal, Khalid; Liu, Fei

2017-01-01

Microtubule-associated protein tau is hyperphosphorylated and aggregated in affected neurons in Alzheimer disease (AD) brains. The tau pathology starts from the entorhinal cortex (EC), spreads to the hippocampus and frontal and temporal cortices, and finally to all isocortex areas, but the cerebellum is spared from tau lesions. The molecular basis of differential vulnerability of different brain regions to tau pathology is not understood. In the present study, we analyzed brain regional expressions of tau and tau pathology-related proteins. We found that tau was hyperphosphorylated at multiple sites in the frontal cortex (FC), but not in the cerebellum, from AD brain. The level of tau expression in the cerebellum was about 1/4 of that seen in the frontal and temporal cortices in human brain. In the rat brain, the expression level of tau with three microtubule-binding repeats (3R-tau) was comparable in the hippocampus, EC, FC, parietal-temporal cortex (PTC), occipital-temporal cortex (OTC), striatum, thalamus, olfactory bulb (OB) and cerebellum. However, the expression level of 4R-tau was the highest in the EC and the lowest in the cerebellum. Tau phosphatases, kinases, microtubule-related proteins and other tau pathology-related proteins were also expressed in a region-specific manner in the rat brain. These results suggest that higher levels of tau and tau kinases in the EC and low levels of these proteins in the cerebellum may accounts for the vulnerability and resistance of these representative brain regions to the development of tau pathology, respectively. The present study provides the regional expression profiles of tau and tau pathology-related proteins in the brain, which may help understand the brain regional vulnerability to tau pathology in neurodegenerative tauopathies.

Dietary protein restriction causes modification in aluminum-induced alteration in glutamate and GABA system of rat brain

PubMed Central

Nayak, Prasunpriya; Chatterjee, Ajay K

2003-01-01

Background Alteration of glutamate and γ-aminobutyrate system have been reported to be associated with neurodegenerative disorders and have been postulated to be involved in aluminum-induced neurotoxicity as well. Aluminum, an well known and commonly exposed neurotoxin, was found to alter glutamate and γ-aminobutyrate levels as well as activities of associated enzymes with regional specificity. Protein malnutrition also reported to alter glutamate level and some of its metabolic enzymes. Thus the region-wise study of levels of brain glutamate and γ-aminobutyrate system in protein adequacy and inadequacy may be worthwhile to understand the mechanism of aluminum-induced neurotoxicity. Results Protein restriction does not have any significant impact on regional aluminum and γ-aminobutyrate contents of rat brain. Significant interaction of dietary protein restriction and aluminum intoxication to alter regional brain glutamate level was observed in the tested brain regions except cerebellum. Alteration in glutamate α-decarboxylase and γ-aminobutyrate transaminase activities were found to be significantly influenced by interaction of aluminum intoxication and dietary protein restriction in all the tested brain regions. In case of regional brain succinic semialdehyde content, this interaction was significant only in cerebrum and thalamic area. Conclusion The alterations of regional brain glutamate and γ-aminobutyrate levels by aluminum are region specific as well as dependent on dietary protein intake. The impact of aluminum exposure on the metabolism of these amino acid neurotransmitters are also influenced by dietary protein level. Thus, modification of dietary protein level or manipulation of the brain amino acid homeostasis by any other means may be an useful tool to find out a path to restrict amino acid neurotransmitter alterations in aluminum-associated neurodisorders. PMID:12657166

Medication Overuse Headache: Pathophysiological Insights from Structural and Functional Brain MRI Research.

PubMed

Schwedt, Todd J; Chong, Catherine D

2017-07-01

Research imaging of brain structure and function has helped to elucidate the pathophysiology of medication overuse headache (MOH). This is a narrative review of imaging research studies that have investigated brain structural and functional alterations associated with MOH. Studies included in this review have investigated abnormal structure and function of pain processing regions in people with MOH, functional patterns that might predispose individuals to development of MOH, similarity of brain functional patterns in patients with MOH to those found in people with addiction, brain structure that could predict headache improvement following discontinuation of the overused medication, and changes in brain structure and function after discontinuation of medication overuse. MOH is associated with atypical structure and function of brain regions responsible for pain processing as well as brain regions that are commonly implicated in addiction. Several studies have shown "normalization" of structure and function in pain processing regions following discontinuation of the overused medication and resolution of MOH. However, some of the abnormalities in regions also implicated in addiction tend to persist following discontinuation of the overused medication, suggesting that they are a brain trait that predisposes certain individuals to medication overuse and MOH. © 2017 American Headache Society.

Postnatal brain development of the pulse type, weakly electric gymnotid fish Gymnotus omarorum.

PubMed

Iribarne, Leticia; Castelló, María E

2014-01-01

Teleosts are a numerous and diverse group of fish showing great variation in body shape, ecological niches and behaviors, and a correspondent diversity in brain morphology, usually associated with their functional specialization. Weakly electric fish are a paradigmatic example of functional specialization, as these teleosts use self-generated electric fields to sense the nearby environment and communicate with conspecifics, enabling fish to better exploit particular ecological niches. We analyzed the development of the brain of the pulse type gymnotid Gymnotus omarorum, focusing on the brain regions involved directly or indirectly in electrosensory information processing. A morphometric analysis has been made of the whole brain and of brain regions of interest, based on volumetric data obtained from 3-D reconstructions to study the growth of the whole brain and the relative growth of brain regions, from late larvae to adulthood. In the smallest studied larvae some components of the electrosensory pathway appeared to be already organized and functional, as evidenced by tract-tracing and in vivo field potential recordings of electrosensory-evoked activity. From late larval to adult stages, rombencephalic brain regions (cerebellum and electrosensory lateral line lobe) showed a positive allometric growth, mesencephalic brain regions showed a negative allometric growth, and the telencephalon showed an isometric growth. In a first step towards elucidating the role of cell proliferation in the relative growth of the analyzed brain regions, we also studied the spatial distribution of proliferation zones by means of pulse type BrdU labeling revealed by immunohistochemistry. The brain of G. omarorum late larvae showed a widespread distribution of proliferating zones, most of which were located at the ventricular-cisternal lining. Interestingly, we also found extra ventricular-cisternal proliferation zones at in the rombencephalic cerebellum and electrosensory lateral line lobe. We discuss the role of extraventricular-cisternal proliferation in the relative growth of the latter brain regions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Regional gray matter volume is associated with trait modesty: Evidence from voxel-based morphometry.

PubMed

Zheng, Chuhua; Wu, Qiong; Jin, Yan; Wu, Yanhong

2017-11-02

Modesty when defined as a personality trait, is highly beneficial to interpersonal relationship, group performance, and mental health. However, the potential neural underpinnings of trait modesty remain poorly understood. In the current study, we used voxel-based morphometry (VBM) to investigate the structural neural basis of trait modesty in Chinese college students. VBM results showed that higher trait modesty score was associated with lager regional gray matter volume in the dorsomedial prefrontal cortex, right dorsolateral prefrontal cortex, left superior temporal gyrus/left temporal pole, and right posterior insular cortex. These results suggest that individual differences in trait modesty are linked to brain regions associated with self-evaluation, self-regulation, and social cognition. The results remained robust after controlling the confounding factor of global self-esteem, suggesting unique structural correlates of trait modesty. These findings provide evidence for the structural neural basis of individual differences in trait modesty.

Nicotine and the adolescent brain.

PubMed

Yuan, Menglu; Cross, Sarah J; Loughlin, Sandra E; Leslie, Frances M

2015-08-15

Adolescence encompasses a sensitive developmental period of enhanced clinical vulnerability to nicotine, tobacco, and e-cigarettes. While there are sociocultural influences, data at preclinical and clinical levels indicate that this adolescent sensitivity has strong neurobiological underpinnings. Although definitions of adolescence vary, the hallmark of this period is a profound reorganization of brain regions necessary for mature cognitive and executive function, working memory, reward processing, emotional regulation, and motivated behavior. Regulating critical facets of brain maturation are nicotinic acetylcholine receptors (nAChRs). However, perturbations of cholinergic systems during this time with nicotine, via tobacco or e-cigarettes, have unique consequences on adolescent development. In this review, we highlight recent clinical and preclinical data examining the adolescent brain's distinct neurobiology and unique sensitivity to nicotine. First, we discuss what defines adolescence before reviewing normative structural and neurochemical alterations that persist until early adulthood, with an emphasis on dopaminergic systems. We review how acute exposure to nicotine impacts brain development and how drug responses differ from those seen in adults. Finally, we discuss the persistent alterations in neuronal signaling and cognitive function that result from chronic nicotine exposure, while highlighting a low dose, semi-chronic exposure paradigm that may better model adolescent tobacco use. We argue that nicotine exposure, increasingly occurring as a result of e-cigarette use, may induce epigenetic changes that sensitize the brain to other drugs and prime it for future substance abuse. © 2015 The Authors. The Journal of Physiology © 2015 The Physiological Society.

Frontotemporal brain sagging syndrome

PubMed Central

Wicklund, M.R.; Mokri, B.; Drubach, D.A.; Boeve, B.F.; Parisi, J.E.

2011-01-01

Background: Behavioral variant frontotemporal dementia (bvFTD) is a relatively well-defined clinical syndrome. It is associated with frontal and temporal lobe structural/metabolic changes and pathologic findings of a neurodegenerative disease. We have been evaluating patients with clinical and imaging features partially consistent with bvFTD but with evidence also suggestive of brain sagging, which we refer to as frontotemporal brain sagging syndrome (FBSS). Methods: Retrospective medical chart review to identify all patients seen at our institution between 1996 and 2010, who had a clinical diagnosis of FTD and imaging evidence of brain sag. Results: Eight patients, 7 male and 1 female, were diagnosed with FBSS. The median age at symptom onset was 53 years. All patients had insidious onset and slow progression of behavioral and cognitive dysfunction accompanied by daytime somnolence and headache. Of the 5 patients with functional imaging, all showed evidence of hypometabolism of the frontotemporal regions. On brain MRI, all patients had evidence of brain sagging with distortion of the brainstem; 3 patients had diffuse pachymeningeal enhancement. CSF opening pressure was varied and CSF protein was mildly elevated. A definite site of CSF leak was not identified by myelogram or cisternography, except in one patient with a site highly suggestive of leak who subsequently underwent surgery confirming a CSF leak. In 2 patients with a neuropathologic examination, there was no evidence of a neurodegenerative disease. Conclusions: This case series demonstrates that FBSS may mimic typical bvFTD but should be recognized as an unusual presentation that is potentially treatable. PMID:21502595

Brain response to images of food varying in energy density is associated with body composition in 7- to 10-year-old children: Results of an exploratory study.

PubMed

Fearnbach, S Nicole; English, Laural K; Lasschuijt, Marlou; Wilson, Stephen J; Savage, Jennifer S; Fisher, Jennifer O; Rolls, Barbara J; Keller, Kathleen L

2016-08-01

Energy balance is regulated by a multifaceted system of physiological signals that influence energy intake and expenditure. Therefore, variability in the brain's response to food may be partially explained by differences in levels of metabolically active tissues throughout the body, including fat-free mass (FFM) and fat mass (FM). The purpose of this study was to test the hypothesis that children's body composition would be related to their brain response to food images varying in energy density (ED), a measure of energy content per weight of food. Functional magnetic resonance imaging (fMRI) was used to measure brain response to High (>1.5kcal/g) and Low (<1.5kcal/g) ED food images, and Control images, in 36 children ages 7-10years. Body composition was measured using bioelectrical impedance analysis. Multi-subject random effects general linear model (GLM) and two-factor repeated measures analysis of variance (ANOVA) were used to test for main effects of ED (High ED vs. Low ED) in a priori defined brain regions of interest previously implicated in energy homeostasis and reward processing. Pearson's correlations were then calculated between activation in these regions for various contrasts (High ED-Low ED, High ED-Control, Low ED-Control) and child body composition (FFM index, FM index, % body fat). Relative to Low ED foods, High ED foods elicited greater BOLD activation in the left thalamus. In the right substantia nigra, BOLD activation for the contrast of High ED-Low ED foods was positively associated with child FFM. There were no significant results for the High ED-Control or Low ED-Control contrasts. Our findings support literature on FFM as an appetitive driver, such that greater amounts of lean mass were associated with greater activation for High ED foods in an area of the brain associated with dopamine signaling and reward (substantia nigra). These results confirm our hypothesis that brain response to foods varying in energy content is related to measures of child body composition. Copyright © 2016 Elsevier Inc. All rights reserved.

Brain maps 4.0—Structure of the rat brain: An open access atlas with global nervous system nomenclature ontology and flatmaps

PubMed Central

2018-01-01

Abstract The fourth edition (following editions in 1992, 1998, 2004) of Brain maps: structure of the rat brain is presented here as an open access internet resource for the neuroscience community. One new feature is a set of 10 hierarchical nomenclature tables that define and describe all parts of the rat nervous system within the framework of a strictly topographic system devised previously for the human nervous system. These tables constitute a global ontology for knowledge management systems dealing with neural circuitry. A second new feature is an aligned atlas of bilateral flatmaps illustrating rat nervous system development from the neural plate stage to the adult stage, where most gray matter regions, white matter tracts, ganglia, and nerves listed in the nomenclature tables are illustrated schematically. These flatmaps are convenient for future development of online applications analogous to “Google Maps” for systems neuroscience. The third new feature is a completely revised Atlas of the rat brain in spatially aligned transverse sections that can serve as a framework for 3‐D modeling. Atlas parcellation is little changed from the preceding edition, but the nomenclature for rat is now aligned with an emerging panmammalian neuroanatomical nomenclature. All figures are presented in Adobe Illustrator vector graphics format that can be manipulated, modified, and resized as desired, and freely used with a Creative Commons license. PMID:29277900

When Neuroscience 'Touches' Architecture: From Hapticity to a Supramodal Functioning of the Human Brain.

PubMed

Papale, Paolo; Chiesi, Leonardo; Rampinini, Alessandra C; Pietrini, Pietro; Ricciardi, Emiliano

2016-01-01

In the last decades, the rapid growth of functional brain imaging methodologies allowed cognitive neuroscience to address open questions in philosophy and social sciences. At the same time, novel insights from cognitive neuroscience research have begun to influence various disciplines, leading to a turn to cognition and emotion in the fields of planning and architectural design. Since 2003, the Academy of Neuroscience for Architecture has been supporting 'neuro-architecture' as a way to connect neuroscience and the study of behavioral responses to the built environment. Among the many topics related to multisensory perceptual integration and embodiment, the concept of hapticity was recently introduced, suggesting a pivotal role of tactile perception and haptic imagery in architectural appraisal. Arguments have thus risen in favor of the existence of shared cognitive foundations between hapticity and the supramodal functional architecture of the human brain. Precisely, supramodality refers to the functional feature of defined brain regions to process and represent specific information content in a more abstract way, independently of the sensory modality conveying such information to the brain. Here, we highlight some commonalities and differences between the concepts of hapticity and supramodality according to the distinctive perspectives of architecture and cognitive neuroscience. This comparison and connection between these two different approaches may lead to novel observations in regard to people-environment relationships, and even provide empirical foundations for a renewed evidence-based design theory.

[Transsexualism: a Brain Disorder that Begins to Known].

PubMed

López Moratalla, Natalia; Calleja Canela, Amparo

2016-01-01

Transsexualism describes the condition when a person's psychological gender differs from his or her biological sex. People with gender identity disorder suffer persistently from this incongruence and they search hormonal and surgical sex reassignment to the desired anatomical sex. This review, from an ethical perspective, intends to give an overview of structural and functional neurobiological correlations of transsexualism and their course under cross-sex hormonal administration. Several studies demonstrate an increased functional connectivity between cortex regions reaffirming psychosocial distress of psychologicalbiological sex incongruity. Such distress can be ascribed to a disharmonic body image due to changes in the functional connectivity of the key components of body representation network. These brain alterations seem to imply a strategic mechanism dissociating bodily emotions from bodily images. For a number of sexually dimorphic brain structures or processes, signs of feminization or masculinization are observable in transsexual individuals, who during hormonal administration seem to partly further adjust to characteristics of the desired sex. These changes allow a reduction of psychosocial distress. However, a model leading to a ″gender affirmation″ does not solve the problem, since brain disorders causing it are not corrected. This is a serious medical ethics issue. Prejudices should be left aside. To know what happens in the brain of transsexuals is a medical need, both to define what is and what is not, and so to choose an adequate treatment, and to decide and guide legal actions.

Progenitor cell dynamics in the Newt Telencephalon during homeostasis and neuronal regeneration.

PubMed

Kirkham, Matthew; Hameed, L Shahul; Berg, Daniel A; Wang, Heng; Simon, András

2014-04-08

The adult newt brain has a marked neurogenic potential and is highly regenerative. Ventricular, radial glia-like ependymoglia cells give rise to neurons both during normal homeostasis and after injury, but subpopulations among ependymoglia cells have not been defined. We show here that a substantial portion of GFAP(+) ependymoglia cells in the proliferative hot spots of the telencephalon has transit-amplifying characteristics. In contrast, proliferating ependymoglia cells, which are scattered along the ventricular wall, have stem cell features in terms of label retention and insensitivity to AraC treatment. Ablation of neurons remodels the proliferation dynamics and leads to de novo formation of regions displaying features of neurogenic niches, such as the appearance of cells with transit-amplifying features and proliferating neuroblasts. The results have implication both for our understanding of the evolutionary diversification of radial glia cells as well as the processes regulating neurogenesis and regeneration in the adult vertebrate brain.

Exploring difference and overlap between schizophrenia, schizoaffective and bipolar disorders using resting-state brain functional networks.

PubMed

Du, Yuhui; Liu, Jingyu; Sui, Jing; He, Hao; Pearlson, Godfrey D; Calhoun, Vince D

2014-01-01

Schizophrenia, schizoaffective and bipolar disorders share some common symptoms. However, the biomarkers underlying those disorders remain unclear. In fact, there is still controversy about the schizoaffective disorder with respect to its validity of independent category and its relationship with schizophrenia and bipolar disorders. In this paper, based on brain functional networks extracted from resting-state fMRI using a recently proposed group information guided ICA (GIG-ICA) method, we explore the biomarkers for discriminating healthy controls, schizophrenia patients, bipolar patients, and patients with two symptom defined subsets of schizoaffective disorder, and then investigate the relationship between different groups. The results demonstrate that the discriminating regions mainly including frontal, parietal, precuneus, cingulate, supplementary motor, cerebellar, insular and supramarginal cortices perform well in distinguishing the different diagnostic groups. The results also suggest that schizoaffective disorder may be an independent disorder, although its subtype characterized by depressive episodes shares more similarity with schizophrenia.

Dynamic functional connectivity using state-based dynamic community structure: method and application to opioid analgesia.

PubMed

Robinson, Lucy F; Atlas, Lauren Y; Wager, Tor D

2015-03-01

We present a new method, State-based Dynamic Community Structure, that detects time-dependent community structure in networks of brain regions. Most analyses of functional connectivity assume that network behavior is static in time, or differs between task conditions with known timing. Our goal is to determine whether brain network topology remains stationary over time, or if changes in network organization occur at unknown time points. Changes in network organization may be related to shifts in neurological state, such as those associated with learning, drug uptake or experimental conditions. Using a hidden Markov stochastic blockmodel, we define a time-dependent community structure. We apply this approach to data from a functional magnetic resonance imaging experiment examining how contextual factors influence drug-induced analgesia. Results reveal that networks involved in pain, working memory, and emotion show distinct profiles of time-varying connectivity. Copyright © 2014 Elsevier Inc. All rights reserved.

Case-control study on the use of cellular and cordless phones and the risk for malignant brain tumours.

PubMed

Hardell, L; Mild, K H; Carlberg, M

2002-10-01

To investigate the use of cellular and cordless phones and the risk for malignant brain tumours. A case-control study was performed on 649 patients aged 20-80 years of both sexes with malignant brain tumour diagnosed from 1 January 1997 to 30 June 2000. All patients were alive during the time of the study and had histopathology verified brain tumours. One matched control to each case was selected from the Swedish Population Register. The study area was the Uppsala-Orebro, Stockholm, Linköping and Göteborg medical regions of Sweden. Exposure was assessed by a questionnaire answered by 588 (91%) cases and 581 (90%) controls. Phone usage was defined as 'ever use' and usage starting within 1 year before diagnosis was disregarded. Overall, no significantly increased risks were found: analogue cellular phones yielded an odds ratio (OR)=1.13, 95% confidence interval (CI)=0.82-1.57, digital cellular phones OR=1.13, CI=0.86-1.48, and cordless phones OR=1.13, CI=0.85-1.50. For ipsilateral (same side) radiofrequency exposure, analogue mobile phones gave OR=1.85, CI=1.16-2.96, for all malignant brain tumours. For astrocytoma, this risk was OR=1.95, CI=1.12-3.39. For all malignant brain tumours, digital mobile phones yielded OR=1.59, CI=1.05-2.41, and cordless phones yielded OR=1.46, CI=0.96-2.23, in the analysis of ipsilateral exposure. The ipsilateral use of an analogue cellular phone yielded a significantly increased risk for malignant brain tumours.

A Unified Estimation Framework for State-Related Changes in Effective Brain Connectivity.

PubMed

Samdin, S Balqis; Ting, Chee-Ming; Ombao, Hernando; Salleh, Sh-Hussain

2017-04-01

This paper addresses the critical problem of estimating time-evolving effective brain connectivity. Current approaches based on sliding window analysis or time-varying coefficient models do not simultaneously capture both slow and abrupt changes in causal interactions between different brain regions. To overcome these limitations, we develop a unified framework based on a switching vector autoregressive (SVAR) model. Here, the dynamic connectivity regimes are uniquely characterized by distinct vector autoregressive (VAR) processes and allowed to switch between quasi-stationary brain states. The state evolution and the associated directed dependencies are defined by a Markov process and the SVAR parameters. We develop a three-stage estimation algorithm for the SVAR model: 1) feature extraction using time-varying VAR (TV-VAR) coefficients, 2) preliminary regime identification via clustering of the TV-VAR coefficients, 3) refined regime segmentation by Kalman smoothing and parameter estimation via expectation-maximization algorithm under a state-space formulation, using initial estimates from the previous two stages. The proposed framework is adaptive to state-related changes and gives reliable estimates of effective connectivity. Simulation results show that our method provides accurate regime change-point detection and connectivity estimates. In real applications to brain signals, the approach was able to capture directed connectivity state changes in functional magnetic resonance imaging data linked with changes in stimulus conditions, and in epileptic electroencephalograms, differentiating ictal from nonictal periods. The proposed framework accurately identifies state-dependent changes in brain network and provides estimates of connectivity strength and directionality. The proposed approach is useful in neuroscience studies that investigate the dynamics of underlying brain states.

A comparative study of brain perfusion single-photon emission computed tomography and magnetic resonance imaging in patients with post-traumatic anosmia.

PubMed

Atighechi, Saeid; Salari, Hadi; Baradarantar, Mohammad Hossein; Jafari, Rozita; Karimi, Ghasem; Mirjali, Mehdi

2009-01-01

Loss of smell is a problem that can occur in up to 30% of patients with head trauma. The olfactory function investigation methods so far in use have mostly relied on subjective responses given by patients. Recently, some studies have used magnetic resonance imaging (MRI) and single-photon emission computed tomography (SPECT) to evaluate patients with post-traumatic anosmia. The present study seeks to detect post-traumatic anosmia and the areas in the brain that are related to olfactory impairment by using SPECT and MRI as imaging techniques. The study was conducted on 21 patients suffering from head injury and consequently anosmia as defined by an olfactory identification test. Two control groups (traumatic normosmic and nontraumatic healthy individuals) were selected. Brain MRI, qualitative and semiquantitative SPECT with 99mtc-ethyl-cysteinate-dimer were taken from all the patients. Then the brain SPECT and MRI were compared with each other. Semi-quantitative assessment of the brain perfusion SPECT revealed frontal, left parietal, and left temporal hypoperfusion as compared with the two control groups. Eighty-five percent of the anosmic patients had abnormal brain MRI. Regarding the MRI, the main abnormality proved to be in the anterior inferior region of the frontal lobes and olfactory bulbs. The findings of this study suggest that damage to the frontal lobes and olfactory bulbs as shown in the brain MRI and hypoperfusion in the frontal, left parietal, and left temporal lobes in the semiquantitative SPECT corresponds to post-traumatic anosmia. Further neurophysiological and imaging studies are definitely needed to set the idea completely.

Automatic detection of the hippocampal region associated with Alzheimer's disease from microscopic images of mice brain

NASA Astrophysics Data System (ADS)

Albaidhani, Tahseen; Hawkes, Cheryl; Jassim, Sabah; Al-Assam, Hisham

2016-05-01

The hippocampus is the region of the brain that is primarily associated with memory and spatial navigation. It is one of the first brain regions to be damaged when a person suffers from Alzheimer's disease. Recent research in this field has focussed on the assessment of damage to different blood vessels within the hippocampal region from a high throughput brain microscopic images. The ultimate aim of our research is the creation of an automatic system to count and classify different blood vessels such as capillaries, veins, and arteries in the hippocampus region. This work should provide biologists with efficient and accurate tools in their investigation of the causes of Alzheimer's disease. Locating the boundary of the Region of Interest in the hippocampus from microscopic images of mice brain is the first essential stage towards developing such a system. This task benefits from the variation in colour channels and texture between the two sides of the hippocampus and the boundary region. Accordingly, the developed initial step of our research to locating the hippocampus edge uses a colour-based segmentation of the brain image followed by Hough transforms on the colour channel that isolate the hippocampus region. The output is then used to split the brain image into two sides of the detected section of the boundary: the inside region and the outside region. Experimental results on a sufficiently number of microscopic images demonstrate the effectiveness of the developed solution.

Thermodynamic laws apply to brain function.

PubMed

Salerian, Alen J

2010-02-01

Thermodynamic laws and complex system dynamics govern brain function. Thus, any change in brain homeostasis by an alteration in brain temperature, neurotransmission or content may cause region-specific brain dysfunction. This is the premise for the Salerian Theory of Brain built upon a new paradigm for neuropsychiatric disorders: the governing influence of neuroanatomy, neurophysiology, thermodynamic laws. The principles of region-specific brain function thermodynamics are reviewed. The clinical and supporting evidence including the paradoxical effects of various agents that alter brain homeostasis is demonstrated.

Age related rise in lactate and its correlation with lactate dehydrogenase (LDH) status in post-mitochondrial fractions isolated from different regions of brain in mice.

PubMed

Datta, Siddhartha; Chakrabarti, Nilkanta

2018-04-18

Rise in brain lactate is the hallmark of ageing. Separate studies report that ageing is associated with elevation of lactate level and alterations of lactate dehydrogenase (LDH)-A/B mRNA-expression-ratio in cerebral cortex and hippocampus. However, age related lactate rise in brain and its association with LDH status and their brain regional variations are still elusive. In the present study, level of lactate, LDH (A and B) activity and LDH-A expression were evaluated in post-mitochondrial fraction of tissues isolated from four different brain regions (cerebral cortex, hippocampus, substantia nigra and cerebellum) of young and aged mice. Lactate levels elevated in four brain regions with maximum rise in substantia nigra of aged mice. LDH-A protein expression and its activity decreased in cerebral cortex, hippocampus and substantia nigra without any changes of these parameters in cerebellum of aged mice. LDH-B activity decreased in hippocampus, substantia nigra and cerebellum whereas its activity remains unaltered in cerebral cortex of aged mice. Accordingly, the ratio of LDH-A/LDH-B-activity remains unaltered in hippocampus and substantia nigra, decreased in cerebral cortex and increased in cerebellum. Therefore, rise of lactate in three brain regions (cerebral cortex, hippocampus, substantia nigra) appeared to be not correlated with the alterations of its regulatory enzymes activities in these three brain regions, rather it supports the fact of involvement of other mechanisms, like lactate transport and/or aerobic/anaerobic metabolism as the possible cause(s) of lactate rise in these three brain regions. The increase in LDH-A/LDH-B-activity-ratio appeared to be positively correlated with elevated lactate level in cerebellum of aged mice. Overall, the present study indicates that the mechanism of rise in lactate in brain varies with brain regions where LDH status plays an important role during ageing. Copyright © 2018 Elsevier Ltd. All rights reserved.

Region-Specific Protein Abundance Changes in the Brain of MPTP-induced Parkinson’s Disease Mouse Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Xu; Zhou, Jianying; Chin, Mark H

2010-02-15

Parkinson’s disease (PD) is characterized by dopaminergic neurodegeneration in the nigrostriatal region of the brain; however, the neurodegeneration extends well beyond dopaminergic neurons. To gain a better understanding of the molecular changes relevant to PD, we applied two-dimensional LC-MS/MS to comparatively analyze the proteome changes in four brain regions (striatum, cerebellum, cortex, and the rest of brain) using a MPTP-induced PD mouse model with the objective to identify nigrostriatal-specific and other region-specific protein abundance changes. The combined analyses resulted in the identification of 4,895 non-redundant proteins with at least two unique peptides per protein. The relative abundance changes in eachmore » analyzed brain region were estimated based on the spectral count information. A total of 518 proteins were observed with significant MPTP-induced changes across different brain regions. 270 of these proteins were observed with specific changes occurring either only in the striatum and/or in the rest of the brain region that contains substantia nigra, suggesting that these proteins are associated with the underlying nigrostriatal pathways. Many of the proteins that exhibit significant abundance changes were associated with dopamine signaling, mitochondrial dysfunction, the ubiquitin system, calcium signaling, the oxidative stress response, and apoptosis. A set of proteins with either consistent change across all brain regions or with changes specific to the cortex and cerebellum regions were also detected. One of the interesting proteins is ubiquitin specific protease (USP9X), a deubiquination enzyme involved in the protection of proteins from degradation and promotion of the TGF-β pathway, which exhibited altered abundances in all brain regions. Western blot validation showed similar spatial changes, suggesting that USP9X is potentially associated with neurodegeneration. Together, this study for the first time presents an overall picture of proteome changes underlying both nigrostriatal pathways and other brain regions potentially involved in MPTP-induced neurodegeneration. The observed molecular changes provide a valuable reference resource for future hypothesis-driven functional studies of PD.« less

Brain Dominance & Self-Actualization.

ERIC Educational Resources Information Center

Bernhoft, Franklin O.

Numerous areas associated with brain dominance have been researched since Bogen and Sperry's work with split-brain patients in the 1960s, but only slight attention has been given to the connection between brain dominance and personality. No study appears in the literature seeking to understand optimal mental health as defined by Maslow's…

Primary brain tumors, neural stem cell, and brain tumor cancer cells: where is the link?

PubMed Central

Germano, Isabelle; Swiss, Victoria; Casaccia, Patrizia

2010-01-01

The discovery of brain tumor-derived cells (BTSC) with the properties of stem cells has led to the formulation of the hypothesis that neural stem cells could be the cell of origin of primary brain tumors (PBT). In this review we present the most common molecular changes in PBT, define the criteria of identification of BTSC and discuss the similarities between the characteristics of these cells and those of the endogenous population of neural stem cells (NPCs) residing in germinal areas of the adult brain. Finally, we propose possible mechanisms of cancer initiation and progression and suggest a model of tumor initiation that includes intrinsic changes of resident NSC and potential changes in the microenvironment defining the niche where the NSC reside. PMID:20045420

Regional brain injury on conventional and diffusion weighted MRI is associated with outcome after pediatric cardiac arrest.

PubMed

Fink, Ericka L; Panigrahy, A; Clark, R S B; Fitz, C R; Landsittel, D; Kochanek, P M; Zuccoli, G

2013-08-01

To assess regional brain injury on magnetic resonance imaging (MRI) after pediatric cardiac arrest (CA) and to associate regional injury with patient outcome and effects of hypothermia therapy for neuroprotection. We performed a retrospective chart review with prospective imaging analysis. Children between 1 week and 17 years of age who had a brain MRI in the first 2 weeks after CA without other acute brain injury between 2002 and 2008 were included. Brain MRI (1.5 T General Electric, Milwaukee, WI, USA) images were analyzed by 2 blinded neuroradiologists with adjudication; images were visually graded. Brain lobes, basal ganglia, thalamus, brain stem, and cerebellum were analyzed using T1, T2, and diffusion-weighted images (DWI). We examined 28 subjects with median age 1.9 years (IQR 0.4-13.0) and 19 (68 %) males. Increased intensity on T2 in the basal ganglia and restricted diffusion in the brain lobes were associated with unfavorable outcome (all P < 0.05). Therapeutic hypothermia had no effect on regional brain injury. Repeat brain MRI was infrequently performed but demonstrated evolution of lesions. Children with lesions in the basal ganglia on conventional MRI and brain lobes on DWI within the first 2 weeks after CA represent a group with increased risk of poor outcome. These findings may be important for developing neuroprotective strategies based on regional brain injury and for evaluating response to therapy in interventional clinical trials.

Regional deposition of nasal sprays in adults: A wide ranging computational study.

PubMed

Kiaee, Milad; Wachtel, Herbert; Noga, Michelle L; Martin, Andrew R; Finlay, Warren H

2018-05-01

The present work examines regional deposition within the nose for nasal sprays over a large and wide ranging parameter space by using numerical simulation. A set of 7 realistic adult nasal airway geometries was defined based on computed tomography images. Deposition in 6 regions of each nasal airway geometry (the vestibule, valve, anterior turbinate, posterior turbinate, olfactory, and nasopharynx) was determined for varying particle diameter, spray cone angle, spray release direction, particle injection speed, and particle injection location. Penetration of nasal spray particles through the airway geometries represented unintended lung exposure. Penetration was found to be relatively insensitive to injection velocity, but highly sensitive to particle size. Penetration remained at or above 30% for particles exceeding 10 μm in diameter for several airway geometries studied. Deposition in the turbinates, viewed as desirable for both local and systemic nasal drug delivery, was on average maximized for particles ranging from ~20 to 30 μm in diameter, and for low to zero injection velocity. Similar values of particle diameter and injection velocity were found to maximize deposition in the olfactory region, a potential target for nose-to-brain drug delivery. However, olfactory deposition was highly variable between airway geometries, with maximum olfactory deposition ranging over 2 orders of magnitude between geometries. This variability is an obstacle to overcome if consistent dosing between subjects is to be achieved for nose-to-brain drug delivery. Copyright © 2018 John Wiley & Sons, Ltd.

Expanding the spectrum of neuronal pathology in multiple system atrophy.

PubMed

Cykowski, Matthew D; Coon, Elizabeth A; Powell, Suzanne Z; Jenkins, Sarah M; Benarroch, Eduardo E; Low, Phillip A; Schmeichel, Ann M; Parisi, Joseph E

2015-08-01

Multiple system atrophy is a sporadic alpha-synucleinopathy that typically affects patients in their sixth decade of life and beyond. The defining clinical features of the disease include progressive autonomic failure, parkinsonism, and cerebellar ataxia leading to significant disability. Pathologically, multiple system atrophy is characterized by glial cytoplasmic inclusions containing filamentous alpha-synuclein. Neuronal inclusions also have been reported but remain less well defined. This study aimed to further define the spectrum of neuronal pathology in 35 patients with multiple system atrophy (20 male, 15 female; mean age at death 64.7 years; median disease duration 6.5 years, range 2.2 to 15.6 years). The morphologic type, topography, and frequencies of neuronal inclusions, including globular cytoplasmic (Lewy body-like) neuronal inclusions, were determined across a wide spectrum of brain regions. A correlation matrix of pathologic severity also was calculated between distinct anatomic regions of involvement (striatum, substantia nigra, olivary and pontine nuclei, hippocampus, forebrain and thalamus, anterior cingulate and neocortex, and white matter of cerebrum, cerebellum, and corpus callosum). The major finding was the identification of widespread neuronal inclusions in the majority of patients, not only in typical disease-associated regions (striatum, substantia nigra), but also within anterior cingulate cortex, amygdala, entorhinal cortex, basal forebrain and hypothalamus. Neuronal inclusion pathology appeared to follow a hierarchy of region-specific susceptibility, independent of the clinical phenotype, and the severity of pathology was duration-dependent. Neuronal inclusions also were identified in regions not previously implicated in the disease, such as within cerebellar roof nuclei. Lewy body-like inclusions in multiple system atrophy followed the stepwise anatomic progression of Lewy body-spectrum disease inclusion pathology in 25.7% of patients with multiple system atrophy, including a patient with visual hallucinations. Further, the presence of Lewy body-like inclusions in neocortex, but not hippocampal alpha-synuclein pathology, was associated with cognitive impairment (P = 0.002). However, several cases had the presence of isolated Lewy body-like inclusions at atypical sites (e.g. thalamus, deep cerebellar nuclei) that are not typical for Lewy body-spectrum disease. Finally, interregional correlations (rho ≥ 0.6) in pathologic glial and neuronal lesion burden suggest shared mechanisms of disease progression between both discrete anatomic regions (e.g. basal forebrain and hippocampus) and cell types (neuronal and glial inclusions in frontal cortex and white matter, respectively). These findings suggest that in addition to glial inclusions, neuronal pathology plays an important role in the developmental and progression of multiple system atrophy. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Neonatal physiological correlates of near-term brain development on MRI and DTI in very-low-birth-weight preterm infants.

PubMed

Rose, Jessica; Vassar, Rachel; Cahill-Rowley, Katelyn; Stecher Guzman, Ximena; Hintz, Susan R; Stevenson, David K; Barnea-Goraly, Naama

2014-01-01

Structural brain abnormalities identified at near-term age have been recognized as potential predictors of neurodevelopment in children born preterm. The aim of this study was to examine the relationship between neonatal physiological risk factors and early brain structure in very-low-birth-weight (VLBW) preterm infants using structural MRI and diffusion tensor imaging (DTI) at near-term age. Structural brain MRI, diffusion-weighted scans, and neonatal physiological risk factors were analyzed in a cross-sectional sample of 102 VLBW preterm infants (BW ≤ 1500 g, gestational age (GA) ≤ 32 weeks), who were admitted to the Lucile Packard Children's Hospital, Stanford NICU and recruited to participate prior to routine near-term brain MRI conducted at 36.6 ± 1.8 weeks postmenstrual age (PMA) from 2010 to 2011; 66/102 also underwent a diffusion-weighted scan. Brain abnormalities were assessed qualitatively on structural MRI, and white matter (WM) microstructure was analyzed quantitatively on DTI in six subcortical regions defined by DiffeoMap neonatal brain atlas. Specific regions of interest included the genu and splenium of the corpus callosum, anterior and posterior limbs of the internal capsule, the thalamus, and the globus pallidus. Regional fractional anisotropy (FA) and mean diffusivity (MD) were calculated using DTI data and examined in relation to neonatal physiological risk factors including gestational age (GA), bronchopulmonary dysplasia (BPD), necrotizing enterocolitis (NEC), retinopathy of prematurity (ROP), and sepsis, as well as serum levels of C-reactive protein (CRP), glucose, albumin, and total bilirubin. Brain abnormalities were observed on structural MRI in 38/102 infants including 35% of females and 40% of males. Infants with brain abnormalities observed on MRI had higher incidence of BPD (42% vs. 25%) and sepsis (21% vs. 6%) and higher mean and peak serum CRP levels, respectively, (0.64 vs. 0.34 mg/dL, p = .008; 1.57 vs. 0.67 mg/dL, p= .006) compared to those without. The number of signal abnormalities observed on structural MRI correlated to mean and peak CRP (rho = .316, p = .002; rho = .318, p= .002). The number of signal abnormalities observed on MRI correlated with thalamus MD (left: r= .382, p= .002; right: r= .400, p= .001), controlling for PMA-at-scan. Thalamus WM microstructure demonstrated the strongest associations with neonatal risk factors. Higher thalamus MD on the left and right, respectively, was associated with lower GA (r = -.322, p = .009; r= -.381, p= .002), lower mean albumin (r = -.276, p= .029; r= -.385, p= .002), and lower mean bilirubin (r = -.293, p= .020; r= -.337 p= .007). Results suggest that at near-term age, thalamus WM microstructure may be particularly vulnerable to certain neonatal risk factors. Interactions between albumin, bilirubin, phototherapy, and brain development warrant further investigation. Identification of physiological risk factors associated with selective vulnerability of certain brain regions at near-term age may clarify the etiology of neurodevelopmental impairment and inform neuroprotective treatment for VLBW preterm infants.

Evidence for hubs in human functional brain networks

PubMed Central

Power, Jonathan D; Schlaggar, Bradley L; Lessov-Schlaggar, Christina N; Petersen, Steven E

2013-01-01

Summary Hubs integrate and distribute information in powerful ways due to the number and positioning of their contacts in a network. Several resting state functional connectivity MRI reports have implicated regions of the default mode system as brain hubs; we demonstrate that previous degree-based approaches to hub identification may have identified portions of large brain systems rather than critical nodes of brain networks. We utilize two methods to identify hub-like brain regions: 1) finding network nodes that participate in multiple sub-networks of the brain, and 2) finding spatial locations where several systems are represented within a small volume. These methods converge on a distributed set of regions that differ from previous reports on hubs. This work identifies regions that support multiple systems, leading to spatially constrained predictions about brain function that may be tested in terms of lesions, evoked responses, and dynamic patterns of activity. PMID:23972601

Long-term variability of importance of brain regions in evolving epileptic brain networks

NASA Astrophysics Data System (ADS)

Geier, Christian; Lehnertz, Klaus

2017-04-01

We investigate the temporal and spatial variability of the importance of brain regions in evolving epileptic brain networks. We construct these networks from multiday, multichannel electroencephalographic data recorded from 17 epilepsy patients and use centrality indices to assess the importance of brain regions. Time-resolved indications of highest importance fluctuate over time to a greater or lesser extent, however, with some periodic temporal structure that can mostly be attributed to phenomena unrelated to the disease. In contrast, relevant aspects of the epileptic process contribute only marginally. Indications of highest importance also exhibit pronounced alternations between various brain regions that are of relevance for studies aiming at an improved understanding of the epileptic process with graph-theoretical approaches. Nonetheless, these findings may guide new developments for individualized diagnosis, treatment, and control.

Source-based neurofeedback methods using EEG recordings: training altered brain activity in a functional brain source derived from blind source separation

PubMed Central

White, David J.; Congedo, Marco; Ciorciari, Joseph

2014-01-01

A developing literature explores the use of neurofeedback in the treatment of a range of clinical conditions, particularly ADHD and epilepsy, whilst neurofeedback also provides an experimental tool for studying the functional significance of endogenous brain activity. A critical component of any neurofeedback method is the underlying physiological signal which forms the basis for the feedback. While the past decade has seen the emergence of fMRI-based protocols training spatially confined BOLD activity, traditional neurofeedback has utilized a small number of electrode sites on the scalp. As scalp EEG at a given electrode site reflects a linear mixture of activity from multiple brain sources and artifacts, efforts to successfully acquire some level of control over the signal may be confounded by these extraneous sources. Further, in the event of successful training, these traditional neurofeedback methods are likely influencing multiple brain regions and processes. The present work describes the use of source-based signal processing methods in EEG neurofeedback. The feasibility and potential utility of such methods were explored in an experiment training increased theta oscillatory activity in a source derived from Blind Source Separation (BSS) of EEG data obtained during completion of a complex cognitive task (spatial navigation). Learned increases in theta activity were observed in two of the four participants to complete 20 sessions of neurofeedback targeting this individually defined functional brain source. Source-based EEG neurofeedback methods using BSS may offer important advantages over traditional neurofeedback, by targeting the desired physiological signal in a more functionally and spatially specific manner. Having provided preliminary evidence of the feasibility of these methods, future work may study a range of clinically and experimentally relevant brain processes where individual brain sources may be targeted by source-based EEG neurofeedback. PMID:25374520

Rapid induction of heme oxygenase 1 mRNA and protein by hyperthermia in rat brain: heme oxygenase 2 is not a heat shock protein.

PubMed Central

Ewing, J F; Maines, M D

1991-01-01

Catalytic activity of heme oxygenase (heme, hydrogen-donor:oxygen oxidoreductase, EC 1.14.99.3) isozymes, HO-1 and HO-2, permits production of physiologic isomers of bile pigments. In turn, bile pigments biliverdin and bilirubin are effective antioxidants in biological systems. In the rat brain we have identified only the HO-1 isozyme of heme oxygenase as a heat shock protein and defined hyperthermia as a stimulus that causes an increase in brain HO-1 protein. Exposure of male rats to 42 degrees C for 20 min caused a rapid and marked increase in brain 1.8-kilobase HO-1 mRNA. Specifically, a 33-fold increase in brain HO-1 mRNA was observed within 1 h and sustained for at least 6 h posttreatment. In contrast, the two HO-2 homologous transcripts (1.3 and 1.9 kilobases) did not respond to heat shock; neither the ratio nor the level of the two messages differed from that of the control when measured either at 1, 6, or 24 h after hyperthermia. The induction of a 1.8-kilobase HO-1 mRNA resulted in a pronounced increase in HO-1 protein 6 h after hyperthermia, as detected by both Western immunoblot and RIA. Immunocytochemistry of rat brain showed discrete localization of HO-1-like protein only in neurons of select brain regions. Six hours after heat shock, an intense increase in HO-1-like protein was observed in both Purkinje cells of the cerebellum and epithelial cells lining the cerebral aqueduct of the brain. We suggest that the increase in HO-1 protein, hence increased capacity to form bile pigments, represents a neuronal defense mechanism against heat shock stress. Images PMID:2052613

Cerebral Apolipoprotein-D Is Hypoglycosylated Compared to Peripheral Tissues and Is Variably Expressed in Mouse and Human Brain Regions.

PubMed

Li, Hongyun; Ruberu, Kalani; Karl, Tim; Garner, Brett

2016-01-01

Recent studies have shown that cerebral apoD levels increase with age and in Alzheimer's disease (AD). In addition, loss of cerebral apoD in the mouse increases sensitivity to lipid peroxidation and accelerates AD pathology. Very little data are available, however, regarding the expression of apoD protein levels in different brain regions. This is important as both brain lipid peroxidation and neurodegeneration occur in a region-specific manner. Here we addressed this using western blotting of seven different regions (olfactory bulb, hippocampus, frontal cortex, striatum, cerebellum, thalamus and brain stem) of the mouse brain. Our data indicate that compared to most brain regions, the hippocampus is deficient in apoD. In comparison to other major organs and tissues (liver, spleen, kidney, adrenal gland, heart and skeletal muscle), brain apoD was approximately 10-fold higher (corrected for total protein levels). Our analysis also revealed that brain apoD was present at a lower apparent molecular weight than tissue and plasma apoD. Utilising peptide N-glycosidase-F and neuraminidase to remove N-glycans and sialic acids, respectively, we found that N-glycan composition (but not sialylation alone) were responsible for this reduction in molecular weight. We extended the studies to an analysis of human brain regions (hippocampus, frontal cortex, temporal cortex and cerebellum) where we found that the hippocampus had the lowest levels of apoD. We also confirmed that human brain apoD was present at a lower molecular weight than in plasma. In conclusion, we demonstrate apoD protein levels are variable across different brain regions, that apoD levels are much higher in the brain compared to other tissues and organs, and that cerebral apoD has a lower molecular weight than peripheral apoD; a phenomenon that is due to the N-glycan content of the protein.

Determination of regional brain temperature using proton magnetic resonance spectroscopy to assess brain-body temperature differences in healthy human subjects.

PubMed

Childs, Charmaine; Hiltunen, Yrjö; Vidyasagar, Rishma; Kauppinen, Risto A

2007-01-01

Proton magnetic resonance spectroscopy ((1)H MRS) was used to determine brain temperature in healthy volunteers. Partially water-suppressed (1)H MRS data sets were acquired at 3T from four different gray matter (GM)/white matter (WM) volumes. Brain temperatures were determined from the chemical-shift difference between the CH(3) of N-acetyl aspartate (NAA) at 2.01 ppm and water. Brain temperatures in (1)H MRS voxels of 2 x 2 x 2 cm(3) showed no substantial heterogeneity. The volume-averaged temperature from single-voxel spectroscopy was compared with body temperatures obtained from the oral cavity, tympanum, and temporal artery regions. The mean brain parenchyma temperature was 0.5 degrees C cooler than readings obtained from three extra-brain sites (P < 0.01). (1)H MRS imaging (MRSI) data were acquired from a slice encompassing the single-voxel volumes to assess the ability of spectroscopic imaging to determine regional brain temperature within the imaging slice. Brain temperature away from the center of the brain determined by MRSI differed from that obtained by single-voxel MRS in the same brain region, possibly due to a poor line width (LW) in MRSI. The data are discussed in the light of proposed brain-body temperature gradients and the use of (1)H MRSI to monitor brain temperature in pathologies, such as brain trauma.

Ivy Sign on Fluid-Attenuated Inversion Recovery Images in Moyamoya Disease: Correlation with Clinical Severity and Old Brain Lesions.

PubMed

Seo, Kwon-Duk; Suh, Sang Hyun; Kim, Yong Bae; Kim, Ji Hwa; Ahn, Sung Jun; Kim, Dong-Seok; Lee, Kyung-Yul

2015-09-01

Leptomeningeal collateral, in moyamoya disease (MMD), appears as an ivy sign on fluid-attenuated inversion-recovery (FLAIR) images. There has been little investigation into the relationship between presentation of ivy signs and old brain lesions. We aimed to evaluate clinical significance of ivy signs and whether they correlate with old brain lesions and the severity of clinical symptoms in patients with MMD. FLAIR images of 83 patients were reviewed. Each cerebral hemisphere was divided into 4 regions and each region was scored based on the prominence of the ivy sign. Total ivy score (TIS) was defined as the sum of the scores from the eight regions and dominant hemispheric ivy sign (DHI) was determined by comparing the ivy scores from each hemisphere. According to the degree of ischemic symptoms, patients were classified into four subgroups: 1) nonspecific symptoms without motor weakness, 2) single transient ischemic attack (TIA), 3) recurrent TIA, or 4) complete stroke. TIS was significantly different as follows: 4.86±2.55 in patients with nonspecific symptoms, 5.89±3.10 in patients with single TIA, 9.60±3.98 in patients with recurrent TIA and 8.37±3.39 in patients with complete stroke (p=0.003). TIS associated with old lesions was significantly higher than those not associated with old lesions (9.35±4.22 vs. 7.49±3.37, p=0.032). We found a significant correlation between DHI and motor symptoms (p=0.001). Because TIS has a strong tendency with severity of ischemic motor symptom and the presence of old lesions, the ivy sign may be useful in predicting severity of disease progression.

Ivy Sign on Fluid-Attenuated Inversion Recovery Images in Moyamoya Disease: Correlation with Clinical Severity and Old Brain Lesions

PubMed Central

Seo, Kwon-Duk; Suh, Sang Hyun; Kim, Yong Bae; Kim, Ji Hwa; Ahn, Sung Jun; Kim, Dong-Seok

2015-01-01

Purpose Leptomeningeal collateral, in moyamoya disease (MMD), appears as an ivy sign on fluid-attenuated inversion-recovery (FLAIR) images. There has been little investigation into the relationship between presentation of ivy signs and old brain lesions. We aimed to evaluate clinical significance of ivy signs and whether they correlate with old brain lesions and the severity of clinical symptoms in patients with MMD. Materials and Methods FLAIR images of 83 patients were reviewed. Each cerebral hemisphere was divided into 4 regions and each region was scored based on the prominence of the ivy sign. Total ivy score (TIS) was defined as the sum of the scores from the eight regions and dominant hemispheric ivy sign (DHI) was determined by comparing the ivy scores from each hemisphere. According to the degree of ischemic symptoms, patients were classified into four subgroups: 1) nonspecific symptoms without motor weakness, 2) single transient ischemic attack (TIA), 3) recurrent TIA, or 4) complete stroke. Results TIS was significantly different as follows: 4.86±2.55 in patients with nonspecific symptoms, 5.89±3.10 in patients with single TIA, 9.60±3.98 in patients with recurrent TIA and 8.37±3.39 in patients with complete stroke (p=0.003). TIS associated with old lesions was significantly higher than those not associated with old lesions (9.35±4.22 vs. 7.49±3.37, p=0.032). We found a significant correlation between DHI and motor symptoms (p=0.001). Conclusion Because TIS has a strong tendency with severity of ischemic motor symptom and the presence of old lesions, the ivy sign may be useful in predicting severity of disease progression. PMID:26256975

Synchronization, non-linear dynamics and low-frequency fluctuations: Analogy between spontaneous brain activity and networked single-transistor chaotic oscillators

PubMed Central

Minati, Ludovico; Chiesa, Pietro; Tabarelli, Davide; D'Incerti, Ludovico

2015-01-01

In this paper, the topographical relationship between functional connectivity (intended as inter-regional synchronization), spectral and non-linear dynamical properties across cortical areas of the healthy human brain is considered. Based upon functional MRI acquisitions of spontaneous activity during wakeful idleness, node degree maps are determined by thresholding the temporal correlation coefficient among all voxel pairs. In addition, for individual voxel time-series, the relative amplitude of low-frequency fluctuations and the correlation dimension (D2), determined with respect to Fourier amplitude and value distribution matched surrogate data, are measured. Across cortical areas, high node degree is associated with a shift towards lower frequency activity and, compared to surrogate data, clearer saturation to a lower correlation dimension, suggesting presence of non-linear structure. An attempt to recapitulate this relationship in a network of single-transistor oscillators is made, based on a diffusive ring (n = 90) with added long-distance links defining four extended hub regions. Similarly to the brain data, it is found that oscillators in the hub regions generate signals with larger low-frequency cycle amplitude fluctuations and clearer saturation to a lower correlation dimension compared to surrogates. The effect emerges more markedly close to criticality. The homology observed between the two systems despite profound differences in scale, coupling mechanism and dynamics appears noteworthy. These experimental results motivate further investigation into the heterogeneity of cortical non-linear dynamics in relation to connectivity and underline the ability for small networks of single-transistor oscillators to recreate collective phenomena arising in much more complex biological systems, potentially representing a future platform for modelling disease-related changes. PMID:25833429

Histone methylation at gene promoters is associated with developmental regulation and region-specific expression of ionotropic and metabotropic glutamate receptors in human brain.

PubMed

Stadler, Florian; Kolb, Gabriele; Rubusch, Lothar; Baker, Stephen P; Jones, Edward G; Akbarian, Schahram

2005-07-01

Glutamatergic signaling is regulated, in part, through differential expression of NMDA and AMPA/KA channel subunits and G protein-coupled metabotropic receptors. In human brain, region-specific expression patterns of glutamate receptor genes are maintained over the course of decades, suggesting a role for molecular mechanisms involved in long-term regulation of transcription, including methylation of lysine residues at histone N-terminal tails. Using a native chromatin immunoprecipitation assay, we studied histone methylation marks at proximal promoters of 16 ionotropic and metabotropic glutamate receptor genes (GRIN1,2A-D; GRIA1,3,4; GRIK2,4,5; GRM1,3,4,6,7 ) in cerebellar cortex collected across a wide age range from midgestation to 90 years old. Levels of di- and trimethylated histone H3-lysine 4, which are associated with open chromatin and transcription, showed significant differences between promoters and a robust correlation with corresponding mRNA levels in immature and mature cerebellar cortex. In contrast, levels of trimethylated H3-lysine 27 and H4-lysine 20, two histone modifications defining silenced or condensed chromatin, did not correlate with transcription but were up-regulated overall in adult cerebellum. Furthermore, differential gene expression patterns in prefrontal and cerebellar cortex were reflected by similar differences in H3-lysine 4 methylation at promoters. Together, these findings suggest that histone lysine methylation at gene promoters is involved in developmental regulation and maintenance of region-specific expression patterns of ionotropic and metabotropic glutamate receptors. The association of a specific epigenetic mark, H3-(methyl)-lysine 4, with the molecular architecture of glutamatergic signaling in human brain has potential implications for schizophrenia and other disorders with altered glutamate receptor function.

Synchronization, non-linear dynamics and low-frequency fluctuations: Analogy between spontaneous brain activity and networked single-transistor chaotic oscillators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Minati, Ludovico, E-mail: lminati@ieee.org, E-mail: ludovico.minati@unitn.it, E-mail: lminati@istituto-besta.it; Center for Mind/Brain Sciences, University of Trento, Trento; Chiesa, Pietro

In this paper, the topographical relationship between functional connectivity (intended as inter-regional synchronization), spectral and non-linear dynamical properties across cortical areas of the healthy human brain is considered. Based upon functional MRI acquisitions of spontaneous activity during wakeful idleness, node degree maps are determined by thresholding the temporal correlation coefficient among all voxel pairs. In addition, for individual voxel time-series, the relative amplitude of low-frequency fluctuations and the correlation dimension (D{sub 2}), determined with respect to Fourier amplitude and value distribution matched surrogate data, are measured. Across cortical areas, high node degree is associated with a shift towards lower frequencymore » activity and, compared to surrogate data, clearer saturation to a lower correlation dimension, suggesting presence of non-linear structure. An attempt to recapitulate this relationship in a network of single-transistor oscillators is made, based on a diffusive ring (n = 90) with added long-distance links defining four extended hub regions. Similarly to the brain data, it is found that oscillators in the hub regions generate signals with larger low-frequency cycle amplitude fluctuations and clearer saturation to a lower correlation dimension compared to surrogates. The effect emerges more markedly close to criticality. The homology observed between the two systems despite profound differences in scale, coupling mechanism and dynamics appears noteworthy. These experimental results motivate further investigation into the heterogeneity of cortical non-linear dynamics in relation to connectivity and underline the ability for small networks of single-transistor oscillators to recreate collective phenomena arising in much more complex biological systems, potentially representing a future platform for modelling disease-related changes.« less

Acute engagement of Gq-mediated signaling in the bed nucleus of the stria terminalis induces anxiety-like behavior.

PubMed

Mazzone, C M; Pati, D; Michaelides, M; DiBerto, J; Fox, J H; Tipton, G; Anderson, C; Duffy, K; McKlveen, J M; Hardaway, J A; Magness, S T; Falls, W A; Hammack, S E; McElligott, Z A; Hurd, Y L; Kash, T L

2018-01-01

The bed nucleus of the stria terminalis (BNST) is a brain region important for regulating anxiety-related behavior in both humans and rodents. Here we used a chemogenetic strategy to investigate how engagement of G protein-coupled receptor (GPCR) signaling cascades in genetically defined GABAergic BNST neurons modulates anxiety-related behavior and downstream circuit function. We saw that stimulation of vesicular γ-aminobutyric acid (GABA) transporter (VGAT)-expressing BNST neurons using hM3Dq, but neither hM4Di nor rM3Ds designer receptors exclusively activated by a designer drug (DREADD), promotes anxiety-like behavior. Further, we identified that activation of hM3Dq receptors in BNST VGAT neurons can induce a long-term depression-like state of glutamatergic synaptic transmission, indicating DREADD-induced changes in synaptic plasticity. Further, we used DREADD-assisted metabolic mapping to profile brain-wide network activity following activation of G q -mediated signaling in BNST VGAT neurons and saw increased activity within ventral midbrain structures, including the ventral tegmental area and hindbrain structures such as the locus coeruleus and parabrachial nucleus. These results highlight that G q -mediated signaling in BNST VGAT neurons can drive downstream network activity that correlates with anxiety-like behavior and points to the importance of identifying endogenous GPCRs within genetically defined cell populations. We next used a microfluidics approach to profile the receptorome of single BNST VGAT neurons. This approach yielded multiple G q -coupled receptors that are associated with anxiety-like behavior and several potential novel candidates for regulation of anxiety-like behavior. From this, we identified that stimulation of the G q -coupled receptor 5-HT 2C R in the BNST is sufficient to elevate anxiety-like behavior in an acoustic startle task. Together, these results provide a novel profile of receptors within genetically defined BNST VGAT neurons that may serve as therapeutic targets for regulating anxiety states and provide a blueprint for examining how G-protein-mediated signaling in a genetically defined cell type can be used to assess behavior and brain-wide circuit function.

Intranasal Administration of PACAP: Uptake by Brain and Brain Region Targeting with Cyclodextrins

PubMed Central

Nonaka, Naoko; Farr, Susan A.; Nakamachi, Tomoya; Morley, John E.; Nakamura, Masanori; Shioda, Seiji; Banks, William A.

2012-01-01

Pituitary adenylate cyclase activating polypeptide (PACAP) is a potent neurotrophic and neuroprotectant that is transported across the blood-brain barrier in amounts sufficient to affect brain function. However, its short half-life in blood makes it difficult to administer peripherally. Here, we determined whether the radioactively labeled 38 amino acid form of PACAP can enter the brain after intranasal (i.n.) administration. Occipital cortex and striatum were the regions with the highest uptake, peaking at levels of about 2-4 percent of the injected dose per g of brain region. Inclusion of unlabeled PACAP greatly increased retention of I-PACAP by brain probably because of inhibition of the brain-to-blood efflux transporter for PACAP located at the blood-brain barrier. Sufficient amounts of PACAP could be delivered to the brain to affect function as shown by improvement of memory in aged SAMP8 mice, a model of Alzheimer’s disease. We found that each of three cyclodextrins when included in the i.n. injection produced a unique distribution pattern of I-PACAP among brain regions. As examples, β-cyclodextrin greatly increased uptake by the occipital cortex and hypothalamus, α-cyclodextrin increased uptake by the olfactory bulb and decreased uptake by the occipital cortex and striatum, and (2-hydropropyl)-β-cyclodextrin increased uptake by the thalamus and decreased uptake by the striatum. These results show that therapeutic amounts of PACAP can be delivered to the brain by intranasal administration and that cyclodextrins may be useful in the therapeutic targeting of peptides to specific brain regions. PMID:22687366

Macro-to-micro cortical vascular imaging underlies regional differences in ischemic brain

NASA Astrophysics Data System (ADS)

Dziennis, Suzan; Qin, Jia; Shi, Lei; Wang, Ruikang K.

2015-05-01

The ability to non-invasively monitor and quantify hemodynamic responses down to the capillary level is important for improved diagnosis, treatment and management of neurovascular disorders, including stroke. We developed an integrated multi-functional imaging system, in which synchronized dual wavelength laser speckle contrast imaging (DWLS) was used as a guiding tool for optical microangiography (OMAG) to test whether detailed vascular responses to experimental stroke in male mice can be evaluated with wide range sensitivity from arteries and veins down to the capillary level. DWLS enabled rapid identification of cerebral blood flow (CBF), prediction of infarct area and hemoglobin oxygenation over the whole mouse brain and was used to guide the OMAG system to hone in on depth information regarding blood volume, blood flow velocity and direction, vascular architecture, vessel diameter and capillary density pertaining to defined regions of CBF in response to ischemia. OMAG-DWLS is a novel imaging platform technology to simultaneously evaluate multiple vascular responses to ischemic injury, which can be useful in improving our understanding of vascular responses under pathologic and physiological conditions, and ultimately facilitating clinical diagnosis, monitoring and therapeutic interventions of neurovascular diseases.

Lateral Prefrontal Cortex Subregions Make Dissociable Contributions during Fluid Reasoning

PubMed Central

Thompson, Russell; Duncan, John; Owen, Adrian M.

2011-01-01

Reasoning is a key component of adaptable “executive” behavior and is known to depend on a network of frontal and parietal brain regions. However, the mechanisms by which this network supports reasoning and adaptable behavior remain poorly defined. Here, we examine the relationship between reasoning, executive control, and frontoparietal function in a series of nonverbal reasoning experiments. Our results demonstrate that, in accordance with previous studies, a network of frontal and parietal brain regions is recruited during reasoning. Our results also reveal that this network can be fractionated according to how different subregions respond when distinct reasoning demands are manipulated. While increased rule complexity modulates activity within a right lateralized network including the middle frontal gyrus and the superior parietal cortex, analogical reasoning demand—or the requirement to remap rules on to novel features—recruits the left inferior rostrolateral prefrontal cortex and the lateral occipital complex. In contrast, the posterior extent of the inferior frontal gyrus, associated with simpler executive demands, is not differentially sensitive to rule complexity or analogical demand. These findings accord well with the hypothesis that different reasoning demands are supported by different frontal and parietal subregions. PMID:20483908

Gray matter density in relation to different facets of verbal creativity.

PubMed

Fink, Andreas; Koschutnig, Karl; Hutterer, Lisa; Steiner, Elisabeth; Benedek, Mathias; Weber, Bernhard; Reishofer, Gernot; Papousek, Ilona; Weiss, Elisabeth M

2014-07-01

Neuroscience studies on creativity have revealed highly variegated findings that often seem to be inconsistent. As recently argued in Fink and Benedek (Neurosci Biobehav Rev, 2012), this might be primarily due to the broad diversity in defining and measuring creativity as well as to the diversity of experimental procedures and methodologies used in this field of research. In specifically focusing on one measure of brain activation and on the well-established process of creative ideation (i.e., divergent thinking), EEG studies revealed a quite consistent and replicable pattern of right-lateralized brain activity over posterior parietal and occipital sites. In this study, we related regional gray matter density (as assessed by means of voxel-based morphometry) to different facets of psychometrically determined verbal creativity in a sample of 71 participants. Results revealed that verbal creativity was significantly and positively associated with gray matter density in clusters involving the right cuneus and the right precuneus. Enhanced gray matter density in these regions may be indicative of vivid imaginative abilities in more creative individuals. These findings complement existing functional studies on creative ideation which are, taken as a whole, among the most consistent findings in this field.

The social phenotype of Williams syndrome.

PubMed

Järvinen, Anna; Korenberg, Julie R; Bellugi, Ursula

2013-06-01

Williams syndrome (WS) offers an exciting model for social neuroscience because its genetic basis is well-defined, and the unique phenotype reflects dimensions of prosocial behaviors. WS is associated with a strong drive to approach strangers, a gregarious personality, heightened social engagement yet difficult peer interactions, high nonsocial anxiety, unusual bias toward positive affect, and diminished sensitivity to fear. New neurobiological evidence points toward alterations in structure, function, and connectivity of the social brain (amygdala, fusiform face area, orbital-frontal regions). Recent genetic studies implicate gene networks in the WS region with the dysregulation of prosocial neuropeptides. The study of WS has implications for understanding human social development, and may provide insight for translating genetic and neuroendocrine evidence into treatments for disorders of social behavior. Copyright © 2013 Elsevier Ltd. All rights reserved.

Fused cerebral organoids model interactions between brain regions.

PubMed

Bagley, Joshua A; Reumann, Daniel; Bian, Shan; Lévi-Strauss, Julie; Knoblich, Juergen A

2017-07-01

Human brain development involves complex interactions between different regions, including long-distance neuronal migration or formation of major axonal tracts. Different brain regions can be cultured in vitro within 3D cerebral organoids, but the random arrangement of regional identities limits the reliable analysis of complex phenotypes. Here, we describe a coculture method combining brain regions of choice within one organoid tissue. By fusing organoids of dorsal and ventral forebrain identities, we generate a dorsal-ventral axis. Using fluorescent reporters, we demonstrate CXCR4-dependent GABAergic interneuron migration from ventral to dorsal forebrain and describe methodology for time-lapse imaging of human interneuron migration. Our results demonstrate that cerebral organoid fusion cultures can model complex interactions between different brain regions. Combined with reprogramming technology, fusions should offer researchers the possibility to analyze complex neurodevelopmental defects using cells from neurological disease patients and to test potential therapeutic compounds.

A Closer Look at the Brain As Related to Teachers and Learners.

ERIC Educational Resources Information Center

Haglund, Elaine

1981-01-01

Recent findings related to neurological research include: (1) the Proster Theory implies that the brain works by sets of programs or prosters; (2) the Brain Growth Spurts theory defines the growth of the brain in spurts with cycles of rest; and (3) in the Hemispheric Specialization Theory, the left and right hemispheres of the brain have specific…

Control-related systems in the human brain

PubMed Central

Power, Jonathan D; Petersen, Steven E

2013-01-01

A fundamental question in cognitive neuroscience is how the human brain self-organizes to perform tasks. Multiple accounts of this self-organization are currently influential and in this article we survey one of these accounts. We begin by introducing a psychological model of task control and several neuroimaging signals it predicts. We then discuss where such signals are found across tasks with emphasis on brain regions where multiple control signals are present. We then present results derived from spontaneous task-free functional connectivity between control-related regions that dovetail with distinctions made by control signals present in these regions, leading to a proposal that there are at least two task control systems in the brain. This prompts consideration of whether and how such control systems distinguish themselves from other brain regions in a whole-brain context. We present evidence from whole-brain networks that such distinctions do occur and that control systems comprise some of the basic system-level organizational elements of the human brain. We close with observations from the whole-brain networks that may suggest parsimony between multiple accounts of cognitive control. PMID:23347645

A pediatric brain structure atlas from T1-weighted MR images

NASA Astrophysics Data System (ADS)

Shan, Zuyao Y.; Parra, Carlos; Ji, Qing; Ogg, Robert J.; Zhang, Yong; Laningham, Fred H.; Reddick, Wilburn E.

2006-03-01

In this paper, we have developed a digital atlas of the pediatric human brain. Human brain atlases, used to visualize spatially complex structures of the brain, are indispensable tools in model-based segmentation and quantitative analysis of brain structures. However, adult brain atlases do not adequately represent the normal maturational patterns of the pediatric brain, and the use of an adult model in pediatric studies may introduce substantial bias. Therefore, we proposed to develop a digital atlas of the pediatric human brain in this study. The atlas was constructed from T1 weighted MR data set of a 9 year old, right-handed girl. Furthermore, we extracted and simplified boundary surfaces of 25 manually defined brain structures (cortical and subcortical) based on surface curvature. Higher curvature surfaces were simplified with more reference points; lower curvature surfaces, with fewer. We constructed a 3D triangular mesh model for each structure by triangulation of the structure's reference points. Kappa statistics (cortical, 0.97; subcortical, 0.91) indicated substantial similarities between the mesh-defined and the original volumes. Our brain atlas and structural mesh models (www.stjude.org/BrainAtlas) can be used to plan treatment, to conduct knowledge and modeldriven segmentation, and to analyze the shapes of brain structures in pediatric patients.

Calcified Mass on Brain CT in a Teenager with Refractory Seizures.

PubMed

Khalatbari, Mahmoud Reza; Brunetti, Enrico; Shobeiri, Elham; Moharamzad, Yashar

2014-12-01

Cerebral echinococcosis is very rare, representing 2% of all cystic echinococcosis (CE) cases. Primary echinococcal cysts of the brain are extremely rare in pediatric patients. We report on a 16-year-old boy referred to our tertiary center with intractable epilepsy for the previous three years despite receiving full doses of three antiepileptic medications. Brain computed tomography (CT) showed a left frontal calcified mass. Magnetic resonance imaging (MRI) of the brain revealed a well-defined spherical mass in the left frontal lobe, slightly hypointense on T1-weighted and heterogeneous hyperintense on T2-weighted images with no contrast enhancement. With a broad differential list in mind, a surgical intervention was planned. During surgery, a primary calcified cerebral echinococcal cyst with severe adhesion to the adjacent dura of the frontal region was discovered and removed intact. Histopathology examination confirmed the diagnosis. Only phenobarbital was continued and no medical therapy for CE was administered. Two years after surgery, the patient remained free of seizures. In areas endemic for CE, cerebral echinococcal cyst should be included in the differential list of patients with intractable seizures. Though rare, this entity can present itself as a calcified mass on neuroimaging. Surgical removal of the calcified cyst is necessary for control and treatment of the epilepsy.