Chen, Zikuan; Calhoun, Vince D
2016-03-01
Conventionally, independent component analysis (ICA) is performed on an fMRI magnitude dataset to analyze brain functional mapping (AICA). By solving the inverse problem of fMRI, we can reconstruct the brain magnetic susceptibility (χ) functional states. Upon the reconstructed χ dataspace, we propose an ICA-based brain functional χ mapping method (χICA) to extract task-evoked brain functional map. A complex division algorithm is applied to a timeseries of fMRI phase images to extract temporal phase changes (relative to an OFF-state snapshot). A computed inverse MRI (CIMRI) model is used to reconstruct a 4D brain χ response dataset. χICA is implemented by applying a spatial InfoMax ICA algorithm to the reconstructed 4D χ dataspace. With finger-tapping experiments on a 7T system, the χICA-extracted χ-depicted functional map is similar to the SPM-inferred functional χ map by a spatial correlation of 0.67 ± 0.05. In comparison, the AICA-extracted magnitude-depicted map is correlated with the SPM magnitude map by 0.81 ± 0.05. The understanding of the inferiority of χICA to AICA for task-evoked functional map is an ongoing research topic. For task-evoked brain functional mapping, we compare the data-driven ICA method with the task-correlated SPM method. In particular, we compare χICA with AICA for extracting task-correlated timecourses and functional maps. χICA can extract a χ-depicted task-evoked brain functional map from a reconstructed χ dataspace without the knowledge about brain hemodynamic responses. The χICA-extracted brain functional χ map reveals a bidirectional BOLD response pattern that is unavailable (or different) from AICA. Copyright © 2016 Elsevier B.V. All rights reserved.
Brain-mapping projects using the common marmoset.
Okano, Hideyuki; Mitra, Partha
2015-04-01
Globally, there is an increasing interest in brain-mapping projects, including the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative project in the USA, the Human Brain Project (HBP) in Europe, and the Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS) project in Japan. These projects aim to map the structure and function of neuronal circuits to ultimately understand the vast complexity of the human brain. Brain/MINDS is focused on structural and functional mapping of the common marmoset (Callithrix jacchus) brain. This non-human primate has numerous advantages for brain mapping, including a well-developed frontal cortex and a compact brain size, as well as the availability of transgenic technologies. In the present review article, we discuss strategies for structural and functional mapping of the marmoset brain and the relation of the common marmoset to other animals models. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.
Brain/MINDS: brain-mapping project in Japan
Okano, Hideyuki; Miyawaki, Atsushi; Kasai, Kiyoto
2015-01-01
There is an emerging interest in brain-mapping projects in countries across the world, including the USA, Europe, Australia and China. In 2014, Japan started a brain-mapping project called Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS). Brain/MINDS aims to map the structure and function of neuronal circuits to ultimately understand the vast complexity of the human brain, and takes advantage of a unique non-human primate animal model, the common marmoset (Callithrix jacchus). In Brain/MINDS, the RIKEN Brain Science Institute acts as a central institute. The objectives of Brain/MINDS can be categorized into the following three major subject areas: (i) structure and functional mapping of a non-human primate brain (the marmoset brain); (ii) development of innovative neurotechnologies for brain mapping; and (iii) human brain mapping; and clinical research. Brain/MINDS researchers are highly motivated to identify the neuronal circuits responsible for the phenotype of neurological and psychiatric disorders, and to understand the development of these devastating disorders through the integration of these three subject areas. PMID:25823872
2017-05-14
AFRL-AFOSR-JP-TR-2017-0052 Non-invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognative Functions...invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognative Functions 5a. CONTRACT NUMBER 5b. GRANT...SUPPLEMENTARY NOTES 14. ABSTRACT Brain stress level measurement (non-invasively) in quantitative term is very helpful to correlate with various
2017-05-14
AFRL-AFOSR-JP-TR-2017-0052 Non-invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognative Functions...invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognative Functions 5a. CONTRACT NUMBER 5b. GRANT...SUPPLEMENTARY NOTES 14. ABSTRACT Brain stress level measurement (non-invasively) in quantitative term is very helpful to correlate with various
Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping.
Pinho, Ana Luísa; Amadon, Alexis; Ruest, Torsten; Fabre, Murielle; Dohmatob, Elvis; Denghien, Isabelle; Ginisty, Chantal; Becuwe-Desmidt, Séverine; Roger, Séverine; Laurier, Laurence; Joly-Testault, Véronique; Médiouni-Cloarec, Gaëlle; Doublé, Christine; Martins, Bernadette; Pinel, Philippe; Eger, Evelyn; Varoquaux, Gaël; Pallier, Christophe; Dehaene, Stanislas; Hertz-Pannier, Lucie; Thirion, Bertrand
2018-06-12
Functional Magnetic Resonance Imaging (fMRI) has furthered brain mapping on perceptual, motor, as well as higher-level cognitive functions. However, to date, no data collection has systematically addressed the functional mapping of cognitive mechanisms at a fine spatial scale. The Individual Brain Charting (IBC) project stands for a high-resolution multi-task fMRI dataset that intends to provide the objective basis toward a comprehensive functional atlas of the human brain. The data refer to a cohort of 12 participants performing many different tasks. The large amount of task-fMRI data on the same subjects yields a precise mapping of the underlying functions, free from both inter-subject and inter-site variability. The present article gives a detailed description of the first release of the IBC dataset. It comprises a dozen of tasks, addressing both low- and high- level cognitive functions. This openly available dataset is thus intended to become a reference for cognitive brain mapping.
NASA Astrophysics Data System (ADS)
Kinkingnehun, Serge R. J.; du Boisgueheneuc, Foucaud; Golmard, Jean-Louis; Zhang, Sandy X.; Levy, Richard; Dubois, Bruno
2004-04-01
We have developed a new technique to analyze correlations between brain anatomy and its neurological functions. The technique is based on the anatomic MRI of patients with brain lesions who are administered neuropsychological tests. Brain lesions of the MRI scans are first manually segmented. The MRI volumes are then normalized to a reference map, using the segmented area as a mask. After normalization, the brain lesions of the MRI are segmented again in order to redefine the border of the lesions in the context of the normalized brain. Once the MRI is segmented, the patient's score on the neuropsychological test is assigned to each voxel in the lesioned area, while the rest of the voxels of the image are set to 0. Subsequently, the individual patient's MRI images are superimposed, and each voxel is reassigned the average score of the patients who have a lesion at that voxel. A threshold is applied to remove regions having less than three overlaps. This process leads to an anatomo-functional map that links brain areas to functional loss. Other maps can be created to aid in analyzing the functional maps, such as one that indicates the 95% confidence interval of the averaged scores for each area. This anatomo-clinical overlapping map (AnaCOM) method was used to obtain functional maps from patients with lesions in the superior frontal gyrus. By finding particular subregions more responsible for a particular deficit, this method can generate new hypotheses to be tested by conventional group methods.
Mapping Language Function in the Brain: A Review of the Recent Literature.
ERIC Educational Resources Information Center
Crafton, Robert E.; Kido, Elissa
2000-01-01
Considers the potential importance of brain study for composition instruction, briefly describes functional imaging techniques, and reviews the findings of recent brain-mapping studies investigating the neurocognitive systems involved in language function. Presents a review of the recent literature and considers the possible implications of this…
Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping
Robinson, Jennifer; Calhoun, Vince
2018-01-01
Purpose To computationally separate dynamic brain functional BOLD responses from static background in a brain functional activity for forward fMRI signal analysis and inverse mapping. Methods A brain functional activity is represented in terms of magnetic source by a perturbation model: χ = χ0 +δχ, with δχ for BOLD magnetic perturbations and χ0 for background. A brain fMRI experiment produces a timeseries of complex-valued images (T2* images), whereby we extract the BOLD phase signals (denoted by δP) by a complex division. By solving an inverse problem, we reconstruct the BOLD δχ dataset from the δP dataset, and the brain χ distribution from a (unwrapped) T2* phase image. Given a 4D dataset of task BOLD fMRI, we implement brain functional mapping by temporal correlation analysis. Results Through a high-field (7T) and high-resolution (0.5mm in plane) task fMRI experiment, we demonstrated in detail the BOLD perturbation model for fMRI phase signal separation (P + δP) and reconstructing intrinsic brain magnetic source (χ and δχ). We also provided to a low-field (3T) and low-resolution (2mm) task fMRI experiment in support of single-subject fMRI study. Our experiments show that the δχ-depicted functional map reveals bidirectional BOLD χ perturbations during the task performance. Conclusions The BOLD perturbation model allows us to separate fMRI phase signal (by complex division) and to perform inverse mapping for pure BOLD δχ reconstruction for intrinsic functional χ mapping. The full brain χ reconstruction (from unwrapped fMRI phase) provides a new brain tissue image that allows to scrutinize the brain tissue idiosyncrasy for the pure BOLD δχ response through an automatic function/structure co-localization. PMID:29351339
BrainMap VBM: An environment for structural meta-analysis.
Vanasse, Thomas J; Fox, P Mickle; Barron, Daniel S; Robertson, Michaela; Eickhoff, Simon B; Lancaster, Jack L; Fox, Peter T
2018-05-02
The BrainMap database is a community resource that curates peer-reviewed, coordinate-based human neuroimaging literature. By pairing the results of neuroimaging studies with their relevant meta-data, BrainMap facilitates coordinate-based meta-analysis (CBMA) of the neuroimaging literature en masse or at the level of experimental paradigm, clinical disease, or anatomic location. Initially dedicated to the functional, task-activation literature, BrainMap is now expanding to include voxel-based morphometry (VBM) studies in a separate sector, titled: BrainMap VBM. VBM is a whole-brain, voxel-wise method that measures significant structural differences between or within groups which are reported as standardized, peak x-y-z coordinates. Here we describe BrainMap VBM, including the meta-data structure, current data volume, and automated reverse inference functions (region-to-disease profile) of this new community resource. CBMA offers a robust methodology for retaining true-positive and excluding false-positive findings across studies in the VBM literature. As with BrainMap's functional database, BrainMap VBM may be synthesized en masse or at the level of clinical disease or anatomic location. As a use-case scenario for BrainMap VBM, we illustrate a trans-diagnostic data-mining procedure wherein we explore the underlying network structure of 2,002 experiments representing over 53,000 subjects through independent components analysis (ICA). To reduce data-redundancy effects inherent to any database, we demonstrate two data-filtering approaches that proved helpful to ICA. Finally, we apply hierarchical clustering analysis (HCA) to measure network- and disease-specificity. This procedure distinguished psychiatric from neurological diseases. We invite the neuroscientific community to further exploit BrainMap VBM with other modeling approaches. © 2018 Wiley Periodicals, Inc.
Altered Whole-Brain and Network-Based Functional Connectivity in Parkinson's Disease.
de Schipper, Laura J; Hafkemeijer, Anne; van der Grond, Jeroen; Marinus, Johan; Henselmans, Johanna M L; van Hilten, Jacobus J
2018-01-01
Background: Functional imaging methods, such as resting-state functional magnetic resonance imaging, reflect changes in neural connectivity and may help to assess the widespread consequences of disease-specific network changes in Parkinson's disease. In this study we used a relatively new graph analysis approach in functional imaging: eigenvector centrality mapping. This model-free method, applied to all voxels in the brain, identifies prominent regions in the brain network hierarchy and detects localized differences between patient populations. In other neurological disorders, eigenvector centrality mapping has been linked to changes in functional connectivity in certain nodes of brain networks. Objectives: Examining changes in functional brain connectivity architecture on a whole brain and network level in patients with Parkinson's disease. Methods: Whole brain resting-state functional architecture was studied with a recently introduced graph analysis approach (eigenvector centrality mapping). Functional connectivity was further investigated in relation to eight known resting-state networks. Cross-sectional analyses included group comparison of functional connectivity measures of Parkinson's disease patients ( n = 107) with control subjects ( n = 58) and correlations with clinical data, including motor and cognitive impairment and a composite measure of predominantly non-dopaminergic symptoms. Results: Eigenvector centrality mapping revealed that frontoparietal regions were more prominent in the whole-brain network function in patients compared to control subjects, while frontal and occipital brain areas were less prominent in patients. Using standard resting-state networks, we found predominantly increased functional connectivity, namely within sensorimotor system and visual networks in patients. Regional group differences in functional connectivity of both techniques between patients and control subjects partly overlapped for highly connected posterior brain regions, in particular in the posterior cingulate cortex and precuneus. Clinico-functional imaging relations were not found. Conclusions: Changes on the level of functional brain connectivity architecture might provide a different perspective of pathological consequences of Parkinson's disease. The involvement of specific, highly connected (hub) brain regions may influence whole brain functional network architecture in Parkinson's disease.
Intraoperative Functional Ultrasound Imaging of Human Brain Activity.
Imbault, Marion; Chauvet, Dorian; Gennisson, Jean-Luc; Capelle, Laurent; Tanter, Mickael
2017-08-04
The functional mapping of brain activity is essential to perform optimal glioma surgery and to minimize the risk of postoperative deficits. We introduce a new, portable neuroimaging modality of the human brain based on functional ultrasound (fUS) for deep functional cortical mapping. Using plane-wave transmissions at an ultrafast frame rate (1 kHz), fUS is performed during surgery to measure transient changes in cerebral blood volume with a high spatiotemporal resolution (250 µm, 1 ms). fUS identifies, maps and differentiates regions of brain activation during task-evoked cortical responses within the depth of a sulcus in both awake and anaesthetized patients.
Tamura, Yukie; Ogawa, Hiroshi; Kapeller, Christoph; Prueckl, Robert; Takeuchi, Fumiya; Anei, Ryogo; Ritaccio, Anthony; Guger, Christoph; Kamada, Kyousuke
2016-12-01
OBJECTIVE Electrocortical stimulation (ECS) is the gold standard for functional brain mapping; however, precise functional mapping is still difficult in patients with language deficits. High gamma activity (HGA) between 80 and 140 Hz on electrocorticography is assumed to reflect localized cortical processing, whereas the cortico-cortical evoked potential (CCEP) can reflect bidirectional responses evoked by monophasic pulse stimuli to the language cortices when there is no patient cooperation. The authors propose the use of "passive" mapping by combining HGA mapping and CCEP recording without active tasks during conscious resections of brain tumors. METHODS Five patients, each with an intraaxial tumor in their dominant hemisphere, underwent conscious resection of their lesion with passive mapping. The authors performed functional localization for the receptive language area, using real-time HGA mapping, by listening passively to linguistic sounds. Furthermore, single electrical pulses were delivered to the identified receptive temporal language area to detect CCEPs in the frontal lobe. All mapping results were validated by ECS, and the sensitivity and specificity were evaluated. RESULTS Linguistic HGA mapping quickly identified the language area in the temporal lobe. Electrical stimulation by linguistic HGA mapping to the identified temporal receptive language area evoked CCEPs on the frontal lobe. The combination of linguistic HGA and frontal CCEPs needed no patient cooperation or effort. In this small case series, the sensitivity and specificity were 93.8% and 89%, respectively. CONCLUSIONS The described technique allows for simple and quick functional brain mapping with higher sensitivity and specificity than ECS mapping. The authors believe that this could improve the reliability of functional brain mapping and facilitate rational and objective operations. Passive mapping also sheds light on the underlying physiological mechanisms of language in the human brain.
Wang, Yinghua; Yan, Jiaqing; Wen, Jianbin; Yu, Tao; Li, Xiaoli
2016-01-01
Before epilepsy surgeries, intracranial electroencephalography (iEEG) is often employed in function mapping and epileptogenic foci localization. Although the implanted electrodes provide crucial information for epileptogenic zone resection, a convenient clinical tool for electrode position registration and Brain Function Mapping (BFM) visualization is still lacking. In this study, we developed a BFM Tool, which facilitates electrode position registration and BFM visualization, with an application to epilepsy surgeries. The BFM Tool mainly utilizes electrode location registration and function mapping based on pre-defined brain models from other software. In addition, the electrode node and mapping properties, such as the node size/color, edge color/thickness, mapping method, can be adjusted easily using the setting panel. Moreover, users may manually import/export location and connectivity data to generate figures for further application. The role of this software is demonstrated by a clinical study of language area localization. The BFM Tool helps clinical doctors and researchers visualize implanted electrodes and brain functions in an easy, quick and flexible manner. Our tool provides convenient electrode registration, easy brain function visualization, and has good performance. It is clinical-oriented and is easy to deploy and use. The BFM tool is suitable for epilepsy and other clinical iEEG applications.
Wang, Yinghua; Yan, Jiaqing; Wen, Jianbin; Yu, Tao; Li, Xiaoli
2016-01-01
Objects: Before epilepsy surgeries, intracranial electroencephalography (iEEG) is often employed in function mapping and epileptogenic foci localization. Although the implanted electrodes provide crucial information for epileptogenic zone resection, a convenient clinical tool for electrode position registration and Brain Function Mapping (BFM) visualization is still lacking. In this study, we developed a BFM Tool, which facilitates electrode position registration and BFM visualization, with an application to epilepsy surgeries. Methods: The BFM Tool mainly utilizes electrode location registration and function mapping based on pre-defined brain models from other software. In addition, the electrode node and mapping properties, such as the node size/color, edge color/thickness, mapping method, can be adjusted easily using the setting panel. Moreover, users may manually import/export location and connectivity data to generate figures for further application. The role of this software is demonstrated by a clinical study of language area localization. Results: The BFM Tool helps clinical doctors and researchers visualize implanted electrodes and brain functions in an easy, quick and flexible manner. Conclusions: Our tool provides convenient electrode registration, easy brain function visualization, and has good performance. It is clinical-oriented and is easy to deploy and use. The BFM tool is suitable for epilepsy and other clinical iEEG applications. PMID:27199729
NASA Astrophysics Data System (ADS)
Bauer, Adam Q.; Kraft, Andrew; Baxter, Grant A.; Bruchas, Michael; Lee, Jin-Moo; Culver, Joseph P.
2017-02-01
Functional magnetic resonance imaging (fMRI) has transformed our understanding of the brain's functional organization. However, mapping subunits of a functional network using hemoglobin alone presents several disadvantages. Evoked and spontaneous hemodynamic fluctuations reflect ensemble activity from several populations of neurons making it difficult to discern excitatory vs inhibitory network activity. Still, blood-based methods of brain mapping remain powerful because hemoglobin provides endogenous contrast in all mammalian brains. To add greater specificity to hemoglobin assays, we integrated optical intrinsic signal(OIS) imaging with optogenetic stimulation to create an Opto-OIS mapping tool that combines the cell-specificity of optogenetics with label-free, hemoglobin imaging. Before mapping, titrated photostimuli determined which stimulus parameters elicited linear hemodynamic responses in the cortex. Optimized stimuli were then scanned over the left hemisphere to create a set of optogenetically-defined effective connectivity (Opto-EC) maps. For many sites investigated, Opto-EC maps exhibited higher spatial specificity than those determined using spontaneous hemodynamic fluctuations. For example, resting-state functional connectivity (RS-FC) patterns exhibited widespread ipsilateral connectivity while Opto-EC maps contained distinct short- and long-range constellations of ipsilateral connectivity. Further, RS-FC maps were usually symmetric about midline while Opto-EC maps displayed more heterogeneous contralateral homotopic connectivity. Both Opto-EC and RS-FC patterns were compared to mouse connectivity data from the Allen Institute. Unlike RS-FC maps, Thy1-based maps collected in awake, behaving mice closely recapitulated the connectivity structure derived using ex vivo anatomical tracer methods. Opto-OIS mapping could be a powerful tool for understanding cellular and molecular contributions to network dynamics and processing in the mouse brain.
Brain Entropy Mapping Using fMRI
Wang, Ze; Li, Yin; Childress, Anna Rose; Detre, John A.
2014-01-01
Entropy is an important trait for life as well as the human brain. Characterizing brain entropy (BEN) may provide an informative tool to assess brain states and brain functions. Yet little is known about the distribution and regional organization of BEN in normal brain. The purpose of this study was to examine the whole brain entropy patterns using a large cohort of normal subjects. A series of experiments were first performed to validate an approximate entropy measure regarding its sensitivity, specificity, and reliability using synthetic data and fMRI data. Resting state fMRI data from a large cohort of normal subjects (n = 1049) from multi-sites were then used to derive a 3-dimensional BEN map, showing a sharp low-high entropy contrast between the neocortex and the rest of brain. The spatial heterogeneity of resting BEN was further studied using a data-driven clustering method, and the entire brain was found to be organized into 7 hierarchical regional BEN networks that are consistent with known structural and functional brain parcellations. These findings suggest BEN mapping as a physiologically and functionally meaningful measure for studying brain functions. PMID:24657999
Magnetic Resonance, Functional (fMRI) -- Brain
... thought, speech, movement and sensation, which is called brain mapping. help assess the effects of stroke, trauma, or degenerative disease (such as Alzheimer's) on brain function. monitor the growth and function of brain ...
Mapping Prefrontal Cortex Functions in Human Infancy
ERIC Educational Resources Information Center
Grossmann, Tobias
2013-01-01
It has long been thought that the prefrontal cortex, as the seat of most higher brain functions, is functionally silent during most of infancy. This review highlights recent work concerned with the precise mapping (localization) of brain activation in human infants, providing evidence that prefrontal cortex exhibits functional activation much…
Korea Brain Initiative: Integration and Control of Brain Functions.
Jeong, Sung-Jin; Lee, Haejin; Hur, Eun-Mi; Choe, Youngshik; Koo, Ja Wook; Rah, Jong-Cheol; Lee, Kea Joo; Lim, Hyun-Ho; Sun, Woong; Moon, Cheil; Kim, Kyungjin
2016-11-02
This article introduces the history and the long-term goals of the Korea Brain Initiative, which is centered on deciphering the brain functions and mechanisms that mediate the integration and control of brain functions that underlie decision-making. The goal of this initiative is the mapping of a functional connectome with searchable, multi-dimensional, and information-integrated features. The project also includes the development of novel technologies and neuro-tools for integrated brain mapping. Beyond the scientific goals this grand endeavor will ultimately have socioeconomic ramifications that not only facilitate global collaboration in the neuroscience community, but also develop various brain science-related industrial and medical innovations. Copyright © 2016. Published by Elsevier Inc.
Neonatal brain resting-state functional connectivity imaging modalities.
Mohammadi-Nejad, Ali-Reza; Mahmoudzadeh, Mahdi; Hassanpour, Mahlegha S; Wallois, Fabrice; Muzik, Otto; Papadelis, Christos; Hansen, Anne; Soltanian-Zadeh, Hamid; Gelovani, Juri; Nasiriavanaki, Mohammadreza
2018-06-01
Infancy is the most critical period in human brain development. Studies demonstrate that subtle brain abnormalities during this state of life may greatly affect the developmental processes of the newborn infants. One of the rapidly developing methods for early characterization of abnormal brain development is functional connectivity of the brain at rest. While the majority of resting-state studies have been conducted using magnetic resonance imaging (MRI), there is clear evidence that resting-state functional connectivity (rs-FC) can also be evaluated using other imaging modalities. The aim of this review is to compare the advantages and limitations of different modalities used for the mapping of infants' brain functional connectivity at rest. In addition, we introduce photoacoustic tomography, a novel functional neuroimaging modality, as a complementary modality for functional mapping of infants' brain.
Spatially Regularized Machine Learning for Task and Resting-state fMRI
Song, Xiaomu; Panych, Lawrence P.; Chen, Nan-kuei
2015-01-01
Background Reliable mapping of brain function across sessions and/or subjects in task- and resting-state has been a critical challenge for quantitative fMRI studies although it has been intensively addressed in the past decades. New Method A spatially regularized support vector machine (SVM) technique was developed for the reliable brain mapping in task- and resting-state. Unlike most existing SVM-based brain mapping techniques, which implement supervised classifications of specific brain functional states or disorders, the proposed method performs a semi-supervised classification for the general brain function mapping where spatial correlation of fMRI is integrated into the SVM learning. The method can adapt to intra- and inter-subject variations induced by fMRI nonstationarity, and identify a true boundary between active and inactive voxels, or between functionally connected and unconnected voxels in a feature space. Results The method was evaluated using synthetic and experimental data at the individual and group level. Multiple features were evaluated in terms of their contributions to the spatially regularized SVM learning. Reliable mapping results in both task- and resting-state were obtained from individual subjects and at the group level. Comparison with Existing Methods A comparison study was performed with independent component analysis, general linear model, and correlation analysis methods. Experimental results indicate that the proposed method can provide a better or comparable mapping performance at the individual and group level. Conclusions The proposed method can provide accurate and reliable mapping of brain function in task- and resting-state, and is applicable to a variety of quantitative fMRI studies. PMID:26470627
Topographic Brain Mapping: A Window on Brain Function?
ERIC Educational Resources Information Center
Karniski, Walt M.
1989-01-01
The article reviews the method of topographic mapping of the brain's electrical activity. Multiple electroencephalogram (EEG) electrodes and computerized analysis of the EEG signal are used to generate maps of frequency and voltage (evoked potential). This relatively new technique holds promise in the evaluation of children with behavioral and…
Correspondence of the brain's functional architecture during activation and rest.
Smith, Stephen M; Fox, Peter T; Miller, Karla L; Glahn, David C; Fox, P Mickle; Mackay, Clare E; Filippini, Nicola; Watkins, Kate E; Toro, Roberto; Laird, Angela R; Beckmann, Christian F
2009-08-04
Neural connections, providing the substrate for functional networks, exist whether or not they are functionally active at any given moment. However, it is not known to what extent brain regions are continuously interacting when the brain is "at rest." In this work, we identify the major explicit activation networks by carrying out an image-based activation network analysis of thousands of separate activation maps derived from the BrainMap database of functional imaging studies, involving nearly 30,000 human subjects. Independently, we extract the major covarying networks in the resting brain, as imaged with functional magnetic resonance imaging in 36 subjects at rest. The sets of major brain networks, and their decompositions into subnetworks, show close correspondence between the independent analyses of resting and activation brain dynamics. We conclude that the full repertoire of functional networks utilized by the brain in action is continuously and dynamically "active" even when at "rest."
ERIC Educational Resources Information Center
Yeh, Yu-Chu
2004-01-01
This study proposes an interactive model of "cross-domain" concept mapping with an emphasis on brain functions, and it further investigates the relationships between academic achievement, creative thinking, and cross-domain concept mapping. Sixty-nine seventh graders participated in this study which employed two 50-minute instructional…
aMAP is a validated pipeline for registration and segmentation of high-resolution mouse brain data
Niedworok, Christian J.; Brown, Alexander P. Y.; Jorge Cardoso, M.; Osten, Pavel; Ourselin, Sebastien; Modat, Marc; Margrie, Troy W.
2016-01-01
The validation of automated image registration and segmentation is crucial for accurate and reliable mapping of brain connectivity and function in three-dimensional (3D) data sets. While validation standards are necessarily high and routinely met in the clinical arena, they have to date been lacking for high-resolution microscopy data sets obtained from the rodent brain. Here we present a tool for optimized automated mouse atlas propagation (aMAP) based on clinical registration software (NiftyReg) for anatomical segmentation of high-resolution 3D fluorescence images of the adult mouse brain. We empirically evaluate aMAP as a method for registration and subsequent segmentation by validating it against the performance of expert human raters. This study therefore establishes a benchmark standard for mapping the molecular function and cellular connectivity of the rodent brain. PMID:27384127
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.
Barrett, Lisa Feldman; Satpute, Ajay
2013-01-01
Understanding how a human brain creates a human mind ultimately depends on mapping psychological categories and concepts to physical measurements of neural response. Although it has long been assumed that emotional, social, and cognitive phenomena are realized in the operations of separate brain regions or brain networks, we demonstrate that it is possible to understand the body of neuroimaging evidence using a framework that relies on domain general, distributed structure-function mappings. We review current research in affective and social neuroscience and argue that the emerging science of large-scale intrinsic brain networks provides a coherent framework for a domain-general functional architecture of the human brain. PMID:23352202
Chu, Shu-Hsien; Parhi, Keshab K; Lenglet, Christophe
2018-03-16
A joint structural-functional brain network model is presented, which enables the discovery of function-specific brain circuits, and recovers structural connections that are under-estimated by diffusion MRI (dMRI). Incorporating information from functional MRI (fMRI) into diffusion MRI to estimate brain circuits is a challenging task. Usually, seed regions for tractography are selected from fMRI activation maps to extract the white matter pathways of interest. The proposed method jointly analyzes whole brain dMRI and fMRI data, allowing the estimation of complete function-specific structural networks instead of interactively investigating the connectivity of individual cortical/sub-cortical areas. Additionally, tractography techniques are prone to limitations, which can result in erroneous pathways. The proposed framework explicitly models the interactions between structural and functional connectivity measures thereby improving anatomical circuit estimation. Results on Human Connectome Project (HCP) data demonstrate the benefits of the approach by successfully identifying function-specific anatomical circuits, such as the language and resting-state networks. In contrast to correlation-based or independent component analysis (ICA) functional connectivity mapping, detailed anatomical connectivity patterns are revealed for each functional module. Results on a phantom (Fibercup) also indicate improvements in structural connectivity mapping by rejecting false-positive connections with insufficient support from fMRI, and enhancing under-estimated connectivity with strong functional correlation.
Hemispherical map for the human brain cortex
NASA Astrophysics Data System (ADS)
Tosun, Duygu; Prince, Jerry L.
2001-07-01
Understanding the function of the human brain cortex is a primary goal in human brain mapping. Methods to unfold and flatten the cortical surface for visualization and measurement have been described in previous literature; but comparison across multiple subjects is still difficult because of the lack of a standard mapping technique. We describe a new approach that maps each hemisphere of the cortex to a portion of a sphere in a standard way, making comparison of anatomy and function across different subjects possible. Starting with a three-dimensional magnetic resonance image of the brain, the cortex is segmented and represented as a triangle mesh. Defining a cut around the corpus collosum identifies the left and right hemispheres. Together, the two hemispheres are mapped to the complex plane using a conformal mapping technique. A Mobius transformation, which is conformal, is used to transform the points on the complex plane so that a projective transformation maps each brain hemisphere onto a spherical segment comprising a sphere with a cap removed. We determined the best size of the spherical cap by minimizing the relative area distortion between hemispherical maps and original cortical surfaces. The relative area distortion between the hemispherical maps and the original cortical surfaces for fifteen human brains is analyzed.
Cerebral cartography and connectomics
Sporns, Olaf
2015-01-01
Cerebral cartography and connectomics pursue similar goals in attempting to create maps that can inform our understanding of the structural and functional organization of the cortex. Connectome maps explicitly aim at representing the brain as a complex network, a collection of nodes and their interconnecting edges. This article reflects on some of the challenges that currently arise in the intersection of cerebral cartography and connectomics. Principal challenges concern the temporal dynamics of functional brain connectivity, the definition of areal parcellations and their hierarchical organization into large-scale networks, the extension of whole-brain connectivity to cellular-scale networks, and the mapping of structure/function relations in empirical recordings and computational models. Successfully addressing these challenges will require extensions of methods and tools from network science to the mapping and analysis of human brain connectivity data. The emerging view that the brain is more than a collection of areas, but is fundamentally operating as a complex networked system, will continue to drive the creation of ever more detailed and multi-modal network maps as tools for on-going exploration and discovery in human connectomics. PMID:25823870
Mapping Informative Clusters in a Hierarchial Framework of fMRI Multivariate Analysis
Xu, Rui; Zhen, Zonglei; Liu, Jia
2010-01-01
Pattern recognition methods have become increasingly popular in fMRI data analysis, which are powerful in discriminating between multi-voxel patterns of brain activities associated with different mental states. However, when they are used in functional brain mapping, the location of discriminative voxels varies significantly, raising difficulties in interpreting the locus of the effect. Here we proposed a hierarchical framework of multivariate approach that maps informative clusters rather than voxels to achieve reliable functional brain mapping without compromising the discriminative power. In particular, we first searched for local homogeneous clusters that consisted of voxels with similar response profiles. Then, a multi-voxel classifier was built for each cluster to extract discriminative information from the multi-voxel patterns. Finally, through multivariate ranking, outputs from the classifiers were served as a multi-cluster pattern to identify informative clusters by examining interactions among clusters. Results from both simulated and real fMRI data demonstrated that this hierarchical approach showed better performance in the robustness of functional brain mapping than traditional voxel-based multivariate methods. In addition, the mapped clusters were highly overlapped for two perceptually equivalent object categories, further confirming the validity of our approach. In short, the hierarchical framework of multivariate approach is suitable for both pattern classification and brain mapping in fMRI studies. PMID:21152081
Spectral mapping of brain functional connectivity from diffusion imaging.
Becker, Cassiano O; Pequito, Sérgio; Pappas, George J; Miller, Michael B; Grafton, Scott T; Bassett, Danielle S; Preciado, Victor M
2018-01-23
Understanding the relationship between the dynamics of neural processes and the anatomical substrate of the brain is a central question in neuroscience. On the one hand, modern neuroimaging technologies, such as diffusion tensor imaging, can be used to construct structural graphs representing the architecture of white matter streamlines linking cortical and subcortical structures. On the other hand, temporal patterns of neural activity can be used to construct functional graphs representing temporal correlations between brain regions. Although some studies provide evidence that whole-brain functional connectivity is shaped by the underlying anatomy, the observed relationship between function and structure is weak, and the rules by which anatomy constrains brain dynamics remain elusive. In this article, we introduce a methodology to map the functional connectivity of a subject at rest from his or her structural graph. Using our methodology, we are able to systematically account for the role of structural walks in the formation of functional correlations. Furthermore, in our empirical evaluations, we observe that the eigenmodes of the mapped functional connectivity are associated with activity patterns associated with different cognitive systems.
The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture.
Fan, Lingzhong; Li, Hai; Zhuo, Junjie; Zhang, Yu; Wang, Jiaojian; Chen, Liangfu; Yang, Zhengyi; Chu, Congying; Xie, Sangma; Laird, Angela R; Fox, Peter T; Eickhoff, Simon B; Yu, Chunshui; Jiang, Tianzi
2016-08-01
The human brain atlases that allow correlating brain anatomy with psychological and cognitive functions are in transition from ex vivo histology-based printed atlases to digital brain maps providing multimodal in vivo information. Many current human brain atlases cover only specific structures, lack fine-grained parcellations, and fail to provide functionally important connectivity information. Using noninvasive multimodal neuroimaging techniques, we designed a connectivity-based parcellation framework that identifies the subdivisions of the entire human brain, revealing the in vivo connectivity architecture. The resulting human Brainnetome Atlas, with 210 cortical and 36 subcortical subregions, provides a fine-grained, cross-validated atlas and contains information on both anatomical and functional connections. Additionally, we further mapped the delineated structures to mental processes by reference to the BrainMap database. It thus provides an objective and stable starting point from which to explore the complex relationships between structure, connectivity, and function, and eventually improves understanding of how the human brain works. The human Brainnetome Atlas will be made freely available for download at http://atlas.brainnetome.org, so that whole brain parcellations, connections, and functional data will be readily available for researchers to use in their investigations into healthy and pathological states. © The Author 2016. Published by Oxford University Press.
Ogawa, Hiroshi; Kamada, Kyousuke; Kapeller, Christoph; Hiroshima, Satoru; Prueckl, Robert; Guger, Christoph
2014-11-01
Electrocortical stimulation (ECS) is the gold standard for functional brain mapping during an awake craniotomy. The critical issue is to set aside enough time to identify eloquent cortices by ECS. High gamma activity (HGA) ranging between 80 and 120 Hz on electrocorticogram is assumed to reflect localized cortical processing. In this report, we used real-time HGA mapping and functional neuronavigation integrated with functional magnetic resonance imaging (fMRI) for rapid and reliable identification of motor and language functions. Four patients with intra-axial tumors in their dominant hemisphere underwent preoperative fMRI and lesion resection with an awake craniotomy. All patients showed significant fMRI activation evoked by motor and language tasks. During the craniotomy, we recorded electrocorticogram activity by placing subdural grids directly on the exposed brain surface. Each patient performed motor and language tasks and demonstrated real-time HGA dynamics in hand motor areas and parts of the inferior frontal gyrus. Sensitivity and specificity of HGA mapping were 100% compared with ECS mapping in the frontal lobe, which suggested HGA mapping precisely indicated eloquent cortices. We found different HGA dynamics of language tasks in frontal and temporal regions. Specificities of the motor and language-fMRI did not reach 85%. The results of HGA mapping was mostly consistent with those of ECS mapping, although fMRI tended to overestimate functional areas. This novel technique enables rapid and accurate identification of motor and frontal language areas. Furthermore, real-time HGA mapping sheds light on underlying physiological mechanisms related to human brain functions. Copyright © 2014 Elsevier Inc. All rights reserved.
Mapping Resting-State Brain Networks in Conscious Animals
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
Correspondence of the brain's functional architecture during activation and rest
Smith, Stephen M.; Fox, Peter T.; Miller, Karla L.; Glahn, David C.; Fox, P. Mickle; Mackay, Clare E.; Filippini, Nicola; Watkins, Kate E.; Toro, Roberto; Laird, Angela R.; Beckmann, Christian F.
2009-01-01
Neural connections, providing the substrate for functional networks, exist whether or not they are functionally active at any given moment. However, it is not known to what extent brain regions are continuously interacting when the brain is “at rest.” In this work, we identify the major explicit activation networks by carrying out an image-based activation network analysis of thousands of separate activation maps derived from the BrainMap database of functional imaging studies, involving nearly 30,000 human subjects. Independently, we extract the major covarying networks in the resting brain, as imaged with functional magnetic resonance imaging in 36 subjects at rest. The sets of major brain networks, and their decompositions into subnetworks, show close correspondence between the independent analyses of resting and activation brain dynamics. We conclude that the full repertoire of functional networks utilized by the brain in action is continuously and dynamically “active” even when at “rest.” PMID:19620724
Researching and Reducing the Health Burden of Stroke
... the result of continuing research to map the brain and interface it with a computer to enable stroke patients to regain function. How important is the new effort to map the human brain? The brain is more complex than any computer ...
Cerebral cartography and connectomics.
Sporns, Olaf
2015-05-19
Cerebral cartography and connectomics pursue similar goals in attempting to create maps that can inform our understanding of the structural and functional organization of the cortex. Connectome maps explicitly aim at representing the brain as a complex network, a collection of nodes and their interconnecting edges. This article reflects on some of the challenges that currently arise in the intersection of cerebral cartography and connectomics. Principal challenges concern the temporal dynamics of functional brain connectivity, the definition of areal parcellations and their hierarchical organization into large-scale networks, the extension of whole-brain connectivity to cellular-scale networks, and the mapping of structure/function relations in empirical recordings and computational models. Successfully addressing these challenges will require extensions of methods and tools from network science to the mapping and analysis of human brain connectivity data. The emerging view that the brain is more than a collection of areas, but is fundamentally operating as a complex networked system, will continue to drive the creation of ever more detailed and multi-modal network maps as tools for on-going exploration and discovery in human connectomics. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
Clinical Impact and Implication of Real-Time Oscillation Analysis for Language Mapping.
Ogawa, Hiroshi; Kamada, Kyousuke; Kapeller, Christoph; Prueckl, Robert; Takeuchi, Fumiya; Hiroshima, Satoru; Anei, Ryogo; Guger, Christoph
2017-01-01
We developed a functional brain analysis system that enabled us to perform real-time task-related electrocorticography (ECoG) and evaluated its potential in clinical practice. We hypothesized that high gamma activity (HGA) mapping would provide better spatial and temporal resolution with high signal-to-noise ratios. Seven awake craniotomy patients were evaluated. ECoG was recorded during language tasks using subdural grids, and HGA (60-170 Hz) maps were obtained in real time. The patients also underwent electrocortical stimulation (ECS) mapping to validate the suspected functional locations on HGA mapping. The results were compared and calculated to assess the sensitivity and specificity of HGA mapping. For reference, bedside HGA-ECS mapping was performed in 5 epilepsy patients. HGA mapping demonstrated functional brain areas in real time and was comparable with ECS mapping. Sensitivity and specificity for the language area were 90.1% ± 11.2% and 90.0% ± 4.2%, respectively. Most HGA-positive areas were consistent with ECS-positive regions in both groups, and there were no statistical between-group differences. Although this study included a small number of subjects, it showed real-time HGA mapping with the same setting and tasks under different conditions. This study demonstrates the clinical feasibility of real-time HGA mapping. Real-time HGA mapping enabled simple and rapid detection of language functional areas in awake craniotomy. The mapping results were highly accurate, although the mapping environment was noisy. Further studies of HGA mapping may provide the potential to elaborate complex brain functions and networks. Copyright © 2016 Elsevier Inc. All rights reserved.
Event-related functional MRI: Past, present, and future
Rosen, Bruce R.; Buckner, Randy L.; Dale, Anders M.
1998-01-01
The past two decades have seen an enormous growth in the field of human brain mapping. Investigators have extensively exploited techniques such as positron emission tomography and MRI to map patterns of brain activity based on changes in cerebral hemodynamics. However, until recently, most studies have investigated equilibrium changes in blood flow measured over time periods upward of 1 min. The advent of high-speed MRI methods, capable of imaging the entire brain with a temporal resolution of a few seconds, allows for brain mapping based on more transient aspects of the hemodynamic response. Today it is now possible to map changes in cerebrovascular parameters essentially in real time, conferring the ability to observe changes in brain state that occur over time periods of seconds. Furthermore, because robust hemodynamic alterations are detectable after neuronal stimuli lasting only a few tens of milliseconds, a new class of task paradigms designed to measure regional responses to single sensory or cognitive events can now be studied. Such “event related” functional MRI should provide for fundamentally new ways to interrogate brain function, and allow for the direct comparison and ultimately integration of data acquired by using more traditional behavioral and electrophysiological methods. PMID:9448240
Zhang, Shengyu; Hu, Qiang; Tang, Tao; Liu, Chao; Li, Chengchong; Zang, Yin-Yin; Cai, Wei-Xiong
2018-06-13
BACKGROUND Using regional homogeneity (ReHo) blood oxygen level-dependent functional MR (BOLD-fMRI), we investigated the structural and functional alterations of brain regions among patients with methamphetamine-associated psychosis (MAP). MATERIAL AND METHODS This retrospective study included 17 MAP patients, 16 schizophrenia (SCZ) patients, and 18 healthy controls. Informed consent was obtained from all patients before the clinical assessment, the severity of clinical symptoms was evaluated prior to the fMRI scanning, and then images were acquired and preprocessed after each participant received 6-min fRMI scanning. The participants all underwent BOLD-fMRI scanning. Voxel-based morphometry was used to measure gray matter density (GMD). Resting-state fMRI (rs-fMRI) was conducted to analyze functional MR, ReHo, and functional connectivity (FC). RESULTS GMD analysis results suggest that MAP patients, SCZ patients, and healthy volunteers show different GMDs within different brain regions. Similarly, the ReHo analysis results suggest that MAP patients, SCZ patients, and healthy volunteers have different GMDs within different brain regions. Negative correlations were found between ReHo- and the PANSS-positive scores within the left orbital interior frontal gyrus (L-orb-IFG) of MAP patients. ReHo- and PANSS-negative scores of R-SFG were negatively correlated among SCZ patients. The abnormal FC of R-MFG showed a negative correlation with the PANSS score among MAP patients. CONCLUSIONS The abnormalities in brain structure and FC were associated with the development of MAP.
Susceptibility-based functional brain mapping by 3D deconvolution of an MR-phase activation map.
Chen, Zikuan; Liu, Jingyu; Calhoun, Vince D
2013-05-30
The underlying source of T2*-weighted magnetic resonance imaging (T2*MRI) for brain imaging is magnetic susceptibility (denoted by χ). T2*MRI outputs a complex-valued MR image consisting of magnitude and phase information. Recent research has shown that both the magnitude and the phase images are morphologically different from the source χ, primarily due to 3D convolution, and that the source χ can be reconstructed from complex MR images by computed inverse MRI (CIMRI). Thus, we can obtain a 4D χ dataset from a complex 4D MR dataset acquired from a brain functional MRI study by repeating CIMRI to reconstruct 3D χ volumes at each timepoint. Because the reconstructed χ is a more direct representation of neuronal activity than the MR image, we propose a method for χ-based functional brain mapping, which is numerically characterised by a temporal correlation map of χ responses to a stimulant task. Under the linear imaging conditions used for T2*MRI, we show that the χ activation map can be calculated from the MR phase map by CIMRI. We validate our approach using numerical simulations and Gd-phantom experiments. We also analyse real data from a finger-tapping visuomotor experiment and show that the χ-based functional mapping provides additional activation details (in the form of positive and negative correlation patterns) beyond those generated by conventional MR-magnitude-based mapping. Copyright © 2013 Elsevier B.V. All rights reserved.
Okamura-Oho, Yuko; Shimokawa, Kazuro; Nishimura, Masaomi; Takemoto, Satoko; Sato, Akira; Furuichi, Teiichi; Yokota, Hideo
2014-01-01
Using a recently invented technique for gene expression mapping in the whole-anatomy context, termed transcriptome tomography, we have generated a dataset of 36,000 maps of overall gene expression in the adult-mouse brain. Here, using an informatics approach, we identified a broad co-expression network that follows an inverse power law and is rich in functional interaction and gene-ontology terms. Our framework for the integrated analysis of expression maps and graphs of co-expression networks revealed that groups of combinatorially expressed genes, which regulate cell differentiation during development, were present in the adult brain and each of these groups was associated with a discrete cell types. These groups included non-coding genes of unknown function. We found that these genes specifically linked developmentally conserved groups in the network. A previously unrecognized robust expression pattern covering the whole brain was related to the molecular anatomy of key biological processes occurring in particular areas. PMID:25382412
Understanding brain networks and brain organization
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
Cooper, Leroy L; Himali, Jayandra J; Torjesen, Alyssa; Tsao, Connie W; Beiser, Alexa; Hamburg, Naomi M; DeCarli, Charles; Vasan, Ramachandran S; Seshadri, Sudha; Pase, Matthew P; Mitchell, Gary F
2017-08-17
Relations of orthostatic change in blood pressure with brain structure and function have not been studied thoroughly, particularly in younger, healthier individuals. Elucidation of factors that contribute to early changes in brain integrity may lead to development of interventions that delay or prevent cognitive impairment. In a sample of the Framingham Heart Study Third Generation (N=2119; 53% women; mean age±SD, 47±8 years), we assessed orthostatic change in mean arterial pressure (MAP), aortic stiffness (carotid-femoral pulse wave velocity), neuropsychological function, and markers of subclinical brain injury on magnetic resonance imaging. Multivariable regression analyses were used to assess relations between orthostatic change in MAP and brain structural and neuropsychological outcomes. Greater orthostatic increase in MAP on standing was related to better Trails B-A performance among participants aged <49 years (β±SE, 0.062±0.029; P =0.031) and among participants with carotid-femoral pulse wave velocity <6.9 m/s (β±SE, 0.063±0.026; P =0.016). This relation was not significant among participants who were older or had stiffer aortas. Conversely, greater orthostatic increase in MAP was related to larger total brain volume among older participants (β±SE, 0.065±0.029; P =0.023) and among participants with carotid-femoral pulse wave velocity ≥6.9 m/s (β±SE, 0.078±0.031; P =0.011). Blunted orthostatic increase in MAP was associated with smaller brain volume among participants who were older or had stiffer aortas and with poorer executive function among persons who were younger or who had more-elastic aortas. Our findings suggest that the brain is sensitive to orthostatic change in MAP, with results dependent on age and aortic stiffness. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.
Pallud, J; Mandonnet, E; Corns, R; Dezamis, E; Parraga, E; Zanello, M; Spena, G
2017-06-01
Intraoperative application of electrical current to the brain is a standard technique during brain surgery for inferring the function of the underlying brain. The purpose of intraoperative functional mapping is to reliably identify cortical areas and subcortical pathways involved in eloquent functions, especially motor, sensory, language and cognitive functions. The aim of this article is to review the rationale and the electrophysiological principles of the use of direct bipolar electrostimulation for cortical and subcortical mapping under awake conditions. Direct electrical stimulation is a window into the whole functional network that sustains a particular function. It is an accurate (spatial resolution of about 5mm) and a reproducible technique particularly adapted to clinical practice for brain resection in eloquent areas. If the procedure is rigorously applied, the sensitivity of direct electrical stimulation for the detection of cortical and subcortical eloquent areas is nearly 100%. The main disadvantage of this technique is its suboptimal specificity. Another limitation is the identification of eloquent areas during surgery, which, however, could have been functionally compensated postoperatively if removed surgically. Direct electrical stimulation is an easy, accurate, reliable and safe invasive technique for the intraoperative detection of both cortical and subcortical functional brain connectivity for clinical purpose. In our opinion, it is the optimal technique for minimizing the risk of neurological sequelae when resecting in eloquent brain areas. Copyright © 2017 Elsevier Masson SAS. All rights reserved.
Variability in Cortical Representations of Speech Sound Perception
ERIC Educational Resources Information Center
Boatman, Dana F.
2007-01-01
Recent brain mapping studies have provided new insights into the cortical systems that mediate human speech perception. Electrocortical stimulation mapping (ESM) is a brain mapping method that is used clinically to localize cortical functions in neurosurgical patients. Recent ESM studies have yielded new insights into the cortical systems that…
Functional Geometry Alignment and Localization of Brain Areas.
Langs, Georg; Golland, Polina; Tie, Yanmei; Rigolo, Laura; Golby, Alexandra J
2010-01-01
Matching functional brain regions across individuals is a challenging task, largely due to the variability in their location and extent. It is particularly difficult, but highly relevant, for patients with pathologies such as brain tumors, which can cause substantial reorganization of functional systems. In such cases spatial registration based on anatomical data is only of limited value if the goal is to establish correspondences of functional areas among different individuals, or to localize potentially displaced active regions. Rather than rely on spatial alignment, we propose to perform registration in an alternative space whose geometry is governed by the functional interaction patterns in the brain. We first embed each brain into a functional map that reflects connectivity patterns during a fMRI experiment. The resulting functional maps are then registered, and the obtained correspondences are propagated back to the two brains. In application to a language fMRI experiment, our preliminary results suggest that the proposed method yields improved functional correspondences across subjects. This advantage is pronounced for subjects with tumors that affect the language areas and thus cause spatial reorganization of the functional regions.
From blood oxygenation level dependent (BOLD) signals to brain temperature maps.
Sotero, Roberto C; Iturria-Medina, Yasser
2011-11-01
A theoretical framework is presented for converting Blood Oxygenation Level Dependent (BOLD) images to brain temperature maps, based on the idea that disproportional local changes in cerebral blood flow (CBF) as compared with cerebral metabolic rate of oxygen consumption (CMRO₂) during functional brain activity, lead to both brain temperature changes and the BOLD effect. Using an oxygen limitation model and a BOLD signal model, we obtain a transcendental equation relating CBF and CMRO₂ changes with the corresponding BOLD signal, which is solved in terms of the Lambert W function. Inserting this result in the dynamic bioheat equation describing the rate of temperature changes in the brain, we obtain a nonautonomous ordinary differential equation that depends on the BOLD response, which is solved numerically for each brain voxel. Temperature maps obtained from a real BOLD dataset registered in an attention to visual motion experiment were calculated, obtaining temperature variations in the range: (-0.15, 0.1) which is consistent with experimental results. The statistical analysis revealed that significant temperature activations have a similar distribution pattern than BOLD activations. An interesting difference was the activation of the precuneus in temperature maps, a region involved in visuospatial processing, an effect that was not observed on BOLD maps. Furthermore, temperature maps were more localized to gray matter regions than the original BOLD maps, showing less activated voxels in white matter and cerebrospinal fluid.
Whole Brain Functional Connectivity Pattern Homogeneity Mapping.
Wang, Lijie; Xu, Jinping; Wang, Chao; Wang, Jiaojian
2018-01-01
Mounting studies have demonstrated that brain functions are determined by its external functional connectivity patterns. However, how to characterize the voxel-wise similarity of whole brain functional connectivity pattern is still largely unknown. In this study, we introduced a new method called functional connectivity homogeneity (FcHo) to delineate the voxel-wise similarity of whole brain functional connectivity patterns. FcHo was defined by measuring the whole brain functional connectivity patterns similarity of a given voxel with its nearest 26 neighbors using Kendall's coefficient concordance (KCC). The robustness of this method was tested in four independent datasets selected from a large repository of MRI. Furthermore, FcHo mapping results were further validated using the nearest 18 and six neighbors and intra-subject reproducibility with each subject scanned two times. We also compared FcHo distribution patterns with local regional homogeneity (ReHo) to identify the similarity and differences of the two methods. Finally, FcHo method was used to identify the differences of whole brain functional connectivity patterns between professional Chinese chess players and novices to test its application. FcHo mapping consistently revealed that the high FcHo was mainly distributed in association cortex including parietal lobe, frontal lobe, occipital lobe and default mode network (DMN) related areas, whereas the low FcHo was mainly found in unimodal cortex including primary visual cortex, sensorimotor cortex, paracentral lobule and supplementary motor area. These results were further supported by analyses of the nearest 18 and six neighbors and intra-subject similarity. Moreover, FcHo showed both similar and different whole brain distribution patterns compared to ReHo. Finally, we demonstrated that FcHo can effectively identify the whole brain functional connectivity pattern differences between professional Chinese chess players and novices. Our findings indicated that FcHo is a reliable method to delineate the whole brain functional connectivity pattern similarity and may provide a new way to study the functional organization and to reveal neuropathological basis for brain disorders.
Ille, Sebastian; Drummer, Katharina; Giglhuber, Katrin; Conway, Neal; Maurer, Stefanie; Meyer, Bernhard; Krieg, Sandro M
2018-06-01
Preserving functionality is important during neurosurgical resection of brain tumors. Specialized centers also map further brain functions apart from motor and language functions, such as arithmetic processing (AP). The mapping of AP by navigated repetitive transcranial magnetic stimulation (nrTMS) in healthy volunteers has been reported. The present study aimed to correlate the results of mapping AP with functional patient outcomes. We included 26 patients with parietal brain tumors. Because of preoperative impairment of AP, mapping was not possible in 8 patients (31%). We stimulated 52 cortical sites by nrTMS while patients performed a calculation task. Preoperatively and postoperatively, patients underwent a standardized number-processing and calculation test (NPCT). Tumor resection was blinded to nrTMS results, and the change in NPCT performance was correlated to resected AP-positive spots as identified by nrTMS. The resection of AP-positive sites correlated with a worsening of the postoperative NPCT result in 12 cases. In 3 cases, no AP-positive sites were resected and the postoperative NPCT result was similar to or better than preoperatively. Also, in 3 cases, the postoperative NPCT result was better than preoperatively, although AP-positive sites were resected. Despite presenting only a few cases, nrTMS might be a useful tool for preoperative mapping of AP. However, the reliability of the present results has to be evaluated in a larger series and by intraoperative mapping data. Copyright © 2018 Elsevier Inc. All rights reserved.
From a meso- to micro-scale connectome: array tomography and mGRASP
Rah, Jong-Cheol; Feng, Linqing; Druckmann, Shaul; Lee, Hojin; Kim, Jinhyun
2015-01-01
Mapping mammalian synaptic connectivity has long been an important goal of neuroscience because knowing how neurons and brain areas are connected underpins an understanding of brain function. Meeting this goal requires advanced techniques with single synapse resolution and large-scale capacity, especially at multiple scales tethering the meso- and micro-scale connectome. Among several advanced LM-based connectome technologies, Array Tomography (AT) and mammalian GFP-Reconstitution Across Synaptic Partners (mGRASP) can provide relatively high-throughput mapping synaptic connectivity at multiple scales. AT- and mGRASP-assisted circuit mapping (ATing and mGRASPing), combined with techniques such as retrograde virus, brain clearing techniques, and activity indicators will help unlock the secrets of complex neural circuits. Here, we discuss these useful new tools to enable mapping of brain circuits at multiple scales, some functional implications of spatial synaptic distribution, and future challenges and directions of these endeavors. PMID:26089781
Duffau, H; Denvil, D; Capelle, L
2002-01-01
Objectives: To describe cortical reorganisation and the effects of glioma infiltration on local brain function in three patients who underwent two operations 12–24 months apart. Methods: Three patients who had no neurological deficit underwent two operations for low grade glioma, located in functionally important brain regions. During each operation, local brain function was characterised by electrical mapping and awake craniotomy. Results: Language or sensorimotor areas had been invaded by the tumour at the time of the first operation, leading to incomplete glioma removal in all cases. Because of a tumour recurrence, the patients were reoperated on between 12 and 24 months later. Functional reorganisation of the language, sensory, and motor maps was detected by electrical stimulation of the brain, and this allowed total glioma removal without neurological sequelae. Conclusions: These findings show that surgical resection of a glioma can lead to functional reorganisation in the peritumorous and infiltrated brain. It may be that this reorganisation is directly or indirectly caused by the surgical procedure. If this hypothesis is confirmed by other studies, the use of such brain plasticity potential could be used when planning surgical options in some patients with low grade glioma. Such a strategy could extend the limits of tumour resection in gliomas involving eloquent brain areas without causing permanent morbidity. PMID:11909913
ICA model order selection of task co-activation networks.
Ray, Kimberly L; McKay, D Reese; Fox, Peter M; Riedel, Michael C; Uecker, Angela M; Beckmann, Christian F; Smith, Stephen M; Fox, Peter T; Laird, Angela R
2013-01-01
Independent component analysis (ICA) has become a widely used method for extracting functional networks in the brain during rest and task. Historically, preferred ICA dimensionality has widely varied within the neuroimaging community, but typically varies between 20 and 100 components. This can be problematic when comparing results across multiple studies because of the impact ICA dimensionality has on the topology of its resultant components. Recent studies have demonstrated that ICA can be applied to peak activation coordinates archived in a large neuroimaging database (i.e., BrainMap Database) to yield whole-brain task-based co-activation networks. A strength of applying ICA to BrainMap data is that the vast amount of metadata in BrainMap can be used to quantitatively assess tasks and cognitive processes contributing to each component. In this study, we investigated the effect of model order on the distribution of functional properties across networks as a method for identifying the most informative decompositions of BrainMap-based ICA components. Our findings suggest dimensionality of 20 for low model order ICA to examine large-scale brain networks, and dimensionality of 70 to provide insight into how large-scale networks fractionate into sub-networks. We also provide a functional and organizational assessment of visual, motor, emotion, and interoceptive task co-activation networks as they fractionate from low to high model-orders.
ICA model order selection of task co-activation networks
Ray, Kimberly L.; McKay, D. Reese; Fox, Peter M.; Riedel, Michael C.; Uecker, Angela M.; Beckmann, Christian F.; Smith, Stephen M.; Fox, Peter T.; Laird, Angela R.
2013-01-01
Independent component analysis (ICA) has become a widely used method for extracting functional networks in the brain during rest and task. Historically, preferred ICA dimensionality has widely varied within the neuroimaging community, but typically varies between 20 and 100 components. This can be problematic when comparing results across multiple studies because of the impact ICA dimensionality has on the topology of its resultant components. Recent studies have demonstrated that ICA can be applied to peak activation coordinates archived in a large neuroimaging database (i.e., BrainMap Database) to yield whole-brain task-based co-activation networks. A strength of applying ICA to BrainMap data is that the vast amount of metadata in BrainMap can be used to quantitatively assess tasks and cognitive processes contributing to each component. In this study, we investigated the effect of model order on the distribution of functional properties across networks as a method for identifying the most informative decompositions of BrainMap-based ICA components. Our findings suggest dimensionality of 20 for low model order ICA to examine large-scale brain networks, and dimensionality of 70 to provide insight into how large-scale networks fractionate into sub-networks. We also provide a functional and organizational assessment of visual, motor, emotion, and interoceptive task co-activation networks as they fractionate from low to high model-orders. PMID:24339802
Hu, Yi; Wu, Yue; Tian, Kunlun; Lan, Dan; Chen, Xiangyun; Xue, Mingying; Liu, Liangming; Li, Tao
2015-05-01
Traumatic brain injury (TBI) is often associated with uncontrolled hemorrhagic shock (UHS), which contributes significantly to the mortality of severe trauma. Studies have demonstrated that permissive hypotension resuscitation improves the survival for uncontrolled hemorrhage. What the ideal target mean arterial pressure (MAP) is for TBI with UHS remains unclear. With the rat model of TBI in combination with UHS, we investigated the effects of a series of target resuscitation pressures (MAP from 50-90 mm Hg) on animal survival, brain perfusion, and organ function before hemorrhage controlled. Rats in 50-, 60-, and 70-mm Hg target MAP groups had less blood loss and less fluid requirement, a better vital organ including mitochondrial function and better cerebral blood flow, and animal survival (8, 6, and 7 of 10, respectively) than 80- and 90-mm Hg groups. The 70-mm Hg group had a better cerebral blood flow and cerebral mitochondrial function than in 50- and 60-mm Hg groups. In contrast, 80- and 90-mm Hg groups resulted in an excessive hemodilution, a decreased blood flow, an increased brain water content, and more severe cerebral edema. A 50-mm Hg target MAP is not suitable for the resuscitation of TBI combined with UHS. A 70 mm Hg of MAP is the ideal target resuscitation pressure for this trauma, which can keep sufficient perfusion to the brain and keep good organ function including cerebral mitochondrial function. Copyright © 2015 Elsevier Inc. All rights reserved.
Connectopic mapping with resting-state fMRI.
Haak, Koen V; Marquand, Andre F; Beckmann, Christian F
2018-04-15
Brain regions are often topographically connected: nearby locations within one brain area connect with nearby locations in another area. Mapping these connection topographies, or 'connectopies' in short, is crucial for understanding how information is processed in the brain. Here, we propose principled, fully data-driven methods for mapping connectopies using functional magnetic resonance imaging (fMRI) data acquired at rest by combining spectral embedding of voxel-wise connectivity 'fingerprints' with a novel approach to spatial statistical inference. We apply the approach in human primary motor and visual cortex, and show that it can trace biologically plausible, overlapping connectopies in individual subjects that follow these regions' somatotopic and retinotopic maps. As a generic mechanism to perform inference over connectopies, the new spatial statistics approach enables rigorous statistical testing of hypotheses regarding the fine-grained spatial profile of functional connectivity and whether that profile is different between subjects or between experimental conditions. The combined framework offers a fundamental alternative to existing approaches to investigating functional connectivity in the brain, from voxel- or seed-pair wise characterizations of functional association, towards a full, multivariate characterization of spatial topography. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Jiménez de la Peña, M; Gil Robles, S; Recio Rodríguez, M; Ruiz Ocaña, C; Martínez de Vega, V
2013-01-01
To describe the detection of cortical areas and subcortical pathways involved in language observed in MRI activation studies and tractography in a 3T MRI scanner and to correlate the findings of these functional studies with direct intraoperative cortical and subcortical stimulation. We present a series of 14 patients with focal brain tumors adjacent to eloquent brain areas. All patients underwent neuropsychological evaluation before and after surgery. All patients underwent MRI examination including structural sequences, perfusion imaging, spectroscopy, functional imaging to determine activation of motor and language areas, and 3D tractography. All patients underwent cortical mapping through cortical and subcortical stimulation during the operation to resect the tumor. Postoperative follow-up studies were done 24 hours after surgery. The correlation of motor function and of the corticospinal tract determined by functional MRI and tractography with intraoperative mapping of cortical and subcortical motor areas was complete. The eloquent brain areas of language expression and reception were strongly correlated with intraoperative cortical mapping in all but two cases (a high grade infiltrating glioma and a low grade glioma located in the frontal lobe). 3D tractography identified the arcuate fasciculus, the lateral part of the superior longitudinal fasciculus, the subcallosal fasciculus, the inferior fronto-occipital fasciculus, and the optic radiations, which made it possible to mark the limits of the resection. The correlation with the subcortical mapping of the anatomic arrangement of the fasciculi with respect to the lesions was complete. The best treatment for brain tumors is maximum resection without associated deficits, so high quality functional studies are necessary for preoperative planning. Copyright © 2011 SERAM. Published by Elsevier Espana. All rights reserved.
Language Mapping in Awake Surgery: Report of Two Cases with Review of Language Networks.
Lim, Liang Hooi; Idris, Zamzuri; Reza, Faruque; Wan Hassan, Wan Mohd Nazaruddin; Mukmin, Laila Abd; Abdullah, Jafri Malin
2018-01-01
The role of language in communication plays a crucial role in human development and function. In patients who have a surgical lesion at the functional language areas, surgery should be intricately planned to avoid incurring further morbidity. This normally requires extensive functional and anatomical mappings of the brain to identify regions that are involved in language processing and production. In our case report, regions of the brain that are important for language functions were studied before surgery by employing (a) extraoperative methods such as functional magnetic resonance imaging, transmagnetic stimulation, and magnetoencephalography; (b) during the surgery by utilizing intraoperative awake surgical methods such as an intraoperative electrical stimulation; and (c) a two-stage surgery, in which electrical stimulation and first mapping are made thoroughly in the ward before second remapping during surgery. The extraoperative methods before surgery can guide the neurosurgeon to localize the functional language regions and tracts preoperatively. This will be confirmed using single-stage intraoperative electrical brain stimulation during surgery or a two-stage electrical brain stimulation before and during surgery. Here, we describe two cases in whom one has a superficial lesion and another a deep-seated lesion at language-related regions, in which language mapping was done to preserve its function. Additional review on the neuroanatomy of language regions, language network, and its impairment was also described.
Conduction aphasia as a function of the dominant posterior perisylvian cortex. Report of two cases.
Quigg, Mark; Geldmacher, David S; Elias, W Jeff
2006-05-01
Assessment of eloquent functions during brain mapping usually relies on testing reading, speech, and comprehension to uncover transient deficits during electrical stimulation. These tests stem from findings predicted by the Geschwind-Wernicke hypothesis of receptive and expressive cortices connected by white matter tracts. Later work, however, has emphasized cortical mechanisms of language function. The authors report two cases that demonstrate that conduction aphasia is cortically mediated and can be inadequately assessed if not specifically evaluated during brain mapping. To determine the distribution of language on the dominant cortex, electrical cortical stimulation was performed in two cases by using implanted subdural electrodes during brain mapping before epilepsy surgery. A transient isolated deficit in repetition of language was reported during stimulation of the posterior portion of the dominant superior temporal gyrus in one patient and during stimulation of the supramarginal gyrus in the other patient. These cases demonstrate a localization of language repetition to the posterior perisylvian cortex. Brain mapping of this region should include assessment of verbal repetition to avoid potential deficits resembling conduction aphasia.
Awake surgery between art and science. Part II: language and cognitive mapping
Talacchi, Andrea; Santini, Barbara; Casartelli, Marilena; Monti, Alessia; Capasso, Rita; Miceli, Gabriele
Summary Direct cortical and subcortical stimulation has been claimed to be the gold standard for exploring brain function. In this field, efforts are now being made to move from intraoperative naming-assisted surgical resection towards the use of other language and cognitive tasks. However, before relying on new protocols and new techniques, we need a multi-staged system of evidence (low and high) relating to each step of functional mapping and its clinical validity. In this article we examine the possibilities and limits of brain mapping with the aid of a visual object naming task and various other tasks used to date. The methodological aspects of intraoperative brain mapping, as well as the clinical and operative settings, were discussed in Part I of this review. PMID:24139658
Korn, Akiva; Kirschner, Adi; Perry, Daniella; Hendler, Talma; Ram, Zvi
2017-01-01
Direct cortical stimulation (DCS) is considered the gold-standard for functional cortical mapping during awake surgery for brain tumor resection. DCS is performed by stimulating one local cortical area at a time. We present a feasibility study using an intra-operative technique aimed at improving our ability to map brain functions which rely on activity in distributed cortical regions. Following standard DCS, Multi-Site Stimulation (MSS) was performed in 15 patients by applying simultaneous cortical stimulations at multiple locations. Language functioning was chosen as a case-cognitive domain due to its relatively well-known cortical organization. MSS, performed at sites that did not produce disruption when applied in a single stimulation point, revealed additional language dysfunction in 73% of the patients. Functional regions identified by this technique were presumed to be significant to language circuitry and were spared during surgery. No new neurological deficits were observed in any of the patients following surgery. Though the neuro-electrical effects of MSS need further investigation, this feasibility study may provide a first step towards sophistication of intra-operative cortical mapping. PMID:28700619
Gonen, Tal; Gazit, Tomer; Korn, Akiva; Kirschner, Adi; Perry, Daniella; Hendler, Talma; Ram, Zvi
2017-01-01
Direct cortical stimulation (DCS) is considered the gold-standard for functional cortical mapping during awake surgery for brain tumor resection. DCS is performed by stimulating one local cortical area at a time. We present a feasibility study using an intra-operative technique aimed at improving our ability to map brain functions which rely on activity in distributed cortical regions. Following standard DCS, Multi-Site Stimulation (MSS) was performed in 15 patients by applying simultaneous cortical stimulations at multiple locations. Language functioning was chosen as a case-cognitive domain due to its relatively well-known cortical organization. MSS, performed at sites that did not produce disruption when applied in a single stimulation point, revealed additional language dysfunction in 73% of the patients. Functional regions identified by this technique were presumed to be significant to language circuitry and were spared during surgery. No new neurological deficits were observed in any of the patients following surgery. Though the neuro-electrical effects of MSS need further investigation, this feasibility study may provide a first step towards sophistication of intra-operative cortical mapping.
Genetic and Diagnostic Biomarker Development in ASD Toddlers Using Resting State Functional MRI
2015-09-01
for public release; distribution unlimited Autism spectrum disorder (ASD); biomarker; early brain development; intrinsic functional brain networks...three large neuroimaging/neurobehavioral datasets to identify brain-imaging based biomarkers for Autism Spectrum Disorders (ASD). At Yale, we focus...neurobehavioral!datasets!in!order!to!identify! brainFimaging!based!biomarkers!for! Autism ! Spectrum ! Disorders !(ASD),!including!1)!BrainMap,! developed!and
Klijn, Eva; Hulscher, Hester C; Balvers, Rutger K; Holland, Wim P J; Bakker, Jan; Vincent, Arnaud J P E; Dirven, Clemens M F; Ince, Can
2013-02-01
The goal of awake neurosurgery is to maximize resection of brain lesions with minimal injury to functional brain areas. Laser speckle imaging (LSI) is a noninvasive macroscopic technique with high spatial and temporal resolution used to monitor changes in capillary perfusion. In this study, the authors hypothesized that LSI can be useful as a noncontact method of functional brain mapping during awake craniotomy for tumor removal. Such a modality would be an advance in this type of neurosurgery since current practice involves the application of invasive intraoperative single-point electrocortical (electrode) stimulation and measurements. After opening the dura mater, patients were woken up, and LSI was set up to image the exposed brain area. Patients were instructed to follow a rest-activation-rest protocol in which activation consisted of the hand-clenching motor task. Subsequently, exposed brain areas were mapped for functional motor areas by using standard electrocortical stimulation (ECS). Changes in the LSI signal were analyzed offline and compared with the results of ECS. In functional motor areas of the hand mapped with ECS, cortical blood flow measured using LSI significantly increased from 2052 ± 818 AU to 2471 ± 675 AU during hand clenching, whereas capillary blood flow did not change in the control regions (areas mapped using ECS with no functional activity). The main finding of this study was that changes in laser speckle perfusion as a measure of cortical microvascular blood flow when performing a motor task with the hand relate well to the ECS map. The authors have shown the feasibility of using LSI for direct visualization of cortical microcirculatory blood flow changes during neurosurgery.
Li, Yun; Wang, Shengpei; Pan, Chuxiong; Xue, Fushan; Xian, Junfang; Huang, Yaqi; Wang, Xiaoyi; Li, Tianzuo; He, Huiguang
2018-01-01
The mechanism of general anesthesia (GA) has been explored for hundreds of years, but unclear. Previous studies indicated a possible correlation between NREM sleep and GA. The purpose of this study is to compare them by in vivo human brain function to probe the neuromechanism of consciousness, so as to find out a clue to GA mechanism. 24 healthy participants were equally assigned to sleep or propofol sedation group by sleeping ability. EEG and Ramsay Sedation Scale were applied to determine sleep stage and sedation depth respectively. Resting-state functional magnetic resonance imaging (RS-fMRI) was acquired at each status. Regional homogeneity (ReHo) and seed-based whole brain functional connectivity maps (WB-FC maps) were compared. During sleep, ReHo primarily weakened on frontal lobe (especially preoptic area), but strengthened on brainstem. While during sedation, ReHo changed in various brain areas, including cingulate, precuneus, thalamus and cerebellum. Cingulate, fusiform and insula were concomitance of sleep and sedation. Comparing to sleep, FCs between the cortex and subcortical centers (centralized in cerebellum) were significantly attenuated under sedation. As sedation deepening, cerebellum-based FC maps were diminished, while thalamus- and brainstem-based FC maps were increased. There're huge distinctions in human brain function between sleep and GA. Sleep mainly rely on brainstem and frontal lobe function, while sedation is prone to affect widespread functional network. The most significant differences exist in the precuneus and cingulate, which may play important roles in mechanisms of inducing unconciousness by anesthetics. Institutional Review Board (IRB) ChiCTR-IOC-15007454.
Resting State Network Estimation in Individual Subjects
Hacker, Carl D.; Laumann, Timothy O.; Szrama, Nicholas P.; Baldassarre, Antonello; Snyder, Abraham Z.
2014-01-01
Resting-state functional magnetic resonance imaging (fMRI) has been used to study brain networks associated with both normal and pathological cognitive function. The objective of this work is to reliably compute resting state network (RSN) topography in single participants. We trained a supervised classifier (multi-layer perceptron; MLP) to associate blood oxygen level dependent (BOLD) correlation maps corresponding to pre-defined seeds with specific RSN identities. Hard classification of maps obtained from a priori seeds was highly reliable across new participants. Interestingly, continuous estimates of RSN membership retained substantial residual error. This result is consistent with the view that RSNs are hierarchically organized, and therefore not fully separable into spatially independent components. After training on a priori seed-based maps, we propagated voxel-wise correlation maps through the MLP to produce estimates of RSN membership throughout the brain. The MLP generated RSN topography estimates in individuals consistent with previous studies, even in brain regions not represented in the training data. This method could be used in future studies to relate RSN topography to other measures of functional brain organization (e.g., task-evoked responses, stimulation mapping, and deficits associated with lesions) in individuals. The multi-layer perceptron was directly compared to two alternative voxel classification procedures, specifically, dual regression and linear discriminant analysis; the perceptron generated more spatially specific RSN maps than either alternative. PMID:23735260
Images Are Not the (Only) Truth: Brain Mapping, Visual Knowledge, and Iconoclasm.
ERIC Educational Resources Information Center
Beaulieu, Anne
2002-01-01
Debates the paradoxical nature of claims about the emerging contributions of functional brain mapping. Examines the various ways that images are deployed and rejected and highlights an approach that provides insight into the current demarcation of imaging. (Contains 68 references.) (DDR)
Combining task-evoked and spontaneous activity to improve pre-operative brain mapping with fMRI
Fox, Michael D.; Qian, Tianyi; Madsen, Joseph R.; Wang, Danhong; Li, Meiling; Ge, Manling; Zuo, Huan-cong; Groppe, David M.; Mehta, Ashesh D.; Hong, Bo; Liu, Hesheng
2016-01-01
Noninvasive localization of brain function is used to understand and treat neurological disease, exemplified by pre-operative fMRI mapping prior to neurosurgical intervention. The principal approach for generating these maps relies on brain responses evoked by a task and, despite known limitations, has dominated clinical practice for over 20 years. Recently, pre-operative fMRI mapping based on correlations in spontaneous brain activity has been demonstrated, however this approach has its own limitations and has not seen widespread clinical use. Here we show that spontaneous and task-based mapping can be performed together using the same pre-operative fMRI data, provide complimentary information relevant for functional localization, and can be combined to improve identification of eloquent motor cortex. Accuracy, sensitivity, and specificity of our approach are quantified through comparison with electrical cortical stimulation mapping in eight patients with intractable epilepsy. Broad applicability and reproducibility of our approach is demonstrated through prospective replication in an independent dataset of six patients from a different center. In both cohorts and every individual patient, we see a significant improvement in signal to noise and mapping accuracy independent of threshold, quantified using receiver operating characteristic curves. Collectively, our results suggest that modifying the processing of fMRI data to incorporate both task-based and spontaneous activity significantly improves functional localization in pre-operative patients. Because this method requires no additional scan time or modification to conventional pre-operative data acquisition protocols it could have widespread utility. PMID:26408860
Tate, Matthew C; Herbet, Guillaume; Moritz-Gasser, Sylvie; Tate, Joseph E; Duffau, Hugues
2014-10-01
The organization of basic functions of the human brain, particularly in the right hemisphere, remains poorly understood. Recent advances in functional neuroimaging have improved our understanding of cortical organization but do not allow for direct interrogation or determination of essential (versus participatory) cortical regions. Direct cortical stimulation represents a unique opportunity to provide novel insights into the functional distribution of critical epicentres. Direct cortical stimulation (bipolar, 60 Hz, 1-ms pulse) was performed in 165 consecutive patients undergoing awake mapping for resection of low-grade gliomas. Tasks included motor, sensory, counting, and picture naming. Stimulation sites eliciting positive (sensory/motor) or negative (speech arrest, dysarthria, anomia, phonological and semantic paraphasias) findings were recorded and mapped onto a standard Montreal Neurological Institute brain atlas. Montreal Neurological Institute-space functional data were subjected to cluster analysis algorithms (K-means, partition around medioids, hierarchical Ward) to elucidate crucial network epicentres. Sensorimotor function was observed in the pre/post-central gyri as expected. Articulation epicentres were also found within the pre/post-central gyri. However, speech arrest localized to ventral premotor cortex, not the classical Broca's area. Anomia/paraphasia data demonstrated foci not only within classical Wernicke's area but also within the middle and inferior frontal gyri. We report the first bilateral probabilistic map for crucial cortical epicentres of human brain functions in the right and left hemispheres, including sensory, motor, and language (speech, articulation, phonology and semantics). These data challenge classical theories of brain organization (e.g. Broca's area as speech output region) and provide a distributed framework for future studies of neural networks. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Optogenetic mapping of brain circuitry
NASA Astrophysics Data System (ADS)
Augustine, George J.; Berglund, Ken; Gill, Harin; Hoffmann, Carolin; Katarya, Malvika; Kim, Jinsook; Kudolo, John; Lee, Li M.; Lee, Molly; Lo, Daniel; Nakajima, Ryuichi; Park, Min Yoon; Tan, Gregory; Tang, Yanxia; Teo, Peggy; Tsuda, Sachiko; Wen, Lei; Yoon, Su-In
2012-10-01
Studies of the brain promise to be revolutionized by new experimental strategies that harness the combined power of optical techniques and genetics. We have mapped the circuitry of the mouse brain by using both optogenetic actuators that control neuronal activity and optogenetic sensors that detect neuronal activity. Using the light-activated cation channel, channelrhodopsin-2, to locally photostimulate neurons allows high-speed mapping of local and long-range circuitry. For example, with this approach we have mapped local circuits in the cerebral cortex, cerebellum and many other brain regions. Using the fluorescent sensor for chloride ions, Clomeleon, allows imaging of the spatial and temporal dimensions of inhibitory circuits in the brain. This approach allows imaging of both conventional "phasic" synaptic inhibition as well as unconventional "tonic" inhibition. The combined use of light to both control and monitor neural activity creates unprecedented opportunities to explore brain function, screen pharmaceutical agents, and potentially to use light to ameliorate psychiatric and neurological disorders.
Mapping Functional Brain Development: Building a Social Brain through Interactive Specialization
ERIC Educational Resources Information Center
Johnson, Mark H.; Grossmann, Tobias; Kadosh, Kathrin Cohen
2009-01-01
The authors review a viewpoint on human functional brain development, interactive specialization (IS), and its application to the emerging network of cortical regions referred to as the "social brain." They advance the IS view in 2 new ways. First, they extend IS into a domain to which it has not previously been applied--the emergence of social…
Mapping Multiplex Hubs in Human Functional Brain Networks
De Domenico, Manlio; Sasai, Shuntaro; Arenas, Alex
2016-01-01
Typical brain networks consist of many peripheral regions and a few highly central ones, i.e., hubs, playing key functional roles in cerebral inter-regional interactions. Studies have shown that networks, obtained from the analysis of specific frequency components of brain activity, present peculiar architectures with unique profiles of region centrality. However, the identification of hubs in networks built from different frequency bands simultaneously is still a challenging problem, remaining largely unexplored. Here we identify each frequency component with one layer of a multiplex network and face this challenge by exploiting the recent advances in the analysis of multiplex topologies. First, we show that each frequency band carries unique topological information, fundamental to accurately model brain functional networks. We then demonstrate that hubs in the multiplex network, in general different from those ones obtained after discarding or aggregating the measured signals as usual, provide a more accurate map of brain's most important functional regions, allowing to distinguish between healthy and schizophrenic populations better than conventional network approaches. PMID:27471443
Pan, Chuxiong; Xue, Fushan; Xian, Junfang; Huang, Yaqi; Wang, Xiaoyi; He, Huiguang
2018-01-01
Background The mechanism of general anesthesia (GA) has been explored for hundreds of years, but unclear. Previous studies indicated a possible correlation between NREM sleep and GA. The purpose of this study is to compare them by in vivo human brain function to probe the neuromechanism of consciousness, so as to find out a clue to GA mechanism. Methods 24 healthy participants were equally assigned to sleep or propofol sedation group by sleeping ability. EEG and Ramsay Sedation Scale were applied to determine sleep stage and sedation depth respectively. Resting-state functional magnetic resonance imaging (RS-fMRI) was acquired at each status. Regional homogeneity (ReHo) and seed-based whole brain functional connectivity maps (WB-FC maps) were compared. Results During sleep, ReHo primarily weakened on frontal lobe (especially preoptic area), but strengthened on brainstem. While during sedation, ReHo changed in various brain areas, including cingulate, precuneus, thalamus and cerebellum. Cingulate, fusiform and insula were concomitance of sleep and sedation. Comparing to sleep, FCs between the cortex and subcortical centers (centralized in cerebellum) were significantly attenuated under sedation. As sedation deepening, cerebellum-based FC maps were diminished, while thalamus- and brainstem-based FC maps were increased. Conclusion There’re huge distinctions in human brain function between sleep and GA. Sleep mainly rely on brainstem and frontal lobe function, while sedation is prone to affect widespread functional network. The most significant differences exist in the precuneus and cingulate, which may play important roles in mechanisms of inducing unconciousness by anesthetics. Trial registration Institutional Review Board (IRB) ChiCTR-IOC-15007454. PMID:29486001
Blood pressure, brain structure, and cognition: opposite associations in men and women.
Cherbuin, Nicolas; Mortby, Moyra E; Janke, Andrew L; Sachdev, Perminder S; Abhayaratna, Walter P; Anstey, Kaarin J
2015-02-01
Research on associations between blood pressure, brain structure, and cognitive function has produced somewhat inconsistent results. In part, this may be due to differences in age ranges studied and because of sex differences in physiology and/or exposure to risk factors, which may lead to different time course or patterns in cardiovascular disease progression. The aim of this study was to investigate the impact of sex on associations between blood pressure, regional cerebral volumes, and cognitive function in older individuals. In this cohort study, brachial blood pressure was measured twice at rest in 266 community-based individuals free of dementia aged 68-73 years who had also undergone a brain scan and a neuropsychological assessment. Associations between mean blood pressure (MAP), regional brain volumes, and cognition were investigated with voxel-wise regression analyses. Positive associations between MAP and regional volumes were detected in men, whereas negative associations were found in women. Similarly, there were sex differences in the brain-volume cognition relationship, with a positive relationship between regional brain volumes associated with MAP in men and a negative relationship in women. In this cohort of older individuals, higher MAP was associated with larger regional volume and better cognition in men, whereas opposite findings were demonstrated in women. These effects may be due to different lifetime risk exposure or because of physiological differences between men and women. Future studies investigating the relationship between blood pressure and brain structure or cognitive function should evaluate the potential for differential sex effects. © American Journal of Hypertension, Ltd 2014. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Wig, Gagan S.; Laumann, Timothy O.; Cohen, Alexander L.; Power, Jonathan D.; Nelson, Steven M.; Glasser, Matthew F.; Miezin, Francis M.; Snyder, Abraham Z.; Schlaggar, Bradley L.; Petersen, Steven E.
2014-01-01
We describe methods for parcellating an individual subject's cortical and subcortical brain structures using resting-state functional correlations (RSFCs). Inspired by approaches from social network analysis, we first describe the application of snowball sampling on RSFC data (RSFC-Snowballing) to identify the centers of cortical areas, subdivisions of subcortical nuclei, and the cerebellum. RSFC-Snowballing parcellation is then compared with parcellation derived from identifying locations where RSFC maps exhibit abrupt transitions (RSFC-Boundary Mapping). RSFC-Snowballing and RSFC-Boundary Mapping largely complement one another, but also provide unique parcellation information; together, the methods identify independent entities with distinct functional correlations across many cortical and subcortical locations in the brain. RSFC parcellation is relatively reliable within a subject scanned across multiple days, and while the locations of many area centers and boundaries appear to exhibit considerable overlap across subjects, there is also cross-subject variability—reinforcing the motivation to parcellate brains at the level of individuals. Finally, examination of a large meta-analysis of task-evoked functional magnetic resonance imaging data reveals that area centers defined by task-evoked activity exhibit correspondence with area centers defined by RSFC-Snowballing. This observation provides important evidence for the ability of RSFC to parcellate broad expanses of an individual's brain into functionally meaningful units. PMID:23476025
Evans, Alan C; Janke, Andrew L; Collins, D Louis; Baillet, Sylvain
2012-08-15
The core concept within the field of brain mapping is the use of a standardized, or "stereotaxic", 3D coordinate frame for data analysis and reporting of findings from neuroimaging experiments. This simple construct allows brain researchers to combine data from many subjects such that group-averaged signals, be they structural or functional, can be detected above the background noise that would swamp subtle signals from any single subject. Where the signal is robust enough to be detected in individuals, it allows for the exploration of inter-individual variance in the location of that signal. From a larger perspective, it provides a powerful medium for comparison and/or combination of brain mapping findings from different imaging modalities and laboratories around the world. Finally, it provides a framework for the creation of large-scale neuroimaging databases or "atlases" that capture the population mean and variance in anatomical or physiological metrics as a function of age or disease. However, while the above benefits are not in question at first order, there are a number of conceptual and practical challenges that introduce second-order incompatibilities among experimental data. Stereotaxic mapping requires two basic components: (i) the specification of the 3D stereotaxic coordinate space, and (ii) a mapping function that transforms a 3D brain image from "native" space, i.e. the coordinate frame of the scanner at data acquisition, to that stereotaxic space. The first component is usually expressed by the choice of a representative 3D MR image that serves as target "template" or atlas. The native image is re-sampled from native to stereotaxic space under the mapping function that may have few or many degrees of freedom, depending upon the experimental design. The optimal choice of atlas template and mapping function depend upon considerations of age, gender, hemispheric asymmetry, anatomical correspondence, spatial normalization methodology and disease-specificity. Accounting, or not, for these various factors in defining stereotaxic space has created the specter of an ever-expanding set of atlases, customized for a particular experiment, that are mutually incompatible. These difficulties continue to plague the brain mapping field. This review article summarizes the evolution of stereotaxic space in term of the basic principles and associated conceptual challenges, the creation of population atlases and the future trends that can be expected in atlas evolution. Copyright © 2012 Elsevier Inc. All rights reserved.
A comprehensive neuropsychological mapping battery for functional magnetic resonance imaging.
Karakas, Sirel; Baran, Zeynel; Ceylan, Arzu Ozkan; Tileylioglu, Emre; Tali, Turgut; Karakas, Hakki Muammer
2013-11-01
Existing batteries for FMRI do not precisely meet the criteria for comprehensive mapping of cognitive functions within minimum data acquisition times using standard scanners and head coils. The goal was to develop a battery of neuropsychological paradigms for FMRI that can also be used in other brain imaging techniques and behavioural research. Participants were 61 healthy, young adult volunteers (48 females and 13 males, mean age: 22.25 ± 3.39 years) from the university community. The battery included 8 paradigms for basic (visual, auditory, sensory-motor, emotional arousal) and complex (language, working memory, inhibition/interference control, learning) cognitive functions. Imaging was performed using standard functional imaging capabilities (1.5-T MR scanner, standard head coil). Structural and functional data series were analysed using Brain Voyager QX2.9 and Statistical Parametric Mapping-8. For basic processes, activation centres for individuals were within a distance of 3-11 mm of the group centres of the target regions and for complex cognitive processes, between 7 mm and 15 mm. Based on fixed-effect and random-effects analyses, the distance between the activation centres was 0-4 mm. There was spatial variability between individual cases; however, as shown by the distances between the centres found with fixed-effect and random-effects analyses, the coordinates for individual cases can be used to represent those of the group. The findings show that the neuropsychological brain mapping battery described here can be used in basic science studies that investigate the relationship of the brain to the mind and also as functional localiser in clinical studies for diagnosis, follow-up and pre-surgical mapping. © 2013.
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.
Green, Adam E; Kraemer, David J M; Fugelsang, Jonathan A; Gray, Jeremy R; Dunbar, Kevin N
2010-01-01
Solving problems often requires seeing new connections between concepts or events that seemed unrelated at first. Innovative solutions of this kind depend on analogical reasoning, a relational reasoning process that involves mapping similarities between concepts. Brain-based evidence has implicated the frontal pole of the brain as important for analogical mapping. Separately, cognitive research has identified semantic distance as a key characteristic of the kind of analogical mapping that can support innovation (i.e., identifying similarities across greater semantic distance reveals connections that support more innovative solutions and models). However, the neural substrates of semantically distant analogical mapping are not well understood. Here, we used functional magnetic resonance imaging (fMRI) to measure brain activity during an analogical reasoning task, in which we parametrically varied the semantic distance between the items in the analogies. Semantic distance was derived quantitatively from latent semantic analysis. Across 23 participants, activity in an a priori region of interest (ROI) in left frontopolar cortex covaried parametrically with increasing semantic distance, even after removing effects of task difficulty. This ROI was centered on a functional peak that we previously associated with analogical mapping. To our knowledge, these data represent a first empirical characterization of how the brain mediates semantically distant analogical mapping.
On testing for spatial correspondence between maps of human brain structure and function.
Alexander-Bloch, Aaron F; Shou, Haochang; Liu, Siyuan; Satterthwaite, Theodore D; Glahn, David C; Shinohara, Russell T; Vandekar, Simon N; Raznahan, Armin
2018-06-01
A critical issue in many neuroimaging studies is the comparison between brain maps. Nonetheless, it remains unclear how one should test hypotheses focused on the overlap or spatial correspondence between two or more brain maps. This "correspondence problem" affects, for example, the interpretation of comparisons between task-based patterns of functional activation, resting-state networks or modules, and neuroanatomical landmarks. To date, this problem has been addressed with remarkable variability in terms of methodological approaches and statistical rigor. In this paper, we address the correspondence problem using a spatial permutation framework to generate null models of overlap by applying random rotations to spherical representations of the cortical surface, an approach for which we also provide a theoretical statistical foundation. We use this method to derive clusters of cognitive functions that are correlated in terms of their functional neuroatomical substrates. In addition, using publicly available data, we formally demonstrate the correspondence between maps of task-based functional activity, resting-state fMRI networks and gyral-based anatomical landmarks. We provide open-access code to implement the methods presented for two commonly-used tools for surface based cortical analysis (https://www.github.com/spin-test). This spatial permutation approach constitutes a useful advance over widely-used methods for the comparison of cortical maps, thereby opening new possibilities for the integration of diverse neuroimaging data. Copyright © 2018 Elsevier Inc. All rights reserved.
Connectivity and functional profiling of abnormal brain structures in pedophilia
Poeppl, Timm B.; Eickhoff, Simon B.; Fox, Peter T.; Laird, Angela R.; Rupprecht, Rainer; Langguth, Berthold; Bzdok, Danilo
2015-01-01
Despite its 0.5–1% lifetime prevalence in men and its general societal relevance, neuroimaging investigations in pedophilia are scarce. Preliminary findings indicate abnormal brain structure and function. However, no study has yet linked structural alterations in pedophiles to both connectional and functional properties of the aberrant hotspots. The relationship between morphological alterations and brain function in pedophilia as well as their contribution to its psychopathology thus remain unclear. First, we assessed bimodal connectivity of structurally altered candidate regions using meta-analytic connectivity modeling (MACM) and resting-state correlations employing openly accessible data. We compared the ensuing connectivity maps to the activation likelihood estimation (ALE) maps of a recent quantitative meta-analysis of brain activity during processing of sexual stimuli. Second, we functionally characterized the structurally altered regions employing meta-data of a large-scale neuroimaging database. Candidate regions were functionally connected to key areas for processing of sexual stimuli. Moreover, we found that the functional role of structurally altered brain regions in pedophilia relates to nonsexual emotional as well as neurocognitive and executive functions, previously reported to be impaired in pedophiles. Our results suggest that structural brain alterations affect neural networks for sexual processing by way of disrupted functional connectivity, which may entail abnormal sexual arousal patterns. The findings moreover indicate that structural alterations account for common affective and neurocognitive impairments in pedophilia. The present multi-modal integration of brain structure and function analyses links sexual and nonsexual psychopathology in pedophilia. PMID:25733379
Connectivity and functional profiling of abnormal brain structures in pedophilia.
Poeppl, Timm B; Eickhoff, Simon B; Fox, Peter T; Laird, Angela R; Rupprecht, Rainer; Langguth, Berthold; Bzdok, Danilo
2015-06-01
Despite its 0.5-1% lifetime prevalence in men and its general societal relevance, neuroimaging investigations in pedophilia are scarce. Preliminary findings indicate abnormal brain structure and function. However, no study has yet linked structural alterations in pedophiles to both connectional and functional properties of the aberrant hotspots. The relationship between morphological alterations and brain function in pedophilia as well as their contribution to its psychopathology thus remain unclear. First, we assessed bimodal connectivity of structurally altered candidate regions using meta-analytic connectivity modeling (MACM) and resting-state correlations employing openly accessible data. We compared the ensuing connectivity maps to the activation likelihood estimation (ALE) maps of a recent quantitative meta-analysis of brain activity during processing of sexual stimuli. Second, we functionally characterized the structurally altered regions employing meta-data of a large-scale neuroimaging database. Candidate regions were functionally connected to key areas for processing of sexual stimuli. Moreover, we found that the functional role of structurally altered brain regions in pedophilia relates to nonsexual emotional as well as neurocognitive and executive functions, previously reported to be impaired in pedophiles. Our results suggest that structural brain alterations affect neural networks for sexual processing by way of disrupted functional connectivity, which may entail abnormal sexual arousal patterns. The findings moreover indicate that structural alterations account for common affective and neurocognitive impairments in pedophilia. The present multimodal integration of brain structure and function analyses links sexual and nonsexual psychopathology in pedophilia. © 2015 Wiley Periodicals, Inc.
Constructing fine-granularity functional brain network atlases via deep convolutional autoencoder.
Zhao, Yu; Dong, Qinglin; Chen, Hanbo; Iraji, Armin; Li, Yujie; Makkie, Milad; Kou, Zhifeng; Liu, Tianming
2017-12-01
State-of-the-art functional brain network reconstruction methods such as independent component analysis (ICA) or sparse coding of whole-brain fMRI data can effectively infer many thousands of volumetric brain network maps from a large number of human brains. However, due to the variability of individual brain networks and the large scale of such networks needed for statistically meaningful group-level analysis, it is still a challenging and open problem to derive group-wise common networks as network atlases. Inspired by the superior spatial pattern description ability of the deep convolutional neural networks (CNNs), a novel deep 3D convolutional autoencoder (CAE) network is designed here to extract spatial brain network features effectively, based on which an Apache Spark enabled computational framework is developed for fast clustering of larger number of network maps into fine-granularity atlases. To evaluate this framework, 10 resting state networks (RSNs) were manually labeled from the sparsely decomposed networks of Human Connectome Project (HCP) fMRI data and 5275 network training samples were obtained, in total. Then the deep CAE models are trained by these functional networks' spatial maps, and the learned features are used to refine the original 10 RSNs into 17 network atlases that possess fine-granularity functional network patterns. Interestingly, it turned out that some manually mislabeled outliers in training networks can be corrected by the deep CAE derived features. More importantly, fine granularities of networks can be identified and they reveal unique network patterns specific to different brain task states. By further applying this method to a dataset of mild traumatic brain injury study, it shows that the technique can effectively identify abnormal small networks in brain injury patients in comparison with controls. In general, our work presents a promising deep learning and big data analysis solution for modeling functional connectomes, with fine granularities, based on fMRI data. Copyright © 2017 Elsevier B.V. All rights reserved.
Analysis of multiplex gene expression maps obtained by voxelation.
An, Li; Xie, Hongbo; Chin, Mark H; Obradovic, Zoran; Smith, Desmond J; Megalooikonomou, Vasileios
2009-04-29
Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we present an approach for identifying the relation between gene expression maps obtained by voxelation and gene functions. To analyze the dataset, we chose typical genes as queries and aimed at discovering similar gene groups. Gene similarity was determined by using the wavelet features extracted from the left and right hemispheres averaged gene expression maps, and by the Euclidean distance between each pair of feature vectors. We also performed a multiple clustering approach on the gene expression maps, combined with hierarchical clustering. Among each group of similar genes and clusters, the gene function similarity was measured by calculating the average gene function distances in the gene ontology structure. By applying our methodology to find similar genes to certain target genes we were able to improve our understanding of gene expression patterns and gene functions. By applying the clustering analysis method, we obtained significant clusters, which have both very similar gene expression maps and very similar gene functions respectively to their corresponding gene ontologies. The cellular component ontology resulted in prominent clusters expressed in cortex and corpus callosum. The molecular function ontology gave prominent clusters in cortex, corpus callosum and hypothalamus. The biological process ontology resulted in clusters in cortex, hypothalamus and choroid plexus. Clusters from all three ontologies combined were most prominently expressed in cortex and corpus callosum. The experimental results confirm the hypothesis that genes with similar gene expression maps might have similar gene functions. The voxelation data takes into account the location information of gene expression level in mouse brain, which is novel in related research. The proposed approach can potentially be used to predict gene functions and provide helpful suggestions to biologists.
Multimodal connectivity of motor learning-related dorsal premotor cortex.
Hardwick, Robert M; Lesage, Elise; Eickhoff, Claudia R; Clos, Mareike; Fox, Peter; Eickhoff, Simon B
2015-12-01
The dorsal premotor cortex (dPMC) is a key region for motor learning and sensorimotor integration, yet we have limited understanding of its functional interactions with other regions. Previous work has started to examine functional connectivity in several brain areas using resting state functional connectivity (RSFC) and meta-analytical connectivity modelling (MACM). More recently, structural covariance (SC) has been proposed as a technique that may also allow delineation of functional connectivity. Here, we applied these three approaches to provide a comprehensive characterization of functional connectivity with a seed in the left dPMC that a previous meta-analysis of functional neuroimaging studies has identified as playing a key role in motor learning. Using data from two sources (the Rockland sample, containing resting state data and anatomical scans from 132 participants, and the BrainMap database, which contains peak activation foci from over 10,000 experiments), we conducted independent whole-brain functional connectivity mapping analyses of a dPMC seed. RSFC and MACM revealed similar connectivity maps spanning prefrontal, premotor, and parietal regions, while the SC map identified more widespread frontal regions. Analyses indicated a relatively consistent pattern of functional connectivity between RSFC and MACM that was distinct from that identified by SC. Notably, results indicate that the seed is functionally connected to areas involved in visuomotor control and executive functions, suggesting that the dPMC acts as an interface between motor control and cognition. Copyright © 2015 Elsevier Inc. All rights reserved.
Analyzing and Assessing Brain Structure with Graph Connectivity Measures
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
Structure-Function Network Mapping and Its Assessment via Persistent Homology
2017-01-01
Understanding the relationship between brain structure and function is a fundamental problem in network neuroscience. This work deals with the general method of structure-function mapping at the whole-brain level. We formulate the problem as a topological mapping of structure-function connectivity via matrix function, and find a stable solution by exploiting a regularization procedure to cope with large matrices. We introduce a novel measure of network similarity based on persistent homology for assessing the quality of the network mapping, which enables a detailed comparison of network topological changes across all possible thresholds, rather than just at a single, arbitrary threshold that may not be optimal. We demonstrate that our approach can uncover the direct and indirect structural paths for predicting functional connectivity, and our network similarity measure outperforms other currently available methods. We systematically validate our approach with (1) a comparison of regularized vs. non-regularized procedures, (2) a null model of the degree-preserving random rewired structural matrix, (3) different network types (binary vs. weighted matrices), and (4) different brain parcellation schemes (low vs. high resolutions). Finally, we evaluate the scalability of our method with relatively large matrices (2514x2514) of structural and functional connectivity obtained from 12 healthy human subjects measured non-invasively while at rest. Our results reveal a nonlinear structure-function relationship, suggesting that the resting-state functional connectivity depends on direct structural connections, as well as relatively parsimonious indirect connections via polysynaptic pathways. PMID:28046127
Connectome analysis for pre-operative brain mapping in neurosurgery
Hart, Michael G.; Price, Stephen J.; Suckling, John
2016-01-01
Abstract Object: Brain mapping has entered a new era focusing on complex network connectivity. Central to this is the search for the connectome or the brains ‘wiring diagram’. Graph theory analysis of the connectome allows understanding of the importance of regions to network function, and the consequences of their impairment or excision. Our goal was to apply connectome analysis in patients with brain tumours to characterise overall network topology and individual patterns of connectivity alterations. Methods: Resting-state functional MRI data were acquired using multi-echo, echo planar imaging pre-operatively from five participants each with a right temporal–parietal–occipital glioblastoma. Complex networks analysis was initiated by parcellating the brain into anatomically regions amongst which connections were identified by retaining the most significant correlations between the respective wavelet decomposed time-series. Results: Key characteristics of complex networks described in healthy controls were preserved in these patients, including ubiquitous small world organization. An exponentially truncated power law fit to the degree distribution predicted findings of general network robustness to injury but with a core of hubs exhibiting disproportionate vulnerability. Tumours produced a consistent reduction in local and long-range connectivity with distinct patterns of connection loss depending on lesion location. Conclusions: Connectome analysis is a feasible and novel approach to brain mapping in individual patients with brain tumours. Applications to pre-surgical planning include identifying regions critical to network function that should be preserved and visualising connections at risk from tumour resection. In the future one could use such data to model functional plasticity and recovery of cognitive deficits. PMID:27447756
Assessing Variations in Areal Organization for the Intrinsic Brain: From Fingerprints to Reliability
Xu, Ting; Opitz, Alexander; Craddock, R. Cameron; Wright, Margaret J.; Zuo, Xi-Nian; Milham, Michael P.
2016-01-01
Resting state fMRI (R-fMRI) is a powerful in-vivo tool for examining the functional architecture of the human brain. Recent studies have demonstrated the ability to characterize transitions between functionally distinct cortical areas through the mapping of gradients in intrinsic functional connectivity (iFC) profiles. To date, this novel approach has primarily been applied to iFC profiles averaged across groups of individuals, or in one case, a single individual scanned multiple times. Here, we used a publically available R-fMRI dataset, in which 30 healthy participants were scanned 10 times (10 min per session), to investigate differences in full-brain transition profiles (i.e., gradient maps, edge maps) across individuals, and their reliability. 10-min R-fMRI scans were sufficient to achieve high accuracies in efforts to “fingerprint” individuals based upon full-brain transition profiles. Regarding test–retest reliability, the image-wise intraclass correlation coefficient (ICC) was moderate, and vertex-level ICC varied depending on region; larger durations of data yielded higher reliability scores universally. Initial application of gradient-based methodologies to a recently published dataset obtained from twins suggested inter-individual variation in areal profiles might have genetic and familial origins. Overall, these results illustrate the utility of gradient-based iFC approaches for studying inter-individual variation in brain function. PMID:27600846
Wig, Gagan S; Laumann, Timothy O; Cohen, Alexander L; Power, Jonathan D; Nelson, Steven M; Glasser, Matthew F; Miezin, Francis M; Snyder, Abraham Z; Schlaggar, Bradley L; Petersen, Steven E
2014-08-01
We describe methods for parcellating an individual subject's cortical and subcortical brain structures using resting-state functional correlations (RSFCs). Inspired by approaches from social network analysis, we first describe the application of snowball sampling on RSFC data (RSFC-Snowballing) to identify the centers of cortical areas, subdivisions of subcortical nuclei, and the cerebellum. RSFC-Snowballing parcellation is then compared with parcellation derived from identifying locations where RSFC maps exhibit abrupt transitions (RSFC-Boundary Mapping). RSFC-Snowballing and RSFC-Boundary Mapping largely complement one another, but also provide unique parcellation information; together, the methods identify independent entities with distinct functional correlations across many cortical and subcortical locations in the brain. RSFC parcellation is relatively reliable within a subject scanned across multiple days, and while the locations of many area centers and boundaries appear to exhibit considerable overlap across subjects, there is also cross-subject variability-reinforcing the motivation to parcellate brains at the level of individuals. Finally, examination of a large meta-analysis of task-evoked functional magnetic resonance imaging data reveals that area centers defined by task-evoked activity exhibit correspondence with area centers defined by RSFC-Snowballing. This observation provides important evidence for the ability of RSFC to parcellate broad expanses of an individual's brain into functionally meaningful units. © The Author 2013. Published by Oxford University Press.
Minati, Ludovico; Cercignani, Mara; Chan, Dennis
2013-10-01
Graph theory-based analyses of brain network topology can be used to model the spatiotemporal correlations in neural activity detected through fMRI, and such approaches have wide-ranging potential, from detection of alterations in preclinical Alzheimer's disease through to command identification in brain-machine interfaces. However, due to prohibitive computational costs, graph-based analyses to date have principally focused on measuring connection density rather than mapping the topological architecture in full by exhaustive shortest-path determination. This paper outlines a solution to this problem through parallel implementation of Dijkstra's algorithm in programmable logic. The processor design is optimized for large, sparse graphs and provided in full as synthesizable VHDL code. An acceleration factor between 15 and 18 is obtained on a representative resting-state fMRI dataset, and maps of Euclidean path length reveal the anticipated heterogeneous cortical involvement in long-range integrative processing. These results enable high-resolution geodesic connectivity mapping for resting-state fMRI in patient populations and real-time geodesic mapping to support identification of imagined actions for fMRI-based brain-machine interfaces. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.
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.
Functional brain microstate predicts the outcome in a visuospatial working memory task.
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.
Using Immediate-Early Genes to Map Hippocampal Subregional Functions
ERIC Educational Resources Information Center
Kubik, Stepan; Miyashita, Teiko; Guzowski, John F.
2007-01-01
Different functions have been suggested for the hippocampus and its subdivisions along both transversal and longitudinal axes. Expression of immediate-early genes (IEGs) has been used to map specific functions onto neuronal activity in different areas of the brain including the hippocampus (IEG imaging). Here we review IEG studies on hippocampal…
Regional anatomy of the pedunculopontine nucleus: relevance for deep brain stimulation.
Fournier-Gosselin, Marie-Pierre; Lipsman, Nir; Saint-Cyr, Jean A; Hamani, Clement; Lozano, Andres M
2013-09-01
The pedunculopontine nucleus (PPN) is currently being investigated as a potential deep brain stimulation target to improve gait and posture in Parkinson's disease. This review examines the complex anatomy of the PPN region and suggests a functional mapping of the surrounding nuclei and fiber tracts that may serve as a guide to a more accurate placement of electrodes while avoiding potentially adverse effects. The relationships of the PPN were examined in different human brain atlases. Schematic representations of those structures in the vicinity of the PPN were generated and correlated with their potential stimulation effects. By providing a functional map and representative schematics of the PPN region, we hope to optimize the placement of deep brain stimulation electrodes, thereby maximizing safety and clinical efficacy. © 2013 International Parkinson and Movement Disorder Society.
Quantitative Susceptibility Mapping of Human Brain Reflects Spatial Variation in Tissue Composition
Li, Wei; Wu, Bing; Liu, Chunlei
2011-01-01
Image phase from gradient echo MRI provides a unique contrast that reflects brain tissue composition variations, such as iron and myelin distribution. Phase imaging is emerging as a powerful tool for the investigation of functional brain anatomy and disease diagnosis. However, the quantitative value of phase is compromised by its nonlocal and orientation dependent properties. There is an increasing need for reliable quantification of magnetic susceptibility, the intrinsic property of tissue. In this study, we developed a novel and accurate susceptibility mapping method that is also phase-wrap insensitive. The proposed susceptibility mapping method utilized two complementary equations: (1) the Fourier relationship of phase and magnetic susceptibility; and (2) the first-order partial derivative of the first equation in the spatial frequency domain. In numerical simulation, this method reconstructed the susceptibility map almost free of streaking artifact. Further, the iterative implementation of this method allowed for high quality reconstruction of susceptibility maps of human brain in vivo. The reconstructed susceptibility map provided excellent contrast of iron-rich deep nuclei and white matter bundles from surrounding tissues. Further, it also revealed anisotropic magnetic susceptibility in brain white matter. Hence, the proposed susceptibility mapping method may provide a powerful tool for the study of brain physiology and pathophysiology. Further elucidation of anisotropic magnetic susceptibility in vivo may allow us to gain more insight into the white matter microarchitectures. PMID:21224002
Brain Mapping in a Patient with Congenital Blindness – A Case for Multimodal Approaches
Roland, Jarod L.; Hacker, Carl D.; Breshears, Jonathan D.; Gaona, Charles M.; Hogan, R. Edward; Burton, Harold; Corbetta, Maurizio; Leuthardt, Eric C.
2013-01-01
Recent advances in basic neuroscience research across a wide range of methodologies have contributed significantly to our understanding of human cortical electrophysiology and functional brain imaging. Translation of this research into clinical neurosurgery has opened doors for advanced mapping of functionality that previously was prohibitively difficult, if not impossible. Here we present the case of a unique individual with congenital blindness and medically refractory epilepsy who underwent neurosurgical treatment of her seizures. Pre-operative evaluation presented the challenge of accurately and robustly mapping the cerebral cortex for an individual with a high probability of significant cortical re-organization. Additionally, a blind individual has unique priorities in one’s ability to read Braille by touch and sense the environment primarily by sound than the non-vision impaired person. For these reasons we employed additional measures to map sensory, motor, speech, language, and auditory perception by employing a number of cortical electrophysiologic mapping and functional magnetic resonance imaging methods. Our data show promising results in the application of these adjunctive methods in the pre-operative mapping of otherwise difficult to localize, and highly variable, functional cortical areas. PMID:23914170
Functional magnetic resonance imaging.
Buchbinder, Bradley R
2016-01-01
Functional magnetic resonance imaging (fMRI) maps the spatiotemporal distribution of neural activity in the brain under varying cognitive conditions. Since its inception in 1991, blood oxygen level-dependent (BOLD) fMRI has rapidly become a vital methodology in basic and applied neuroscience research. In the clinical realm, it has become an established tool for presurgical functional brain mapping. This chapter has three principal aims. First, we review key physiologic, biophysical, and methodologic principles that underlie BOLD fMRI, regardless of its particular area of application. These principles inform a nuanced interpretation of the BOLD fMRI signal, along with its neurophysiologic significance and pitfalls. Second, we illustrate the clinical application of task-based fMRI to presurgical motor, language, and memory mapping in patients with lesions near eloquent brain areas. Integration of BOLD fMRI and diffusion tensor white-matter tractography provides a road map for presurgical planning and intraoperative navigation that helps to maximize the extent of lesion resection while minimizing the risk of postoperative neurologic deficits. Finally, we highlight several basic principles of resting-state fMRI and its emerging translational clinical applications. Resting-state fMRI represents an important paradigm shift, focusing attention on functional connectivity within intrinsic cognitive networks. © 2016 Elsevier B.V. All rights reserved.
Nanotools for Neuroscience and Brain Activity Mapping
Alivisatos, A. Paul; Andrews, Anne M.; Boyden, Edward S.; Chun, Miyoung; Church, George M.; Deisseroth, Karl; Donoghue, John P.; Fraser, Scott E.; Lippincott-Schwartz, Jennifer; Looger, Loren L.; Masmanidis, Sotiris; McEuen, Paul L.; Nurmikko, Arto V.; Park, Hongkun; Peterka, Darcy S.; Reid, Clay; Roukes, Michael L.; Scherer, Axel; Schnitzer, Mark; Sejnowski, Terrence J.; Shepard, Kenneth L.; Tsao, Doris; Turrigiano, Gina; Weiss, Paul S.; Xu, Chris; Yuste, Rafael; Zhuang, Xiaowei
2013-01-01
Neuroscience is at a crossroads. Great effort is being invested into deciphering specific neural interactions and circuits. At the same time, there exist few general theories or principles that explain brain function. We attribute this disparity, in part, to limitations in current methodologies. Traditional neurophysiological approaches record the activities of one neuron or a few neurons at a time. Neurochemical approaches focus on single neurotransmitters. Yet, there is an increasing realization that neural circuits operate at emergent levels, where the interactions between hundreds or thousands of neurons, utilizing multiple chemical transmitters, generate functional states. Brains function at the nanoscale, so tools to study brains must ultimately operate at this scale, as well. Nanoscience and nanotechnology are poised to provide a rich toolkit of novel methods to explore brain function by enabling simultaneous measurement and manipulation of activity of thousands or even millions of neurons. We and others refer to this goal as the Brain Activity Mapping Project. In this Nano Focus, we discuss how recent developments in nanoscale analysis tools and in the design and synthesis of nanomaterials have generated optical, electrical, and chemical methods that can readily be adapted for use in neuroscience. These approaches represent exciting areas of technical development and research. Moreover, unique opportunities exist for nanoscientists, nanotechnologists, and other physical scientists and engineers to contribute to tackling the challenging problems involved in understanding the fundamentals of brain function. PMID:23514423
Bassett, Danielle S; Sporns, Olaf
2017-01-01
Despite substantial recent progress, our understanding of the principles and mechanisms underlying complex brain function and cognition remains incomplete. Network neuroscience proposes to tackle these enduring challenges. Approaching brain structure and function from an explicitly integrative perspective, network neuroscience pursues new ways to map, record, analyze and model the elements and interactions of neurobiological systems. Two parallel trends drive the approach: the availability of new empirical tools to create comprehensive maps and record dynamic patterns among molecules, neurons, brain areas and social systems; and the theoretical framework and computational tools of modern network science. The convergence of empirical and computational advances opens new frontiers of scientific inquiry, including network dynamics, manipulation and control of brain networks, and integration of network processes across spatiotemporal domains. We review emerging trends in network neuroscience and attempt to chart a path toward a better understanding of the brain as a multiscale networked system. PMID:28230844
Interpreting fMRI data: maps, modules and dimensions
Op de Beeck, Hans P.; Haushofer, Johannes; Kanwisher, Nancy G.
2009-01-01
Neuroimaging research over the past decade has revealed a detailed picture of the functional organization of the human brain. Here we focus on two fundamental questions that are raised by the detailed mapping of sensory and cognitive functions and illustrate these questions with findings from the object-vision pathway. First, are functionally specific regions that are located close together best understood as distinct cortical modules or as parts of a larger-scale cortical map? Second, what functional properties define each cortical map or module? We propose a model in which overlapping continuous maps of simple features give rise to discrete modules that are selective for complex stimuli. PMID:18200027
Mechanism of orientation of stimulating currents in magnetic brain stimulation (abstract)
NASA Astrophysics Data System (ADS)
Ueno, S.; Matsuda, T.
1991-04-01
We made a functional map of the human motor cortex related to the hand and foot areas by stimulating the human brain with a focused magnetic pulse. We observed that each functional area in the cortex has an optimum direction for which stimulating currents can produce neural excitation. The present report focuses on the mechanism which is responsible for producing this anisotropic response to brain stimulation. We first obtained a functional map of the brain related to the left ADM (abductor digiti minimi muscles). When the stimulating currents were aligned in the direction from the left to the right hemisphere, clear EMG (electromyographic) responses were obtained only from the left ADM to magnetic stimulation of both hemisphere. When the stimulating currents were aligned in the direction from the right to the left hemisphere, clear EMG signals were obtained only from the right ADM to magnetic stimulation of both hemisphere. The functional maps of the brain were sensitive to changes in the direction of the stimulating currents. To explain the phenomena obtained in the experiments, we developed a model of neural excitation elicited by magnetic stimulation. When eddy currents which are induced by pulsed magnetic fields flow in the direction from soma to the distal part of neural fiber, depolarized area in the distal part are excited, and the membrane excitation propagates along the nerve fiber. In contrast, when the induced currents flow in the direction from the distal part to soma, hyperpolarized parts block or inhibit neural excitation even if the depolarized parts near the soma can be excited. The model explains our observation that the orientation of the induced current vectors reflect both the functional and anatomical organization of the neural fibers in the brain.
Anomalous brain functional connectivity contributing to poor adaptive behavior in Down syndrome.
Pujol, Jesus; del Hoyo, Laura; Blanco-Hinojo, Laura; de Sola, Susana; Macià, Dídac; Martínez-Vilavella, Gerard; Amor, Marta; Deus, Joan; Rodríguez, Joan; Farré, Magí; Dierssen, Mara; de la Torre, Rafael
2015-03-01
Research in Down syndrome has substantially progressed in the understanding of the effect of gene overexpression at the molecular level, but there is a paucity of information on the ultimate consequences on overall brain functional organization. We have assessed the brain functional status in Down syndrome using functional connectivity MRI. Resting-state whole-brain connectivity degree maps were generated in 20 Down syndrome individuals and 20 control subjects to identify sites showing anomalous synchrony with other areas. A subsequent region-of-interest mapping served to detail the anomalies and to assess their potential contribution to poor adaptive behavior. Down syndrome individuals showed higher regional connectivity in a ventral brain system involving the amygdala/anterior temporal region and the ventral aspect of both the anterior cingulate and frontal cortices. By contrast, lower functional connectivity was identified in dorsal executive networks involving dorsal prefrontal and anterior cingulate cortices and posterior insula. Both functional connectivity increases and decreases contributed to account for patient scoring on adaptive behavior related to communication skills. The data overall suggest a distinctive functional organization with system-specific anomalies associated with reduced adaptive efficiency. Opposite effects were identified on distinct frontal and anterior temporal structures and relative sparing of posterior brain areas, which is generally consistent with Down syndrome cognitive profile. Relevantly, measurable connectivity changes, as a marker of the brain functional anomaly, could have a role in the development of therapeutic strategies addressed to improve the quality of life in Down syndrome individuals. Copyright © 2014 Elsevier Ltd. All rights reserved.
Rezakova, M V; Mazhirina, K G; Pokrovskiy, M A; Savelov, A A; Savelova, O A; Shtark, M B
2013-04-01
Using functional magnetic resonance imaging technique, we performed online brain mapping of gamers, practiced to voluntary (cognitively) control their heart rate, the parameter that operated a competitive virtual gameplay in the adaptive feedback loop. With the default start picture, the regions of interest during the formation of optimal cognitive strategy were as follows: Brodmann areas 19, 37, 39 and 40, i.e. cerebellar structures (vermis, amygdala, pyramids, clivus). "Localization" concept of the contribution of the cerebellum to cognitive processes is discussed.
Tan, Francisca M; Caballero-Gaudes, César; Mullinger, Karen J; Cho, Siu-Yeung; Zhang, Yaping; Dryden, Ian L; Francis, Susan T; Gowland, Penny A
2017-11-01
Most functional MRI (fMRI) studies map task-driven brain activity using a block or event-related paradigm. Sparse paradigm free mapping (SPFM) can detect the onset and spatial distribution of BOLD events in the brain without prior timing information, but relating the detected events to brain function remains a challenge. In this study, we developed a decoding method for SPFM using a coordinate-based meta-analysis method of activation likelihood estimation (ALE). We defined meta-maps of statistically significant ALE values that correspond to types of events and calculated a summation overlap between the normalized meta-maps and SPFM maps. As a proof of concept, this framework was applied to relate SPFM-detected events in the sensorimotor network (SMN) to six motor functions (left/right fingers, left/right toes, swallowing, and eye blinks). We validated the framework using simultaneous electromyography (EMG)-fMRI experiments and motor tasks with short and long duration, and random interstimulus interval. The decoding scores were considerably lower for eye movements relative to other movement types tested. The average successful rate for short and long motor events were 77 ± 13% and 74 ± 16%, respectively, excluding eye movements. We found good agreement between the decoding results and EMG for most events and subjects, with a range in sensitivity between 55% and 100%, excluding eye movements. The proposed method was then used to classify the movement types of spontaneous single-trial events in the SMN during resting state, which produced an average successful rate of 22 ± 12%. Finally, this article discusses methodological implications and improvements to increase the decoding performance. Hum Brain Mapp 38:5778-5794, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Kura, Sreekanth; Xie, Hongyu; Fu, Buyin; Ayata, Cenk; Boas, David A; Sakadžić, Sava
2018-06-01
Resting state functional connectivity (RSFC) allows the study of functional organization in normal and diseased brain by measuring the spontaneous brain activity generated under resting conditions. Intrinsic optical signal imaging (IOSI) based on multiple illumination wavelengths has been used successfully to compute RSFC maps in animal studies. The IOSI setup complexity would be greatly reduced if only a single wavelength can be used to obtain comparable RSFC maps. We used anesthetized mice and performed various comparisons between the RSFC maps based on single wavelength as well as oxy-, deoxy- and total hemoglobin concentration changes. The RSFC maps based on IOSI at a single wavelength selected for sensitivity to the blood volume changes are quantitatively comparable to the RSFC maps based on oxy- and total hemoglobin concentration changes obtained by the more complex IOSI setups. Moreover, RSFC maps do not require CCD cameras with very high frame acquisition rates, since our results demonstrate that they can be computed from the data obtained at frame rates as low as 5 Hz. Our results will have general utility for guiding future RSFC studies based on IOSI and making decisions about the IOSI system designs.
Zavaglia, Melissa; Forkert, Nils D.; Cheng, Bastian; Gerloff, Christian; Thomalla, Götz; Hilgetag, Claus C.
2015-01-01
Lesion analysis reveals causal contributions of brain regions to mental functions, aiding the understanding of normal brain function as well as rehabilitation of brain-damaged patients. We applied a novel lesion inference technique based on game theory, Multi-perturbation Shapley value Analysis (MSA), to a large clinical lesion dataset. We used MSA to analyze the lesion patterns of 148 acute stroke patients together with their neurological deficits, as assessed by the National Institutes of Health Stroke Scale (NIHSS). The results revealed regional functional contributions to essential behavioral and cognitive functions as reflected in the NIHSS, particularly by subcortical structures. There were also side specific differences of functional contributions between the right and left hemispheric brain regions which may reflect the dominance of the left hemispheric syndrome aphasia in the NIHSS. Comparison of MSA to established lesion inference methods demonstrated the feasibility of the approach for analyzing clinical data and indicated its capability for objectively inferring functional contributions from multiple injured, potentially interacting sites, at the cost of having to predict the outcome of unknown lesion configurations. The analysis of regional functional contributions to neurological symptoms measured by the NIHSS contributes to the interpretation of this widely used standardized stroke scale in clinical practice as well as clinical trials and provides a first approximation of a ‘map of stroke’. PMID:26448908
Zavaglia, Melissa; Forkert, Nils D; Cheng, Bastian; Gerloff, Christian; Thomalla, Götz; Hilgetag, Claus C
2015-01-01
Lesion analysis reveals causal contributions of brain regions to mental functions, aiding the understanding of normal brain function as well as rehabilitation of brain-damaged patients. We applied a novel lesion inference technique based on game theory, Multi-perturbation Shapley value Analysis (MSA), to a large clinical lesion dataset. We used MSA to analyze the lesion patterns of 148 acute stroke patients together with their neurological deficits, as assessed by the National Institutes of Health Stroke Scale (NIHSS). The results revealed regional functional contributions to essential behavioral and cognitive functions as reflected in the NIHSS, particularly by subcortical structures. There were also side specific differences of functional contributions between the right and left hemispheric brain regions which may reflect the dominance of the left hemispheric syndrome aphasia in the NIHSS. Comparison of MSA to established lesion inference methods demonstrated the feasibility of the approach for analyzing clinical data and indicated its capability for objectively inferring functional contributions from multiple injured, potentially interacting sites, at the cost of having to predict the outcome of unknown lesion configurations. The analysis of regional functional contributions to neurological symptoms measured by the NIHSS contributes to the interpretation of this widely used standardized stroke scale in clinical practice as well as clinical trials and provides a first approximation of a 'map of stroke'.
Neshige, Shuichiro; Matsuhashi, Masao; Kobayashi, Katsuya; Sakurai, Takeyo; Shimotake, Akihiro; Hitomi, Takefumi; Kikuchi, Takayuki; Yoshida, Kazumichi; Kunieda, Takeharu; Matsumoto, Riki; Takahashi, Ryosuke; Miyamoto, Susumu; Maruyama, Hirofumi; Matsumoto, Masayasu; Ikeda, Akio
2018-06-18
To assess the feasibility of multi-component electrocorticography (ECoG)-based mapping using "wide-spectrum, intrinsic-brain activities" for identifying the primary sensori-motor area (S1-M1) by comparing that using electrical cortical stimulation (ECS). We evaluated 14 epilepsy patients with 1514 subdural electrodes implantation covering the perirolandic cortices at Kyoto University Hospital between 2011 and 2016. We performed multi-component, ECoG-based mapping (band-pass filter, 0.016-300/600 Hz) involving combined analyses of the single components: movement-related cortical potential (<0.5-1 Hz), event-related synchronization (76-200 Hz), and event-related de-synchronization (8-24 Hz) to identify the S1-M1. The feasibility of multi-component mapping was assessed through comparisons with single-component mapping and ECS. Among 54 functional areas evaluation, ECoG-based maps showed significantly higher rate of localization concordances with ECS maps when the three single-component maps were consistent than when those were inconsistent with each other (p < 0.001 in motor, and p = 0.02 in sensory mappings). Multi-component mapping revealed high sensitivity (89-90%) and specificity (94-97%) as compared with ECS. Wide-spectrum, multi-component ECoG-based mapping is feasible, having high sensitivity/specificity relative to ECS. This safe (non-stimulus) mapping strategy, alternative to ECS, would allow clinicians to rule in/out the possibility of brain function prior to resection surgery. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.
From chemotaxis to the cognitive map: The function of olfaction
Jacobs, Lucia F.
2012-01-01
A paradox of vertebrate brain evolution is the unexplained variability in the size of the olfactory bulb (OB), in contrast to other brain regions, which scale predictably with brain size. Such variability appears to be the result of selection for olfactory function, yet there is no obvious concordance that would predict the causal relationship between OB size and behavior. This discordance may derive from assuming the primary function of olfaction is odorant discrimination and acuity. If instead the primary function of olfaction is navigation, i.e., predicting odorant distributions in time and space, variability in absolute OB size could be ascribed and explained by variability in navigational demand. This olfactory spatial hypothesis offers a single functional explanation to account for patterns of olfactory system scaling in vertebrates, the primacy of olfaction in spatial navigation, even in visual specialists, and proposes an evolutionary scenario to account for the convergence in olfactory structure and function across protostomes and deuterostomes. In addition, the unique percepts of olfaction may organize odorant information in a parallel map structure. This could have served as a scaffold for the evolution of the parallel map structure of the mammalian hippocampus, and possibly the arthropod mushroom body, and offers an explanation for similar flexible spatial navigation strategies in arthropods and vertebrates. PMID:22723365
Forthergillian Lecture. Imaging human brain function.
Frackowiak, R S
The non-invasive brain scanning techniques introduced a quarter of a century ago have become crucial for diagnosis in clinical neurology. They have also been used to investigate brain function and have provided information about normal activity and pathogenesis. They have been used to investigate functional specialization in the brain and how specialized areas communicate to generate complex integrated functions such as speech, memory, the emotions and so on. The phenomenon of brain plasticity is poorly understood and yet clinical neurologists are aware, from everyday observations, that spontaneous recovery from brain lesions is common. An improved understanding of the mechanisms of recovery may generate new therapeutic strategies and indicate ways of modulating mechanisms that promote plastic compensation for loss of function. The main methods used to investigate these issues are positron emission tomography and magnetic resonance imaging (M.R.I.). M.R.I. is also used to map brain structure. The techniques of functional brain mapping and computational morphometrics depend on high performance scanners and a validated set of analytic statistical procedures that generate reproducible data and meaningful inferences from brain scanning data. The motor system presents a good paradigm to illustrate advances made by scanning towards an understanding of plasticity at the level of brain areas. The normal motor system is organized in a nested hierarchy. Recovery from paralysis caused by internal capsule strokes involves functional reorganization manifesting itself as changed patterns of activity in the component brain areas of the normal motor system. The pattern of plastic modification depends in part on patterns of residual or disturbed connectivity after brain injury. Therapeutic manipulations in patients with Parkinson's disease using deep brain stimulation, dopaminergic agents or fetal mesencephalic transplantation provide a means to examine mechanisms underpinning plastic change. Other models of plastic change, such as normal visuospatial learning or re-establishing speech comprehension after cochlear implantation in the deaf illustrate how patterns of brain function adapt over time. Limitations of the scanning techniques and prospects for the future are discussed in relation to new developments in the neuroimaging field.
Su, Yun-Ting; Gu, Meng-Yang; Chu, Xi; Feng, Xiang; Yu, Yan-Qin
2018-06-01
The GABAergic neurons in the parafacial zone (PZ) play an important role in sleep-wake regulation and have been identified as part of a sleep-promoting center in the brainstem, but the long-range connections mediating this function remain poorly characterized. Here, we performed whole-brain mapping of both the inputs and outputs of the GABAergic neurons in the PZ of the mouse brain. We used the modified rabies virus EnvA-ΔG-DsRed combined with a Cre/loxP gene-expression strategy to map the direct monosynaptic inputs to the GABAergic neurons in the PZ, and found that they receive inputs mainly from the hypothalamic area, zona incerta, and parasubthalamic nucleus in the hypothalamus; the substantia nigra, pars reticulata and deep mesencephalic nucleus in the midbrain; and the intermediate reticular nucleus and medial vestibular nucleus (parvocellular part) in the pons and medulla. We also mapped the axonal projections of the PZ GABAergic neurons with adeno-associated virus, and defined the reciprocal connections of the PZ GABAergic neurons with their input and output nuclei. The newly-found inputs and outputs of the PZ were also listed compared with the literature. This cell-type-specific neuronal whole-brain mapping of the PZ GABAergic neurons may reveal the circuits underlying various functions such as sleep-wake regulation.
Selection of independent components based on cortical mapping of electromagnetic activity
NASA Astrophysics Data System (ADS)
Chan, Hui-Ling; Chen, Yong-Sheng; Chen, Li-Fen
2012-10-01
Independent component analysis (ICA) has been widely used to attenuate interference caused by noise components from the electromagnetic recordings of brain activity. However, the scalp topographies and associated temporal waveforms provided by ICA may be insufficient to distinguish functional components from artifactual ones. In this work, we proposed two component selection methods, both of which first estimate the cortical distribution of the brain activity for each component, and then determine the functional components based on the parcellation of brain activity mapped onto the cortical surface. Among all independent components, the first method can identify the dominant components, which have strong activity in the selected dominant brain regions, whereas the second method can identify those inter-regional associating components, which have similar component spectra between a pair of regions. For a targeted region, its component spectrum enumerates the amplitudes of its parceled brain activity across all components. The selected functional components can be remixed to reconstruct the focused electromagnetic signals for further analysis, such as source estimation. Moreover, the inter-regional associating components can be used to estimate the functional brain network. The accuracy of the cortical activation estimation was evaluated on the data from simulation studies, whereas the usefulness and feasibility of the component selection methods were demonstrated on the magnetoencephalography data recorded from a gender discrimination study.
Visualising inter-subject variability in fMRI using threshold-weighted overlap maps
NASA Astrophysics Data System (ADS)
Seghier, Mohamed L.; Price, Cathy J.
2016-02-01
Functional neuroimaging studies are revealing the neural systems sustaining many sensory, motor and cognitive abilities. A proper understanding of these systems requires an appreciation of the degree to which they vary across subjects. Some sources of inter-subject variability might be easy to measure (demographics, behavioural scores, or experimental factors), while others are more difficult (cognitive strategies, learning effects, and other hidden sources). Here, we introduce a simple way of visualising whole-brain consistency and variability in brain responses across subjects using threshold-weighted voxel-based overlap maps. The output quantifies the proportion of subjects activating a particular voxel or region over a wide range of statistical thresholds. The sensitivity of our approach was assessed in 30 healthy adults performing a matching task with their dominant hand. We show how overlap maps revealed many effects that were only present in a subsample of our group; we discuss how overlap maps can provide information that may be missed or misrepresented by standard group analysis, and how this information can help users to understand their data. In particular, we emphasize that functional overlap maps can be particularly useful when it comes to explaining typical (or atypical) compensatory mechanisms used by patients following brain damage.
Delion, Matthieu; Terminassian, Aram; Lehousse, Thierry; Aubin, Ghislaine; Malka, Jean; N'Guyen, Sylvie; Mercier, Philippe; Menei, Philippe
2015-12-01
In the pediatric population, awake craniotomy began to be used for the resection of brain tumor located close to eloquent areas. Some specificities must be taken into account to adapt this method to children. The aim of this clinical study is to not only confirm the feasibility of awake craniotomy and language brain mapping in the pediatric population but also identify the specificities and necessary adaptations of the procedure. Six children aged 11 to 16 were operated on while awake under local anesthesia with language brain mapping for supratentorial brain lesions (tumor and cavernoma). The preoperative planning comprised functional magnetic resonance imaging (MRI) and neuropsychologic and psychologic assessment. The specific preoperative preparation is clearly explained including hypnosis conditioning and psychiatric evaluation. The success of the procedure was based on the ability to perform the language brain mapping and the tumor removal without putting the patient to sleep. We investigated the pediatric specificities, psychological experience, and neuropsychologic follow-up. The children experienced little anxiety, probably in large part due to the use of hypnosis. We succeeded in doing the cortical-subcortical mapping and removing the tumor without putting the patient to sleep in all cases. The psychological experience was good, and the neuropsychologic follow-up showed a favorable evolution. Preoperative preparation and hypnosis in children seemed important for performing awake craniotomy and contributing language brain mapping with the best possible psychological experience. The pediatrics specificities are discussed. Copyright © 2015 Elsevier Inc. All rights reserved.
Duffau, H
2001-01-01
OBJECTIVES—Brain plasticity is supposed to allow the compensation of motor function in cases of rolandic lesion. The aim was to analyse the mechanisms of functional reorganisation during surgery in the central area. METHODS—A motor brain mapping was performed in three right handed patients without any neurological deficit, operated on for a slow growing lesion near the rolandic region (two precentral resected under general anaesthesia and one retrocentral removed under local anaesthesia to allow also sensory mapping) using intraoperative direct electrical stimulations (5 mm space tips bipolar stimulator probe, biphasic square wave pulse current: 1 ms/phase, 60 Hz, 4 to 18mA). RESULTS—For each patient, the motor areas of the hand and forearm in the primary motor cortex (M1) were identified before and after lesion removal with the same stimulation parameters: the same eloquent sites were found, plus the appearance after resection of additional sites in M1 inducing the same movement during stimulations as the previous areas. CONCLUSIONS—Multiple cortical representations for hand and forearm movements in M1 seem to exist. In addition, the results demonstrate the short term capacity of the brain to make changes in local motor maps, by sudden unmasking after tumour resection of a second redundant site participating in the same movement. Finally, it seems not necessary for the whole of the redundant sites to be functional to provide normal movement, a concept with potential implications for surgery within the central region. PMID:11254775
Mesoscale brain explorer, a flexible python-based image analysis and visualization tool.
Haupt, Dirk; Vanni, Matthieu P; Bolanos, Federico; Mitelut, Catalin; LeDue, Jeffrey M; Murphy, Tim H
2017-07-01
Imaging of mesoscale brain activity is used to map interactions between brain regions. This work has benefited from the pioneering studies of Grinvald et al., who employed optical methods to image brain function by exploiting the properties of intrinsic optical signals and small molecule voltage-sensitive dyes. Mesoscale interareal brain imaging techniques have been advanced by cell targeted and selective recombinant indicators of neuronal activity. Spontaneous resting state activity is often collected during mesoscale imaging to provide the basis for mapping of connectivity relationships using correlation. However, the information content of mesoscale datasets is vast and is only superficially presented in manuscripts given the need to constrain measurements to a fixed set of frequencies, regions of interest, and other parameters. We describe a new open source tool written in python, termed mesoscale brain explorer (MBE), which provides an interface to process and explore these large datasets. The platform supports automated image processing pipelines with the ability to assess multiple trials and combine data from different animals. The tool provides functions for temporal filtering, averaging, and visualization of functional connectivity relations using time-dependent correlation. Here, we describe the tool and show applications, where previously published datasets were reanalyzed using MBE.
Eytan, Danny; Pang, Elizabeth W; Doesburg, Sam M; Nenadovic, Vera; Gavrilovic, Bojan; Laussen, Peter; Guerguerian, Anne-Marie
2016-01-01
Acute brain injury is a common cause of death and critical illness in children and young adults. Fundamental management focuses on early characterization of the extent of injury and optimizing recovery by preventing secondary damage during the days following the primary injury. Currently, bedside technology for measuring neurological function is mainly limited to using electroencephalography (EEG) for detection of seizures and encephalopathic features, and evoked potentials. We present a proof of concept study in patients with acute brain injury in the intensive care setting, featuring a bedside functional imaging set-up designed to map cortical brain activation patterns by combining high density EEG recordings, multi-modal sensory stimulation (auditory, visual, and somatosensory), and EEG source modeling. Use of source-modeling allows for examination of spatiotemporal activation patterns at the cortical region level as opposed to the traditional scalp potential maps. The application of this system in both healthy and brain-injured participants is demonstrated with modality-specific source-reconstructed cortical activation patterns. By combining stimulation obtained with different modalities, most of the cortical surface can be monitored for changes in functional activation without having to physically transport the subject to an imaging suite. The results in patients in an intensive care setting with anatomically well-defined brain lesions suggest a topographic association between their injuries and activation patterns. Moreover, we report the reproducible application of a protocol examining a higher-level cortical processing with an auditory oddball paradigm involving presentation of the patient's own name. This study reports the first successful application of a bedside functional brain mapping tool in the intensive care setting. This application has the potential to provide clinicians with an additional dimension of information to manage critically-ill children and adults, and potentially patients not suited for magnetic resonance imaging technologies.
Topodynamics of metastable brains
NASA Astrophysics Data System (ADS)
Tozzi, Arturo; Peters, James F.; Fingelkurts, Andrew A.; Fingelkurts, Alexander A.; Marijuán, Pedro C.
2017-07-01
The brain displays both the anatomical features of a vast amount of interconnected topological mappings as well as the functional features of a nonlinear, metastable system at the edge of chaos, equipped with a phase space where mental random walks tend towards lower energetic basins. Nevertheless, with the exception of some advanced neuro-anatomic descriptions and present-day connectomic research, very few studies have been addressing the topological path of a brain embedded or embodied in its external and internal environment. Herein, by using new formal tools derived from algebraic topology, we provide an account of the metastable brain, based on the neuro-scientific model of Operational Architectonics of brain-mind functioning. We introduce a ;topodynamic; description that shows how the relationships among the countless intertwined spatio-temporal levels of brain functioning can be assessed in terms of projections and mappings that take place on abstract structures, equipped with different dimensions, curvatures and energetic constraints. Such a topodynamical approach, apart from providing a biologically plausible model of brain function that can be operationalized, is also able to tackle the issue of a long-standing dichotomy: it throws indeed a bridge between the subjective, immediate datum of the naïve complex of sensations and mentations and the objective, quantitative, data extracted from experimental neuro-scientific procedures. Importantly, it opens the door to a series of new predictions and future directions of advancement for neuroscientific research.
The cognitive atlas: toward a knowledge foundation for cognitive neuroscience.
Poldrack, Russell A; Kittur, Aniket; Kalar, Donald; Miller, Eric; Seppa, Christian; Gil, Yolanda; Parker, D Stott; Sabb, Fred W; Bilder, Robert M
2011-01-01
Cognitive neuroscience aims to map mental processes onto brain function, which begs the question of what "mental processes" exist and how they relate to the tasks that are used to manipulate and measure them. This topic has been addressed informally in prior work, but we propose that cumulative progress in cognitive neuroscience requires a more systematic approach to representing the mental entities that are being mapped to brain function and the tasks used to manipulate and measure mental processes. We describe a new open collaborative project that aims to provide a knowledge base for cognitive neuroscience, called the Cognitive Atlas (accessible online at http://www.cognitiveatlas.org), and outline how this project has the potential to drive novel discoveries about both mind and brain.
Brain Mapping of Language and Auditory Perception in High-Functioning Autistic Adults: A PET Study.
ERIC Educational Resources Information Center
Muller, R-A.; Behen, M. E.; Rothermel, R. D.; Chugani, D. C.; Muzik, O.; Mangner, T. J.; Chugani, H. T.
1999-01-01
A study used positron emission tomography (PET) to study patterns of brain activation during auditory processing in five high-functioning adults with autism. Results found that participants showed reversed hemispheric dominance during the verbal auditory stimulation and reduced activation of the auditory cortex and cerebellum. (CR)
ERIC Educational Resources Information Center
Staudt, Martin; Ticini, Luca F.; Grodd, Wolfgang; Krageloh-Mann, Ingeborg; Karnath, Hans-Otto
2008-01-01
Early periventricular brain lesions can not only cause cerebral palsy, but can also induce a reorganization of language. Here, we asked whether these different functional consequences can be attributed to topographically distinct portions of the periventricular white matter damage. Eight patients with pre- and perinatally acquired left-sided…
NASA Astrophysics Data System (ADS)
Diwadkar, Vaibhav A.
2015-12-01
The human brain is an impossibly difficult cartographic landscape to map out. Within it's convoluted and labyrinthine structure is folded a million years of phylogeny, somehow expressed in the ontogeny of the specific organism; an ontogeny that conceals idiosyncratic effects of countless genes, and then the (perhaps) countably infinite effects of processes of the organism's lifespan subsequently resulting in remarkable heterogeneity [1,2]. The physical brain itself is therefore a nearly un-decodable ;time machine; motivating more questions than frameworks for answering those questions: Why has evolution endowed it with the general structure that is possesses [3]; Is there regularity in macroscopic metrics of structure across species [4]; What are the most meaningful structural units in the brain: molecules, neurons, cortical columns or cortical maps [5]? Remarkably, understanding the intricacies of structure is perhaps not even the most difficult aspect of understanding the human brain. In fact, and as recently argued, a central issue lies in resolving the dialectic between structure and function: how does dynamic function arises from static (at least at the time scales at which human brain function is experimentally studied) brain structures [6]? In other words, if the mind is the brain ;in action;, how does it arise?
Fierstra, Jorn; Burkhardt, Jan-Karl; van Niftrik, Christiaan Hendrik Bas; Piccirelli, Marco; Pangalu, Athina; Kocian, Roman; Neidert, Marian Christoph; Valavanis, Antonios; Regli, Luca; Bozinov, Oliver
2017-02-01
To assess the feasibility of functional blood oxygen-level dependent (BOLD) MRI to evaluate intraoperative cerebrovascular reactivity (CVR) at 3 Tesla field strength. Ten consecutive neurosurgical subjects scheduled for a clinical intraoperative MRI examination were enrolled in this study. In addition to the clinical protocol a BOLD sequence was implemented with three cycles of 44 s apnea to calculate CVR values on a voxel-by-voxel basis throughout the brain. The CVR range was then color-coded and superimposed on an anatomical volume to create high spatial resolution CVR maps. Ten subjects (mean age 34.8 ± 13.4; 2 females) uneventfully underwent the intraoperative BOLD protocol, with no complications occurring. Whole-brain CVR for all subjects was (mean ± SD) 0.69 ± 0.42, whereas CVR was markedly higher for tumor subjects as compared to vascular subjects, 0.81 ± 0.44 versus 0.33 ± 0.10, respectively. Furthermore, color-coded functional maps could be robustly interpreted for a whole-brain assessment of CVR. We demonstrate that intraoperative BOLD MRI is feasible in creating functional maps to assess cerebrovascular reactivity throughout the brain in subjects undergoing a neurosurgical procedure. Magn Reson Med 77:806-813, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.
Mah, Yee-Haur; Jager, Rolf; Kennard, Christopher; Husain, Masud; Nachev, Parashkev
2014-07-01
Making robust inferences about the functional neuroanatomy of the brain is critically dependent on experimental techniques that examine the consequences of focal loss of brain function. Unfortunately, the use of the most comprehensive such technique-lesion-function mapping-is complicated by the need for time-consuming and subjective manual delineation of the lesions, greatly limiting the practicability of the approach. Here we exploit a recently-described general measure of statistical anomaly, zeta, to devise a fully-automated, high-dimensional algorithm for identifying the parameters of lesions within a brain image given a reference set of normal brain images. We proceed to evaluate such an algorithm in the context of diffusion-weighted imaging of the commonest type of lesion used in neuroanatomical research: ischaemic damage. Summary performance metrics exceed those previously published for diffusion-weighted imaging and approach the current gold standard-manual segmentation-sufficiently closely for fully-automated lesion-mapping studies to become a possibility. We apply the new method to 435 unselected images of patients with ischaemic stroke to derive a probabilistic map of the pattern of damage in lesions involving the occipital lobe, demonstrating the variation of anatomical resolvability of occipital areas so as to guide future lesion-function studies of the region. Copyright © 2012 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Ren, Hugang; Luo, Zhongchi; Yuan, Zhijia; Pan, Yingtian; Du, Congwu
2012-02-01
Characterization of cerebral hemodynamic and oxygenation metabolic changes, as well neuronal function is of great importance to study of brain functions and the relevant brain disorders such as drug addiction. Compared with other neuroimaging modalities, optical imaging techniques have the potential for high spatiotemporal resolution and dissection of the changes in cerebral blood flow (CBF), blood volume (CBV), and hemoglobing oxygenation and intracellular Ca ([Ca2+]i), which serves as markers of vascular function, tissue metabolism and neuronal activity, respectively. Recently, we developed a multiwavelength imaging system and integrated it into a surgical microscope. Three LEDs of λ1=530nm, λ2=570nm and λ3=630nm were used for exciting [Ca2+]i fluorescence labeled by Rhod2 (AM) and sensitizing total hemoglobin (i.e., CBV), and deoxygenated-hemoglobin, whereas one LD of λ1=830nm was used for laser speckle imaging to form a CBF mapping of the brain. These light sources were time-sharing for illumination on the brain and synchronized with the exposure of CCD camera for multichannel images of the brain. Our animal studies indicated that this optical approach enabled simultaneous mapping of cocaine-induced changes in CBF, CBV and oxygenated- and deoxygenated hemoglobin as well as [Ca2+]i in the cortical brain. Its high spatiotemporal resolution (30μm, 10Hz) and large field of view (4x5 mm2) are advanced as a neuroimaging tool for brain functional study.
Fast periodic stimulation (FPS): a highly effective approach in fMRI brain mapping.
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.
Loizzo, Joseph J
2016-06-01
Meditation research has begun to clarify the brain effects and mechanisms of contemplative practices while generating a range of typologies and explanatory models to guide further study. This comparative review explores a neglected area relevant to current research: the validity of a traditional central nervous system (CNS) model that coevolved with the practices most studied today and that provides the first comprehensive neural-based typology and mechanistic framework of contemplative practices. The subtle body model, popularly known as the chakra system from Indian yoga, was and is used as a map of CNS function in traditional Indian and Tibetan medicine, neuropsychiatry, and neuropsychology. The study presented here, based on the Nalanda tradition, shows that the subtle body model can be cross-referenced with modern CNS maps and challenges modern brain maps with its embodied network model of CNS function. It also challenges meditation research by: (1) presenting a more rigorous, neural-based typology of contemplative practices; (2) offering a more refined and complete network model of the mechanisms of contemplative practices; and (3) serving as an embodied, interoceptive neurofeedback aid that is more user friendly and complete than current teaching aids for clinical and practical applications of contemplative practice. © 2016 New York Academy of Sciences.
Zhang, Jiang; Liu, Qi; Chen, Huafu; Yuan, Zhen; Huang, Jin; Deng, Lihua; Lu, Fengmei; Zhang, Junpeng; Wang, Yuqing; Wang, Mingwen; Chen, Liangyin
2015-01-01
Clustering analysis methods have been widely applied to identifying the functional brain networks of a multitask paradigm. However, the previously used clustering analysis techniques are computationally expensive and thus impractical for clinical applications. In this study a novel method, called SOM-SAPC that combines self-organizing mapping (SOM) and supervised affinity propagation clustering (SAPC), is proposed and implemented to identify the motor execution (ME) and motor imagery (MI) networks. In SOM-SAPC, SOM was first performed to process fMRI data and SAPC is further utilized for clustering the patterns of functional networks. As a result, SOM-SAPC is able to significantly reduce the computational cost for brain network analysis. Simulation and clinical tests involving ME and MI were conducted based on SOM-SAPC, and the analysis results indicated that functional brain networks were clearly identified with different response patterns and reduced computational cost. In particular, three activation clusters were clearly revealed, which include parts of the visual, ME and MI functional networks. These findings validated that SOM-SAPC is an effective and robust method to analyze the fMRI data with multitasks.
Hierarchical functional modularity in the resting-state human brain.
Ferrarini, Luca; Veer, Ilya M; Baerends, Evelinda; van Tol, Marie-José; Renken, Remco J; van der Wee, Nic J A; Veltman, Dirk J; Aleman, André; Zitman, Frans G; Penninx, Brenda W J H; van Buchem, Mark A; Reiber, Johan H C; Rombouts, Serge A R B; Milles, Julien
2009-07-01
Functional magnetic resonance imaging (fMRI) studies have shown that anatomically distinct brain regions are functionally connected during the resting state. Basic topological properties in the brain functional connectivity (BFC) map have highlighted the BFC's small-world topology. Modularity, a more advanced topological property, has been hypothesized to be evolutionary advantageous, contributing to adaptive aspects of anatomical and functional brain connectivity. However, current definitions of modularity for complex networks focus on nonoverlapping clusters, and are seriously limited by disregarding inclusive relationships. Therefore, BFC's modularity has been mainly qualitatively investigated. Here, we introduce a new definition of modularity, based on a recently improved clustering measurement, which overcomes limitations of previous definitions, and apply it to the study of BFC in resting state fMRI of 53 healthy subjects. Results show hierarchical functional modularity in the brain. Copyright 2009 Wiley-Liss, Inc
Quantitative Architectural Analysis: A New Approach to Cortical Mapping
ERIC Educational Resources Information Center
Schleicher, Axel; Morosan, Patricia; Amunts, Katrin; Zilles, Karl
2009-01-01
Results from functional imaging studies are often still interpreted using the classical architectonic brain maps of Brodmann and his successors. One obvious weakness in traditional, architectural mapping is the subjective nature of localizing borders between cortical areas by means of a purely visual, microscopical examination of histological…
From Brain Maps to Cognitive Ontologies: Informatics and the Search for Mental Structure.
Poldrack, Russell A; Yarkoni, Tal
2016-01-01
A major goal of cognitive neuroscience is to delineate how brain systems give rise to mental function. Here we review the increasingly large role informatics-driven approaches are playing in such efforts. We begin by reviewing a number of challenges conventional neuroimaging approaches face in trying to delineate brain-cognition mappings--for example, the difficulty in establishing the specificity of postulated associations. Next, we demonstrate how these limitations can potentially be overcome using complementary approaches that emphasize large-scale analysis--including meta-analytic methods that synthesize hundreds or thousands of studies at a time; latent-variable approaches that seek to extract structure from data in a bottom-up manner; and predictive modeling approaches capable of quantitatively inferring mental states from patterns of brain activity. We highlight the underappreciated but critical role for formal cognitive ontologies in helping to clarify, refine, and test theories of brain and cognitive function. Finally, we conclude with a speculative discussion of what future informatics developments may hold for cognitive neuroscience.
Cognitive memory and mapping in a brain-like system for robotic navigation.
Tang, Huajin; Huang, Weiwei; Narayanamoorthy, Aditya; Yan, Rui
2017-03-01
Electrophysiological studies in animals may provide a great insight into developing brain-like models of spatial cognition for robots. These studies suggest that the spatial ability of animals requires proper functioning of the hippocampus and the entorhinal cortex (EC). The involvement of the hippocampus in spatial cognition has been extensively studied, both in animal as well as in theoretical studies, such as in the brain-based models by Edelman and colleagues. In this work, we extend these earlier models, with a particular focus on the spatial coding properties of the EC and how it functions as an interface between the hippocampus and the neocortex, as proposed by previous work. By realizing the cognitive memory and mapping functions of the hippocampus and the EC, respectively, we develop a neurobiologically-inspired system to enable a mobile robot to perform task-based navigation in a maze environment. Copyright © 2016 Elsevier Ltd. All rights reserved.
A Hybrid CPU-GPU Accelerated Framework for Fast Mapping of High-Resolution Human Brain Connectome
Ren, Ling; Xu, Mo; Xie, Teng; Gong, Gaolang; Xu, Ningyi; Yang, Huazhong; He, Yong
2013-01-01
Recently, a combination of non-invasive neuroimaging techniques and graph theoretical approaches has provided a unique opportunity for understanding the patterns of the structural and functional connectivity of the human brain (referred to as the human brain connectome). Currently, there is a very large amount of brain imaging data that have been collected, and there are very high requirements for the computational capabilities that are used in high-resolution connectome research. In this paper, we propose a hybrid CPU-GPU framework to accelerate the computation of the human brain connectome. We applied this framework to a publicly available resting-state functional MRI dataset from 197 participants. For each subject, we first computed Pearson’s Correlation coefficient between any pairs of the time series of gray-matter voxels, and then we constructed unweighted undirected brain networks with 58 k nodes and a sparsity range from 0.02% to 0.17%. Next, graphic properties of the functional brain networks were quantified, analyzed and compared with those of 15 corresponding random networks. With our proposed accelerating framework, the above process for each network cost 80∼150 minutes, depending on the network sparsity. Further analyses revealed that high-resolution functional brain networks have efficient small-world properties, significant modular structure, a power law degree distribution and highly connected nodes in the medial frontal and parietal cortical regions. These results are largely compatible with previous human brain network studies. Taken together, our proposed framework can substantially enhance the applicability and efficacy of high-resolution (voxel-based) brain network analysis, and have the potential to accelerate the mapping of the human brain connectome in normal and disease states. PMID:23675425
NASA Astrophysics Data System (ADS)
Kura, Sreekanth; Xie, Hongyu; Fu, Buyin; Ayata, Cenk; Boas, David A.; Sakadžić, Sava
2018-06-01
Objective. Resting state functional connectivity (RSFC) allows the study of functional organization in normal and diseased brain by measuring the spontaneous brain activity generated under resting conditions. Intrinsic optical signal imaging (IOSI) based on multiple illumination wavelengths has been used successfully to compute RSFC maps in animal studies. The IOSI setup complexity would be greatly reduced if only a single wavelength can be used to obtain comparable RSFC maps. Approach. We used anesthetized mice and performed various comparisons between the RSFC maps based on single wavelength as well as oxy-, deoxy- and total hemoglobin concentration changes. Main results. The RSFC maps based on IOSI at a single wavelength selected for sensitivity to the blood volume changes are quantitatively comparable to the RSFC maps based on oxy- and total hemoglobin concentration changes obtained by the more complex IOSI setups. Moreover, RSFC maps do not require CCD cameras with very high frame acquisition rates, since our results demonstrate that they can be computed from the data obtained at frame rates as low as 5 Hz. Significance. Our results will have general utility for guiding future RSFC studies based on IOSI and making decisions about the IOSI system designs.
Andersen, Flemming; Watanabe, Hideaki; Bjarkam, Carsten; Danielsen, Erik H; Cumming, Paul
2005-07-15
The analysis of physiological processes in brain by position emission tomography (PET) is facilitated when images are spatially normalized to a standard coordinate system. Thus, PET activation studies of human brain frequently employ the common stereotaxic coordinates of Talairach. We have developed an analogous stereotaxic coordinate system for the brain of the Gottingen miniature pig, based on automatic co-registration of magnetic resonance (MR) images obtained in 22 male pigs. The origin of the pig brain stereotaxic space (0, 0, 0) was arbitrarily placed in the centroid of the pineal gland as identified on the average MRI template. The orthogonal planes were imposed using the line between stereotaxic zero and the optic chiasm. A series of mean MR images in the coronal, sagittal and horizontal planes were generated. To test the utility of the common coordinate system for functional imaging studies of minipig brain, we calculated cerebral blood flow (CBF) maps from normal minipigs and from minipigs with a syndrome of parkisonism induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-poisoning. These maps were transformed from the native space into the common stereotaxic space. After global normalization of these maps, an undirected search for differences between the groups was then performed using statistical parametric mapping. Using this method, we detected a statistically significant focal increase in CBF in the left cerebellum of the MPTP-lesioned group. We expect the present approach to be of general use in the statistical parametric mapping of CBF and other physiological parameters in living pig brain.
Della Puppa, Alessandro; De Pellegrin, Serena; d'Avella, Elena; Gioffrè, Giorgio; Munari, Marina; Saladini, Marina; Salillas, Elena; Scienza, Renato; Semenza, Carlo
2013-11-01
The role of parietal areas in number processing is well known. The significance of intraoperative functional mapping of these areas has been only partially explored, however, and only a few discordant data are available in the surgical literature with regard to the right parietal lobe. The purpose of this study was to evaluate the clinical impact of simple calculation in cortical electrostimulation of right-handed patients affected by a right parietal brain tumor. Calculation mapping in awake surgery was performed in 3 right-handed patients affected by high-grade gliomas located in the right parietal lobe. Preoperatively, none of the patients presented with calculation deficits. In all 3 cases, after sensorimotor and language mapping, cortical and intraparietal sulcus areas involved in single-digit multiplication and addition calculations were mapped using bipolar electrostimulation. In all patients, different sites of the right parietal cortex, mainly in the inferior lobule, were detected as being specifically related to calculation (multiplication or addition). In 2 patients the intraparietal sulcus was functionally specific for multiplication. No functional sites for language were detected. All sites functional for calculation were spared during tumor resection, which was complete in all cases without postoperative neurological deficits. These findings provide intraoperative data in support of an anatomofunctional organization for multiplication and addition within the right parietal area. Furthermore, the study shows the potential clinical relevance of intraoperative mapping of calculation in patients undergoing surgery in the right parietal area. Further and larger studies are needed to confirm these data and assess whether mapped areas are effectively essential for function.
The Cognitive Atlas: Toward a Knowledge Foundation for Cognitive Neuroscience
Poldrack, Russell A.; Kittur, Aniket; Kalar, Donald; Miller, Eric; Seppa, Christian; Gil, Yolanda; Parker, D. Stott; Sabb, Fred W.; Bilder, Robert M.
2011-01-01
Cognitive neuroscience aims to map mental processes onto brain function, which begs the question of what “mental processes” exist and how they relate to the tasks that are used to manipulate and measure them. This topic has been addressed informally in prior work, but we propose that cumulative progress in cognitive neuroscience requires a more systematic approach to representing the mental entities that are being mapped to brain function and the tasks used to manipulate and measure mental processes. We describe a new open collaborative project that aims to provide a knowledge base for cognitive neuroscience, called the Cognitive Atlas (accessible online at http://www.cognitiveatlas.org), and outline how this project has the potential to drive novel discoveries about both mind and brain. PMID:21922006
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
NASA Astrophysics Data System (ADS)
Senarathna, Janaka; Hadjiabadi, Darian; Gil, Stacy; Thakor, Nitish V.; Pathak, Arvind P.
2017-02-01
Different brain regions exhibit complex information processing even at rest. Therefore, assessing temporal correlations between regions permits task-free visualization of their `resting state connectivity'. Although functional MRI (fMRI) is widely used for mapping resting state connectivity in the human brain, it is not well suited for `microvascular scale' imaging in rodents because of its limited spatial resolution. Moreover, co-registered cerebral blood flow (CBF) and total hemoglobin (HbT) data are often unavailable in conventional fMRI experiments. Therefore, we built a customized system that combines laser speckle contrast imaging (LSCI), intrinsic optical signal (IOS) imaging and fluorescence imaging (FI) to generate multi-contrast functional connectivity maps at a spatial resolution of 10 μm. This system comprised of three illumination sources: a 632 nm HeNe laser (for LSCI), a 570 nm ± 5 nm filtered white light source (for IOS), and a 473 nm blue laser (for FI), as well as a sensitive CCD camera operating at 10 frames per second for image acquisition. The acquired data enabled visualization of changes in resting state neurophysiology at microvascular spatial scales. Moreover, concurrent mapping of CBF and HbT-based temporal correlations enabled in vivo mapping of how resting brain regions were linked in terms of their hemodynamics. Additionally, we complemented this approach by exploiting the transit times of a fluorescent tracer (Dextran-FITC) to distinguish arterial from venous perfusion. Overall, we demonstrated the feasibility of wide area mapping of resting state connectivity at microvascular resolution and created a new toolbox for interrogating neurovascular function.
Chan, Kevin C.; Fan, Shu-Juan; Chan, Russell W.; Cheng, Joe S.; Zhou, Iris Y.; Wu, Ed X.
2014-01-01
The rodents are an increasingly important model for understanding the mechanisms of development, plasticity, functional specialization and disease in the visual system. However, limited tools have been available for assessing the structural and functional connectivity of the visual brain network globally, in vivo and longitudinally. There are also ongoing debates on whether functional brain connectivity directly reflects structural brain connectivity. In this study, we explored the feasibility of manganese-enhanced MRI (MEMRI) via 3 different routes of Mn2+ administration for visuotopic brain mapping and understanding of physiological transport in normal and visually deprived adult rats. In addition, resting-state functional connectivity MRI (RSfcMRI) was performed to evaluate the intrinsic functional network and structural-functional relationships in the corresponding anatomical visual brain connections traced by MEMRI. Upon intravitreal, subcortical, and intracortical Mn2+ injection, different topographic and layer-specific Mn enhancement patterns could be revealed in the visual cortex and subcortical visual nuclei along retinal, callosal, cortico-subcortical, transsynaptic and intracortical horizontal connections. Loss of visual input upon monocular enucleation to adult rats appeared to reduce interhemispheric polysynaptic Mn2+ transfer but not intra- or inter-hemispheric monosynaptic Mn2+ transport after Mn2+ injection into visual cortex. In normal adults, both structural and functional connectivity by MEMRI and RSfcMRI was stronger interhemispherically between bilateral primary/secondary visual cortex (V1/V2) transition zones (TZ) than between V1/V2 TZ and other cortical nuclei. Intrahemispherically, structural and functional connectivity was stronger between visual cortex and subcortical visual nuclei than between visual cortex and other subcortical nuclei. The current results demonstrated the sensitivity of MEMRI and RSfcMRI for assessing the neuroarchitecture, neurophysiology and structural-functional relationships of the visual brains in vivo. These may possess great potentials for effective monitoring and understanding of the basic anatomical and functional connections in the visual system during development, plasticity, disease, pharmacological interventions and genetic modifications in future studies. PMID:24394694
Functional brain networks in schizophrenia: a review.
Calhoun, Vince D; Eichele, Tom; Pearlson, Godfrey
2009-01-01
Functional magnetic resonance imaging (fMRI) has become a major technique for studying cognitive function and its disruption in mental illness, including schizophrenia. The major proportion of imaging studies focused primarily upon identifying regions which hemodynamic response amplitudes covary with particular stimuli and differentiate between patient and control groups. In addition to such amplitude based comparisons, one can estimate temporal correlations and compute maps of functional connectivity between regions which include the variance associated with event-related responses as well as intrinsic fluctuations of hemodynamic activity. Functional connectivity maps can be computed by correlating all voxels with a seed region when a spatial prior is available. An alternative are multivariate decompositions such as independent component analysis (ICA) which extract multiple components, each of which is a spatially distinct map of voxels with a common time course. Recent work has shown that these networks are pervasive in relaxed resting and during task performance and hence provide robust measures of intact and disturbed brain activity. This in turn bears the prospect of yielding biomarkers for schizophrenia, which can be described both in terms of disrupted local processing as well as altered global connectivity between large-scale networks. In this review we will summarize functional connectivity measures with a focus upon work with ICA and discuss the meaning of intrinsic fluctuations. In addition, examples of how brain networks have been used for classification of disease will be shown. We present work with functional network connectivity, an approach that enables the evaluation of the interplay between multiple networks and how they are affected in disease. We conclude by discussing new variants of ICA for extracting maximally group discriminative networks from data. In summary, it is clear that identification of brain networks and their inter-relationships with fMRI has great potential to improve our understanding of schizophrenia.
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.
Decreased Complexity in Alzheimer's Disease: Resting-State fMRI Evidence of Brain Entropy Mapping.
Wang, Bin; Niu, Yan; Miao, Liwen; Cao, Rui; Yan, Pengfei; Guo, Hao; Li, Dandan; Guo, Yuxiang; Yan, Tianyi; Wu, Jinglong; Xiang, Jie; Zhang, Hui
2017-01-01
Alzheimer's disease (AD) is a frequently observed, irreversible brain function disorder among elderly individuals. Resting-state functional magnetic resonance imaging (rs-fMRI) has been introduced as an alternative approach to assessing brain functional abnormalities in AD patients. However, alterations in the brain rs-fMRI signal complexities in mild cognitive impairment (MCI) and AD patients remain unclear. Here, we described the novel application of permutation entropy (PE) to investigate the abnormal complexity of rs-fMRI signals in MCI and AD patients. The rs-fMRI signals of 30 normal controls (NCs), 33 early MCI (EMCI), 32 late MCI (LMCI), and 29 AD patients were obtained from the Alzheimer's disease Neuroimaging Initiative (ADNI) database. After preprocessing, whole-brain entropy maps of the four groups were extracted and subjected to Gaussian smoothing. We performed a one-way analysis of variance (ANOVA) on the brain entropy maps of the four groups. The results after adjusting for age and sex differences together revealed that the patients with AD exhibited lower complexity than did the MCI and NC controls. We found five clusters that exhibited significant differences and were distributed primarily in the occipital, frontal, and temporal lobes. The average PE of the five clusters exhibited a decreasing trend from MCI to AD. The AD group exhibited the least complexity. Additionally, the average PE of the five clusters was significantly positively correlated with the Mini-Mental State Examination (MMSE) scores and significantly negatively correlated with Functional Assessment Questionnaire (FAQ) scores and global Clinical Dementia Rating (CDR) scores in the patient groups. Significant correlations were also found between the PE and regional homogeneity (ReHo) in the patient groups. These results indicated that declines in PE might be related to changes in regional functional homogeneity in AD. These findings suggested that complexity analyses using PE in rs-fMRI signals can provide important information about the fMRI characteristics of cognitive impairments in MCI and AD.
Decreased Complexity in Alzheimer's Disease: Resting-State fMRI Evidence of Brain Entropy Mapping
Wang, Bin; Niu, Yan; Miao, Liwen; Cao, Rui; Yan, Pengfei; Guo, Hao; Li, Dandan; Guo, Yuxiang; Yan, Tianyi; Wu, Jinglong; Xiang, Jie; Zhang, Hui
2017-01-01
Alzheimer's disease (AD) is a frequently observed, irreversible brain function disorder among elderly individuals. Resting-state functional magnetic resonance imaging (rs-fMRI) has been introduced as an alternative approach to assessing brain functional abnormalities in AD patients. However, alterations in the brain rs-fMRI signal complexities in mild cognitive impairment (MCI) and AD patients remain unclear. Here, we described the novel application of permutation entropy (PE) to investigate the abnormal complexity of rs-fMRI signals in MCI and AD patients. The rs-fMRI signals of 30 normal controls (NCs), 33 early MCI (EMCI), 32 late MCI (LMCI), and 29 AD patients were obtained from the Alzheimer's disease Neuroimaging Initiative (ADNI) database. After preprocessing, whole-brain entropy maps of the four groups were extracted and subjected to Gaussian smoothing. We performed a one-way analysis of variance (ANOVA) on the brain entropy maps of the four groups. The results after adjusting for age and sex differences together revealed that the patients with AD exhibited lower complexity than did the MCI and NC controls. We found five clusters that exhibited significant differences and were distributed primarily in the occipital, frontal, and temporal lobes. The average PE of the five clusters exhibited a decreasing trend from MCI to AD. The AD group exhibited the least complexity. Additionally, the average PE of the five clusters was significantly positively correlated with the Mini-Mental State Examination (MMSE) scores and significantly negatively correlated with Functional Assessment Questionnaire (FAQ) scores and global Clinical Dementia Rating (CDR) scores in the patient groups. Significant correlations were also found between the PE and regional homogeneity (ReHo) in the patient groups. These results indicated that declines in PE might be related to changes in regional functional homogeneity in AD. These findings suggested that complexity analyses using PE in rs-fMRI signals can provide important information about the fMRI characteristics of cognitive impairments in MCI and AD. PMID:29209199
R2* mapping for brain iron: associations with cognition in normal aging.
Ghadery, Christine; Pirpamer, Lukas; Hofer, Edith; Langkammer, Christian; Petrovic, Katja; Loitfelder, Marisa; Schwingenschuh, Petra; Seiler, Stephan; Duering, Marco; Jouvent, Eric; Schmidt, Helena; Fazekas, Franz; Mangin, Jean-Francois; Chabriat, Hugues; Dichgans, Martin; Ropele, Stefan; Schmidt, Reinhold
2015-02-01
Brain iron accumulates during aging and has been associated with neurodegenerative disorders including Alzheimer's disease. Magnetic resonance (MR)-based R2* mapping enables the in vivo detection of iron content in brain tissue. We investigated if during normal brain aging iron load relates to cognitive impairment in region-specific patterns in a community-dwelling cohort of 336 healthy, middle aged, and older adults from the Austrian Stroke Prevention Family Study. MR imaging and R2* mapping in the basal ganglia and neocortex were done at 3T. Comprehensive neuropsychological testing assessed memory, executive function, and psychomotor speed. We found the highest iron concentration in the globus pallidus, and pallidal and putaminal iron was significantly and inversely associated with cognitive performance in all cognitive domains, except memory. These associations were iron load dependent. Vascular brain lesions and brain volume did not mediate the relationship between iron and cognitive performance. We conclude that higher R2*-determined iron in the basal ganglia correlates with cognitive impairment during brain aging independent of concomitant brain abnormalities. The prognostic significance of this finding needs to be determined. Copyright © 2015 Elsevier Inc. All rights reserved.
Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Cabanban, Romeo; Crosson, Bruce A
2015-06-01
A major focus of brain research recently has been to map the resting-state functional connectivity (rsFC) network architecture of the normal brain and pathology through functional magnetic resonance imaging. However, the phenomenon of anticorrelations in resting-state signals between different brain regions has not been adequately examined. The preponderance of studies on resting-state fMRI (rsFMRI) have either ignored anticorrelations in rsFC networks or adopted methods in data analysis, which have rendered anticorrelations in rsFC networks uninterpretable. The few studies that have examined anticorrelations in rsFC networks using conventional methods have found anticorrelations to be weak in strength and not very reproducible across subjects. Anticorrelations in rsFC network architecture could reflect mechanisms that subserve a number of important brain processes. In this preliminary study, we examined the properties of anticorrelated rsFC networks by systematically focusing on negative cross-correlation coefficients (CCs) among rsFMRI voxel time series across the brain with graph theory-based network analysis. A number of methods were implemented to enhance the neuronal specificity of resting-state functional connections that yield negative CCs, although at the cost of decreased sensitivity. Hubs of anticorrelation were seen in a number of cortical and subcortical brain regions. Examination of the anticorrelation maps of these hubs indicated that negative CCs in rsFC network architecture highlight a number of regulatory interactions between brain networks and regions, including reciprocal modulations, suppression, inhibition, and neurofeedback.
The study of the wonderful: the first topographical mapping of vision in the brain.
Fishman, Ronald S
2008-12-01
The conception by René Descartes of the human brain, notorious as it is for placing the soul or mind in the pineal gland, had yet within it the basic idea of the brain as a highly organized mechanism with topographical sensory mapping and different functions localized in specific areas. Descartes was directly led to this idea by his appreciation of what the retinal image conceived by Johannes Kepler implied, not only for the nature of vision, but for the operation of the brain in general. The linkage between Kepler and Descartes is not widely appreciated but is one of the best examples of synergism in the history of science.
Martin, Anna; Schurz, Matthias; Kronbichler, Martin
2015-01-01
Abstract We used quantitative, coordinate‐based meta‐analysis to objectively synthesize age‐related commonalities and differences in brain activation patterns reported in 40 functional magnetic resonance imaging (fMRI) studies of reading in children and adults. Twenty fMRI studies with adults (age means: 23–34 years) were matched to 20 studies with children (age means: 7–12 years). The separate meta‐analyses of these two sets showed a pattern of reading‐related brain activation common to children and adults in left ventral occipito‐temporal (OT), inferior frontal, and posterior parietal regions. The direct statistical comparison between the two meta‐analytic maps of children and adults revealed higher convergence in studies with children in left superior temporal and bilateral supplementary motor regions. In contrast, higher convergence in studies with adults was identified in bilateral posterior OT/cerebellar and left dorsal precentral regions. The results are discussed in relation to current neuroanatomical models of reading and tentative functional interpretations of reading‐related activation clusters in children and adults are provided. Hum Brain Mapp 36:1963–1981, 2015. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.. PMID:25628041
State Space Modeling of Time-Varying Contemporaneous and Lagged Relations in Connectivity Maps
Molenaar, Peter C. M.; Beltz, Adriene M.; Gates, Kathleen M.; Wilson, Stephen J.
2017-01-01
Most connectivity mapping techniques for neuroimaging data assume stationarity (i.e., network parameters are constant across time), but this assumption does not always hold true. The authors provide a description of a new approach for simultaneously detecting time-varying (or dynamic) contemporaneous and lagged relations in brain connectivity maps. Specifically, they use a novel raw data likelihood estimation technique (involving a second-order extended Kalman filter/smoother embedded in a nonlinear optimizer) to determine the variances of the random walks associated with state space model parameters and their autoregressive components. The authors illustrate their approach with simulated and blood oxygen level-dependent functional magnetic resonance imaging data from 30 daily cigarette smokers performing a verbal working memory task, focusing on seven regions of interest (ROIs). Twelve participants had dynamic directed functional connectivity maps: Eleven had one or more time-varying contemporaneous ROI state loadings, and one had a time-varying autoregressive parameter. Compared to smokers without dynamic maps, smokers with dynamic maps performed the task with greater accuracy. Thus, accurate detection of dynamic brain processes is meaningfully related to behavior in a clinical sample. PMID:26546863
Detection of Brain Reorganization in Pediatric Multiple Sclerosis Using Functional MRI
2014-10-01
Unclassified b. ABSTRACT Unclassified c. THIS PAGE Unclassified Unclassified 19b. TELEPHONE NUMBER (include area code ) Standard Form 298 (Rev. 8-98...Research titled: “Passive fMRI mapping of language function for pediatric epilepsy surgery : validation using Wada, ECS, and FMAER” 2. Invited talk to...The mapping of language is important in pediatric patients who will undergo resection surgery near cortical regions essential for language function
Agarwal, Shruti; Lu, Hanzhang; Pillai, Jay J
2017-08-01
The aim of this study was to explore whether the phenomenon of brain tumor-related neurovascular uncoupling (NVU) in resting-state blood oxygen level-dependent functional magnetic resonance imaging (BOLD fMRI) (rsfMRI) may also affect the resting-state fMRI (rsfMRI) frequency domain metrics the amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF). Twelve de novo brain tumor patients, who underwent clinical fMRI examinations, including task-based fMRI (tbfMRI) and rsfMRI, were included in this Institutional Review Board-approved study. Each patient displayed decreased/absent tbfMRI activation in the primary ipsilesional (IL) sensorimotor cortex in the absence of a corresponding motor deficit or suboptimal task performance, consistent with NVU. Z-score maps for the motor tasks were obtained from general linear model analysis (reflecting motor activation vs. rest). Seed-based correlation analysis (SCA) maps of sensorimotor network, ALFF, and fALFF were calculated from rsfMRI data. Precentral and postcentral gyri in contralesional (CL) and IL hemispheres were parcellated using an automated anatomical labeling template for each patient. Region of interest (ROI) analysis was performed on four maps: tbfMRI, SCA, ALFF, and fALFF. Voxel values in the CL and IL ROIs of each map were divided by the corresponding global mean of ALFF and fALFF in the cortical brain tissue. Group analysis revealed significantly decreased IL ALFF (p = 0.02) and fALFF (p = 0.03) metrics compared with CL ROIs, consistent with similar findings of significantly decreased IL BOLD signal for tbfMRI (p = 0.0005) and SCA maps (p = 0.0004). The frequency domain metrics ALFF and fALFF may be markers of lesion-induced NVU in rsfMRI similar to previously reported alterations in tbfMRI activation and SCA-derived resting-state functional connectivity maps.
Takebayashi, Kento; Saito, Taiichi; Nitta, Masayuki; Tamura, Manabu; Maruyama, Takashi; Muragaki, Yoshihiro; Okada, Yoshikazu
2015-01-01
Surgical resection of gliomas located in the dominant parietal lobe is difficult because this lesion is surrounded by multiple functional areas. Although functional mapping during awake craniotomy is very useful for resection of gliomas adjacent to eloquent areas, the limited time available makes it difficult to sufficiently evaluate multiple functions, such as language, calculative ability, distinction of right and left sides, and finger recognition. Here, we report a case of anaplastic oligodendroglioma, which was successfully treated with a combination of functional mapping using subdural electrodes and monitoring under awake craniotomy for glioma. A 32-year-old man presented with generalized seizure. Magnetic resonance imaging revealed a non-enhanced tumor in the left angular and supramarginal gyri. In addition, the tumor showed high accumulation on 11C-methionine positron emission tomography(PET)(tumor/normal brain tissue ratio=3.20). Preparatory mapping using subdural electrodes showed absence of brain function on the tumor lesion. Surgical removal was performed using cortical mapping during awake craniotomy with an updated navigation system using intraoperative magnetic resonance imaging(MRI). The tumor was resected until aphasia was detected by functional monitoring, and the extent of tumor resection was 93%. The patient showed transient transcortical aphasia and Gerstmann's syndrome after surgery but eventually recovered. The pathological diagnosis was anaplastic oligodendroglioma, and the patient was administered chemo-radiotherapy. The patient has been progression free for more than 2 years. The combination of subdural electrode mapping and monitoring during awake craniotomy is useful in order to achieve preservation of function and extensive resection for gliomas in the dominant parietal lobe.
The role of image registration in brain mapping
Toga, A.W.; Thompson, P.M.
2008-01-01
Image registration is a key step in a great variety of biomedical imaging applications. It provides the ability to geometrically align one dataset with another, and is a prerequisite for all imaging applications that compare datasets across subjects, imaging modalities, or across time. Registration algorithms also enable the pooling and comparison of experimental findings across laboratories, the construction of population-based brain atlases, and the creation of systems to detect group patterns in structural and functional imaging data. We review the major types of registration approaches used in brain imaging today. We focus on their conceptual basis, the underlying mathematics, and their strengths and weaknesses in different contexts. We describe the major goals of registration, including data fusion, quantification of change, automated image segmentation and labeling, shape measurement, and pathology detection. We indicate that registration algorithms have great potential when used in conjunction with a digital brain atlas, which acts as a reference system in which brain images can be compared for statistical analysis. The resulting armory of registration approaches is fundamental to medical image analysis, and in a brain mapping context provides a means to elucidate clinical, demographic, or functional trends in the anatomy or physiology of the brain. PMID:19890483
The CLAIR model: Extension of Brodmann areas based on brain oscillations and connectivity.
Başar, Erol; Düzgün, Aysel
2016-05-01
Since the beginning of the last century, the localization of brain function has been represented by Brodmann areas, maps of the anatomic organization of the brain. They are used to broadly represent cortical structures with their given sensory-cognitive functions. In recent decades, the analysis of brain oscillations has become important in the correlation of brain functions. Moreover, spectral connectivity can provide further information on the dynamic connectivity between various structures. In addition, brain responses are dynamic in nature and structural localization is almost impossible, according to Luria (1966). Therefore, brain functions are very difficult to localize; hence, a combined analysis of oscillation and event-related coherences is required. In this study, a model termed as "CLAIR" is described to enrich and possibly replace the concept of the Brodmann areas. A CLAIR model with optimum function may take several years to develop, but this study sets out to lay its foundation. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
Riccelli, Roberta; Indovina, Iole; Staab, Jeffrey P; Nigro, Salvatore; Augimeri, Antonio; Lacquaniti, Francesco; Passamonti, Luca
2017-02-01
Different lines of research suggest that anxiety-related personality traits may influence the visual and vestibular control of balance, although the brain mechanisms underlying this effect remain unclear. To our knowledge, this is the first functional magnetic resonance imaging (fMRI) study that investigates how individual differences in neuroticism and introversion, two key personality traits linked to anxiety, modulate brain regional responses and functional connectivity patterns during a fMRI task simulating self-motion. Twenty-four healthy individuals with variable levels of neuroticism and introversion underwent fMRI while performing a virtual reality rollercoaster task that included two main types of trials: (1) trials simulating downward or upward self-motion (vertical motion), and (2) trials simulating self-motion in horizontal planes (horizontal motion). Regional brain activity and functional connectivity patterns when comparing vertical versus horizontal motion trials were correlated with personality traits of the Five Factor Model (i.e., neuroticism, extraversion-introversion, openness, agreeableness, and conscientiousness). When comparing vertical to horizontal motion trials, we found a positive correlation between neuroticism scores and regional activity in the left parieto-insular vestibular cortex (PIVC). For the same contrast, increased functional connectivity between the left PIVC and right amygdala was also detected as a function of higher neuroticism scores. Together, these findings provide new evidence that individual differences in personality traits linked to anxiety are significantly associated with changes in the activity and functional connectivity patterns within visuo-vestibular and anxiety-related systems during simulated vertical self-motion. Hum Brain Mapp 38:715-726, 2017. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
Neural Development Under Conditions of Spaceflight
NASA Technical Reports Server (NTRS)
Kosik, Kenneth S.; Steward, Oswald; Temple, Meredith D.; Denslow, Maria J.
2003-01-01
One of the key tasks the developing brain must learn is how to navigate within the environment. This skill depends on the brain's ability to establish memories of places and things in the environment so that it can form cognitive maps. Earth's gravity defines the plane of orientation of the spatial environment in which animals navigate, and cognitive maps are based on this plane of orientation. Given that experience during early development plays a key role in the development of other aspects of brain function, experience in a gravitational environment is likely to be essential for the proper organization of brain regions mediating learning and memory of spatial information. Since the hippocampus is the brain region responsible for cognitive mapping abilities, this study evaluated the development of hippocampal structure and function in rats that spent part of their early development in microgravity. Litters of male and female Sprague-Dawley rats were launched into space aboard the Space Shuttle Columbia on either postnatal day eight (P8) or 14 (P14) and remained in space for 16 days. Upon return to Earth, the rats were tested for their ability to remember spatial information and navigate using a variety of tests (the Morris water maze, a modified radial arm maze, and an open field apparatus). These rats were then tested physiologically to determine whether they exhibited normal synaptic plasticity in the hippocampus. In a separate group of rats (flight and controls), the hippocampus was analyzed using anatomical, molecular biological, and biochemical techniques immediately postlanding. There were remarkably few differences between the flight groups and their Earth-bound controls in either the navigation and spatial memory tasks or activity-induced synaptic plasticity. Microscopic and immunocytochemical analyses of the brain also did not reveal differences between flight animals and ground-based controls. These data suggest that, within the developmental window studied, microgravity has minimal long-term impact on cognitive mapping function and cellular substrates important for this function. Any differences due to development in microgravity were transient and returned to normal soon after return to Earth.
Individualized localization and cortical surface-based registration of intracranial electrodes
Dykstra, Andrew R.; Chan, Alexander M.; Quinn, Brian T.; Zepeda, Rodrigo; Keller, Corey J.; Cormier, Justine; Madsen, Joseph R.; Eskandar, Emad N.; Cash, Sydney S.
2011-01-01
In addition to its widespread clinical use, the intracranial electroencephalogram (iEEG) is increasingly being employed as a tool to map the neural correlates of normal cognitive function as well as for developing neuroprosthetics. Despite recent advances, and unlike other established brain mapping modalities (e.g. functional MRI, magneto- and electroencephalography), registering the iEEG with respect to neuroanatomy in individuals – and coregistering functional results across subjects – remains a significant challenge. Here we describe a method which coregisters high-resolution preoperative MRI with postoperative computerized tomography (CT) for the purpose of individualized functional mapping of both normal and pathological (e.g., interictal discharges and seizures) brain activity. Our method accurately (within 3mm, on average) localizes electrodes with respect to an individual’s neuroanatomy. Furthermore, we outline a principled procedure for either volumetric or surface-based group analyses. We demonstrate our method in five patients with medically-intractable epilepsy undergoing invasive monitoring of the seizure focus prior to its surgical removal. The straight-forward application of this procedure to all types of intracranial electrodes, robustness to deformations in both skull and brain, and the ability to compare electrode locations across groups of patients makes this procedure an important tool for basic scientists as well as clinicians. PMID:22155045
Individualized localization and cortical surface-based registration of intracranial electrodes.
Dykstra, Andrew R; Chan, Alexander M; Quinn, Brian T; Zepeda, Rodrigo; Keller, Corey J; Cormier, Justine; Madsen, Joseph R; Eskandar, Emad N; Cash, Sydney S
2012-02-15
In addition to its widespread clinical use, the intracranial electroencephalogram (iEEG) is increasingly being employed as a tool to map the neural correlates of normal cognitive function as well as for developing neuroprosthetics. Despite recent advances, and unlike other established brain-mapping modalities (e.g. functional MRI, magneto- and electroencephalography), registering the iEEG with respect to neuroanatomy in individuals-and coregistering functional results across subjects-remains a significant challenge. Here we describe a method which coregisters high-resolution preoperative MRI with postoperative computerized tomography (CT) for the purpose of individualized functional mapping of both normal and pathological (e.g., interictal discharges and seizures) brain activity. Our method accurately (within 3mm, on average) localizes electrodes with respect to an individual's neuroanatomy. Furthermore, we outline a principled procedure for either volumetric or surface-based group analyses. We demonstrate our method in five patients with medically-intractable epilepsy undergoing invasive monitoring of the seizure focus prior to its surgical removal. The straight-forward application of this procedure to all types of intracranial electrodes, robustness to deformations in both skull and brain, and the ability to compare electrode locations across groups of patients makes this procedure an important tool for basic scientists as well as clinicians. Copyright © 2011 Elsevier Inc. All rights reserved.
Novel techniques of real-time blood flow and functional mapping: technical note.
Kamada, Kyousuke; Ogawa, Hiroshi; Saito, Masato; Tamura, Yukie; Anei, Ryogo; Kapeller, Christoph; Hayashi, Hideaki; Prueckl, Robert; Guger, Christoph
2014-01-01
There are two main approaches to intraoperative monitoring in neurosurgery. One approach is related to fluorescent phenomena and the other is related to oscillatory neuronal activity. We developed novel techniques to visualize blood flow (BF) conditions in real time, based on indocyanine green videography (ICG-VG) and the electrophysiological phenomenon of high gamma activity (HGA). We investigated the use of ICG-VG in four patients with moyamoya disease and two with arteriovenous malformation (AVM), and we investigated the use of real-time HGA mapping in four patients with brain tumors who underwent lesion resection with awake craniotomy. Real-time data processing of ICG-VG was based on perfusion imaging, which generated parameters including arrival time (AT), mean transit time (MTT), and BF of brain surface vessels. During awake craniotomy, we analyzed the frequency components of brain oscillation and performed real-time HGA mapping to identify functional areas. Processed results were projected on a wireless monitor linked to the operating microscope. After revascularization for moyamoya disease, AT and BF were significantly shortened and increased, respectively, suggesting hyperperfusion. Real-time fusion images on the wireless monitor provided anatomical, BF, and functional information simultaneously, and allowed the resection of AVMs under the microscope. Real-time HGA mapping during awake craniotomy rapidly indicated the eloquent areas of motor and language function and significantly shortened the operation time. These novel techniques, which we introduced might improve the reliability of intraoperative monitoring and enable the development of rational and objective surgical strategies.
Novel Techniques of Real-time Blood Flow and Functional Mapping: Technical Note
KAMADA, Kyousuke; OGAWA, Hiroshi; SAITO, Masato; TAMURA, Yukie; ANEI, Ryogo; KAPELLER, Christoph; HAYASHI, Hideaki; PRUECKL, Robert; GUGER, Christoph
2014-01-01
There are two main approaches to intraoperative monitoring in neurosurgery. One approach is related to fluorescent phenomena and the other is related to oscillatory neuronal activity. We developed novel techniques to visualize blood flow (BF) conditions in real time, based on indocyanine green videography (ICG-VG) and the electrophysiological phenomenon of high gamma activity (HGA). We investigated the use of ICG-VG in four patients with moyamoya disease and two with arteriovenous malformation (AVM), and we investigated the use of real-time HGA mapping in four patients with brain tumors who underwent lesion resection with awake craniotomy. Real-time data processing of ICG-VG was based on perfusion imaging, which generated parameters including arrival time (AT), mean transit time (MTT), and BF of brain surface vessels. During awake craniotomy, we analyzed the frequency components of brain oscillation and performed real-time HGA mapping to identify functional areas. Processed results were projected on a wireless monitor linked to the operating microscope. After revascularization for moyamoya disease, AT and BF were significantly shortened and increased, respectively, suggesting hyperperfusion. Real-time fusion images on the wireless monitor provided anatomical, BF, and functional information simultaneously, and allowed the resection of AVMs under the microscope. Real-time HGA mapping during awake craniotomy rapidly indicated the eloquent areas of motor and language function and significantly shortened the operation time. These novel techniques, which we introduced might improve the reliability of intraoperative monitoring and enable the development of rational and objective surgical strategies. PMID:25263624
2016-01-01
When blood oxygenation level-dependent (BOLD) contrast functional magnetic resonance imaging (fMRI) was discovered in the early 1990s, it provoked an explosion of interest in exploring human cognition, using brain mapping techniques based on MRI. Standards for data acquisition and analysis were rapidly put in place, in order to assist comparison of results across laboratories. Recently, MRI data acquisition capabilities have improved dramatically, inviting a rethink of strategies for relating functional brain activity at the systems level with its neuronal substrates and functional connections. This paper reviews the established capabilities of BOLD contrast fMRI, the perceived weaknesses of major methods of analysis, and current results that may provide insights into improved brain modelling. These results have inspired the use of in vivo myeloarchitecture for localizing brain activity, individual subject analysis without spatial smoothing and mapping of changes in cerebral blood volume instead of BOLD activation changes. The apparent fundamental limitations of all methods based on nuclear magnetic resonance are also discussed. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’. PMID:27574303
Turner, Robert
2016-10-05
When blood oxygenation level-dependent (BOLD) contrast functional magnetic resonance imaging (fMRI) was discovered in the early 1990s, it provoked an explosion of interest in exploring human cognition, using brain mapping techniques based on MRI. Standards for data acquisition and analysis were rapidly put in place, in order to assist comparison of results across laboratories. Recently, MRI data acquisition capabilities have improved dramatically, inviting a rethink of strategies for relating functional brain activity at the systems level with its neuronal substrates and functional connections. This paper reviews the established capabilities of BOLD contrast fMRI, the perceived weaknesses of major methods of analysis, and current results that may provide insights into improved brain modelling. These results have inspired the use of in vivo myeloarchitecture for localizing brain activity, individual subject analysis without spatial smoothing and mapping of changes in cerebral blood volume instead of BOLD activation changes. The apparent fundamental limitations of all methods based on nuclear magnetic resonance are also discussed.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'. © 2016 The Authors.
DICCCOL: Dense Individualized and Common Connectivity-Based Cortical Landmarks
Zhu, Dajiang; Guo, Lei; Jiang, Xi; Zhang, Tuo; Zhang, Degang; Chen, Hanbo; Deng, Fan; Faraco, Carlos; Jin, Changfeng; Wee, Chong-Yaw; Yuan, Yixuan; Lv, Peili; Yin, Yan; Hu, Xiaolei; Duan, Lian; Hu, Xintao; Han, Junwei; Wang, Lihong; Shen, Dinggang; Miller, L Stephen
2013-01-01
Is there a common structural and functional cortical architecture that can be quantitatively encoded and precisely reproduced across individuals and populations? This question is still largely unanswered due to the vast complexity, variability, and nonlinearity of the cerebral cortex. Here, we hypothesize that the common cortical architecture can be effectively represented by group-wise consistent structural fiber connections and take a novel data-driven approach to explore the cortical architecture. We report a dense and consistent map of 358 cortical landmarks, named Dense Individualized and Common Connectivity–based Cortical Landmarks (DICCCOLs). Each DICCCOL is defined by group-wise consistent white-matter fiber connection patterns derived from diffusion tensor imaging (DTI) data. Our results have shown that these 358 landmarks are remarkably reproducible over more than one hundred human brains and possess accurate intrinsically established structural and functional cross-subject correspondences validated by large-scale functional magnetic resonance imaging data. In particular, these 358 cortical landmarks can be accurately and efficiently predicted in a new single brain with DTI data. Thus, this set of 358 DICCCOL landmarks comprehensively encodes the common structural and functional cortical architectures, providing opportunities for many applications in brain science including mapping human brain connectomes, as demonstrated in this work. PMID:22490548
The Topographical Mapping in Drosophila Central Complex Network and Its Signal Routing
Chang, Po-Yen; Su, Ta-Shun; Shih, Chi-Tin; Lo, Chung-Chuan
2017-01-01
Neural networks regulate brain functions by routing signals. Therefore, investigating the detailed organization of a neural circuit at the cellular levels is a crucial step toward understanding the neural mechanisms of brain functions. To study how a complicated neural circuit is organized, we analyzed recently published data on the neural circuit of the Drosophila central complex, a brain structure associated with a variety of functions including sensory integration and coordination of locomotion. We discovered that, except for a small number of “atypical” neuron types, the network structure formed by the identified 194 neuron types can be described by only a few simple mathematical rules. Specifically, the topological mapping formed by these neurons can be reconstructed by applying a generation matrix on a small set of initial neurons. By analyzing how information flows propagate with or without the atypical neurons, we found that while the general pattern of signal propagation in the central complex follows the simple topological mapping formed by the “typical” neurons, some atypical neurons can substantially re-route the signal pathways, implying specific roles of these neurons in sensory signal integration. The present study provides insights into the organization principle and signal integration in the central complex. PMID:28443014
Parker, Jason G; Zalusky, Eric J; Kirbas, Cemil
2014-03-01
Accurate mapping of visual function and selective attention using fMRI is important in the study of human performance as well as in presurgical treatment planning of lesions in or near visual centers of the brain. Conjunctive visual search (CVS) is a useful tool for mapping visual function during fMRI because of its greater activation extent compared with high-capacity parallel search processes. The purpose of this work was to develop and evaluate a CVS that was capable of generating consistent activation in the basic and higher level visual areas of the brain by using a high number of distractors as well as an optimized contrast condition. Images from 10 healthy volunteers were analyzed and brain regions of greatest activation and deactivation were determined using a nonbiased decomposition of the results at the hemisphere, lobe, and gyrus levels. The results were quantified in terms of activation and deactivation extent and mean z-statistic. The proposed CVS was found to generate robust activation of the occipital lobe, as well as regions in the middle frontal gyrus associated with coordinating eye movements and in regions of the insula associated with task-level control and focal attention. As expected, the task demonstrated deactivation patterns commonly implicated in the default-mode network. Further deactivation was noted in the posterior region of the cerebellum, most likely associated with the formation of optimal search strategy. We believe the task will be useful in studies of visual and selective attention in the neuroscience community as well as in mapping visual function in clinical fMRI.
Optical mapping of brain activation in gambling disorders
NASA Astrophysics Data System (ADS)
Yuan, Zhen; Lin, Xiaohong
2018-02-01
In this study, fNIRS was utilized to identify the brain activation difference between pathological gamblers (PGs) and heathy controls (HCs). We inspected the hemodynamic changes in the prefrontal cortex using fNIRS recordings during the completion of executive function and decision making tasks. Our finding revealed that the PG and HC groups exhibited significant differences in brain activation.
Roux, Alexandre; Mellerio, Charles; Lechapt-Zalcman, Emmanuelle; Still, Megan; Zerah, Michel; Bourgeois, Marie; Pallud, Johan
2018-06-01
We report the surgical management of a lesional drug-resistant epilepsy caused by a meningioangiomatosis associated with a type IIIc focal cortical dysplasia located in the left supplementary motor area in a young male patient. A first anatomically based partial surgical resection was performed on an 11-year-old under general anesthesia without intraoperative mapping, which allowed for postoperative seizure control (Engel IA) for 6 years. The patient then exhibited intractable right sensatory and aphasic focal onset seizures despite 2 appropriate antiepileptic drugs. A second functional-based surgical resection was performed using intraoperative corticosubcortical functional mapping with direct electrical stimulation under awake conditions. A complete surgical resection was performed, and a left partial supplementary motor area syndrome was observed. At 6 months postoperatively, the patient is seizure free (Engel IA) with an ongoing decrease in antiepileptic drug therapy. Intraoperative functional brain mapping can be applied to preserve the brain function and networks around a meningioangiomatosis to facilitate the resection of potentially epileptogenic perilesional dysplastic cortex and to tailor the extent of resection to functional boundaries. Copyright © 2018 Elsevier Inc. All rights reserved.
Music Listening modulates Functional Connectivity and Information Flow in the Human Brain.
Karmonik, Christof; Brandt, Anthony; Anderson, Jeff; Brooks, Forrest; Lytle, Julie; Silverman, Elliott; Frazier, Jeff T
2016-07-27
Listening to familiar music has recently been reported to be beneficial during recovery from stroke. A better understanding of changes in functional connectivity and information flow is warranted in order to further optimize and target this approach through music therapy. Twelve healthy volunteers listened to seven different auditory samples during an fMRI scanning session: a musical piece chosen by the volunteer that evokes a strong emotional response (referred to as: "self-selected emotional"), two unfamiliar music pieces (Invention #1 by J. S. Bach* and Gagaku - Japanese classical opera, referred to as "unfamiliar"), the Bach piece repeated with visual guidance (DML: Directed Music Listening) and three spoken language pieces (unfamiliar African click language, an excerpt of emotionally charged language, and an unemotional reading of a news bulletin). Functional connectivity and betweenness (BTW) maps, a measure for information flow, were created with a graph-theoretical approach. Distinct variation in functional connectivity was found for different music pieces consistently for all subjects. Largest brain areas were recruited for processing self-selected music with emotional attachment or culturally unfamiliar music. Maps of information flow correlated significantly with fMRI BOLD activation maps (p<0.05). Observed differences in BOLD activation and functional connectivity may help explain previously observed beneficial effects in stroke recovery, as increased blood flow to damaged brain areas stimulated by active engagement through music listening may have supported a state more conducive to therapy.
Kim, Yongsoo; Yang, Guangyu Robert; Pradhan, Kith; Venkataraju, Kannan Umadevi; Bota, Mihail; García Del Molino, Luis Carlos; Fitzgerald, Greg; Ram, Keerthi; He, Miao; Levine, Jesse Maurica; Mitra, Partha; Huang, Z Josh; Wang, Xiao-Jing; Osten, Pavel
2017-10-05
The stereotyped features of neuronal circuits are those most likely to explain the remarkable capacity of the brain to process information and govern behaviors, yet it has not been possible to comprehensively quantify neuronal distributions across animals or genders due to the size and complexity of the mammalian brain. Here we apply our quantitative brain-wide (qBrain) mapping platform to document the stereotyped distributions of mainly inhibitory cell types. We discover an unexpected cortical organizing principle: sensory-motor areas are dominated by output-modulating parvalbumin-positive interneurons, whereas association, including frontal, areas are dominated by input-modulating somatostatin-positive interneurons. Furthermore, we identify local cell type distributions with more cells in the female brain in 10 out of 11 sexually dimorphic subcortical areas, in contrast to the overall larger brains in males. The qBrain resource can be further mined to link stereotyped aspects of neuronal distributions to known and unknown functions of diverse brain regions. Copyright © 2017 Elsevier Inc. All rights reserved.
Caspers, Svenja; Moebus, Susanne; Lux, Silke; Pundt, Noreen; Schütz, Holger; Mühleisen, Thomas W; Gras, Vincent; Eickhoff, Simon B; Romanzetti, Sandro; Stöcker, Tony; Stirnberg, Rüdiger; Kirlangic, Mehmet E; Minnerop, Martina; Pieperhoff, Peter; Mödder, Ulrich; Das, Samir; Evans, Alan C; Jöckel, Karl-Heinz; Erbel, Raimund; Cichon, Sven; Nöthen, Markus M; Sturma, Dieter; Bauer, Andreas; Jon Shah, N; Zilles, Karl; Amunts, Katrin
2014-01-01
The ongoing 1000 brains study (1000BRAINS) is an epidemiological and neuroscientific investigation of structural and functional variability in the human brain during aging. The two recruitment sources are the 10-year follow-up cohort of the German Heinz Nixdorf Recall (HNR) Study, and the HNR MultiGeneration Study cohort, which comprises spouses and offspring of HNR subjects. The HNR is a longitudinal epidemiological investigation of cardiovascular risk factors, with a comprehensive collection of clinical, laboratory, socioeconomic, and environmental data from population-based subjects aged 45-75 years on inclusion. HNR subjects underwent detailed assessments in 2000, 2006, and 2011, and completed annual postal questionnaires on health status. 1000BRAINS accesses these HNR data and applies a separate protocol comprising: neuropsychological tests of attention, memory, executive functions and language; examination of motor skills; ratings of personality, life quality, mood and daily activities; analysis of laboratory and genetic data; and state-of-the-art magnetic resonance imaging (MRI, 3 Tesla) of the brain. The latter includes (i) 3D-T1- and 3D-T2-weighted scans for structural analyses and myelin mapping; (ii) three diffusion imaging sequences optimized for diffusion tensor imaging, high-angular resolution diffusion imaging for detailed fiber tracking and for diffusion kurtosis imaging; (iii) resting-state and task-based functional MRI; and (iv) fluid-attenuated inversion recovery and MR angiography for the detection of vascular lesions and the mapping of white matter lesions. The unique design of 1000BRAINS allows: (i) comprehensive investigation of various influences including genetics, environment and health status on variability in brain structure and function during aging; and (ii) identification of the impact of selected influencing factors on specific cognitive subsystems and their anatomical correlates.
Functional Connectivity Bias in the Prefrontal Cortex of Psychopaths.
Contreras-Rodríguez, Oren; Pujol, Jesus; Batalla, Iolanda; Harrison, Ben J; Soriano-Mas, Carles; Deus, Joan; López-Solà, Marina; Macià, Dídac; Pera, Vanessa; Hernández-Ribas, Rosa; Pifarré, Josep; Menchón, José M; Cardoner, Narcís
2015-11-01
Psychopathy is characterized by a distinctive interpersonal style that combines callous-unemotional traits with inflexible and antisocial behavior. Traditional emotion-based perspectives link emotional impairment mostly to alterations in amygdala-ventromedial frontal circuits. However, these models alone cannot explain why individuals with psychopathy can regularly benefit from emotional information when placed on their focus of attention and why they are more resistant to interference from nonaffective contextual cues. The present study aimed to identify abnormal or distinctive functional links between and within emotional and cognitive brain systems in the psychopathic brain to characterize further the neural bases of psychopathy. High-resolution anatomic magnetic resonance imaging with a functional sequence acquired in the resting state was used to assess 22 subjects with psychopathy and 22 control subjects. Anatomic and functional connectivity alterations were investigated first using a whole-brain analysis. Brain regions showing overlapping anatomic and functional changes were examined further using seed-based functional connectivity mapping. Subjects with psychopathy showed gray matter reduction involving prefrontal cortex, paralimbic, and limbic structures. Anatomic changes overlapped with areas showing increased degree of functional connectivity at the medial-dorsal frontal cortex. Subsequent functional seed-based connectivity mapping revealed a pattern of reduced functional connectivity of prefrontal areas with limbic-paralimbic structures and enhanced connectivity within the dorsal frontal lobe in subjects with psychopathy. Our results suggest that a weakened link between emotional and cognitive domains in the psychopathic brain may combine with enhanced functional connections within frontal executive areas. The identified functional alterations are discussed in the context of potential contributors to the inflexible behavior displayed by individuals with psychopathy. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
Hart, Michael G; Ypma, Rolf J F; Romero-Garcia, Rafael; Price, Stephen J; Suckling, John
2016-06-01
Neuroanatomy has entered a new era, culminating in the search for the connectome, otherwise known as the brain's wiring diagram. While this approach has led to landmark discoveries in neuroscience, potential neurosurgical applications and collaborations have been lagging. In this article, the authors describe the ideas and concepts behind the connectome and its analysis with graph theory. Following this they then describe how to form a connectome using resting state functional MRI data as an example. Next they highlight selected insights into healthy brain function that have been derived from connectome analysis and illustrate how studies into normal development, cognitive function, and the effects of synthetic lesioning can be relevant to neurosurgery. Finally, they provide a précis of early applications of the connectome and related techniques to traumatic brain injury, functional neurosurgery, and neurooncology.
Detection of Brain Reorganization in Pediatric Multiple Sclerosis Using Functional MRI
2015-10-01
accomplish this, we apply comparative assessments of fMRI mappings of language, memory , and motor function, and performance on clinical neurocognitive...community at a target rate of 13 volunteers per quarter period; acquire fMRI data for language, memory , and visual-motor functions (months 3-12). c...consensus fMRI activation maps for language, memory , and visual-motor tasks (months 8-12). f) Subtask 1f. Prepare publication to disseminate our
Ren, Yudan; Nguyen, Vinh Thai; Guo, Lei; Guo, Christine Cong
2017-09-07
The brain is constantly monitoring and integrating both cues from the external world and signals generated intrinsically. These extrinsically and intrinsically-driven neural processes are thought to engage anatomically distinct regions, which are thought to constitute the extrinsic and intrinsic systems of the brain. While the specialization of extrinsic and intrinsic system is evident in primary and secondary sensory cortices, a systematic mapping of the whole brain remains elusive. Here, we characterized the extrinsic and intrinsic functional activities in the brain during naturalistic movie-viewing. Using a novel inter-subject functional correlation (ISFC) analysis, we found that the strength of ISFC shifts along the hierarchical organization of the brain. Primary sensory cortices appear to have strong inter-subject functional correlation, consistent with their role in processing exogenous information, while heteromodal regions that attend to endogenous processes have low inter-subject functional correlation. Those brain systems with higher intrinsic tendency show greater inter-individual variability, likely reflecting the aspects of brain connectivity architecture unique to individuals. Our study presents a novel framework for dissecting extrinsically- and intrinsically-driven processes, as well as examining individual differences in brain function during naturalistic stimulation.
Saletu, Bernd; Anderer, Peter; Saletu-Zyhlarz, Gerda M; Pascual-Marqui, Roberto D
2005-04-01
Different psychiatric disorders, such as schizophrenia with predominantly positive and negative symptomatology, major depression, generalized anxiety disorder, agoraphobia, obsessive-compulsive disorder, multi-infarct dementia, senile dementia of the Alzheimer type and alcohol dependence, show EEG maps that differ statistically both from each other and from normal controls. Representative drugs of the main psychopharmacological classes, such as sedative and non-sedative neuroleptics and antidepressants, tranquilizers, hypnotics, psychostimulants and cognition-enhancing drugs, induce significant and typical changes to normal human brain function, which in many variables are opposite to the above-mentioned differences between psychiatric patients and normal controls. Thus, by considering these differences between psychotropic drugs and placebo in normal subjects, as well as between mental disorder patients and normal controls, it may be possible to choose the optimum drug for a specific patient according to a key-lock principle, since the drug should normalize the deviant brain function. This is supported by 3-dimensional low-resolution brain electromagnetic tomography (LORETA), which identifies regions within the brain that are affected by psychiatric disorders and psychopharmacological substances.
Technical Aspects of Awake Craniotomy with Mapping for Brain Tumors in a Limited Resource Setting.
Leal, Rafael Teixeira Magalhaes; Barcellos, Bruno Mendonça; Landeiro, Jose Alberto
2018-05-01
Brain tumor surgery near or within eloquent regions is increasingly common and is associated with a high risk of neurologic injury. Awake craniotomy with mapping has been shown to be a valid method to preserve neurologic function and increase the extent of resection. However, the technique used varies greatly among centers. Most count on professionals such as neuropsychologists, speech therapists, neurophysiologists, or neurologists to help in intraoperative patient evaluation. We describe our technique with the sole participation of neurosurgeons and anesthesiologists. A retrospective review of 19 patients who underwent awake craniotomies for brain tumors between January 2013 and February 2017 at a tertiary university hospital was performed. We sought to identify and describe the most critical stages involved in this surgery as well as show the complications associated with our technique. Preoperative preparation, positioning, anesthesia, brain mapping, resection, and management of seizures and pain were stages deemed relevant to the accomplishment of an awake craniotomy. Sixteen percent of the patients developed new postoperative deficit. Seizures occurred in 24%. None led to awake craniotomy failure. We provide a thorough description of the technique used in awake craniotomies with mapping used in our institution, where the intraoperative patient evaluation is carried out solely by neurosurgeons and anesthesiologists. The absence of other specialized personnel and equipment does not necessarily preclude successful mapping during awake craniotomy. We hope to provide helpful information for those who wish to offer function-guided tumor resection in their own centers. Copyright © 2018 Elsevier Inc. All rights reserved.
Lesions causing freezing of gait localize to a cerebellar functional network
Fasano, Alfonso; Laganiere, Simon E.; Lam, Susy; Fox, Michael D.
2016-01-01
Objective Freezing of gait is a disabling symptom in Parkinson’s disease and related disorders, but the brain regions involved in symptom generation remain unclear. Here we analyze brain lesions causing acute onset freezing of gait to identify regions causally involved in symptom generation. Methods Fourteen cases of lesion-induced freezing of gait were identified from the literature and lesions were mapped to a common brain atlas. Because lesion-induced symptoms can come from sites connected to the lesion location, not just the lesion location itself, we also identified brain regions functionally connected to each lesion location. This technique, termed lesion network mapping, has been recently shown to identify regions involved in symptom generation across a variety of lesion-induced disorders. Results Lesion location was heterogeneous and no single region could be considered necessary for symptom generation. However, over 90% (13/14) of lesions were functionally connected to a focal area in the dorsal medial cerebellum. This cerebellar area overlapped previously recognized regions that are activated by locomotor tasks, termed the cerebellar locomotor region. Connectivity to this region was specific to lesions causing freezing of gait compared to lesions causing other movement disorders (hemichorea or asterixis). Interpretation Lesions causing freezing of gait are located within a common functional network characterized by connectivity to the cerebellar locomotor region. These results based on causal brain lesions complement prior neuroimaging studies in Parkinson’s disease patients, advancing our understanding of the brain regions involved in freezing of gait. PMID:28009063
Zhao, Yu; Ge, Fangfei; Liu, Tianming
2018-07-01
fMRI data decomposition techniques have advanced significantly from shallow models such as Independent Component Analysis (ICA) and Sparse Coding and Dictionary Learning (SCDL) to deep learning models such Deep Belief Networks (DBN) and Convolutional Autoencoder (DCAE). However, interpretations of those decomposed networks are still open questions due to the lack of functional brain atlases, no correspondence across decomposed or reconstructed networks across different subjects, and significant individual variabilities. Recent studies showed that deep learning, especially deep convolutional neural networks (CNN), has extraordinary ability of accommodating spatial object patterns, e.g., our recent works using 3D CNN for fMRI-derived network classifications achieved high accuracy with a remarkable tolerance for mistakenly labelled training brain networks. However, the training data preparation is one of the biggest obstacles in these supervised deep learning models for functional brain network map recognitions, since manual labelling requires tedious and time-consuming labours which will sometimes even introduce label mistakes. Especially for mapping functional networks in large scale datasets such as hundreds of thousands of brain networks used in this paper, the manual labelling method will become almost infeasible. In response, in this work, we tackled both the network recognition and training data labelling tasks by proposing a new iteratively optimized deep learning CNN (IO-CNN) framework with an automatic weak label initialization, which enables the functional brain networks recognition task to a fully automatic large-scale classification procedure. Our extensive experiments based on ABIDE-II 1099 brains' fMRI data showed the great promise of our IO-CNN framework. Copyright © 2018 Elsevier B.V. All rights reserved.
Increased power spectral density in resting-state pain-related brain networks in fibromyalgia.
Kim, Ji-Young; Kim, Seong-Ho; Seo, Jeehye; Kim, Sang-Hyon; Han, Seung Woo; Nam, Eon Jeong; Kim, Seong-Kyu; Lee, Hui Joong; Lee, Seung-Jae; Kim, Yang-Tae; Chang, Yongmin
2013-09-01
Fibromyalgia (FM), characterized by chronic widespread pain, is known to be associated with heightened responses to painful stimuli and atypical resting-state functional connectivity among pain-related regions of the brain. Previous studies of FM using resting-state functional magnetic resonance imaging (rs-fMRI) have focused on intrinsic functional connectivity, which maps the spatial distribution of temporal correlations among spontaneous low-frequency fluctuation in functional MRI (fMRI) resting-state data. In the current study, using rs-fMRI data in the frequency domain, we investigated the possible alteration of power spectral density (PSD) of low-frequency fluctuation in brain regions associated with central pain processing in patients with FM. rsfMRI data were obtained from 19 patients with FM and 20 age-matched healthy female control subjects. For each subject, the PSDs for each brain region identified from functional connectivity maps were computed for the frequency band of 0.01 to 0.25 Hz. For each group, the average PSD was determined for each brain region and a 2-sample t test was performed to determine the difference in power between the 2 groups. According to the results, patients with FM exhibited significantly increased frequency power in the primary somatosensory cortex (S1), supplementary motor area (SMA), dorsolateral prefrontal cortex, and amygdala. In patients with FM, the increase in PSD did not show an association with depression or anxiety. Therefore, our findings of atypical increased frequency power during the resting state in pain-related brain regions may implicate the enhanced resting-state baseline neural activity in several brain regions associated with pain processing in FM. Copyright © 2013 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.
Rewiring the connectome: Evidence and effects.
Bennett, Sophie H; Kirby, Alastair J; Finnerty, Gerald T
2018-05-01
Neuronal connections form the physical basis for communication in the brain. Recently, there has been much interest in mapping the "connectome" to understand how brain structure gives rise to brain function, and ultimately, to behaviour. These attempts to map the connectome have largely assumed that connections are stable once formed. Recent studies, however, indicate that connections in mammalian brains may undergo rewiring during learning and experience-dependent plasticity. This suggests that the connectome is more dynamic than previously thought. To what extent can neural circuitry be rewired in the healthy adult brain? The connectome has been subdivided into multiple levels of scale, from synapses and microcircuits through to long-range tracts. Here, we examine the evidence for rewiring at each level. We then consider the role played by rewiring during learning. We conclude that harnessing rewiring offers new avenues to treat brain diseases. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.
Not single brain areas but a network is involved in language: Applications in presurgical planning.
Alemi, Razieh; Batouli, Seyed Amir Hossein; Behzad, Ebrahim; Ebrahimpoor, Mitra; Oghabian, Mohammad Ali
2018-02-01
Language is an important human function, and is a determinant of the quality of life. In conditions such as brain lesions, disruption of the language function may occur, and lesion resection is a solution for that. Presurgical planning to determine the language-related brain areas would enhance the chances of language preservation after the operation; however, availability of a normative language template is essential. In this study, using data from 60 young individuals who were meticulously checked for mental and physical health, and using fMRI and robust imaging and data analysis methods, functional brain maps for the language production, perception and semantic were produced. The obtained templates showed that the language function should be considered as the product of the collaboration of a network of brain regions, instead of considering only few brain areas to be involved in that. This study has important clinical applications, and extends our knowledge on the neuroanatomy of the language function. Copyright © 2018 Elsevier B.V. All rights reserved.
Data-driven analysis of functional brain interactions during free listening to music and speech.
Fang, Jun; Hu, Xintao; Han, Junwei; Jiang, Xi; Zhu, Dajiang; Guo, Lei; Liu, Tianming
2015-06-01
Natural stimulus functional magnetic resonance imaging (N-fMRI) such as fMRI acquired when participants were watching video streams or listening to audio streams has been increasingly used to investigate functional mechanisms of the human brain in recent years. One of the fundamental challenges in functional brain mapping based on N-fMRI is to model the brain's functional responses to continuous, naturalistic and dynamic natural stimuli. To address this challenge, in this paper we present a data-driven approach to exploring functional interactions in the human brain during free listening to music and speech streams. Specifically, we model the brain responses using N-fMRI by measuring the functional interactions on large-scale brain networks with intrinsically established structural correspondence, and perform music and speech classification tasks to guide the systematic identification of consistent and discriminative functional interactions when multiple subjects were listening music and speech in multiple categories. The underlying premise is that the functional interactions derived from N-fMRI data of multiple subjects should exhibit both consistency and discriminability. Our experimental results show that a variety of brain systems including attention, memory, auditory/language, emotion, and action networks are among the most relevant brain systems involved in classic music, pop music and speech differentiation. Our study provides an alternative approach to investigating the human brain's mechanism in comprehension of complex natural music and speech.
Parés, D; Martínez-Vilalta, M; Ortiz, H; Soriano-Mas, C; Maestre-Gonzalez, Y; Pujol, J; Grande, L
2018-04-14
Voluntary anal sphincter function is driven by an extended network of brain structures, most of which are still unknown. Disturbances in this function may cause fecal incontinence. The aim of this study was to characterize the cerebral areas involved in voluntary contraction of the anorectal sphincter in healthy women and in a group of patients with fecal incontinence by using a standardized functional magnetic resonance imaging (fMRI) protocol. This comparative study included 12 healthy women (mean age 53.17 ± 4.93 years) and 12 women with fecal incontinence (56.25 ± 6.94 years). An MRI-compatible anal manometer was used to register voluntary external anal sphincter contraction. During brain fMRI imaging, participants were cued to perform 10-s series of self-paced anal sphincter contractions at an approximate rate of 1 Hz. Brain structures linked to anal sphincter contractions were mapped and the findings were compared between the 2 study groups. There were no differences in the evoked brain activity between the 2 groups. In healthy women, group fMRI analysis revealed significant activations in medial primary motor cortices, supplementary motor area, bilateral putamen, and cerebellum, as well as in the supramarginal gyrus and visual areas. In patients with fecal incontinence, the activation pattern involved similar regions without significant differences with healthy women. This brain fMRI-anorectal protocol was able to map the brain regions linked to voluntary anal sphincter function in healthy and women with fecal incontinence. © 2018 John Wiley & Sons Ltd.
Gahm, Jin Kyu; Shi, Yonggang
2018-01-01
Surface mapping methods play an important role in various brain imaging studies from tracking the maturation of adolescent brains to mapping gray matter atrophy patterns in Alzheimer’s disease. Popular surface mapping approaches based on spherical registration, however, have inherent numerical limitations when severe metric distortions are present during the spherical parameterization step. In this paper, we propose a novel computational framework for intrinsic surface mapping in the Laplace-Beltrami (LB) embedding space based on Riemannian metric optimization on surfaces (RMOS). Given a diffeomorphism between two surfaces, an isometry can be defined using the pullback metric, which in turn results in identical LB embeddings from the two surfaces. The proposed RMOS approach builds upon this mathematical foundation and achieves general feature-driven surface mapping in the LB embedding space by iteratively optimizing the Riemannian metric defined on the edges of triangular meshes. At the core of our framework is an optimization engine that converts an energy function for surface mapping into a distance measure in the LB embedding space, which can be effectively optimized using gradients of the LB eigen-system with respect to the Riemannian metrics. In the experimental results, we compare the RMOS algorithm with spherical registration using large-scale brain imaging data, and show that RMOS achieves superior performance in the prediction of hippocampal subfields and cortical gyral labels, and the holistic mapping of striatal surfaces for the construction of a striatal connectivity atlas from substantia nigra. PMID:29574399
Effect of brain shift on the creation of functional atlases for deep brain stimulation surgery
Pallavaram, Srivatsan; Remple, Michael S.; Neimat, Joseph S.; Kao, Chris; Konrad, Peter E.; D’Haese, Pierre-François
2011-01-01
Purpose In the recent past many groups have tried to build functional atlases of the deep brain using intra-operatively acquired information such as stimulation responses or micro-electrode recordings. An underlying assumption in building such atlases is that anatomical structures do not move between pre-operative imaging and intra-operative recording. In this study, we present evidences that this assumption is not valid. We quantify the effect of brain shift between pre-operative imaging and intra-operative recording on the creation of functional atlases using intra-operative somatotopy recordings and stimulation response data. Methods A total of 73 somatotopy points from 24 bilateral subthalamic nucleus (STN) implantations and 52 eye deviation stimulation response points from 17 bilateral STN implantations were used. These points were spatially normalized on a magnetic resonance imaging (MRI) atlas using a fully automatic non-rigid registration algorithm. Each implantation was categorized as having low, medium or large brain shift based on the amount of pneumocephalus visible on post-operative CT. The locations of somatotopy clusters and stimulation maps were analyzed for each category. Results The centroid of the large brain shift cluster of the somatotopy data (posterior, lateral, inferior: 3.06, 11.27, 5.36 mm) was found posterior, medial and inferior to that of the medium cluster (2.90, 13.57, 4.53 mm) which was posterior, medial and inferior to that of the low shift cluster (1.94, 13.92, 3.20 mm). The coordinates are referenced with respect to the mid-commissural point. Euclidean distances between the centroids were 1.68, 2.44 and 3.59 mm, respectively for low-medium, medium-large and low-large shift clusters. We found similar trends for the positions of the stimulation maps. The Euclidian distance between the highest probability locations on the low and medium-large shift maps was 4.06 mm. Conclusion The effect of brain shift in deep brain stimulation (DBS) surgery has been demonstrated using intra-operative somatotopy recordings as well as stimulation response data. The results not only indicate that considerable brain shift happens before micro-electrode recordings in DBS but also that brain shift affects the creation of accurate functional atlases. Therefore, care must be taken when building and using such atlases of intra-operative data and also when using intra-operative data to validate anatomical atlases. PMID:20033503
Towards mapping the brain connectome in depression: functional connectivity by perfusion SPECT.
Gardner, Ann; Åstrand, Disa; Öberg, Johanna; Jacobsson, Hans; Jonsson, Cathrine; Larsson, Stig; Pagani, Marco
2014-08-30
Several studies have demonstrated altered brain functional connectivity in the resting state in depression. However, no study has investigated interregional networking in patients with persistent depressive disorder (PDD). The aim of this study was to assess differences in brain perfusion distribution and connectivity between large groups of patients and healthy controls. Participants comprised 91 patients with PDD and 65 age- and sex-matched healthy controls. Resting state perfusion was investigated by single photon emission computed tomography, and group differences were assessed by Statistical Parametric Mapping. Brain connectivity was explored through a voxel-wise interregional correlation analysis using as covariate of interest the normalized values of clusters of voxels in which perfusion differences were found in group analysis. Significantly increased regional brain perfusion distribution covering a large part of the cerebellum was observed in patients as compared with controls. Patients showed a significant negative functional connectivity between the cerebellar cluster and caudate, bilaterally. This study demonstrated inverse relative perfusion between the cerebellum and the caudate in PDD. Functional uncoupling may be associated with a dysregulation between the role of the cerebellum in action control and of the caudate in action selection, initiation and decision making in the patients. The potential impact of the resting state condition and the possibility of mitochondrial impairment are discussed. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.
Liu, Chunyan; Wang, Jiaojian; Hou, Yue; Qi, Zhigang; Wang, Li; Zhan, Shuqin; Wang, Rong; Wang, Yuping
2018-05-01
The hubs of the brain network play a key role in integrating and transferring information between different functional modules. However, whether the changed pattern in functional network hubs contributes to the onset of leg discomfort symptoms in restless legs syndrome (RLS) patients remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory methods, we investigated whether alterations of hubs can be detected in RLS. First, we constructed the whole-brain voxelwise functional connectivity and calculated a functional connectivity strength (FCS) map in each of 16 drug-naive idiopathic RLS patients and 26 gender- and age-matched healthy control (HC) subjects. Next, a two-sample t test was applied to compare the FCS maps between HC and RLS patients, and to identify significant changes in FCS in RLS patients. To further elucidate the corresponding changes in the functional connectivity patterns of the aberrant hubs in RLS patients, whole-brain resting-state functional connectivity analyses for the hub areas were performed. The hub analysis revealed decreased FCS in the cuneus, fusiform gyrus, paracentral lobe, and precuneus, and increased FCS in the superior frontal gyrus and thalamus in idiopathic drug-naive RLS patients. Subsequent functional connectivity analyses revealed decreased functional connectivity in sensorimotor and visual processing networks and increased functional connectivity in the affective cognitive network and cerebellar-thalamic circuit. Furthermore, the mean FCS value in the superior frontal gyrus was significantly correlated with Hamilton Anxiety Rating Scale scores in RLS patients, and the mean FCS value in the fusiform gyrus was significantly correlated with Hamilton Depression Rating Scale scores. These findings may provide novel insight into the pathophysiology of RLS. Copyright © 2018 Elsevier B.V. All rights reserved.
Multichannel optical mapping: investigation of depth information
NASA Astrophysics Data System (ADS)
Sase, Ichiro; Eda, Hideo; Seiyama, Akitoshi; Tanabe, Hiroki C.; Takatsuki, Akira; Yanagida, Toshio
2001-06-01
Near infrared (NIR) light has become a powerful tool for non-invasive imaging of human brain activity. Many systems have been developed to capture the changes in regional brain blood flow and hemoglobin oxygenation, which occur in the human cortex in response to neural activity. We have developed a multi-channel reflectance imaging system, which can be used as a `mapping device' and also as a `multi-channel spectrophotometer'. In the present study, we visualized changes in the hemodynamics of the human occipital region in multiple ways. (1) Stimulating left and right primary visual cortex independently by showing sector shaped checkerboards sequentially over the contralateral visual field, resulted in corresponding changes in the hemodynamics observed by `mapping' measurement. (2) Simultaneous measurement of functional-MRI and NIR (changes in total hemoglobin) during visual stimulation showed good spatial and temporal correlation with each other. (3) Placing multiple channels densely over the occipital region demonstrated spatial patterns more precisely, and depth information was also acquired by placing each pair of illumination and detection fibers at various distances. These results indicate that optical method can provide data for 3D analysis of human brain functions.
Stolzberg, Daniel; Wong, Carmen; Butler, Blake E; Lomber, Stephen G
2017-10-15
Brain atlases play an important role in effectively communicating results from neuroimaging studies in a standardized coordinate system. Furthermore, brain atlases extend analysis of functional magnetic resonance imaging (MRI) data by delineating regions of interest over which to evaluate the extent of functional activation as well as measures of inter-regional connectivity. Here, we introduce a three-dimensional atlas of the cat cerebral cortex based on established cytoarchitectonic and electrophysiological findings. In total, 71 cerebral areas were mapped onto the gray matter (GM) of an averaged T1-weighted structural MRI acquired at 7 T from eight adult domestic cats. In addition, a nonlinear registration procedure was used to generate a common template brain as well as GM, white matter, and cerebral spinal fluid tissue probability maps to facilitate tissue segmentation as part of the standard preprocessing pipeline for MRI data analysis. The atlas and associated files can also be used for planning stereotaxic surgery and for didactic purposes. © 2017 Wiley Periodicals, Inc.
Wang, Nizhuan; Chang, Chunqi; Zeng, Weiming; Shi, Yuhu; Yan, Hongjie
2017-01-01
Independent component analysis (ICA) has been widely used in functional magnetic resonance imaging (fMRI) data analysis to evaluate functional connectivity of the brain; however, there are still some limitations on ICA simultaneously handling neuroimaging datasets with diverse acquisition parameters, e.g., different repetition time, different scanner, etc. Therefore, it is difficult for the traditional ICA framework to effectively handle ever-increasingly big neuroimaging datasets. In this research, a novel feature-map based ICA framework (FMICA) was proposed to address the aforementioned deficiencies, which aimed at exploring brain functional networks (BFNs) at different scales, e.g., the first level (individual subject level), second level (intragroup level of subjects within a certain dataset) and third level (intergroup level of subjects across different datasets), based only on the feature maps extracted from the fMRI datasets. The FMICA was presented as a hierarchical framework, which effectively made ICA and constrained ICA as a whole to identify the BFNs from the feature maps. The simulated and real experimental results demonstrated that FMICA had the excellent ability to identify the intergroup BFNs and to characterize subject-specific and group-specific difference of BFNs from the independent component feature maps, which sharply reduced the size of fMRI datasets. Compared with traditional ICAs, FMICA as a more generalized framework could efficiently and simultaneously identify the variant BFNs at the subject-specific, intragroup, intragroup-specific and intergroup levels, implying that FMICA was able to handle big neuroimaging datasets in neuroscience research.
Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity
Murugesan, Sugeerth; Bouchard, Kristopher; Brown, Jesse A.; ...
2016-05-09
Here, we present Brain Modulyzer, an interactive visual exploration tool for functional magnetic resonance imaging (fMRI) brain scans, aimed at analyzing the correlation between different brain regions when resting or when performing mental tasks. Brain Modulyzer combines multiple coordinated views—such as heat maps, node link diagrams, and anatomical views—using brushing and linking to provide an anatomical context for brain connectivity data. Integrating methods from graph theory and analysis, e.g., community detection and derived graph measures, makes it possible to explore the modular and hierarchical organization of functional brain networks. Providing immediate feedback by displaying analysis results instantaneously while changing parametersmore » gives neuroscientists a powerful means to comprehend complex brain structure more effectively and efficiently and supports forming hypotheses that can then be validated via statistical analysis. In order to demonstrate the utility of our tool, we also present two case studies—exploring progressive supranuclear palsy, as well as memory encoding and retrieval« less
Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity
DOE Office of Scientific and Technical Information (OSTI.GOV)
Murugesan, Sugeerth; Bouchard, Kristopher; Brown, Jesse A.
Here, we present Brain Modulyzer, an interactive visual exploration tool for functional magnetic resonance imaging (fMRI) brain scans, aimed at analyzing the correlation between different brain regions when resting or when performing mental tasks. Brain Modulyzer combines multiple coordinated views—such as heat maps, node link diagrams, and anatomical views—using brushing and linking to provide an anatomical context for brain connectivity data. Integrating methods from graph theory and analysis, e.g., community detection and derived graph measures, makes it possible to explore the modular and hierarchical organization of functional brain networks. Providing immediate feedback by displaying analysis results instantaneously while changing parametersmore » gives neuroscientists a powerful means to comprehend complex brain structure more effectively and efficiently and supports forming hypotheses that can then be validated via statistical analysis. In order to demonstrate the utility of our tool, we also present two case studies—exploring progressive supranuclear palsy, as well as memory encoding and retrieval« less
High-field fMRI unveils orientation columns in humans.
Yacoub, Essa; Harel, Noam; Ugurbil, Kâmil
2008-07-29
Functional (f)MRI has revolutionized the field of human brain research. fMRI can noninvasively map the spatial architecture of brain function via localized increases in blood flow after sensory or cognitive stimulation. Recent advances in fMRI have led to enhanced sensitivity and spatial accuracy of the measured signals, indicating the possibility of detecting small neuronal ensembles that constitute fundamental computational units in the brain, such as cortical columns. Orientation columns in visual cortex are perhaps the best known example of such a functional organization in the brain. They cannot be discerned via anatomical characteristics, as with ocular dominance columns. Instead, the elucidation of their organization requires functional imaging methods. However, because of insufficient sensitivity, spatial accuracy, and image resolution of the available mapping techniques, thus far, they have not been detected in humans. Here, we demonstrate, by using high-field (7-T) fMRI, the existence and spatial features of orientation- selective columns in humans. Striking similarities were found with the known spatial features of these columns in monkeys. In addition, we found that a larger number of orientation columns are devoted to processing orientations around 90 degrees (vertical stimuli with horizontal motion), whereas relatively similar fMRI signal changes were observed across any given active column. With the current proliferation of high-field MRI systems and constant evolution of fMRI techniques, this study heralds the exciting prospect of exploring unmapped and/or unknown columnar level functional organizations in the human brain.
NASA Astrophysics Data System (ADS)
Li, Ting; Zhao, Yue; Li, Kai; Sun, Yunlong
2014-03-01
The low frequency oscillation (LFO) around 0.1 Hz has been observed recently in cerebral hemodynamic signals during rest/sleep, enhanced breathing, and head- up-tilting, showing that cerebral autoregulation can be accessed by LFOs. However, many brain function researches require direct measurement of LFOs during specified brain function activities. This pilot study explored using near-infrared spectroscopy/imaging (NIRS) to noninvasively and simultaneously detect LFOs of prefrontal cerebral hemodynamics (i.e., oxygenated/deoxygenated/total hemoglobin concentration: △[oxy-Hb]/ △[deoxy-Hb]/ △[tot-Hb]) during N-back visual verbal working memory task. The LFOs were extracted from the measured variables using power spectral analysis. We found the brain activation sites struck clear LFOs while other sites did not. The LFO of △[deoxy-Hb] acted as a negative pike and ranged in (0.05, 0.1) Hz, while LFOs of △[oxy-Hb] and △[tot-Hb] acted as a positive pike and ranged in (0.1, 0.15) Hz. The amplitude difference and frequency lag between △[deoxy-Hb] and △[oxy-Hb]/ △[tot-Hb] produced a more focused and sensitive activation map compare to hemodynamic amplitude-quantified activation maps. This study observed LFOs in brain activities and showed strong potential of LFOs in accessing brain functions.
Resting state brain networks and their implications in neurodegenerative disease
NASA Astrophysics Data System (ADS)
Sohn, William S.; Yoo, Kwangsun; Kim, Jinho; Jeong, Yong
2012-10-01
Neurons are the basic units of the brain, and form network by connecting via synapses. So far, there have been limited ways to measure the brain networks. Recently, various imaging modalities are widely used for this purpose. In this paper, brain network mapping using resting state fMRI will be introduced with several applications including neurodegenerative disease such as Alzheimer's disease, frontotemporal lobar degeneration and Parkinson's disease. The resting functional connectivity using intrinsic functional connectivity in mouse is useful since we can take advantage of perturbation or stimulation of certain nodes of the network. The study of brain connectivity will open a new era in understanding of brain and diseases thus will be an essential foundation for future research.
Resting-State Functional Magnetic Resonance Imaging for Language Preoperative Planning
Branco, Paulo; Seixas, Daniela; Deprez, Sabine; Kovacs, Silvia; Peeters, Ronald; Castro, São L.; Sunaert, Stefan
2016-01-01
Functional magnetic resonance imaging (fMRI) is a well-known non-invasive technique for the study of brain function. One of its most common clinical applications is preoperative language mapping, essential for the preservation of function in neurosurgical patients. Typically, fMRI is used to track task-related activity, but poor task performance and movement artifacts can be critical limitations in clinical settings. Recent advances in resting-state protocols open new possibilities for pre-surgical mapping of language potentially overcoming these limitations. To test the feasibility of using resting-state fMRI instead of conventional active task-based protocols, we compared results from fifteen patients with brain lesions while performing a verb-to-noun generation task and while at rest. Task-activity was measured using a general linear model analysis and independent component analysis (ICA). Resting-state networks were extracted using ICA and further classified in two ways: manually by an expert and by using an automated template matching procedure. The results revealed that the automated classification procedure correctly identified language networks as compared to the expert manual classification. We found a good overlay between task-related activity and resting-state language maps, particularly within the language regions of interest. Furthermore, resting-state language maps were as sensitive as task-related maps, and had higher specificity. Our findings suggest that resting-state protocols may be suitable to map language networks in a quick and clinically efficient way. PMID:26869899
Functional connectivity in the mouse brain imaged by B-mode photoacoustic microscopy
NASA Astrophysics Data System (ADS)
Nasiriavanaki, Mohammadreza; Xing, Wenxin; Xia, Jun; Wang, Lihong V.
2014-03-01
The increasing use of mouse models for human brain disease studies, coupled with the fact that existing functional imaging modalities cannot be easily applied to mice, presents an emerging need for a new functional imaging modality. Utilizing acoustic-resolution photoacoustic microscopy (AR-PAM), we imaged spontaneous cerebral hemodynamic fluctuations and their associated functional connections in the mouse brain. The images were acquired noninvasively in B-scan mode with a fast frame rate, a large field of view, and a high spatial resolution. At a location relative to the bregma 0, correlations were investigated inter-hemispherically between bilaterally homologous regions, as well as intra-hemispherically within the same functional regions. The functional connectivity in different functional regions was studied. The locations of these regions agreed well with the Paxinos mouse brain atlas. The functional connectivity map obtained in this study can then be used in the investigation of brain disorders such as stroke, Alzheimer's, schizophrenia, multiple sclerosis, autism, and epilepsy. Our experiments show that photoacoustic microscopy is capable to detect connectivities between different functional regions in B-scan mode, promising a powerful functional imaging modality for future brain research.
Parker, Jason G; Zalusky, Eric J; Kirbas, Cemil
2014-01-01
Background Accurate mapping of visual function and selective attention using fMRI is important in the study of human performance as well as in presurgical treatment planning of lesions in or near visual centers of the brain. Conjunctive visual search (CVS) is a useful tool for mapping visual function during fMRI because of its greater activation extent compared with high-capacity parallel search processes. Aims The purpose of this work was to develop and evaluate a CVS that was capable of generating consistent activation in the basic and higher level visual areas of the brain by using a high number of distractors as well as an optimized contrast condition. Materials and methods Images from 10 healthy volunteers were analyzed and brain regions of greatest activation and deactivation were determined using a nonbiased decomposition of the results at the hemisphere, lobe, and gyrus levels. The results were quantified in terms of activation and deactivation extent and mean z-statistic. Results The proposed CVS was found to generate robust activation of the occipital lobe, as well as regions in the middle frontal gyrus associated with coordinating eye movements and in regions of the insula associated with task-level control and focal attention. As expected, the task demonstrated deactivation patterns commonly implicated in the default-mode network. Further deactivation was noted in the posterior region of the cerebellum, most likely associated with the formation of optimal search strategy. Conclusion We believe the task will be useful in studies of visual and selective attention in the neuroscience community as well as in mapping visual function in clinical fMRI. PMID:24683515
State space modeling of time-varying contemporaneous and lagged relations in connectivity maps.
Molenaar, Peter C M; Beltz, Adriene M; Gates, Kathleen M; Wilson, Stephen J
2016-01-15
Most connectivity mapping techniques for neuroimaging data assume stationarity (i.e., network parameters are constant across time), but this assumption does not always hold true. The authors provide a description of a new approach for simultaneously detecting time-varying (or dynamic) contemporaneous and lagged relations in brain connectivity maps. Specifically, they use a novel raw data likelihood estimation technique (involving a second-order extended Kalman filter/smoother embedded in a nonlinear optimizer) to determine the variances of the random walks associated with state space model parameters and their autoregressive components. The authors illustrate their approach with simulated and blood oxygen level-dependent functional magnetic resonance imaging data from 30 daily cigarette smokers performing a verbal working memory task, focusing on seven regions of interest (ROIs). Twelve participants had dynamic directed functional connectivity maps: Eleven had one or more time-varying contemporaneous ROI state loadings, and one had a time-varying autoregressive parameter. Compared to smokers without dynamic maps, smokers with dynamic maps performed the task with greater accuracy. Thus, accurate detection of dynamic brain processes is meaningfully related to behavior in a clinical sample. Published by Elsevier Inc.
Lisowska, Anna; Rekik, Islem
2018-06-21
Diagnosis of brain dementia, particularly early mild cognitive impairment (eMCI), is critical for early intervention to prevent the onset of Alzheimer's Disease (AD), where cognitive decline is severe and irreversible. There is a large body of machine-learning based research investigating how dementia alters brain connectivity, mainly using structural (derived from diffusion MRI) and functional (derived from resting-state functional MRI) brain connectomic data. However, how early dementia affects cortical brain connections in morphology remains largely unexplored. To fill this gap, we propose a joint morphological brain multiplexes pairing and mapping strategy for early MCI detection, where a brain multiplex not only encodes the similarity in morphology between pairs of brain regions, but also a pair of brain morphological networks. Experimental results confirm that the proposed framework outperforms in classification accuracy several state-of-the-art methods. More importantly, we unprecedentedly identified most discriminative brain morphological networks between eMCI and NC, which included the paired views derived from maximum principal curvature and the sulcal depth for the left hemisphere and sulcal depth and the average curvature for the right hemisphere. We also identified the most highly correlated morphological brain connections in our cohort, which included the (pericalcarine cortex, insula cortex) on the maximum principal curvature view, (entorhinal cortex, insula cortex) on the mean sulcal depth view, and (entorhinal cortex, pericalcarine cortex) on the mean average curvature view, for both hemispheres. These highly correlated morphological connections might serve as biomarkers for early MCI diagnosis.
Kozák, Lajos R; van Graan, Louis André; Chaudhary, Umair J; Szabó, Ádám György; Lemieux, Louis
2017-12-01
Generally, the interpretation of functional MRI (fMRI) activation maps continues to rely on assessing their relationship to anatomical structures, mostly in a qualitative and often subjective way. Recently, the existence of persistent and stable brain networks of functional nature has been revealed; in particular these so-called intrinsic connectivity networks (ICNs) appear to link patterns of resting state and task-related state connectivity. These networks provide an opportunity of functionally-derived description and interpretation of fMRI maps, that may be especially important in cases where the maps are predominantly task-unrelated, such as studies of spontaneous brain activity e.g. in the case of seizure-related fMRI maps in epilepsy patients or sleep states. Here we present a new toolbox (ICN_Atlas) aimed at facilitating the interpretation of fMRI data in the context of ICN. More specifically, the new methodology was designed to describe fMRI maps in function-oriented, objective and quantitative way using a set of 15 metrics conceived to quantify the degree of 'engagement' of ICNs for any given fMRI-derived statistical map of interest. We demonstrate that the proposed framework provides a highly reliable quantification of fMRI activation maps using a publicly available longitudinal (test-retest) resting-state fMRI dataset. The utility of the ICN_Atlas is also illustrated on a parametric task-modulation fMRI dataset, and on a dataset of a patient who had repeated seizures during resting-state fMRI, confirmed on simultaneously recorded EEG. The proposed ICN_Atlas toolbox is freely available for download at http://icnatlas.com and at http://www.nitrc.org for researchers to use in their fMRI investigations. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Chiu, Hou-Chang
2009-06-01
The brain is the window of the artistic mind. Brain activities lead to the understanding of the outside world by perception and cognition, and the enjoyment of the artistic wonders. This article will demonstrate how different brain areas are responsible for the creative abilities of painting, music, and literature. Due to the advancement in neuroscientic techniques such as functional MRI, brain electric activity mapping, etc, we explore and understand the brain areas that are responsible for cognition and artistic creation. We also understand the functional localization of mental activities from neurological patients with lesions in different brain areas. On the other hand, the artists had produced great works in a way similar to finding the related brain areas in the stimulation experiments. Therefore, many neuroscientists have praised that artists are outstanding neurologists.
Recruitment of prefrontal-striatal circuit in response to skilled motor challenge.
Guo, Yumei; Wang, Zhuo; Prathap, Sandhya; Holschneider, Daniel P
2017-12-13
A variety of physical fitness regimens have been shown to improve cognition, including executive function, yet our understanding of which parameters of motor training are important in optimizing outcomes remains limited. We used functional brain mapping to compare the ability of two motor challenges to acutely recruit the prefrontal-striatal circuit. The two motor tasks - walking in a complex running wheel with irregularly spaced rungs or walking in a running wheel with a smooth internal surface - differed only in the extent of skill required for their execution. Cerebral perfusion was mapped in rats by intravenous injection of [C]-iodoantipyrine during walking in either a motorized complex wheel or in a simple wheel. Regional cerebral blood flow (rCBF) was quantified by whole-brain autoradiography and analyzed in three-dimensional reconstructed brains by statistical parametric mapping and seed-based functional connectivity. Skilled or simple walking compared with rest, increased rCBF in regions of the motor circuit, somatosensory and visual cortex, as well as the hippocampus. Significantly greater rCBF increases were noted during skilled walking than for simple walking. Skilled walking, unlike simple walking or the resting condition, was associated with a significant positive functional connectivity in the prefrontal-striatal circuit (prelimbic cortex-dorsomedial striatum) and greater negative functional connectivity in the prefrontal-hippocampal circuit. Our findings suggest that the level of skill of a motor training task determines the extent of functional recruitment of the prefrontal-corticostriatal circuit, with implications for a new approach in neurorehabilitation that uses circuit-specific neuroplasticity to improve motor and cognitive functions.
Febo, Marcelo; Ferris, Craig F.
2014-01-01
Oxytocin and vasopressin modulate a range of species typical behavioral functions that include social recognition, maternal-infant attachment, and modulation of memory, offensive aggression, defensive fear reactions, and reward seeking. We have employed novel functional magnetic resonance mapping techniques in awake rats to explore the roles of these neuropeptides in the maternal and non-maternal brain. Results from the functional neuroimaging studies that are summarized here have directly and indirectly confirmed and supported previous findings. Oxytocin is released within the lactating rat brain during suckling stimulation and activates specific subcortical networks in the maternal brain. Both vasopressin and oxytocin modulate brain regions involved unconditioned fear, processing of social stimuli and the expression of agonistic behaviors. Across studies there are relatively consistent brain networks associated with internal motivational drives and emotional states that are modulated by oxytocin and vasopressin. PMID:24486356
NASA Astrophysics Data System (ADS)
Bromis, K.; Kakkos, I.; Gkiatis, K.; Karanasiou, I. S.; Matsopoulos, G. K.
2017-11-01
Previous neurocognitive assessments in Small Cell Lung Cancer (SCLC) population, highlight the presence of neurocognitive impairments (mainly in attention processing and executive functioning) in this type of cancer. The majority of these studies, associate these deficits with the Prophylactic Cranial Irradiation (PCI) that patients undergo in order to avoid brain metastasis. However, there is not much evidence exploring cognitive impairments induced by chemotherapy in SCLC patients. For this reason, we aimed to investigate the underlying processes that may potentially affect cognition by examining brain functional connectivity in nineteen SCLC patients after chemotherapy treatment, while additionally including fourteen healthy participants as control group. Independent Component Analysis (ICA) is a functional connectivity measure aiming to unravel the temporal correlation between brain regions, which are called brain networks. We focused on two brain networks related to the aforementioned cognitive functions, the Default Mode Network (DMN) and the Task-Positive Network (TPN). Permutation tests were performed between the two groups to assess the differences and control for familywise errors in the statistical parametric maps. ICA analysis showed functional connectivity disruptions within both of the investigated networks. These results, propose a detrimental effect of chemotherapy on brain functioning in the SCLC population.
Decoding natural images from evoked brain activities using encoding models with invertible mapping.
Li, Chao; Xu, Junhai; Liu, Baolin
2018-05-21
Recent studies have built encoding models in the early visual cortex, and reliable mappings have been made between the low-level visual features of stimuli and brain activities. However, these mappings are irreversible, so that the features cannot be directly decoded. To solve this problem, we designed a sparse framework-based encoding model that predicted brain activities from a complete feature representation. Moreover, according to the distribution and activation rules of neurons in the primary visual cortex (V1), three key transformations were introduced into the basic feature to improve the model performance. In this setting, the mapping was simple enough that it could be inverted using a closed-form formula. Using this mapping, we designed a hybrid identification method based on the support vector machine (SVM), and tested it on a published functional magnetic resonance imaging (fMRI) dataset. The experiments confirmed the rationality of our encoding model, and the identification accuracies for 2 subjects increased from 92% and 72% to 98% and 92% with the chance level only 0.8%. Copyright © 2018 Elsevier Ltd. All rights reserved.
"Clinical brain profiling": a neuroscientific diagnostic approach for mental disorders.
Peled, Abraham; Geva, Amir B
2014-10-01
Clinical brain profiling is an attempt to map a descriptive nosology in psychiatry to underlying constructs in neurobiology and brain dynamics. This paper briefly reviews the motivation behind clinical brain profiling (CBP) and presents some provisional validation using clinical assessments and meta-analyses of neuroscientific publications. The paper has four sections. In the first, we review the nature and motivation for clinical brain profiling. This involves a description of the key aspects of functional anatomy that can lead to psychopathology. These features constitute the dimensions or categories for a profile of brain disorders based upon pathophysiology. The second section describes a mapping or translation matrix that maps from symptoms and signs, of a descriptive sort, to the CBP dimensions that provide a more mechanistic explanation. We will describe how this mapping engenders archetypal diagnoses, referring readers to tables and figures. The third section addresses the construct validity of clinical brain profiling by establishing correlations between profiles based on clinical ratings of symptoms and signs under classical diagnostic categories with the corresponding profiles generated automatically using archetypal diagnoses. We then provide further validation by performing a cluster analysis on the symptoms and signs and showing how they correspond to the equivalent brain profiles based upon clinical and automatic diagnosis. In the fourth section, we address the construct validity of clinical brain profiling by looking for associations between pathophysiological mechanisms (such as connectivity and plasticity) and nosological diagnoses (such as schizophrenia and depression). Based upon the mechanistic perspective offered in the first section, we test some particular hypotheses about double dissociations using a meta-analysis of PubMed searches. The final section concludes with perspectives for the future and outstanding validation issues for clinical brain profiling. Copyright © 2014 Elsevier Ltd. All rights reserved.
Ceschin, Rafael; Panigrahy, Ashok; Gopalakrishnan, Vanathi
2015-01-01
A major challenge in the diagnosis and treatment of brain tumors is tissue heterogeneity leading to mixed treatment response. Additionally, they are often difficult or at very high risk for biopsy, further hindering the clinical management process. To overcome this, novel advanced imaging methods are increasingly being adapted clinically to identify useful noninvasive biomarkers capable of disease stage characterization and treatment response prediction. One promising technique is called functional diffusion mapping (fDM), which uses diffusion-weighted imaging (DWI) to generate parametric maps between two imaging time points in order to identify significant voxel-wise changes in water diffusion within the tumor tissue. Here we introduce serial functional diffusion mapping (sfDM), an extension of existing fDM methods, to analyze the entire tumor diffusion profile along the temporal course of the disease. sfDM provides the tools necessary to analyze a tumor data set in the context of spatiotemporal parametric mapping: the image registration pipeline, biomarker extraction, and visualization tools. We present the general workflow of the pipeline, along with a typical use case for the software. sfDM is written in Python and is freely available as an open-source package under the Berkley Software Distribution (BSD) license to promote transparency and reproducibility.
Unmasking Language Lateralization in Human Brain Intrinsic Activity
McAvoy, Mark; Mitra, Anish; Coalson, Rebecca S.; d'Avossa, Giovanni; Keidel, James L.; Petersen, Steven E.; Raichle, Marcus E.
2016-01-01
Lateralization of function is a fundamental feature of the human brain as exemplified by the left hemisphere dominance of language. Despite the prominence of lateralization in the lesion, split-brain and task-based fMRI literature, surprisingly little asymmetry has been revealed in the increasingly popular functional imaging studies of spontaneous fluctuations in the fMRI BOLD signal (so-called resting-state fMRI). Here, we show the global signal, an often discarded component of the BOLD signal in resting-state studies, reveals a leftward asymmetry that maps onto regions preferential for semantic processing in left frontal and temporal cortex and the right cerebellum and a rightward asymmetry that maps onto putative attention-related regions in right frontal, temporoparietal, and parietal cortex. Hemispheric asymmetries in the global signal resulted from amplitude modulation of the spontaneous fluctuations. To confirm these findings obtained from normal, healthy, right-handed subjects in the resting-state, we had them perform 2 semantic processing tasks: synonym and numerical magnitude judgment and sentence comprehension. In addition to establishing a new technique for studying lateralization through functional imaging of the resting-state, our findings shed new light on the physiology of the global brain signal. PMID:25636911
Viewing the functional consequences of traumatic brain injury by using brain SPECT.
Pavel, D; Jobe, T; Devore-Best, S; Davis, G; Epstein, P; Sinha, S; Kohn, R; Craita, I; Liu, P; Chang, Y
2006-03-01
High-resolution brain SPECT is increasingly benefiting from improved image processing software and multiple complementary display capabilities. This enables detailed functional mapping of the disturbances in relative perfusion occurring after TBI. The patient population consisted of 26 cases (ages 8-61 years)between 3 months and 6 years after traumatic brain injury.A very strong case can be made for the routine use of Brain SPECT in TBI. Indeed it can provide a detailed evaluation of multiple functional consequences after TBI and is thus capable of supplementing the clinical evaluation and tailoring the therapeutic strategies needed. In so doing it also provides significant additional information beyond that available from MRI/CT. The critical factor for Brain SPECT's clinical relevance is a carefully designed technical protocol, including displays which should enable a comprehensive description of the patterns found, in a user friendly mode.
Page, Robert B.; Boley, Meredith A.; Kump, David K.; Voss, Stephen R.
2013-01-01
Very little is known about genetic factors that regulate life history transitions during ontogeny. Closely related tiger salamanders (Ambystoma species complex) show extreme variation in metamorphic timing, with some species foregoing metamorphosis altogether, an adaptive trait called paedomorphosis. Previous studies identified a major effect quantitative trait locus (met1) for metamorphic timing and expression of paedomorphosis in hybrid crosses between the biphasic Eastern tiger salamander (Ambystoma tigrinum tigrinum) and the paedomorphic Mexican axolotl (Ambystoma mexicanum). We used existing hybrid mapping panels and a newly created hybrid cross to map the met1 genomic region and determine the effect of met1 on larval growth, metamorphic timing, and gene expression in the brain. We show that met1 maps to the position of a urodele-specific chromosome rearrangement on linkage group 2 that uniquely brought functionally associated genes into linkage. Furthermore, we found that more than 200 genes were differentially expressed during larval development as a function of met1 genotype. This list of differentially expressed genes is enriched for proteins that function in the mitochondria, providing evidence of a link between met1, thyroid hormone signaling, and mitochondrial energetics associated with metamorphosis. Finally, we found that met1 significantly affected metamorphic timing in hybrids, but not early larval growth rate. Collectively, our results show that met1 regulates species and morph-specific patterns of brain transcription and life history variation. PMID:23946331
Mapping Common Aphasia Assessments to Underlying Cognitive Processes and Their Neural Substrates.
Lacey, Elizabeth H; Skipper-Kallal, Laura M; Xing, Shihui; Fama, Mackenzie E; Turkeltaub, Peter E
2017-05-01
Understanding the relationships between clinical tests, the processes they measure, and the brain networks underlying them, is critical in order for clinicians to move beyond aphasia syndrome classification toward specification of individual language process impairments. To understand the cognitive, language, and neuroanatomical factors underlying scores of commonly used aphasia tests. Twenty-five behavioral tests were administered to a group of 38 chronic left hemisphere stroke survivors and a high-resolution magnetic resonance image was obtained. Test scores were entered into a principal components analysis to extract the latent variables (factors) measured by the tests. Multivariate lesion-symptom mapping was used to localize lesions associated with the factor scores. The principal components analysis yielded 4 dissociable factors, which we labeled Word Finding/Fluency, Comprehension, Phonology/Working Memory Capacity, and Executive Function. While many tests loaded onto the factors in predictable ways, some relied heavily on factors not commonly associated with the tests. Lesion symptom mapping demonstrated discrete brain structures associated with each factor, including frontal, temporal, and parietal areas extending beyond the classical language network. Specific functions mapped onto brain anatomy largely in correspondence with modern neural models of language processing. An extensive clinical aphasia assessment identifies 4 independent language functions, relying on discrete parts of the left middle cerebral artery territory. A better understanding of the processes underlying cognitive tests and the link between lesion and behavior may lead to improved aphasia diagnosis, and may yield treatments better targeted to an individual's specific pattern of deficits and preserved abilities.
Three-dimensional functional magnetic resonance imaging of human brain on a clinical 1.5-T scanner.
van Gelderen, P; Ramsey, N F; Liu, G; Duyn, J H; Frank, J A; Weinberger, D R; Moonen, C T
1995-01-01
Functional magnetic resonance imaging (fMRI) is a tool for mapping brain function that utilizes neuronal activity-induced changes in blood oxygenation. An efficient three-dimensional fMRI method is presented for imaging brain activity on conventional, widely available, 1.5-T scanners, without additional hardware. This approach uses large magnetic susceptibility weighting based on the echo-shifting principle combined with multiple gradient echoes per excitation. Motor stimulation, induced by self-paced finger tapping, reliably produced significant signal increase in the hand region of the contralateral primary motor cortex in every subject tested. Images Fig. 2 Fig. 3 PMID:7624341
Functional brain networks reconstruction using group sparsity-regularized learning.
Zhao, Qinghua; Li, Will X Y; Jiang, Xi; Lv, Jinglei; Lu, Jianfeng; Liu, Tianming
2018-06-01
Investigating functional brain networks and patterns using sparse representation of fMRI data has received significant interests in the neuroimaging community. It has been reported that sparse representation is effective in reconstructing concurrent and interactive functional brain networks. To date, most of data-driven network reconstruction approaches rarely take consideration of anatomical structures, which are the substrate of brain function. Furthermore, it has been rarely explored whether structured sparse representation with anatomical guidance could facilitate functional networks reconstruction. To address this problem, in this paper, we propose to reconstruct brain networks utilizing the structure guided group sparse regression (S2GSR) in which 116 anatomical regions from the AAL template, as prior knowledge, are employed to guide the network reconstruction when performing sparse representation of whole-brain fMRI data. Specifically, we extract fMRI signals from standard space aligned with the AAL template. Then by learning a global over-complete dictionary, with the learned dictionary as a set of features (regressors), the group structured regression employs anatomical structures as group information to regress whole brain signals. Finally, the decomposition coefficients matrix is mapped back to the brain volume to represent functional brain networks and patterns. We use the publicly available Human Connectome Project (HCP) Q1 dataset as the test bed, and the experimental results indicate that the proposed anatomically guided structure sparse representation is effective in reconstructing concurrent functional brain networks.
Henry, Roland G; Berman, Jeffrey I; Nagarajan, Srikantan S; Mukherjee, Pratik; Berger, Mitchel S
2004-02-01
The combination of mapping functional cortical neurons by intraoperative cortical stimulation and axonal architecture by diffusion tensor MRI fiber tracking can be used to delineate the pathways between functional regions. In this study the authors investigated the feasibility of combining these techniques to yield connectivity associated with motor speech and naming. Diffusion tensor MRI fiber tracking provides maps of axonal bundles and was combined with intraoperative mapping of eloquent cortex for a patient undergoing brain tumor surgery. Tracks from eight stimulated sites in the inferior frontal cortex including mouth motor, speech arrest, and anomia were generated from the diffusion tensor MRI data. The regions connected by the fiber tracking were compared to foci from previous functional imaging reports on language tasks. Connections were found between speech arrest, mouth motor, and anomia sites and the SMA proper and cerebral peduncle. The speech arrest and a mouth motor site were also seen to connect to the putamen via the external capsule. This is the first demonstration of delineation of subcortical pathways using diffusion tensor MRI fiber tracking with intraoperative cortical stimulation. The combined techniques may provide improved preservation of eloquent regions during neurological surgery, and may provide access to direct connectivity information between functional regions of the brain.
Henry, Roland G.; Berman, Jeffrey I.; Nagarajan, Srikantan S.; Mukherjee, Pratik; Berger, Mitchel S.
2014-01-01
The combination of mapping functional cortical neurons by intraoperative cortical stimulation and axonal architecture by diffusion tensor MRI fiber tracking can be used to delineate the pathways between functional regions. In this study the authors investigated the feasibility of combining these techniques to yield connectivity associated with motor speech and naming. Diffusion tensor MRI fiber tracking provides maps of axonal bundles and was combined with intraoperative mapping of eloquent cortex for a patient undergoing brain tumor surgery. Tracks from eight stimulated sites in the inferior frontal cortex including mouth motor, speech arrest, and anomia were generated from the diffusion tensor MRI data. The regions connected by the fiber tracking were compared to foci from previous functional imaging reports on language tasks. Connections were found between speech arrest, mouth motor, and anomia sites and the SMA proper and cerebral peduncle. The speech arrest and a mouth motor site were also seen to connect to the putamen via the external capsule. This is the first demonstration of delineation of subcortical pathways using diffusion tensor MRI fiber tracking with intraoperative cortical stimulation. The combined techniques may provide improved preservation of eloquent regions during neurological surgery, and may provide access to direct connectivity information between functional regions of the brain. PMID:14980564
Robust biological parametric mapping: an improved technique for multimodal brain image analysis
NASA Astrophysics Data System (ADS)
Yang, Xue; Beason-Held, Lori; Resnick, Susan M.; Landman, Bennett A.
2011-03-01
Mapping the quantitative relationship between structure and function in the human brain is an important and challenging problem. Numerous volumetric, surface, region of interest and voxelwise image processing techniques have been developed to statistically assess potential correlations between imaging and non-imaging metrics. Recently, biological parametric mapping has extended the widely popular statistical parametric approach to enable application of the general linear model to multiple image modalities (both for regressors and regressands) along with scalar valued observations. This approach offers great promise for direct, voxelwise assessment of structural and functional relationships with multiple imaging modalities. However, as presented, the biological parametric mapping approach is not robust to outliers and may lead to invalid inferences (e.g., artifactual low p-values) due to slight mis-registration or variation in anatomy between subjects. To enable widespread application of this approach, we introduce robust regression and robust inference in the neuroimaging context of application of the general linear model. Through simulation and empirical studies, we demonstrate that our robust approach reduces sensitivity to outliers without substantial degradation in power. The robust approach and associated software package provides a reliable way to quantitatively assess voxelwise correlations between structural and functional neuroimaging modalities.
Murakami, Tatsuya C; Mano, Tomoyuki; Saikawa, Shu; Horiguchi, Shuhei A; Shigeta, Daichi; Baba, Kousuke; Sekiya, Hiroshi; Shimizu, Yoshihiro; Tanaka, Kenji F; Kiyonari, Hiroshi; Iino, Masamitsu; Mochizuki, Hideki; Tainaka, Kazuki; Ueda, Hiroki R
2018-04-01
A three-dimensional single-cell-resolution mammalian brain atlas will accelerate systems-level identification and analysis of cellular circuits underlying various brain functions. However, its construction requires efficient subcellular-resolution imaging throughout the entire brain. To address this challenge, we developed a fluorescent-protein-compatible, whole-organ clearing and homogeneous expansion protocol based on an aqueous chemical solution (CUBIC-X). The expanded, well-cleared brain enabled us to construct a point-based mouse brain atlas with single-cell annotation (CUBIC-Atlas). CUBIC-Atlas reflects inhomogeneous whole-brain development, revealing a significant decrease in the cerebral visual and somatosensory cortical areas during postnatal development. Probabilistic activity mapping of pharmacologically stimulated Arc-dVenus reporter mouse brains onto CUBIC-Atlas revealed the existence of distinct functional structures in the hippocampal dentate gyrus. CUBIC-Atlas is shareable by an open-source web-based viewer, providing a new platform for whole-brain cell profiling.
Sato, Katsushige; Nariai, Tadashi; Momose-Sato, Yoko; Kamino, Kohtaro
2017-07-01
Intrinsic optical imaging as developed by Grinvald et al. is a powerful technique for monitoring neural function in the in vivo central nervous system. The advent of this dye-free imaging has also enabled us to monitor human brain function during neurosurgical operations. We briefly describe our own experience in functional mapping of the human somatosensory cortex, carried out using intraoperative optical imaging. The maps obtained demonstrate new additional evidence of a hierarchy for sensory response patterns in the human primary somatosensory cortex.
Functional mapping of language networks in the normal brain using a word-association task.
Ghosh, Shantanu; Basu, Amrita; Kumaran, Senthil S; Khushu, Subash
2010-08-01
Language functions are known to be affected in diverse neurological conditions, including ischemic stroke, traumatic brain injury, and brain tumors. Because language networks are extensive, interpretation of functional data depends on the task completed during evaluation. The aim was to map the hemodynamic consequences of word association using functional magnetic resonance imaging (fMRI) in normal human subjects. Ten healthy subjects underwent fMRI scanning with a postlexical access semantic association task vs lexical processing task. The fMRI protocol involved a T2*-weighted gradient-echo echo-planar imaging (GE-EPI) sequence (TR 4523 ms, TE 64 ms, flip angle 90°) with alternate baseline and activation blocks. A total of 78 scans were taken (interscan interval = 3 s) with a total imaging time of 587 s. Functional data were processed in Statistical Parametric Mapping software (SPM2) with 8-mm Gaussian kernel by convolving the blood oxygenation level-dependent (BOLD) signal with an hemodynamic response function estimated by general linear method to generate SPM{t} and SPM{F} maps. Single subject analysis of the functional data (FWE-corrected, P≤0.001) revealed extensive activation in the frontal lobes, with overlaps among middle frontal gyrus (MFG), superior, and inferior frontal gyri. BOLD activity was also found in the medial frontal gyrus, middle occipital gyrus (MOG), anterior fusiform gyrus, superior and inferior parietal lobules, and to a smaller extent, the thalamus and right anterior cerebellum. Group analysis (FWE-corrected, P≤0.001) revealed neural recruitment of bilateral lingual gyri, left MFG, bilateral MOG, left superior occipital gyrus, left fusiform gyrus, bilateral thalami, and right cerebellar areas. Group data analysis revealed a cerebellar-occipital-fusiform-thalamic network centered around bilateral lingual gyri for word association, thereby indicating how these areas facilitate language comprehension by activating a semantic association network of words processed postlexical access. This finding is important when assessing the extent of cognitive damage and/or recovery and can be used for presurgical planning after optimization.
Functional Maps of Mechanosensory Features in the Drosophila Brain.
Patella, Paola; Wilson, Rachel I
2018-04-23
Johnston's organ is the largest mechanosensory organ in Drosophila. It contributes to hearing, touch, vestibular sensing, proprioception, and wind sensing. In this study, we used in vivo 2-photon calcium imaging and unsupervised image segmentation to map the tuning properties of Johnston's organ neurons (JONs) at the site where their axons enter the brain. We then applied the same methodology to study two key brain regions that process signals from JONs: the antennal mechanosensory and motor center (AMMC) and the wedge, which is downstream of the AMMC. First, we identified a diversity of JON response types that tile frequency space and form a rough tonotopic map. Some JON response types are direction selective; others are specialized to encode amplitude modulations over a specific range (dynamic range fractionation). Next, we discovered that both the AMMC and the wedge contain a tonotopic map, with a significant increase in tonotopy-and a narrowing of frequency tuning-at the level of the wedge. Whereas the AMMC tonotopic map is unilateral, the wedge tonotopic map is bilateral. Finally, we identified a subregion of the AMMC/wedge that responds preferentially to the coherent rotation of the two mechanical organs in the same angular direction, indicative of oriented steady air flow (directional wind). Together, these maps reveal the broad organization of the primary and secondary mechanosensory regions of the brain. They provide a framework for future efforts to identify the specific cell types and mechanisms that underlie the hierarchical re-mapping of mechanosensory information in this system. Copyright © 2018 Elsevier Ltd. All rights reserved.
Gahm, Jin Kyu; Shi, Yonggang
2018-05-01
Surface mapping methods play an important role in various brain imaging studies from tracking the maturation of adolescent brains to mapping gray matter atrophy patterns in Alzheimer's disease. Popular surface mapping approaches based on spherical registration, however, have inherent numerical limitations when severe metric distortions are present during the spherical parameterization step. In this paper, we propose a novel computational framework for intrinsic surface mapping in the Laplace-Beltrami (LB) embedding space based on Riemannian metric optimization on surfaces (RMOS). Given a diffeomorphism between two surfaces, an isometry can be defined using the pullback metric, which in turn results in identical LB embeddings from the two surfaces. The proposed RMOS approach builds upon this mathematical foundation and achieves general feature-driven surface mapping in the LB embedding space by iteratively optimizing the Riemannian metric defined on the edges of triangular meshes. At the core of our framework is an optimization engine that converts an energy function for surface mapping into a distance measure in the LB embedding space, which can be effectively optimized using gradients of the LB eigen-system with respect to the Riemannian metrics. In the experimental results, we compare the RMOS algorithm with spherical registration using large-scale brain imaging data, and show that RMOS achieves superior performance in the prediction of hippocampal subfields and cortical gyral labels, and the holistic mapping of striatal surfaces for the construction of a striatal connectivity atlas from substantia nigra. Copyright © 2018 Elsevier B.V. All rights reserved.
MRI evaluation and functional assessment of brain injury after hypoxic ischemia in neonatal mice.
Adén, Ulrika; Dahlberg, Viktoria; Fredholm, Bertil B; Lai, Li-Ju; Chen, Zhengguan; Bjelke, Börje
2002-05-01
Severe perinatal asphyxia is an important cause of brain injury in the newborn infant. We examined early events after hypoxic ischemia (HI) in the 7-day-old mouse brain by MRI and related them to long-term functional effects and histopathology in the same animals at 4 to 5 weeks of age. HI was induced in 7-day-old CD1 mice by exposure to 8% oxygen for 30 minutes after occlusion of the left common carotid artery. The resulting unilateral focal lesion was evaluated in vivo by MRI (T2 maps and apparent diffusion coefficient maps) at 3, 6, and 24 hours and 5 days after hypoxia. Locomotion and sensorimotor function were analyzed after 3 weeks. Four weeks after HI, the mice were killed, and cresyl violet-stained brain sections were examined morphologically. A decrease in apparent diffusion coefficient values in cortex on the affected side was found at 3 hours after HI. T2 values were significantly increased after 6 hours and remained so for 5 days. Maximal size of the lesion was attained at 3 to 6 hours after HI and declined thereafter. Animals with MRI-detected lesions had decreased forward locomotion, performed worse than controls in the beam-walking test, and showed a unilateral hypotrophy in the cresyl violet-stained brain sections 4 weeks later. The temporal progression of the damage after HI in 7-day-old mice differs from that of the adult brain as judged by MRI. The early lesions detected by MRI were related to functional impairments for these mice in near-adult life.
Brunner, Clément; Isabel, Clothilde; Martin, Abraham; Dussaux, Clara; Savoye, Anne; Emmrich, Julius; Montaldo, Gabriel; Mas, Jean-Louis; Urban, Alan
2015-01-01
Following middle cerebral artery occlusion, tissue outcome ranges from normal to infarcted depending on depth and duration of hypoperfusion as well as occurrence and efficiency of reperfusion. However, the precise time course of these changes in relation to tissue and behavioral outcome remains unsettled. To address these issues, a three-dimensional wide field-of-view and real-time quantitative functional imaging technique able to map perfusion in the rodent brain would be desirable. Here, we applied functional ultrasound imaging, a novel approach to map relative cerebral blood volume without contrast agent, in a rat model of brief proximal transient middle cerebral artery occlusion to assess perfusion in penetrating arterioles and venules acutely and over six days thanks to a thinned-skull preparation. Functional ultrasound imaging efficiently mapped the acute changes in relative cerebral blood volume during occlusion and following reperfusion with high spatial resolution (100 µm), notably documenting marked focal decreases during occlusion, and was able to chart the fine dynamics of tissue reperfusion (rate: one frame/5 s) in the individual rat. No behavioral and only mild post-mortem immunofluorescence changes were observed. Our study suggests functional ultrasound is a particularly well-adapted imaging technique to study cerebral perfusion in acute experimental stroke longitudinally from the hyper-acute up to the chronic stage in the same subject. PMID:26721392
Functional connectomics from resting-state fMRI
Smith, Stephen M; Vidaurre, Diego; Beckmann, Christian F; Glasser, Matthew F; Jenkinson, Mark; Miller, Karla L; Nichols, Thomas E; Robinson, Emma; Salimi-Khorshidi, Gholamreza; Woolrich, Mark W; Barch, Deanna M; Uğurbil, Kamil; Van Essen, David C
2014-01-01
Spontaneous fluctuations in activity in different parts of the brain can be used to study functional brain networks. We review the use of resting-state functional MRI for the purpose of mapping the macroscopic functional connectome. After describing MRI acquisition and image processing methods commonly used to generate data in a form amenable to connectomics network analysis, we discuss different approaches for estimating network structure from that data. Finally, we describe new possibilities resulting from the high-quality rfMRI data being generated by the Human Connectome Project, and highlight some upcoming challenges in functional connectomics. PMID:24238796
HITS-CLIP yields genome-wide insights into brain alternative RNA processing
NASA Astrophysics Data System (ADS)
Licatalosi, Donny D.; Mele, Aldo; Fak, John J.; Ule, Jernej; Kayikci, Melis; Chi, Sung Wook; Clark, Tyson A.; Schweitzer, Anthony C.; Blume, John E.; Wang, Xuning; Darnell, Jennifer C.; Darnell, Robert B.
2008-11-01
Protein-RNA interactions have critical roles in all aspects of gene expression. However, applying biochemical methods to understand such interactions in living tissues has been challenging. Here we develop a genome-wide means of mapping protein-RNA binding sites in vivo, by high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP). HITS-CLIP analysis of the neuron-specific splicing factor Nova revealed extremely reproducible RNA-binding maps in multiple mouse brains. These maps provide genome-wide in vivo biochemical footprints confirming the previous prediction that the position of Nova binding determines the outcome of alternative splicing; moreover, they are sufficiently powerful to predict Nova action de novo. HITS-CLIP revealed a large number of Nova-RNA interactions in 3' untranslated regions, leading to the discovery that Nova regulates alternative polyadenylation in the brain. HITS-CLIP, therefore, provides a robust, unbiased means to identify functional protein-RNA interactions in vivo.
A symbolic/subsymbolic interface protocol for cognitive modeling
Simen, Patrick; Polk, Thad
2009-01-01
Researchers studying complex cognition have grown increasingly interested in mapping symbolic cognitive architectures onto subsymbolic brain models. Such a mapping seems essential for understanding cognition under all but the most extreme viewpoints (namely, that cognition consists exclusively of digitally implemented rules; or instead, involves no rules whatsoever). Making this mapping reduces to specifying an interface between symbolic and subsymbolic descriptions of brain activity. To that end, we propose parameterization techniques for building cognitive models as programmable, structured, recurrent neural networks. Feedback strength in these models determines whether their components implement classically subsymbolic neural network functions (e.g., pattern recognition), or instead, logical rules and digital memory. These techniques support the implementation of limited production systems. Though inherently sequential and symbolic, these neural production systems can exploit principles of parallel, analog processing from decision-making models in psychology and neuroscience to explain the effects of brain damage on problem solving behavior. PMID:20711520
Diffeomorphic functional brain surface alignment: Functional demons.
Nenning, Karl-Heinz; Liu, Hesheng; Ghosh, Satrajit S; Sabuncu, Mert R; Schwartz, Ernst; Langs, Georg
2017-08-01
Aligning brain structures across individuals is a central prerequisite for comparative neuroimaging studies. Typically, registration approaches assume a strong association between the features used for alignment, such as macro-anatomy, and the variable observed, such as functional activation or connectivity. Here, we propose to use the structure of intrinsic resting state fMRI signal correlation patterns as a basis for alignment of the cortex in functional studies. Rather than assuming the spatial correspondence of functional structures between subjects, we have identified locations with similar connectivity profiles across subjects. We mapped functional connectivity relationships within the brain into an embedding space, and aligned the resulting maps of multiple subjects. We then performed a diffeomorphic alignment of the cortical surfaces, driven by the corresponding features in the joint embedding space. Results show that functional alignment based on resting state fMRI identifies functionally homologous regions across individuals with higher accuracy than alignment based on the spatial correspondence of anatomy. Further, functional alignment enables measurement of the strength of the anatomo-functional link across the cortex, and reveals the uneven distribution of this link. Stronger anatomo-functional dissociation was found in higher association areas compared to primary sensory- and motor areas. Functional alignment based on resting state features improves group analysis of task based functional MRI data, increasing statistical power and improving the delineation of task-specific core regions. Finally, a comparison of the anatomo-functional dissociation between cohorts is demonstrated with a group of left and right handed subjects. Copyright © 2017 Elsevier Inc. All rights reserved.
Mantini, Dante; Hasson, Uri; Betti, Viviana; Perrucci, Mauro G.; Romani, Gian Luca; Corbetta, Maurizio; Orban, Guy A.; Vanduffel, Wim
2012-01-01
Evolution-driven functional changes in the primate brain are typically assessed by aligning monkey and human activation maps using cortical surface expansion models. These models use putative homologous areas as registration landmarks, assuming they are functionally correspondent. In cases where functional changes have occurred in an area, this assumption prohibits to reveal whether other areas may have assumed lost functions. Here we describe a method to examine functional correspondences across species. Without making spatial assumptions, we assess similarities in sensory-driven functional magnetic resonance imaging responses between monkey (Macaca mulatta) and human brain areas by means of temporal correlation. Using natural vision data, we reveal regions for which functional processing has shifted to topologically divergent locations during evolution. We conclude that substantial evolution-driven functional reorganizations have occurred, not always consistent with cortical expansion processes. This novel framework for evaluating changes in functional architecture is crucial to building more accurate evolutionary models. PMID:22306809
Pak, Rebecca W; Hadjiabadi, Darian H; Senarathna, Janaka; Agarwal, Shruti; Thakor, Nitish V; Pillai, Jay J; Pathak, Arvind P
2017-11-01
Functional magnetic resonance imaging (fMRI) serves as a critical tool for presurgical mapping of eloquent cortex and changes in neurological function in patients diagnosed with brain tumors. However, the blood-oxygen-level-dependent (BOLD) contrast mechanism underlying fMRI assumes that neurovascular coupling remains intact during brain tumor progression, and that measured changes in cerebral blood flow (CBF) are correlated with neuronal function. Recent preclinical and clinical studies have demonstrated that even low-grade brain tumors can exhibit neurovascular uncoupling (NVU), which can confound interpretation of fMRI data. Therefore, to avoid neurosurgical complications, it is crucial to understand the biophysical basis of NVU and its impact on fMRI. Here we review the physiology of the neurovascular unit, how it is remodeled, and functionally altered by brain cancer cells. We first discuss the latest findings about the components of the neurovascular unit. Next, we synthesize results from preclinical and clinical studies to illustrate how brain tumor induced NVU affects fMRI data interpretation. We examine advances in functional imaging methods that permit the clinical evaluation of brain tumors with NVU. Finally, we discuss how the suppression of anomalous tumor blood vessel formation with antiangiogenic therapies can "normalize" the brain tumor vasculature, and potentially restore neurovascular coupling.
Molecular Neuroanatomy: A Generation of Progress
Pollock, Jonathan D.; Wu, Da-Yu; Satterlee, John
2014-01-01
The neuroscience research landscape has changed dramatically over the past decade. An impressive array of neuroscience tools and technologies have been generated, including brain gene expression atlases, genetically encoded proteins to monitor and manipulate neuronal activity and function, cost effective genome sequencing, new technologies enabling genome manipulation, new imaging methods and new tools for mapping neuronal circuits. However, despite these technological advances, several significant scientific challenges must be overcome in the coming decade to enable a better understanding of brain function and to develop next generation cell type-targeted therapeutics to treat brain disorders. For example, we do not have an inventory of the different types of cells that exist in the brain, nor do we know how to molecularly phenotype them. We also lack robust technologies to map connections between cells. This review will provide an overview of some of the tools and technologies neuroscientists are currently using to move the field of molecular neuroanatomy forward and also discuss emerging technologies that may enable neuroscientists to address these critical scientific challenges over the coming decade. PMID:24388609
Choi, Hi-Jae; Zilles, Karl; Mohlberg, Hartmut; Schleicher, Axel; Fink, Gereon R.; Armstrong, Este; Amunts, Katrin
2008-01-01
Anatomical studies in the macaque cortex and functional imaging studies in humans have demonstrated the existence of different cortical areas within the IntraParietal Sulcus (IPS). Such functional segregation, however, does not correlate with presently available architectonic maps of the human brain. This is particularly true for the classical Brodmann map, which is still widely used as an anatomical reference in functional imaging studies. The aim of this cytoarchitectonic mapping study was to use previously defined algorithms to determine whether consistent regions and borders can be found within the cortex of the anterior IPS in a population of ten postmortem human brains. Two areas, the human IntraParietal area 1 (hIP1) and the human IntraParietal area 2 (hIP2), were delineated in serial histological sections of the anterior, lateral bank of the human IPS. The region hIP1 is located posterior and medial to hIP2, and the former is always within the depths of the IPS. The latter, on the other hand, sometimes reaches the free surface of the superior parietal lobule. The delineations were registered to standard reference space, and probabilistic maps were calculated, thereby quantifying the intersubject variability in location and extent of both areas. In the future, they can be a tool in analyzing structure – function relationships and a basis for determining degrees of homology in the IPS among anthropoid primates. We conclude that the human intraparietal sulcus has a finer grained parcellation than shown in Brodmann’s map. PMID:16432904
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An anatomical and functional topography of human auditory cortical areas
Moerel, Michelle; De Martino, Federico; Formisano, Elia
2014-01-01
While advances in magnetic resonance imaging (MRI) throughout the last decades have enabled the detailed anatomical and functional inspection of the human brain non-invasively, to date there is no consensus regarding the precise subdivision and topography of the areas forming the human auditory cortex. Here, we propose a topography of the human auditory areas based on insights on the anatomical and functional properties of human auditory areas as revealed by studies of cyto- and myelo-architecture and fMRI investigations at ultra-high magnetic field (7 Tesla). Importantly, we illustrate that—whereas a group-based approach to analyze functional (tonotopic) maps is appropriate to highlight the main tonotopic axis—the examination of tonotopic maps at single subject level is required to detail the topography of primary and non-primary areas that may be more variable across subjects. Furthermore, we show that considering multiple maps indicative of anatomical (i.e., myelination) as well as of functional properties (e.g., broadness of frequency tuning) is helpful in identifying auditory cortical areas in individual human brains. We propose and discuss a topography of areas that is consistent with old and recent anatomical post-mortem characterizations of the human auditory cortex and that may serve as a working model for neuroscience studies of auditory functions. PMID:25120426
Tam, Angela; Dansereau, Christian; Badhwar, AmanPreet; Orban, Pierre; Belleville, Sylvie; Chertkow, Howard; Dagher, Alain; Hanganu, Alexandru; Monchi, Oury; Rosa-Neto, Pedro; Shmuel, Amir; Breitner, John; Bellec, Pierre
2016-12-01
We present group eight resolutions of brain parcellations for clusters generated from resting-state functional magnetic resonance images for 99 cognitively normal elderly persons and 129 patients with mild cognitive impairment, pooled from four independent datasets. This dataset was generated as part of the following study: Common Effects of Amnestic Mild Cognitive Impairment on Resting-State Connectivity Across Four Independent Studies (Tam et al., 2015) [1]. The brain parcellations have been registered to both symmetric and asymmetric MNI brain templates and generated using a method called bootstrap analysis of stable clusters (BASC) (Bellec et al., 2010) [2]. We present two variants of these parcellations. One variant contains bihemisphereic parcels (4, 6, 12, 22, 33, 65, 111, and 208 total parcels across eight resolutions). The second variant contains spatially connected regions of interest (ROIs) that span only one hemisphere (10, 17, 30, 51, 77, 199, and 322 total ROIs across eight resolutions). We also present maps illustrating functional connectivity differences between patients and controls for four regions of interest (striatum, dorsal prefrontal cortex, middle temporal lobe, and medial frontal cortex). The brain parcels and associated statistical maps have been publicly released as 3D volumes, available in .mnc and .nii file formats on figshare and on Neurovault. Finally, the code used to generate this dataset is available on Github.
Assignment of functional activations to probabilistic cytoarchitectonic areas revisited.
Eickhoff, Simon B; Paus, Tomas; Caspers, Svenja; Grosbras, Marie-Helene; Evans, Alan C; Zilles, Karl; Amunts, Katrin
2007-07-01
Probabilistic cytoarchitectonic maps in standard reference space provide a powerful tool for the analysis of structure-function relationships in the human brain. While these microstructurally defined maps have already been successfully used in the analysis of somatosensory, motor or language functions, several conceptual issues in the analysis of structure-function relationships still demand further clarification. In this paper, we demonstrate the principle approaches for anatomical localisation of functional activations based on probabilistic cytoarchitectonic maps by exemplary analysis of an anterior parietal activation evoked by visual presentation of hand gestures. After consideration of the conceptual basis and implementation of volume or local maxima labelling, we comment on some potential interpretational difficulties, limitations and caveats that could be encountered. Extending and supplementing these methods, we then propose a supplementary approach for quantification of structure-function correspondences based on distribution analysis. This approach relates the cytoarchitectonic probabilities observed at a particular functionally defined location to the areal specific null distribution of probabilities across the whole brain (i.e., the full probability map). Importantly, this method avoids the need for a unique classification of voxels to a single cortical area and may increase the comparability between results obtained for different areas. Moreover, as distribution-based labelling quantifies the "central tendency" of an activation with respect to anatomical areas, it will, in combination with the established methods, allow an advanced characterisation of the anatomical substrates of functional activations. Finally, the advantages and disadvantages of the various methods are discussed, focussing on the question of which approach is most appropriate for a particular situation.
Age-related functional brain changes in young children.
Long, Xiangyu; Benischek, Alina; Dewey, Deborah; Lebel, Catherine
2017-07-15
Brain function and structure change significantly during the toddler and preschool years. However, most studies focus on older or younger children, so the specific nature of these changes is unclear. In the present study, we analyzed 77 functional magnetic resonance imaging datasets from 44 children aged 2-6 years. We extracted measures of both local (amplitude of low frequency fluctuation and regional homogeneity) and global (eigenvector centrality mapping) activity and connectivity, and examined their relationships with age using robust linear correlation analysis and strict control for head motion. Brain areas within the default mode network and the frontoparietal network, such as the middle frontal gyrus, the inferior parietal lobule and the posterior cingulate cortex, showed increases in local and global functional features with age. Several brain areas such as the superior parietal lobule and superior temporal gyrus presented opposite development trajectories of local and global functional features, suggesting a shifting connectivity framework in early childhood. This development of functional connectivity in early childhood likely underlies major advances in cognitive abilities, including language and development of theory of mind. These findings provide important insight into the development patterns of brain function during the preschool years, and lay the foundation for future studies of altered brain development in young children with brain disorders or injury. Copyright © 2017 Elsevier Inc. All rights reserved.
Muraskin, Jordan; Dodhia, Sonam; Lieberman, Gregory; Garcia, Javier O; Verstynen, Timothy; Vettel, Jean M; Sherwin, Jason; Sajda, Paul
2016-12-01
Post-task resting state dynamics can be viewed as a task-driven state where behavioral performance is improved through endogenous, non-explicit learning. Tasks that have intrinsic value for individuals are hypothesized to produce post-task resting state dynamics that promote learning. We measured simultaneous fMRI/EEG and DTI in Division-1 collegiate baseball players and compared to a group of controls, examining differences in both functional and structural connectivity. Participants performed a surrogate baseball pitch Go/No-Go task before a resting state scan, and we compared post-task resting state connectivity using a seed-based analysis from the supplementary motor area (SMA), an area whose activity discriminated players and controls in our previous results using this task. Although both groups were equally trained on the task, the experts showed differential activity in their post-task resting state consistent with motor learning. Specifically, we found (1) differences in bilateral SMA-L Insula functional connectivity between experts and controls that may reflect group differences in motor learning, (2) differences in BOLD-alpha oscillation correlations between groups suggests variability in modulatory attention in the post-task state, and (3) group differences between BOLD-beta oscillations that may indicate cognitive processing of motor inhibition. Structural connectivity analysis identified group differences in portions of the functionally derived network, suggesting that functional differences may also partially arise from variability in the underlying white matter pathways. Generally, we find that brain dynamics in the post-task resting state differ as a function of subject expertise and potentially result from differences in both functional and structural connectivity. Hum Brain Mapp 37:4454-4471, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
Lecrux, C; Hamel, E
2016-10-05
Brain imaging techniques that use vascular signals to map changes in neuronal activity, such as blood oxygenation level-dependent functional magnetic resonance imaging, rely on the spatial and temporal coupling between changes in neurophysiology and haemodynamics, known as 'neurovascular coupling (NVC)'. Accordingly, NVC responses, mapped by changes in brain haemodynamics, have been validated for different stimuli under physiological conditions. In the cerebral cortex, the networks of excitatory pyramidal cells and inhibitory interneurons generating the changes in neural activity and the key mediators that signal to the vascular unit have been identified for some incoming afferent pathways. The neural circuits recruited by whisker glutamatergic-, basal forebrain cholinergic- or locus coeruleus noradrenergic pathway stimulation were found to be highly specific and discriminative, particularly when comparing the two modulatory systems to the sensory response. However, it is largely unknown whether or not NVC is still reliable when brain states are altered or in disease conditions. This lack of knowledge is surprising since brain imaging is broadly used in humans and, ultimately, in conditions that deviate from baseline brain function. Using the whisker-to-barrel pathway as a model of NVC, we can interrogate the reliability of NVC under enhanced cholinergic or noradrenergic modulation of cortical circuits that alters brain states.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'. © 2016 The Author(s).
Li, Rui; Yin, Shufei; Zhu, Xinyi; Ren, Weicong; Yu, Jing; Wang, Pengyun; Zheng, Zhiwei; Niu, Ya-Nan; Huang, Xin; Li, Juan
2017-01-01
Increasing evidence suggests that functional brain connectivity is an important determinant of cognitive aging. However, the fundamental concept of inter-individual variations in functional connectivity in older individuals is not yet completely understood. It is essential to evaluate the extent to which inter-individual variability in connectivity impacts cognitive performance at an older age. In the current study, we aimed to characterize individual variability of functional connectivity in the elderly and to examine its significance to individual cognition. We mapped inter-individual variability of functional connectivity by analyzing whole-brain functional connectivity magnetic resonance imaging data obtained from a large sample of cognitively normal older adults. Our results demonstrated a gradual increase in variability in primary regions of the visual, sensorimotor, and auditory networks to specific subcortical structures, particularly the hippocampal formation, and the prefrontal and parietal cortices, which largely constitute the default mode and fronto-parietal networks, to the cerebellum. Further, the inter-individual variability of the functional connectivity correlated significantly with the degree of cognitive relevance. Regions with greater connectivity variability demonstrated more connections that correlated with cognitive performance. These results also underscored the crucial function of the long-range and inter-network connections in individual cognition. Thus, individual connectivity–cognition variability mapping findings may provide important information for future research on cognitive aging and neurocognitive diseases. PMID:29209203
Sanmillan, Jose L; Fernández-Coello, Alejandro; Fernández-Conejero, Isabel; Plans, Gerard; Gabarrós, Andreu
2017-03-01
OBJECTIVE Brain metastases are the most frequent intracranial malignant tumor in adults. Surgical intervention for metastases in eloquent areas remains controversial and challenging. Even when metastases are not infiltrating intra-parenchymal tumors, eloquent areas can be affected. Therefore, this study aimed to describe the role of a functional guided approach for the resection of brain metastases in the central region. METHODS Thirty-three patients (19 men and 14 women) with perirolandic metastases who were treated at the authors' institution were reviewed. All participants underwent resection using a functional guided approach, which consisted of using intraoperative brain mapping and/or neurophysiological monitoring to aid in the resection, depending on the functionality of the brain parenchyma surrounding each metastasis. Motor and sensory functions were monitored in all patients, and supplementary motor and language area functions were assessed in 5 and 4 patients, respectively. Clinical data were analyzed at presentation, discharge, and the 6-month follow-up. RESULTS The most frequent presenting symptom was seizure, followed by paresis. Gross-total removal of the metastasis was achieved in 31 patients (93.9%). There were 6 deaths during the follow-up period. After the removal of the metastasis, 6 patients (18.2%) presented with transient neurological worsening, of whom 4 had worsening of motor function impairment and 2 had acquired new sensory disturbances. Total recovery was achieved before the 3rd month of follow-up in all cases. Excluding those patients who died due to the progression of systemic illness, 88.9% of patients had a Karnofsky Performance Scale score greater than 80% at the 6-month follow-up. The mean survival time was 24.4 months after surgery. CONCLUSIONS The implementation of intraoperative electrical brain stimulation techniques in the resection of central region metastases may improve surgical planning and resection and may spare eloquent areas. This approach also facilitates maximal resection in these and other critical functional areas, thereby helping to avoid new postoperative neurological deficits. Avoiding permanent neurological deficits is critical for a good quality of life, especially in patients with a life expectancy of over a year.
Finding the imposter: brain connectivity of lesions causing delusional misidentifications.
Darby, R Ryan; Laganiere, Simon; Pascual-Leone, Alvaro; Prasad, Sashank; Fox, Michael D
2017-02-01
SEE MCKAY AND FURL DOI101093/AWW323 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Focal brain injury can sometimes lead to bizarre symptoms, such as the delusion that a family member has been replaced by an imposter (Capgras syndrome). How a single brain lesion could cause such a complex disorder is unclear, leading many to speculate that concurrent delirium, psychiatric disease, dementia, or a second lesion is required. Here we instead propose that Capgras and other delusional misidentification syndromes arise from single lesions at unique locations within the human brain connectome. This hypothesis is motivated by evidence that symptoms emerge from sites functionally connected to a lesion location, not just the lesion location itself. First, 17 cases of lesion-induced delusional misidentifications were identified and lesion locations were mapped to a common brain atlas. Second, lesion network mapping was used to identify brain regions functionally connected to the lesion locations. Third, regions involved in familiarity perception and belief evaluation, two processes thought to be abnormal in delusional misidentifications, were identified using meta-analyses of previous functional magnetic resonance imaging studies. We found that all 17 lesion locations were functionally connected to the left retrosplenial cortex, the region most activated in functional magnetic resonance imaging studies of familiarity. Similarly, 16 of 17 lesion locations were functionally connected to the right frontal cortex, the region most activated in functional magnetic resonance imaging studies of expectation violation, a component of belief evaluation. This connectivity pattern was highly specific for delusional misidentifications compared to four other lesion-induced neurological syndromes (P < 0.0001). Finally, 15 lesions causing other types of delusions were connected to expectation violation (P < 0.0001) but not familiarity regions, demonstrating specificity for delusion content. Our results provide potential neuroanatomical correlates for impaired familiarity perception and belief evaluation in patients with delusional misidentifications. More generally, we demonstrate a mechanism by which a single lesion can cause a complex neuropsychiatric syndrome based on that lesion's unique pattern of functional connectivity, without the need for pre-existing or hidden pathology. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Hyper-resting brain entropy within chronic smokers and its moderation by Sex.
Li, Zhengjun; Fang, Zhuo; Hager, Nathan; Rao, Hengyi; Wang, Ze
2016-07-05
Cigarette smoking is a chronic relapsing brain disorder, and remains a premier cause of morbidity and mortality. Functional neuroimaging has been used to assess differences in the mean strength of brain activity in smokers' brains, however less is known about the temporal dynamics within smokers' brains. Temporal dynamics is a key feature of a dynamic system such as the brain, and may carry information critical to understanding the brain mechanisms underlying cigarette smoking. We measured the temporal dynamics of brain activity using brain entropy (BEN) mapping and compared BEN between chronic non-deprived smokers and non-smoking controls. Because of the known sex differences in neural and behavioral smoking characteristics, comparisons were also made between males and females. Associations between BEN and smoking related clinical measures were assessed in smokers. Our data showed globally higher BEN in chronic smokers compared to controls. The escalated BEN was associated with more years of smoking in the right limbic area and frontal region. Female nonsmokers showed higher BEN than male nonsmokers in prefrontal cortex, insula, and precuneus, but the BEN sex difference in smokers was less pronounced. These findings suggest that BEN mapping may provide a useful tool for probing brain mechanisms related to smoking.
At least eighty percent of brain grey matter is modifiable by physical activity: A review study.
Batouli, Seyed Amir Hossein; Saba, Valiallah
2017-08-14
The human brain is plastic, i.e. it can show structural changes in response to the altered environment. Physical activity (PA) is a lifestyle factor which has significant associations with the structural and functional aspects of the human brain, as well as with the mind and body health. Many studies have reported regional/global brain volume increments due to exercising; however, a map which shows the overall extent of the influences of PAs on brain structure is not available. In this study, we collected all the reports on brain structural alterations in association with PA in healthy humans, and next, a brain map of the extent of these effects is provided. The results of this study showed that a large network of brain areas, equal to 82% of the total grey matter volume, were associated with PA. This finding has important implications in utilizing PA as a mediator factor for educational purposes in children, rehabilitation applications in patients, improving the cognitive abilities of the human brain such as in learning or memory, and preventing age-related brain deteriorations. Copyright © 2017 Elsevier B.V. All rights reserved.
[Introduction of neuroethics: out of clinic, beyond academia in human brain research].
Fukushi, Tamami; Sakura, Osamu
2008-11-01
Higher cognitive function in human brain is one of well-developed fields of neuroscience research in the 21st century. Especially functional magnetic resonance imaging (fMRI) and near infrared recording system have brought so many non-clinical researchers whose background is such as cognitive psychology, economics, politics, pedagogy, and so on, to the human brain mapping study. Authors have introduced the ethical issues related to incidental findings during the fMRI recording for non-clinical purpose, which is a typical problem derived from such expanded human brain research under non clinical condition, that is, neuroethics. In the present article we would introduce neuroethical issues in contexts of "out of clinic" and "beyond academia".
Awake right hemisphere brain surgery.
Hulou, M Maher; Cote, David J; Olubiyi, Olutayo I; Smith, Timothy R; Chiocca, E Antonio; Johnson, Mark D
2015-12-01
We report the indications and outcomes of awake right hemispheric brain surgery, as well as a rare patient with crossed aphasia. Awake craniotomies are often performed to protect eloquent cortex. We reviewed the medical records for 35 of 96 patients, in detail, who had awake right hemisphere brain operations. Intraoperative cortical mapping of motor and/or language function was performed in 29 of the 35 patients. A preoperative speech impairment and left hand dominance were the main indicators for awake right-sided craniotomies in patients with right hemisphere lesions. Four patients with lesion proximity to eloquent areas underwent awake craniotomies without cortical mapping. In addition, one patient had a broncho-pulmonary fistula, and another had a recent major cardiac procedure that precluded awake surgery. An eloquent cortex representation was identified in 14 patients (48.3%). Postoperatively, seven of 17 patients (41.1%) who presented with weakness, experienced improvements in their motor functions, 11 of 16 (68.7%) with seizures became seizure-free, and seven of nine (77.7%) with moderate to severe headaches and one of two with a visual field deficit improved significantly. There were also improvements in speech and language functions in all patients who presented with speech difficulties. A right sided awake craniotomy is an excellent option for left handed patients, or those with right sided cortical lesions that result in preoperative speech impairments. When combined with intraoperative cortical mapping, both speech and motor function can be well preserved. Copyright © 2015 Elsevier Ltd. All rights reserved.
Nonequilibrium landscape theory of neural networks.
Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin
2013-11-05
The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape-flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments.
Nonequilibrium landscape theory of neural networks
Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin
2013-01-01
The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape–flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments. PMID:24145451
Niu, Haijing; Wang, Jinhui; Zhao, Tengda; Shu, Ni; He, Yong
2012-01-01
The human brain is a highly complex system that can be represented as a structurally interconnected and functionally synchronized network, which assures both the segregation and integration of information processing. Recent studies have demonstrated that a variety of neuroimaging and neurophysiological techniques such as functional magnetic resonance imaging (MRI), diffusion MRI and electroencephalography/magnetoencephalography can be employed to explore the topological organization of human brain networks. However, little is known about whether functional near infrared spectroscopy (fNIRS), a relatively new optical imaging technology, can be used to map functional connectome of the human brain and reveal meaningful and reproducible topological characteristics. We utilized resting-state fNIRS (R-fNIRS) to investigate the topological organization of human brain functional networks in 15 healthy adults. Brain networks were constructed by thresholding the temporal correlation matrices of 46 channels and analyzed using graph-theory approaches. We found that the functional brain network derived from R-fNIRS data had efficient small-world properties, significant hierarchical modular structure and highly connected hubs. These results were highly reproducible both across participants and over time and were consistent with previous findings based on other functional imaging techniques. Our results confirmed the feasibility and validity of using graph-theory approaches in conjunction with optical imaging techniques to explore the topological organization of human brain networks. These results may expand a methodological framework for utilizing fNIRS to study functional network changes that occur in association with development, aging and neurological and psychiatric disorders.
NASA Astrophysics Data System (ADS)
Marchand, Paul J.; Bouwens, Arno; Shamaei, Vincent; Nguyen, David; Extermann, Jerome; Bolmont, Tristan; Lasser, Theo
2016-03-01
Magnetic Resonance Imaging has revolutionised our understanding of brain function through its ability to image human cerebral structures non-invasively over the entire brain. By exploiting the different magnetic properties of oxygenated and deoxygenated blood, functional MRI can indirectly map areas undergoing neural activation. Alongside the development of fMRI, powerful statistical tools have been developed in an effort to shed light on the neural pathways involved in processing of sensory and cognitive information. In spite of the major improvements made in fMRI technology, the obtained spatial resolution of hundreds of microns prevents MRI in resolving and monitoring processes occurring at the cellular level. In this regard, Optical Coherence Microscopy is an ideal instrumentation as it can image at high spatio-temporal resolution. Moreover, by measuring the mean and the width of the Doppler spectra of light scattered by moving particles, OCM allows extracting the axial and lateral velocity components of red blood cells. The ability to assess quantitatively total blood velocity, as opposed to classical axial velocity Doppler OCM, is of paramount importance in brain imaging as a large proportion of cortical vascular is oriented perpendicularly to the optical axis. We combine here quantitative blood flow imaging with extended-focus Optical Coherence Microscopy and Statistical Parametric Mapping tools to generate maps of stimuli-evoked cortical hemodynamics at the capillary level.
Mapping common aphasia assessments to underlying cognitive processes and their neural substrates
Lacey, Elizabeth H.; Skipper-Kallal, LM; Xing, S; Fama, ME; Turkeltaub, PE
2017-01-01
Background Understanding the relationships between clinical tests, the processes they measure, and the brain networks underlying them, is critical in order for clinicians to move beyond aphasia syndrome classification toward specification of individual language process impairments. Objective To understand the cognitive, language, and neuroanatomical factors underlying scores of commonly used aphasia tests. Methods 25 behavioral tests were administered to a group of 38 chronic left hemisphere stroke survivors and a high resolution MRI was obtained. Test scores were entered into a principal components analysis to extract the latent variables (factors) measured by the tests. Multivariate lesion-symptom mapping was used to localize lesions associated with the factor scores. Results The principal components analysis yielded four dissociable factors, which we labeled Word Finding/Fluency, Comprehension, Phonology/Working Memory Capacity, and Executive Function. While many tests loaded onto the factors in predictable ways, some relied heavily on factors not commonly associated with the tests. Lesion symptom mapping demonstrated discrete brain structures associated with each factor, including frontal, temporal, and parietal areas extending beyond the classical language network. Specific functions mapped onto brain anatomy largely in correspondence with modern neural models of language processing. Conclusions An extensive clinical aphasia assessment identifies four independent language functions, relying on discrete parts of the left middle cerebral artery territory. A better understanding of the processes underlying cognitive tests and the link between lesion and behavior may lead to improved aphasia diagnosis, and may yield treatments better targeted to an individual’s specific pattern of deficits and preserved abilities. PMID:28135902
Calamante, Fernando; Masterton, Richard A J; Tournier, Jacques-Donald; Smith, Robert E; Willats, Lisa; Raffelt, David; Connelly, Alan
2013-04-15
MRI provides a powerful tool for studying the functional and structural connections in the brain non-invasively. The technique of functional connectivity (FC) exploits the intrinsic temporal correlations of slow spontaneous signal fluctuations to characterise brain functional networks. In addition, diffusion MRI fibre-tracking can be used to study the white matter structural connections. In recent years, there has been considerable interest in combining these two techniques to provide an overall structural-functional description of the brain. In this work we applied the recently proposed super-resolution track-weighted imaging (TWI) methodology to demonstrate how whole-brain fibre-tracking data can be combined with FC data to generate a track-weighted (TW) FC map of FC networks. The method was applied to data from 8 healthy volunteers, and illustrated with (i) FC networks obtained using a seeded connectivity-based analysis (seeding in the precuneus/posterior cingulate cortex, PCC, known to be part of the default mode network), and (ii) with FC networks generated using independent component analysis (in particular, the default mode, attention, visual, and sensory-motor networks). TW-FC maps showed high intensity in white matter structures connecting the nodes of the FC networks. For example, the cingulum bundles show the strongest TW-FC values in the PCC seeded-based analysis, due to their major role in the connection between medial frontal cortex and precuneus/posterior cingulate cortex; similarly the superior longitudinal fasciculus was well represented in the attention network, the optic radiations in the visual network, and the corticospinal tract and corpus callosum in the sensory-motor network. The TW-FC maps highlight the white matter connections associated with a given FC network, and their intensity in a given voxel reflects the functional connectivity of the part of the nodes of the network linked by the structural connections traversing that voxel. They therefore contain a different (and novel) image contrast from that of the images used to generate them. The results shown in this study illustrate the potential of the TW-FC approach for the fusion of structural and functional data into a single quantitative image. This technique could therefore have important applications in neuroscience and neurology, such as for voxel-based comparison studies. Copyright © 2012 Elsevier Inc. All rights reserved.
Febo, Marcelo; Ferris, Craig F
2014-09-11
Oxytocin and vasopressin modulate a range of species typical behavioral functions that include social recognition, maternal-infant attachment, and modulation of memory, offensive aggression, defensive fear reactions, and reward seeking. We have employed novel functional magnetic resonance mapping techniques in awake rats to explore the roles of these neuropeptides in the maternal and non-maternal brain. Results from the functional neuroimaging studies that are summarized here have directly and indirectly confirmed and supported previous findings. Oxytocin is released within the lactating rat brain during suckling stimulation and activates specific subcortical networks in the maternal brain. Both vasopressin and oxytocin modulate brain regions involved unconditioned fear, processing of social stimuli and the expression of agonistic behaviors. Across studies there are relatively consistent brain networks associated with internal motivational drives and emotional states that are modulated by oxytocin and vasopressin. This article is part of a Special Issue entitled Oxytocin and Social Behav. Copyright © 2014 Elsevier B.V. All rights reserved.
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.
Mapping the human brain during a specific Vojta's tactile input: the ipsilateral putamen's role.
Sanz-Esteban, Ismael; Calvo-Lobo, Cesar; Ríos-Lago, Marcos; Álvarez-Linera, Juan; Muñoz-García, Daniel; Rodríguez-Sanz, David
2018-03-01
A century of research in human brain parcellation has demonstrated that different brain areas are associated with functional tasks. New neuroscientist perspectives to achieve the parcellation of the human brain have been developed to know the brain areas activation and its relationship with different stimuli. This descriptive study aimed to compare brain regions activation by specific tactile input (STI) stimuli according to the Vojta protocol (STI-group) to a non-STI stimulation (non-STI-group). An exploratory functional magnetic resonance imaging (fMRI) study was performed. The 2 groups of participants were passively stimulated by an expert physical therapist using the same paradigm structure, although differing in the place of stimulation. The stimulation was presented to participants using a block design in all cases. A sample of 16 healthy participants, 5 men and 11 women, with mean age 31.31 ± 8.13 years was recruited. Indeed, 12 participants were allocated in the STI-group and 4 participants in the non-STI-group. fMRI was used to map the human brain in vivo while these tactile stimuli were being applied. Data were analyzed using a general linear model in SPM12 implemented in MATLAB. Differences between groups showed a greater activation in the right cortical areas (temporal and frontal lobes), subcortical regions (thalamus, brainstem, and basal nuclei), and in the cerebellum (anterior lobe). STI-group had specific difference brain activation areas, such as the ipsilateral putamen. Future studies should study clinical implications in neurorehabilitation patients.
Moon, Hyun Im; Pyun, Sung-Bom; Tae, Woo-Suk; Kwon, Hee Kyu
2016-07-01
Stroke impairs motor, balance, and gait function and influences activities of daily living. Understanding the relationship between brain lesions and deficits can help clinicians set goals during rehabilitation. We sought to elucidate the neural substrates of lower extremity motor, balance, and ambulation function using voxel-based lesion symptom mapping (VLSM) in supratentorial stroke patients. We retrospectively screened patients who met the following criteria: first-ever stroke, supratentorial lesion, and available brain magnetic resonance imaging (MRI) data. MRIs of 133 stroke patients were selected for VLSM analysis. We generated statistical maps of lesions related to lower extremity motor (lower extremity Fugl-Meyer assessment, LEFM), balance (Berg Balance Scale, BBS), and gait (Functional Ambulation Category, FAC) using VLSM. VLSM revealed that lower LEFM scores were associated with damage to the bilateral basal ganglia, insula, internal capsule, and subgyral white matter adjacent to the corona radiata. The lesions were more widely distributed in the left than in the right hemisphere, representing motor and praxis function necessary for performing tasks. However, no associations between lesion maps and balance and gait function were established. Motor impairment of the lower extremities was associated with lesions in the basal ganglia, insula, internal capsule, and white matter adjacent to the corona radiata. However, VLSM revealed no specific lesion locations with regard to balance and gait function. This might be because balance and gait are complex skills that require spatial and temporal integration of sensory input and execution of movement patterns. For more accurate prediction, factors other than lesion location need to be investigated.
Model of brain activation predicts the neural collective influence map of the brain
Morone, Flaviano; Roth, Kevin; Min, Byungjoon; Makse, Hernán A.
2017-01-01
Efficient complex systems have a modular structure, but modularity does not guarantee robustness, because efficiency also requires an ingenious interplay of the interacting modular components. The human brain is the elemental paradigm of an efficient robust modular system interconnected as a network of networks (NoN). Understanding the emergence of robustness in such modular architectures from the interconnections of its parts is a longstanding challenge that has concerned many scientists. Current models of dependencies in NoN inspired by the power grid express interactions among modules with fragile couplings that amplify even small shocks, thus preventing functionality. Therefore, we introduce a model of NoN to shape the pattern of brain activations to form a modular environment that is robust. The model predicts the map of neural collective influencers (NCIs) in the brain, through the optimization of the influence of the minimal set of essential nodes responsible for broadcasting information to the whole-brain NoN. Our results suggest intervention protocols to control brain activity by targeting influential neural nodes predicted by network theory. PMID:28351973
Human brain mapping: A systematic comparison of parcellation methods for the human cerebral cortex.
Arslan, Salim; Ktena, Sofia Ira; Makropoulos, Antonios; Robinson, Emma C; Rueckert, Daniel; Parisot, Sarah
2018-04-15
The macro-connectome elucidates the pathways through which brain regions are structurally connected or functionally coupled to perform a specific cognitive task. It embodies the notion of representing and understanding all connections within the brain as a network, while the subdivision of the brain into interacting functional units is inherent in its architecture. As a result, the definition of network nodes is one of the most critical steps in connectivity network analysis. Although brain atlases obtained from cytoarchitecture or anatomy have long been used for this task, connectivity-driven methods have arisen only recently, aiming to delineate more homogeneous and functionally coherent regions. This study provides a systematic comparison between anatomical, connectivity-driven and random parcellation methods proposed in the thriving field of brain parcellation. Using resting-state functional MRI data from the Human Connectome Project and a plethora of quantitative evaluation techniques investigated in the literature, we evaluate 10 subject-level and 24 groupwise parcellation methods at different resolutions. We assess the accuracy of parcellations from four different aspects: (1) reproducibility across different acquisitions and groups, (2) fidelity to the underlying connectivity data, (3) agreement with fMRI task activation, myelin maps, and cytoarchitectural areas, and (4) network analysis. This extensive evaluation of different parcellations generated at the subject and group level highlights the strengths and shortcomings of the various methods and aims to provide a guideline for the choice of parcellation technique and resolution according to the task at hand. The results obtained in this study suggest that there is no optimal method able to address all the challenges faced in this endeavour simultaneously. Copyright © 2017 Elsevier Inc. All rights reserved.
Lee, Vincent K.; Nau, Amy C.; Laymon, Charles; Chan, Kevin C.; Rosario, Bedda L.; Fisher, Chris
2014-01-01
Purpose: Neuronal reorganization after blindness is of critical interest because it has implications for the rational prescription of artificial vision devices. The purpose of this study was to distinguish the microstructural differences between perinatally blind (PB), acquired blind (AB), and normally sighted controls (SCs) and relate these differences to performance on functional tasks using a sensory substitution device (BrainPort). Methods: We enrolled 52 subjects (PB n = 11; AB n = 35; SC n = 6). All subjects spent 15 h undergoing BrainPort device training. Outcomes of light perception, motion, direction, temporal resolution, grating, and acuity were tested at baseline and after training. Twenty-six of the subjects were scanned with a three Tesla MRI scanner for diffusion tensor imaging (DTI), and with a positron emission tomography (PET) scanner for mapping regional brain glucose consumption during sensory substitution function. Non-parametric models were used to analyze fractional anisotropy (FA; a DTI measure of microstructural integrity) of the brain via region-of-interest (ROI) analysis and tract-based spatial statistics (TBSS). Results: At baseline, all subjects performed all tasks at chance level. After training, light perception, time resolution, location and grating acuity tasks improved significantly for all subject groups. ROI and TBSS analyses of FA maps show areas of statistically significant differences (p ≤ 0.025) in the bilateral optic radiations and some visual association connections between all three groups. No relationship was found between FA and functional performance with the BrainPort. Discussion: All subjects showed performance improvements using the BrainPort irrespective of nature and duration of blindness. Definite brain areas with significant microstructural integrity changes exist among PB, AB, and NC, and these variations are most pronounced in the visual pathways. However, the use of sensory substitution devices is feasible irrespective of microstructural integrity of the primary visual pathways between the eye and the brain. Therefore, tongue based devices devices may be usable for a broad array of non-sighted patients. PMID:24860473
Wu, Huawang; Sun, Hui; Xu, Jinping; Wu, Yan; Wang, Chao; Xiao, Jing; She, Shenglin; Huang, Jianwei; Zou, Wenjin; Peng, Hongjun; Lu, Xiaobing; Huang, Guimao; Jiang, Tianzi; Ning, Yuping; Wang, Jiaojian
2016-01-01
Major depressive disorder (MDD) is one of the most prevalent mental disorders. In the brain, the hubs of the brain network play a key role in integrating and transferring information between different functional modules. However, whether the changed pattern in functional network hubs contributes to the onset of MDD remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory methods, we investigated whether alterations of hubs can be detected in MDD. First, we constructed the whole-brain voxel-wise functional networks and calculated a functional connectivity strength (FCS) map in each subject in 34 MDD patients and 34 gender-, age- and education level-matched healthy controls (HCs). Next, the two-sample t-test was applied to compare the FCS maps between HC and MDD patients and identified significant decrease of FCS in subgenual anterior cingulate cortex (sgACC) in MDD patients. Subsequent functional connectivity analyses of sgACC showed disruptions in functional connectivity with posterior insula, middle and inferior temporal gyrus, lingual gyrus and cerebellum in MDD patients. Furthermore, the changed FCS of sgACC and functional connections to sgACC were significantly correlated with the Hamilton Depression Rating Scale (HDRS) scores in MDD patients. The results of the present study revealed the abnormal hub of sgACC and its corresponding disrupted frontal-limbic-visual cognitive-cerebellum functional networks in MDD. These findings may provide a new insight for the diagnosis and treatment of MDD. PMID:28018183
Whole-central nervous system functional imaging in larval Drosophila
Lemon, William C.; Pulver, Stefan R.; Höckendorf, Burkhard; McDole, Katie; Branson, Kristin; Freeman, Jeremy; Keller, Philipp J.
2015-01-01
Understanding how the brain works in tight concert with the rest of the central nervous system (CNS) hinges upon knowledge of coordinated activity patterns across the whole CNS. We present a method for measuring activity in an entire, non-transparent CNS with high spatiotemporal resolution. We combine a light-sheet microscope capable of simultaneous multi-view imaging at volumetric speeds 25-fold faster than the state-of-the-art, a whole-CNS imaging assay for the isolated Drosophila larval CNS and a computational framework for analysing multi-view, whole-CNS calcium imaging data. We image both brain and ventral nerve cord, covering the entire CNS at 2 or 5 Hz with two- or one-photon excitation, respectively. By mapping network activity during fictive behaviours and quantitatively comparing high-resolution whole-CNS activity maps across individuals, we predict functional connections between CNS regions and reveal neurons in the brain that identify type and temporal state of motor programs executed in the ventral nerve cord. PMID:26263051
Hsiao, Mei-Yu; Chen, Chien-Chung; Chen, Jyh-Horng
2009-10-01
With a rapid progress in the field, a great many fMRI studies are published every year, to the extent that it is now becoming difficult for researchers to keep up with the literature, since reading papers is extremely time-consuming and labor-intensive. Thus, automatic information extraction has become an important issue. In this study, we used the Unified Medical Language System (UMLS) to construct a hierarchical concept-based dictionary of brain functions. To the best of our knowledge, this is the first generalized dictionary of this kind. We also developed an information extraction system for recognizing, mapping and classifying terms relevant to human brain study. The precision and recall of our system was on a par with that of human experts in term recognition, term mapping and term classification. Our approach presented in this paper presents an alternative to the more laborious, manual entry approach to information extraction.
Stomach-brain synchrony reveals a novel, delayed-connectivity resting-state network in humans
Devauchelle, Anne-Dominique; Béranger, Benoît; Tallon-Baudry, Catherine
2018-01-01
Resting-state networks offer a unique window into the brain’s functional architecture, but their characterization remains limited to instantaneous connectivity thus far. Here, we describe a novel resting-state network based on the delayed connectivity between the brain and the slow electrical rhythm (0.05 Hz) generated in the stomach. The gastric network cuts across classical resting-state networks with partial overlap with autonomic regulation areas. This network is composed of regions with convergent functional properties involved in mapping bodily space through touch, action or vision, as well as mapping external space in bodily coordinates. The network is characterized by a precise temporal sequence of activations within a gastric cycle, beginning with somato-motor cortices and ending with the extrastriate body area and dorsal precuneus. Our results demonstrate that canonical resting-state networks based on instantaneous connectivity represent only one of the possible partitions of the brain into coherent networks based on temporal dynamics. PMID:29561263
A probabilistic framework to infer brain functional connectivity from anatomical connections.
Deligianni, Fani; Varoquaux, Gael; Thirion, Bertrand; Robinson, Emma; Sharp, David J; Edwards, A David; Rueckert, Daniel
2011-01-01
We present a novel probabilistic framework to learn across several subjects a mapping from brain anatomical connectivity to functional connectivity, i.e. the covariance structure of brain activity. This prediction problem must be formulated as a structured-output learning task, as the predicted parameters are strongly correlated. We introduce a model selection framework based on cross-validation with a parametrization-independent loss function suitable to the manifold of covariance matrices. Our model is based on constraining the conditional independence structure of functional activity by the anatomical connectivity. Subsequently, we learn a linear predictor of a stationary multivariate autoregressive model. This natural parameterization of functional connectivity also enforces the positive-definiteness of the predicted covariance and thus matches the structure of the output space. Our results show that functional connectivity can be explained by anatomical connectivity on a rigorous statistical basis, and that a proper model of functional connectivity is essential to assess this link.
Katwal, Santosh B; Gore, John C; Marois, Rene; Rogers, Baxter P
2013-09-01
We present novel graph-based visualizations of self-organizing maps for unsupervised functional magnetic resonance imaging (fMRI) analysis. A self-organizing map is an artificial neural network model that transforms high-dimensional data into a low-dimensional (often a 2-D) map using unsupervised learning. However, a postprocessing scheme is necessary to correctly interpret similarity between neighboring node prototypes (feature vectors) on the output map and delineate clusters and features of interest in the data. In this paper, we used graph-based visualizations to capture fMRI data features based upon 1) the distribution of data across the receptive fields of the prototypes (density-based connectivity); and 2) temporal similarities (correlations) between the prototypes (correlation-based connectivity). We applied this approach to identify task-related brain areas in an fMRI reaction time experiment involving a visuo-manual response task, and we correlated the time-to-peak of the fMRI responses in these areas with reaction time. Visualization of self-organizing maps outperformed independent component analysis and voxelwise univariate linear regression analysis in identifying and classifying relevant brain regions. We conclude that the graph-based visualizations of self-organizing maps help in advanced visualization of cluster boundaries in fMRI data enabling the separation of regions with small differences in the timings of their brain responses.
Tan, Francisca M.; Caballero-Gaudes, César; Mullinger, Karen J.; Cho, Siu-Yeung; Zhang, Yaping; Dryden, Ian L.; Francis, Susan T.; Gowland, Penny A.
2017-01-01
Most fMRI studies map task-driven brain activity using a block or event-related paradigm. Sparse Paradigm Free Mapping (SPFM) can detect the onset and spatial distribution of BOLD events in the brain without prior timing information; but relating the detected events to brain function remains a challenge. In this study, we developed a decoding method for SPFM using a coordinate-based meta-analysis method of Activation Likelihood Estimation (ALE). We defined meta-maps of statistically significant ALE values that correspond to types of events and calculated a summation overlap between the normalized meta-maps and SPFM maps. As a proof of concept, this framework was applied to relate SPFM-detected events in the Sensorimotor Network (SMN) to six motor function (left/right fingers, left/right toes, swallowing and eye blinks). We validated the framework using simultaneous Electromyography-fMRI experiments and motor tasks with short and long duration, and random inter-stimulus interval. The decoding scores were considerably lower for eye movements relative to other movement types tested. The average successful rate for short and long motor events was 77 ± 13% and 74 ± 16% respectively, excluding eye movements. We found good agreement between the decoding results and EMG for most events and subjects, with a range in sensitivity between 55 and 100%, excluding eye movements. The proposed method was then used to classify the movement types of spontaneous single-trial events in the SMN during resting state, which produced an average successful rate of 22 ± 12%. Finally, this paper discusses methodological implications and improvements to increase the decoding performance. PMID:28815863
NASA Astrophysics Data System (ADS)
Wang, Jiang; Yang, Chen; Wang, Ruofan; Yu, Haitao; Cao, Yibin; Liu, Jing
2016-10-01
In this paper, EEG series are applied to construct functional connections with the correlation between different regions in order to investigate the nonlinear characteristic and the cognitive function of the brain with Alzheimer's disease (AD). First, limited penetrable visibility graph (LPVG) and phase space method map single EEG series into networks, and investigate the underlying chaotic system dynamics of AD brain. Topological properties of the networks are extracted, such as average path length and clustering coefficient. It is found that the network topology of AD in several local brain regions are different from that of the control group with no statistically significant difference existing all over the brain. Furthermore, in order to detect the abnormality of AD brain as a whole, functional connections among different brain regions are reconstructed based on similarity of clustering coefficient sequence (CCSS) of EEG series in the four frequency bands (delta, theta, alpha, and beta), which exhibit obvious small-world properties. Graph analysis demonstrates that for both methodologies, the functional connections between regions of AD brain decrease, particularly in the alpha frequency band. AD causes the graph index complexity of the functional network decreased, the small-world properties weakened, and the vulnerability increased. The obtained results show that the brain functional network constructed by LPVG and phase space method might be more effective to distinguish AD from the normal control than the analysis of single series, which is helpful for revealing the underlying pathological mechanism of the disease.
Sutterer, Matthew J.; Bruss, Joel; Boes, Aaron D.; Voss, Michelle W.; Bechara, Antoine; Tranel, Daniel
2016-01-01
Studies of patients with brain damage have highlighted a broad neural network of limbic and prefrontal areas as important for adaptive decision-making. However, some patients with damage outside these regions have impaired decision-making behavior, and the behavioral impairments observed in these cases are often attributed to the general variability in behavior following brain damage, rather than a deficit in a specific brain-behavior relationship. A novel approach, lesion-derived network mapping, uses healthy subject resting-state functional connectivity (RSFC) data to infer the areas that would be connected with each patient’s lesion area in healthy adults. Here, we used this approach to investigate whether there was a systematic pattern of connectivity associated with decision-making performance in patients with focal damage in areas not classically associated with decision-making. These patients were categorized a priori into “impaired” or “unimpaired” groups based on their performance on the Iowa Gambling Task (IGT). Lesion-derived network maps based on the impaired patients showed overlap in somatosensory, motor and insula cortices, to a greater extent than patients who showed unimpaired IGT performance. Akin to the classic concept of “diaschisis” (von Monakow, 1914), this focus on the remote effects that focal damage can have on large-scale distributed brain networks has the potential to inform not only differences in decision-making behavior, but also other cognitive functions or neurological syndromes where a distinct phenotype has eluded neuroanatomical classification and brain-behavior relationships appear highly heterogeneous. PMID:26994344
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
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.
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.
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.
Heterogeneous fractionation profiles of meta-analytic coactivation networks.
Laird, Angela R; Riedel, Michael C; Okoe, Mershack; Jianu, Radu; Ray, Kimberly L; Eickhoff, Simon B; Smith, Stephen M; Fox, Peter T; Sutherland, Matthew T
2017-04-01
Computational cognitive neuroimaging approaches can be leveraged to characterize the hierarchical organization of distributed, functionally specialized networks in the human brain. To this end, we performed large-scale mining across the BrainMap database of coordinate-based activation locations from over 10,000 task-based experiments. Meta-analytic coactivation networks were identified by jointly applying independent component analysis (ICA) and meta-analytic connectivity modeling (MACM) across a wide range of model orders (i.e., d=20-300). We then iteratively computed pairwise correlation coefficients for consecutive model orders to compare spatial network topologies, ultimately yielding fractionation profiles delineating how "parent" functional brain systems decompose into constituent "child" sub-networks. Fractionation profiles differed dramatically across canonical networks: some exhibited complex and extensive fractionation into a large number of sub-networks across the full range of model orders, whereas others exhibited little to no decomposition as model order increased. Hierarchical clustering was applied to evaluate this heterogeneity, yielding three distinct groups of network fractionation profiles: high, moderate, and low fractionation. BrainMap-based functional decoding of resultant coactivation networks revealed a multi-domain association regardless of fractionation complexity. Rather than emphasize a cognitive-motor-perceptual gradient, these outcomes suggest the importance of inter-lobar connectivity in functional brain organization. We conclude that high fractionation networks are complex and comprised of many constituent sub-networks reflecting long-range, inter-lobar connectivity, particularly in fronto-parietal regions. In contrast, low fractionation networks may reflect persistent and stable networks that are more internally coherent and exhibit reduced inter-lobar communication. Copyright © 2017 Elsevier Inc. All rights reserved.
Heterogeneous fractionation profiles of meta-analytic coactivation networks
Laird, Angela R.; Riedel, Michael C.; Okoe, Mershack; Jianu, Radu; Ray, Kimberly L.; Eickhoff, Simon B.; Smith, Stephen M.; Fox, Peter T.; Sutherland, Matthew T.
2017-01-01
Computational cognitive neuroimaging approaches can be leveraged to characterize the hierarchical organization of distributed, functionally specialized networks in the human brain. To this end, we performed large-scale mining across the BrainMap database of coordinate-based activation locations from over 10,000 task-based experiments. Meta-analytic coactivation networks were identified by jointly applying independent component analysis (ICA) and meta-analytic connectivity modeling (MACM) across a wide range of model orders (i.e., d = 20 to 300). We then iteratively computed pairwise correlation coefficients for consecutive model orders to compare spatial network topologies, ultimately yielding fractionation profiles delineating how “parent” functional brain systems decompose into constituent “child” sub-networks. Fractionation profiles differed dramatically across canonical networks: some exhibited complex and extensive fractionation into a large number of sub-networks across the full range of model orders, whereas others exhibited little to no decomposition as model order increased. Hierarchical clustering was applied to evaluate this heterogeneity, yielding three distinct groups of network fractionation profiles: high, moderate, and low fractionation. BrainMap-based functional decoding of resultant coactivation networks revealed a multi-domain association regardless of fractionation complexity. Rather than emphasize a cognitive-motor-perceptual gradient, these outcomes suggest the importance of inter-lobar connectivity in functional brain organization. We conclude that high fractionation networks are complex and comprised of many constituent sub-networks reflecting long-range, inter-lobar connectivity, particularly in fronto-parietal regions. In contrast, low fractionation networks may reflect persistent and stable networks that are more internally coherent and exhibit reduced inter-lobar communication. PMID:28222386
Visintin, Eleonora; De Panfilis, Chiara; Amore, Mario; Balestrieri, Matteo; Wolf, Robert Christian; Sambataro, Fabio
2016-11-01
Altered intrinsic function of the brain has been implicated in Borderline Personality Disorder (BPD). Nonetheless, imaging studies have yielded inconsistent alterations of brain function. To investigate the neural activity at rest in BPD, we conducted a set of meta-analyses of brain imaging studies performed at rest. A total of seven functional imaging studies (152 patients with BPD and 147 control subjects) were combined using whole-brain Signed Differential Mapping meta-analyses. Furthermore, two conjunction meta-analyses of neural activity at rest were also performed: with neural activity changes during emotional processing, and with structural differences, respectively. We found altered neural activity in the regions of the default mode network (DMN) in BPD. Within the regions of the midline core DMN, patients with BPD showed greater activity in the anterior as well as in the posterior midline hubs relative to controls. Conversely, in the regions of the dorsal DMN they showed reduced activity compared to controls in the right lateral temporal complex and bilaterally in the orbitofrontal cortex. Increased activity in the precuneus was observed both at rest and during emotional processing. Reduced neural activity at rest in lateral temporal complex was associated with smaller volume of this area. Heterogeneity across imaging studies. Altered activity in the regions of the midline core as well as of the dorsal subsystem of the DMN may reflect difficulties with interpersonal and affective regulation in BPD. These findings suggest that changes in spontaneous neural activity could underlie core symptoms in BPD. Copyright © 2016 Elsevier B.V. All rights reserved.
Human brain lesion-deficit inference remapped.
Mah, Yee-Haur; Husain, Masud; Rees, Geraint; Nachev, Parashkev
2014-09-01
Our knowledge of the anatomical organization of the human brain in health and disease draws heavily on the study of patients with focal brain lesions. Historically the first method of mapping brain function, it is still potentially the most powerful, establishing the necessity of any putative neural substrate for a given function or deficit. Great inferential power, however, carries a crucial vulnerability: without stronger alternatives any consistent error cannot be easily detected. A hitherto unexamined source of such error is the structure of the high-dimensional distribution of patterns of focal damage, especially in ischaemic injury-the commonest aetiology in lesion-deficit studies-where the anatomy is naturally shaped by the architecture of the vascular tree. This distribution is so complex that analysis of lesion data sets of conventional size cannot illuminate its structure, leaving us in the dark about the presence or absence of such error. To examine this crucial question we assembled the largest known set of focal brain lesions (n = 581), derived from unselected patients with acute ischaemic injury (mean age = 62.3 years, standard deviation = 17.8, male:female ratio = 0.547), visualized with diffusion-weighted magnetic resonance imaging, and processed with validated automated lesion segmentation routines. High-dimensional analysis of this data revealed a hidden bias within the multivariate patterns of damage that will consistently distort lesion-deficit maps, displacing inferred critical regions from their true locations, in a manner opaque to replication. Quantifying the size of this mislocalization demonstrates that past lesion-deficit relationships estimated with conventional inferential methodology are likely to be significantly displaced, by a magnitude dependent on the unknown underlying lesion-deficit relationship itself. Past studies therefore cannot be retrospectively corrected, except by new knowledge that would render them redundant. Positively, we show that novel machine learning techniques employing high-dimensional inference can nonetheless accurately converge on the true locus. We conclude that current inferences about human brain function and deficits based on lesion mapping must be re-evaluated with methodology that adequately captures the high-dimensional structure of lesion data. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain.
Khavari, Rose; Karmonik, Christof; Shy, Michael; Fletcher, Sophie; Boone, Timothy
2017-02-01
Neurogenic lower urinary tract dysfunction, which is common in patients with multiple sclerosis, has a significant impact on quality of life. In this study we sought to determine brain activity processes during the micturition cycle in female patients with multiple sclerosis and neurogenic lower urinary tract dysfunction. We report brain activity on functional magnetic resonance imaging and simultaneous urodynamic testing in 23 ambulatory female patients with multiple sclerosis. Individual functional magnetic resonance imaging activation maps at strong desire to void and at initiation of voiding were calculated and averaged at Montreal Neuroimaging Institute. Areas of significant activation were identified in these average maps. Subgroup analysis was performed in patients with elicitable neurogenic detrusor overactivity or detrusor-sphincter dyssynergia. Group analysis of all patients at strong desire to void yielded areas of activation in regions associated with executive function (frontal gyrus), emotional regulation (cingulate gyrus) and motor control (putamen, cerebellum and precuneus). Comparison of the average change in activation between previously reported healthy controls and patients with multiple sclerosis showed predominantly stronger, more focal activation in the former and lower, more diffused activation in the latter. Patients with multiple sclerosis who had demonstrable neurogenic detrusor overactivity and detrusor-sphincter dyssynergia showed a trend toward distinct brain activation at full urge and at initiation of voiding respectively. We successfully studied brain activation during the entire micturition cycle in female patients with neurogenic lower urinary tract dysfunction and multiple sclerosis using a concurrent functional magnetic resonance imaging/urodynamic testing platform. Understanding the central neural processes involved in specific parts of micturition in patients with neurogenic lower urinary tract dysfunction may identify areas of interest for future intervention. Copyright © 2017 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.
Stimulus Configuration, Classical Conditioning, and Hippocampal Function.
ERIC Educational Resources Information Center
Schmajuk, Nestor A.; DiCarlo, James J.
1991-01-01
The participation of the hippocampus in classical conditioning is described in terms of a multilayer network portraying stimulus configuration. A model of hippocampal function is presented, and computer simulations are used to study neural activity in the various brain areas mapped according to the model. (SLD)
NASA Astrophysics Data System (ADS)
Huang, Chun-Jung; Sun, Chia-Wei; Chou, Po-Han; Chuang, Ching-Cheng
2016-03-01
Verbal fluency tests (VFT) are widely used neuropsychological tests of frontal lobe and have been frequently used in various functional brain mapping studies. There are two versions of VFT based on the type of cue: the letter fluency task (LFT) and the category fluency task (CFT). However, the fundamental aspect of the brain connectivity across spatial regions of the fronto-temporal regions during the VFTs has not been elucidated to date. In this study we hypothesized that different cortical functional connectivity over bilateral fronto-temporal regions can be observed by means of multi-channel fNIRS in the LFT and the CFT respectively. Our results from fNIRS (ETG-4000) showed different patterns of brain functional connectivity consistent with these different cognitive requirements. We demonstrate more brain functional connectivity over frontal and temporal regions during LFT than CFT, and this was in line with previous brain activity studies using fNIRS demonstrating increased frontal and temporal region activation during LFT and CFT and more pronounced frontal activation by the LFT.
O'Connell, Caitlin; Ho, Leon C; Murphy, Matthew C; Conner, Ian P; Wollstein, Gadi; Cham, Rakie; Chan, Kevin C
2016-11-09
Human visual performance has been observed to show superiority in localized regions of the visual field across many classes of stimuli. However, the underlying neural mechanisms remain unclear. This study aims to determine whether the visual information processing in the human brain is dependent on the location of stimuli in the visual field and the corresponding neuroarchitecture using blood-oxygenation-level-dependent functional MRI (fMRI) and diffusion kurtosis MRI, respectively, in 15 healthy individuals at 3 T. In fMRI, visual stimulation to the lower hemifield showed stronger brain responses and larger brain activation volumes than the upper hemifield, indicative of the differential sensitivity of the human brain across the visual field. In diffusion kurtosis MRI, the brain regions mapping to the lower visual field showed higher mean kurtosis, but not fractional anisotropy or mean diffusivity compared with the upper visual field. These results suggested the different distributions of microstructural organization across visual field brain representations. There was also a strong positive relationship between diffusion kurtosis and fMRI responses in the lower field brain representations. In summary, this study suggested the structural and functional brain involvements in the asymmetry of visual field responses in humans, and is important to the neurophysiological and psychological understanding of human visual information processing.
Resting-state functional connectivity imaging of the mouse brain using photoacoustic tomography
NASA Astrophysics Data System (ADS)
Nasiriavanaki, Mohammadreza; Xia, Jun; Wan, Hanlin; Bauer, Adam Q.; Culver, Joseph P.; Wang, Lihong V.
2014-03-01
Resting-state functional connectivity (RSFC) imaging is an emerging neuroimaging approach that aims to identify spontaneous cerebral hemodynamic fluctuations and their associated functional connections. Clinical studies have demonstrated that RSFC is altered in brain disorders such as stroke, Alzheimer's, autism, and epilepsy. However, conventional neuroimaging modalities cannot easily be applied to mice, the most widely used model species for human brain disease studies. For instance, functional magnetic resonance imaging (fMRI) of mice requires a very high magnetic field to obtain a sufficient signal-to-noise ratio and spatial resolution. Functional connectivity mapping with optical intrinsic signal imaging (fcOIS) is an alternative method. Due to the diffusion of light in tissue, the spatial resolution of fcOIS is limited, and experiments have been performed using an exposed skull preparation. In this study, we show for the first time, the use of photoacoustic computed tomography (PACT) to noninvasively image resting-state functional connectivity in the mouse brain, with a large field of view and a high spatial resolution. Bilateral correlations were observed in eight regions, as well as several subregions. These findings agreed well with the Paxinos mouse brain atlas. This study showed that PACT is a promising, non-invasive modality for small-animal functional brain imaging.
Advanced lesion symptom mapping analyses and implementation as BCBtoolkit.
Foulon, Chris; Cerliani, Leonardo; Kinkingnéhun, Serge; Levy, Richard; Rosso, Charlotte; Urbanski, Marika; Volle, Emmanuelle; Thiebaut de Schotten, Michel
2018-03-01
Patients with brain lesions provide a unique opportunity to understand the functioning of the human mind. However, even when focal, brain lesions have local and remote effects that impact functionally and structurally connected circuits. Similarly, function emerges from the interaction between brain areas rather than their sole activity. For instance, category fluency requires the associations between executive, semantic, and language production functions. Here, we provide, for the first time, a set of complementary solutions for measuring the impact of a given lesion on the neuronal circuits. Our methods, which were applied to 37 patients with a focal frontal brain lesions, revealed a large set of directly and indirectly disconnected brain regions that had significantly impacted category fluency performance. The directly disconnected regions corresponded to areas that are classically considered as functionally engaged in verbal fluency and categorization tasks. These regions were also organized into larger directly and indirectly disconnected functional networks, including the left ventral fronto-parietal network, whose cortical thickness correlated with performance on category fluency. The combination of structural and functional connectivity together with cortical thickness estimates reveal the remote effects of brain lesions, provide for the identification of the affected networks, and strengthen our understanding of their relationship with cognitive and behavioral measures. The methods presented are available and freely accessible in the BCBtoolkit as supplementary software [1].
Brain-Mind Operational Architectonics Imaging: Technical and Methodological Aspects
Fingelkurts, Andrew A; Fingelkurts, Alexander A
2008-01-01
This review paper deals with methodological and technical foundations of the Operational Architectonics framework of brain and mind functioning. This theory provides a framework for mapping and understanding important aspects of the brain mechanisms that constitute perception, cognition, and eventually consciousness. The methods utilized within Operational Architectonics framework allow analyzing with an incredible detail the operational behavior of local neuronal assemblies and their joint activity in the form of unified and metastable operational modules, which constitute the whole hierarchy of brain operations, operations of cognition and phenomenal consciousness. PMID:19526071
Noninvasive near-infrared topography of human brain activity using intensity modulation spectroscopy
NASA Astrophysics Data System (ADS)
Yamashita, Yuichi; Maki, Atsushi; Ito, Yoshitoshi; Watanabe, Eiju; Mayanagi, Yoshiaki; Koizumi, Hideaki
1996-04-01
We describe the functional topography of human brain activity due to motor stimulation by using near-infrared spectroscopy. Finger motion by each hand was used as the motor stimulation, and activity in the left fronto-central region of the brain was measured. A greater change in oxyhemoglobin concentration due to brain activity during the stimulation was obtained for the right hand than for the left hand. Localization of the activity was obtained by topographically mapping the measured changes for ten positions within the region.
Haptic contents of a movie dynamically engage the spectator's sensorimotor cortex.
Lankinen, Kaisu; Smeds, Eero; Tikka, Pia; Pihko, Elina; Hari, Riitta; Koskinen, Miika
2016-11-01
Observation of another person's actions and feelings activates brain areas that support similar functions in the observer, thereby facilitating inferences about the other's mental and bodily states. In real life, events eliciting this kind of vicarious brain activations are intermingled with other complex, ever-changing stimuli in the environment. One practical approach to study the neural underpinnings of real-life vicarious perception is to image brain activity during movie viewing. Here the goal was to find out how observed haptic events in a silent movie would affect the spectator's sensorimotor cortex. The functional state of the sensorimotor cortex was monitored by analyzing, in 16 healthy subjects, magnetoencephalographic (MEG) responses to tactile finger stimuli that were presented once per second throughout the session. Using canonical correlation analysis and spatial filtering, consistent single-trial responses across subjects were uncovered, and their waveform changes throughout the movie were quantified. The long-latency (85-175 ms) parts of the responses were modulated in concordance with the participants' average moment-by-moment ratings of own engagement in the haptic content of the movie (correlation r = 0.49; ratings collected after the MEG session). The results, obtained by using novel signal-analysis approaches, demonstrate that the functional state of the human sensorimotor cortex fluctuates in a fine-grained manner even during passive observation of temporally varying haptic events. Hum Brain Mapp 37:4061-4068, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
Generating Text from Functional Brain Images
Pereira, Francisco; Detre, Greg; Botvinick, Matthew
2011-01-01
Recent work has shown that it is possible to take brain images acquired during viewing of a scene and reconstruct an approximation of the scene from those images. Here we show that it is also possible to generate text about the mental content reflected in brain images. We began with images collected as participants read names of concrete items (e.g., “Apartment’’) while also seeing line drawings of the item named. We built a model of the mental semantic representation of concrete concepts from text data and learned to map aspects of such representation to patterns of activation in the corresponding brain image. In order to validate this mapping, without accessing information about the items viewed for left-out individual brain images, we were able to generate from each one a collection of semantically pertinent words (e.g., “door,” “window” for “Apartment’’). Furthermore, we show that the ability to generate such words allows us to perform a classification task and thus validate our method quantitatively. PMID:21927602
Lesion network localization of criminal behavior
Darby, R. Ryan; Horn, Andreas; Fox, Michael D.
2018-01-01
Following brain lesions, previously normal patients sometimes exhibit criminal behavior. Although rare, these cases can lend unique insight into the neurobiological substrate of criminality. Here we present a systematic mapping of lesions with known temporal association to criminal behavior, identifying 17 lesion cases. The lesion sites were spatially heterogeneous, including the medial prefrontal cortex, orbitofrontal cortex, and different locations within the bilateral temporal lobes. No single brain region was damaged in all cases. Because lesion-induced symptoms can come from sites connected to the lesion location and not just the lesion location itself, we also identified brain regions functionally connected to each lesion location. This technique, termed lesion network mapping, has recently identified regions involved in symptom generation across a variety of lesion-induced disorders. All lesions were functionally connected to the same network of brain regions. This criminality-associated connectivity pattern was unique compared with lesions causing four other neuropsychiatric syndromes. This network includes regions involved in morality, value-based decision making, and theory of mind, but not regions involved in cognitive control or empathy. Finally, we replicated our results in a separate cohort of 23 cases in which a temporal relationship between brain lesions and criminal behavior was implied but not definitive. Our results suggest that lesions in criminals occur in different brain locations but localize to a unique resting state network, providing insight into the neurobiology of criminal behavior. PMID:29255017
Chen, Li M; Turner, Gregory H; Friedman, Robert M; Zhang, Na; Gore, John C; Roe, Anna W; Avison, Malcolm J
2007-08-22
Although blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has been widely used to explore human brain function, questions remain regarding the ultimate spatial resolution of positive BOLD fMRI, and indeed the extent to which functional maps revealed by positive BOLD correlate spatially with maps obtained with other high-spatial-resolution mapping techniques commonly used in animals, such as optical imaging of intrinsic signal (OIS) and single-unit electrophysiology. Here, we demonstrate that the positive BOLD signal at 9.4T can reveal the fine topography of individual fingerpads in single-condition activation maps in nonhuman primates. These digit maps are similar to maps obtained from the same animal using intrinsic optical imaging. Furthermore, BOLD fMRI reliably resolved submillimeter spatial shifts in activation in area 3b previously identified with OIS (Chen et al., 2003) as neural correlates of the "funneling illusion." These data demonstrate that at high field, high-spatial-resolution topographic maps can be achieved using the positive BOLD signal, weakening previous notions regarding the spatial specificity of the positive BOLD signal.
Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks
Ruiz-Rizzo, Adriana L.; Neitzel, Julia; Müller, Hermann J.; Sorg, Christian; Finke, Kathrin
2018-01-01
Separable visual attention functions are assumed to rely on distinct but interacting neural mechanisms. Bundesen's “theory of visual attention” (TVA) allows the mathematical estimation of independent parameters that characterize individuals' visual attentional capacity (i.e., visual processing speed and visual short-term memory storage capacity) and selectivity functions (i.e., top-down control and spatial laterality). However, it is unclear whether these parameters distinctively map onto different brain networks obtained from intrinsic functional connectivity, which organizes slowly fluctuating ongoing brain activity. In our study, 31 demographically homogeneous healthy young participants performed whole- and partial-report tasks and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Report accuracy was modeled using TVA to estimate, individually, the four TVA parameters. Networks encompassing cortical areas relevant for visual attention were derived from independent component analysis of rs-fMRI data: visual, executive control, right and left frontoparietal, and ventral and dorsal attention networks. Two TVA parameters were mapped on particular functional networks. First, participants with higher (vs. lower) visual processing speed showed lower functional connectivity within the ventral attention network. Second, participants with more (vs. less) efficient top-down control showed higher functional connectivity within the dorsal attention network and lower functional connectivity within the visual network. Additionally, higher performance was associated with higher functional connectivity between networks: specifically, between the ventral attention and right frontoparietal networks for visual processing speed, and between the visual and executive control networks for top-down control. The higher inter-network functional connectivity was related to lower intra-network connectivity. These results demonstrate that separable visual attention parameters that are assumed to constitute relatively stable traits correspond distinctly to the functional connectivity both within and between particular functional networks. This implies that individual differences in basic attention functions are represented by differences in the coherence of slowly fluctuating brain activity. PMID:29662444
Ruiz-Rizzo, Adriana L; Neitzel, Julia; Müller, Hermann J; Sorg, Christian; Finke, Kathrin
2018-01-01
Separable visual attention functions are assumed to rely on distinct but interacting neural mechanisms. Bundesen's "theory of visual attention" (TVA) allows the mathematical estimation of independent parameters that characterize individuals' visual attentional capacity (i.e., visual processing speed and visual short-term memory storage capacity) and selectivity functions (i.e., top-down control and spatial laterality). However, it is unclear whether these parameters distinctively map onto different brain networks obtained from intrinsic functional connectivity, which organizes slowly fluctuating ongoing brain activity. In our study, 31 demographically homogeneous healthy young participants performed whole- and partial-report tasks and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Report accuracy was modeled using TVA to estimate, individually, the four TVA parameters. Networks encompassing cortical areas relevant for visual attention were derived from independent component analysis of rs-fMRI data: visual, executive control, right and left frontoparietal, and ventral and dorsal attention networks. Two TVA parameters were mapped on particular functional networks. First, participants with higher (vs. lower) visual processing speed showed lower functional connectivity within the ventral attention network. Second, participants with more (vs. less) efficient top-down control showed higher functional connectivity within the dorsal attention network and lower functional connectivity within the visual network. Additionally, higher performance was associated with higher functional connectivity between networks: specifically, between the ventral attention and right frontoparietal networks for visual processing speed, and between the visual and executive control networks for top-down control. The higher inter-network functional connectivity was related to lower intra-network connectivity. These results demonstrate that separable visual attention parameters that are assumed to constitute relatively stable traits correspond distinctly to the functional connectivity both within and between particular functional networks. This implies that individual differences in basic attention functions are represented by differences in the coherence of slowly fluctuating brain activity.
Feierstein, C E; Portugues, R; Orger, M B
2015-06-18
In recent years, the zebrafish has emerged as an appealing model system to tackle questions relating to the neural circuit basis of behavior. This can be attributed not just to the growing use of genetically tractable model organisms, but also in large part to the rapid advances in optical techniques for neuroscience, which are ideally suited for application to the small, transparent brain of the larval fish. Many characteristic features of vertebrate brains, from gross anatomy down to particular circuit motifs and cell-types, as well as conserved behaviors, can be found in zebrafish even just a few days post fertilization, and, at this early stage, the physical size of the brain makes it possible to analyze neural activity in a comprehensive fashion. In a recent study, we used a systematic and unbiased imaging method to record the pattern of activity dynamics throughout the whole brain of larval zebrafish during a simple visual behavior, the optokinetic response (OKR). This approach revealed the broadly distributed network of neurons that were active during the behavior and provided insights into the fine-scale functional architecture in the brain, inter-individual variability, and the spatial distribution of behaviorally relevant signals. Combined with mapping anatomical and functional connectivity, targeted electrophysiological recordings, and genetic labeling of specific populations, this comprehensive approach in zebrafish provides an unparalleled opportunity to study complete circuits in a behaving vertebrate animal. Copyright © 2014. Published by Elsevier Ltd.
Finding the imposter: brain connectivity of lesions causing delusional misidentifications
Darby, R Ryan; Laganiere, Simon; Pascual-Leone, Alvaro; Prasad, Sashank; Fox, Michael D
2017-01-01
Abstract See McKay and Furl (doi:10.1093/aww323) for a scientific commentary on this article. Focal brain injury can sometimes lead to bizarre symptoms, such as the delusion that a family member has been replaced by an imposter (Capgras syndrome). How a single brain lesion could cause such a complex disorder is unclear, leading many to speculate that concurrent delirium, psychiatric disease, dementia, or a second lesion is required. Here we instead propose that Capgras and other delusional misidentification syndromes arise from single lesions at unique locations within the human brain connectome. This hypothesis is motivated by evidence that symptoms emerge from sites functionally connected to a lesion location, not just the lesion location itself. First, 17 cases of lesion-induced delusional misidentifications were identified and lesion locations were mapped to a common brain atlas. Second, lesion network mapping was used to identify brain regions functionally connected to the lesion locations. Third, regions involved in familiarity perception and belief evaluation, two processes thought to be abnormal in delusional misidentifications, were identified using meta-analyses of previous functional magnetic resonance imaging studies. We found that all 17 lesion locations were functionally connected to the left retrosplenial cortex, the region most activated in functional magnetic resonance imaging studies of familiarity. Similarly, 16 of 17 lesion locations were functionally connected to the right frontal cortex, the region most activated in functional magnetic resonance imaging studies of expectation violation, a component of belief evaluation. This connectivity pattern was highly specific for delusional misidentifications compared to four other lesion-induced neurological syndromes (P < 0.0001). Finally, 15 lesions causing other types of delusions were connected to expectation violation (P < 0.0001) but not familiarity regions, demonstrating specificity for delusion content. Our results provide potential neuroanatomical correlates for impaired familiarity perception and belief evaluation in patients with delusional misidentifications. More generally, we demonstrate a mechanism by which a single lesion can cause a complex neuropsychiatric syndrome based on that lesion’s unique pattern of functional connectivity, without the need for pre-existing or hidden pathology. PMID:28082298
Electro-acupuncture at different acupoints modulating the relative specific brain functional network
NASA Astrophysics Data System (ADS)
Fang, Jiliang; Wang, Xiaoling; Wang, Yin; Liu, Hesheng; Hong, Yang; Liu, Jun; Zhou, Kehua; Wang, Lei; Xue, Chao; Song, Ming; Liu, Baoyan; Zhu, Bing
2010-11-01
Objective: The specific brain effects of acupoint are important scientific concern in acupuncture. However, previous acupuncture fMRI studies focused on acupoints in muscle layer on the limb. Therefore, researches on acupoints within connective tissue at trunk are warranted. Material and Methods: Brain effects of acupuncture on abdomen at acupoints Guanyuan (CV4) and Zhongwan (CV12) were tested using fMRI on 21 healthy volunteers. The data acquisition was performed at resting state, during needle retention, electroacupuncture (EA) and post-EA resting state. Needling sensations were rated after every electroacupuncture (EA) procedure. The needling sensations and the brain functional activity and connectivity were compared between CV4 and CV12 using SPSS, SPM2 and the local and remote connectivity maps. Results and conclusion: EA at CV4 and CV12 induced apparent deactivation effects in the limbic-paralimbic-neocortical network. The default mode of the brain was modified by needle retention and EA, respectively. The functional brain network was significantly changed post EA. However, the minor differences existed between these two acupoints. The results demonstrated similarity between functional brain network mode of acupuncture modulation and functional circuits of emotional and cognitive regulation. Acupuncture may produce analgesia, anti-anxiety and anti-depression via the limbic-paralimbic-neocortical network (LPNN).
Laser technique for anatomical-functional study of the medial prefrontal cortex of the brain
NASA Astrophysics Data System (ADS)
Sanchez-Huerta, Laura; Hernandez, Adan; Ayala, Griselda; Marroquin, Javier; Silva, Adriana B.; Khotiaintsev, Konstantin S.; Svirid, Vladimir A.; Flores, Gonzalo; Khotiaintsev, Sergei N.
1999-05-01
The brain represents one of the most complex systems that we know yet. In its study, non-destructive methods -- in particular, behavioral studies play an important role. By alteration of brain functioning (e.g. by pharmacological means) and observation of consequent behavior changes an important information on brain organization and functioning is obtained. For inducing local alterations, permanent brain lesions are employed. However, for correct results this technique has to be quasi-non-destructive, i.e. not to affect the normal brain function. Hence, the lesions should be very small, accurate and applied precisely over the structure (e.g. the brain nucleus) of interest. These specifications are difficult to meet with the existing techniques for brain lesions -- specifically, neurotoxical, mechanical and electrical means because they result in too extensive damage. In this paper, we present new laser technique for quasi-non- destructive anatomical-functional mapping in vivo of the medial prefrontal cortex (MPFC) of the rat. The technique is based on producing of small-size, well-controlled laser- induced lesions over some areas of the MPFC. The anesthetized animals are subjected to stereotactic surgery and certain points of the MPFC are exposed the confined radiation of the 10 W cw CO2 laser. Subsequent behavioral changes observed in neonatal and adult animals as well as histological data prove effectiveness of this technology for anatomical- functional studies of the brain by areas, and as a treatment method for some pathologies.
Hyper-resting brain entropy within chronic smokers and its moderation by Sex
Li, Zhengjun; Fang, Zhuo; Hager, Nathan; Rao, Hengyi; Wang, Ze
2016-01-01
Cigarette smoking is a chronic relapsing brain disorder, and remains a premier cause of morbidity and mortality. Functional neuroimaging has been used to assess differences in the mean strength of brain activity in smokers’ brains, however less is known about the temporal dynamics within smokers’ brains. Temporal dynamics is a key feature of a dynamic system such as the brain, and may carry information critical to understanding the brain mechanisms underlying cigarette smoking. We measured the temporal dynamics of brain activity using brain entropy (BEN) mapping and compared BEN between chronic non-deprived smokers and non-smoking controls. Because of the known sex differences in neural and behavioral smoking characteristics, comparisons were also made between males and females. Associations between BEN and smoking related clinical measures were assessed in smokers. Our data showed globally higher BEN in chronic smokers compared to controls. The escalated BEN was associated with more years of smoking in the right limbic area and frontal region. Female nonsmokers showed higher BEN than male nonsmokers in prefrontal cortex, insula, and precuneus, but the BEN sex difference in smokers was less pronounced. These findings suggest that BEN mapping may provide a useful tool for probing brain mechanisms related to smoking. PMID:27377552
Mapping brain development during childhood, adolescence and young adulthood
NASA Astrophysics Data System (ADS)
Guo, Xiaojuan; Jin, Zhen; Chen, Kewei; Peng, Danling; Li, Yao
2009-02-01
Using optimized voxel-based morphometry (VBM), this study systematically investigated the differences and similarities of brain structural changes during the early three developmental periods of human lives: childhood, adolescence and young adulthood. These brain changes were discussed in relationship to the corresponding cognitive function development during these three periods. Magnetic Resonance Imaging (MRI) data from 158 Chinese healthy children, adolescents and young adults, aged 7.26 to 22.80 years old, were included in this study. Using the customized brain template together with the gray matter/white matter/cerebrospinal fluid prior probability maps, we found that there were more age-related positive changes in the frontal lobe, less in hippocampus and amygdala during childhood, but more in bilateral hippocampus and amygdala and left fusiform gyrus during adolescence and young adulthood. There were more age-related negative changes near to central sulcus during childhood, but these changes extended to the frontal and parietal lobes, mainly in the parietal lobe, during adolescence and young adulthood, and more in the prefrontal lobe during young adulthood. So gray matter volume in the parietal lobe significantly decreased from childhood and continued to decrease till young adulthood. These findings may aid in understanding the age-related differences in cognitive function.
Electrophysiological correlates of the BOLD signal for EEG-informed fMRI
Murta, Teresa; Leite, Marco; Carmichael, David W; Figueiredo, Patrícia; Lemieux, Louis
2015-01-01
Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are important tools in cognitive and clinical neuroscience. Combined EEG–fMRI has been shown to help to characterise brain networks involved in epileptic activity, as well as in different sensory, motor and cognitive functions. A good understanding of the electrophysiological correlates of the blood oxygen level-dependent (BOLD) signal is necessary to interpret fMRI maps, particularly when obtained in combination with EEG. We review the current understanding of electrophysiological–haemodynamic correlates, during different types of brain activity. We start by describing the basic mechanisms underlying EEG and BOLD signals and proceed by reviewing EEG-informed fMRI studies using fMRI to map specific EEG phenomena over the entire brain (EEG–fMRI mapping), or exploring a range of EEG-derived quantities to determine which best explain colocalised BOLD fluctuations (local EEG–fMRI coupling). While reviewing studies of different forms of brain activity (epileptic and nonepileptic spontaneous activity; cognitive, sensory and motor functions), a significant attention is given to epilepsy because the investigation of its haemodynamic correlates is the most common application of EEG-informed fMRI. Our review is focused on EEG-informed fMRI, an asymmetric approach of data integration. We give special attention to the invasiveness of electrophysiological measurements and the simultaneity of multimodal acquisitions because these methodological aspects determine the nature of the conclusions that can be drawn from EEG-informed fMRI studies. We emphasise the advantages of, and need for, simultaneous intracranial EEG–fMRI studies in humans, which recently became available and hold great potential to improve our understanding of the electrophysiological correlates of BOLD fluctuations. PMID:25277370
Martí-Bonmatí, Luis; Lull, Juan José; García-Martí, Gracián; Aguilar, Eduardo J; Moratal-Pérez, David; Poyatos, Cecilio; Robles, Montserrat; Sanjuán, Julio
2007-08-01
To prospectively evaluate if functional magnetic resonance (MR) imaging abnormalities associated with auditory emotional stimuli coexist with focal brain reductions in schizophrenic patients with chronic auditory hallucinations. Institutional review board approval was obtained and all participants gave written informed consent. Twenty-one right-handed male patients with schizophrenia and persistent hallucinations (started to hear hallucinations at a mean age of 23 years +/- 10, with 15 years +/- 8 of mean illness duration) and 10 healthy paired participants (same ethnic group [white], age, and education level [secondary school]) were studied. Functional echo-planar T2*-weighted (after both emotional and neutral auditory stimulation) and morphometric three-dimensional gradient-recalled echo T1-weighted MR images were analyzed using Statistical Parametric Mapping (SPM2) software. Brain activation images were extracted by subtracting those with emotional from nonemotional words. Anatomic differences were explored by optimized voxel-based morphometry. The functional and morphometric MR images were overlaid to depict voxels statistically reported by both techniques. A coincidence map was generated by multiplying the emotional subtracted functional MR and volume decrement morphometric maps. Statistical analysis used the general linear model, Student t tests, random effects analyses, and analysis of covariance with a correction for multiple comparisons following the false discovery rate method. Large coinciding brain clusters (P < .005) were found in the left and right middle temporal and superior temporal gyri. Smaller coinciding clusters were found in the left posterior and right anterior cingular gyri, left inferior frontal gyrus, and middle occipital gyrus. The middle and superior temporal and the cingular gyri are closely related to the abnormal neural network involved in the auditory emotional dysfunction seen in schizophrenic patients.
Spatio-Temporal Brain Mapping of Motion-Onset VEPs Combined with fMRI and Retinotopic Maps
Pitzalis, Sabrina; Strappini, Francesca; De Gasperis, Marco; Bultrini, Alessandro; Di Russo, Francesco
2012-01-01
Neuroimaging studies have identified several motion-sensitive visual areas in the human brain, but the time course of their activation cannot be measured with these techniques. In the present study, we combined electrophysiological and neuroimaging methods (including retinotopic brain mapping) to determine the spatio-temporal profile of motion-onset visual evoked potentials for slow and fast motion stimuli and to localize its neural generators. We found that cortical activity initiates in the primary visual area (V1) for slow stimuli, peaking 100 ms after the onset of motion. Subsequently, activity in the mid-temporal motion-sensitive areas, MT+, peaked at 120 ms, followed by peaks in activity in the more dorsal area, V3A, at 160 ms and the lateral occipital complex at 180 ms. Approximately 250 ms after stimulus onset, activity fast motion stimuli was predominant in area V6 along the parieto-occipital sulcus. Finally, at 350 ms (100 ms after the motion offset) brain activity was visible again in area V1. For fast motion stimuli, the spatio-temporal brain pattern was similar, except that the first activity was detected at 70 ms in area MT+. Comparing functional magnetic resonance data for slow vs. fast motion, we found signs of slow-fast motion stimulus topography along the posterior brain in at least three cortical regions (MT+, V3A and LOR). PMID:22558222
3D Data Mapping and Real-Time Experiment Control and Visualization in Brain Slices.
Navarro, Marco A; Hibbard, Jaime V K; Miller, Michael E; Nivin, Tyler W; Milescu, Lorin S
2015-10-20
Here, we propose two basic concepts that can streamline electrophysiology and imaging experiments in brain slices and enhance data collection and analysis. The first idea is to interface the experiment with a software environment that provides a 3D scene viewer in which the experimental rig, the brain slice, and the recorded data are represented to scale. Within the 3D scene viewer, the user can visualize a live image of the sample and 3D renderings of the recording electrodes with real-time position feedback. Furthermore, the user can control the instruments and visualize their status in real time. The second idea is to integrate multiple types of experimental data into a spatial and temporal map of the brain slice. These data may include low-magnification maps of the entire brain slice, for spatial context, or any other type of high-resolution structural and functional image, together with time-resolved electrical and optical signals. The entire data collection can be visualized within the 3D scene viewer. These concepts can be applied to any other type of experiment in which high-resolution data are recorded within a larger sample at different spatial and temporal coordinates. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Linking late cognitive outcome with glioma surgery location using resection cavity maps.
Hendriks, Eef J; Habets, Esther J J; Taphoorn, Martin J B; Douw, Linda; Zwinderman, Aeilko H; Vandertop, W Peter; Barkhof, Frederik; Klein, Martin; De Witt Hamer, Philip C
2018-05-01
Patients with a diffuse glioma may experience cognitive decline or improvement upon resective surgery. To examine the impact of glioma location, cognitive alteration after glioma surgery was quantified and related to voxel-based resection probability maps. A total of 59 consecutive patients (range 18-67 years of age) who had resective surgery between 2006 and 2011 for a supratentorial nonenhancing diffuse glioma (grade I-III, WHO 2007) were included in this observational cohort study. Standardized neuropsychological examination and MRI were obtained before and after surgery. Intraoperative stimulation mapping guided resections towards neurological functions (language, sensorimotor function, and visual fields). Maps of resected regions were constructed in standard space. These resection cavity maps were compared between patients with and without new cognitive deficits (z-score difference >1.5 SD between baseline and one year after resection), using a voxel-wise randomization test and calculation of false discovery rates. Brain regions significantly associated with cognitive decline were classified in standard cortical and subcortical anatomy. Cognitive improvement in any domain occurred in 10 (17%) patients, cognitive decline in any domain in 25 (42%), and decline in more than one domain in 10 (17%). The most frequently affected subdomains were attention in 10 (17%) patients and information processing speed in 9 (15%). Resection regions associated with decline in more than one domain were predominantly located in the right hemisphere. For attention decline, no specific region could be identified. For decline in information speed, several regions were found, including the frontal pole and the corpus callosum. Cognitive decline after resective surgery of diffuse glioma is prevalent, in particular, in patients with a tumor located in the right hemisphere without cognitive function mapping. © The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
Kim, Boeun; Yi, Kangjae; Jung, Sunyoung; Ji, Seoyeon; Choi, Mincheol; Yoon, Junghee
2014-01-01
Diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) mapping are functional magnetic resonance imaging techniques for detecting water diffusion. DWI and the ADC map were performed for intracranial lesions in two dogs. In necrotizing leukoencephalitis, cavitated lesions contained a hypointense center with a hyperintense periphery on DWI, and hyperintense signals on the ADC maps. In metastatic sarcoma, masses including a necrotic region were hypointense with DWI, and hyperintense on the ADC map with hyperintense perilesional edema on DWI and ADC map. Since DWI and ADC data reflect the altered water diffusion, they can provide additional information at the molecular level.
Reaction time variability and related brain activity in methamphetamine psychosis.
Fassbender, Catherine; Lesh, Tyler A; Ursu, Stefan; Salo, Ruth
2015-03-01
This study investigated the dynamics of cognitive control instability in methamphetamine (MA) abuse, as well its relationship to substance-induced psychiatric symptoms and drug use patterns. We used an ex-Gaussian reaction time (RT) distribution to examine intraindividual variability (IIV) and excessively long RTs (tau) in an individual's RT on a Stroop task in 30 currently drug-abstinent (3 months to 2 years) MA abusers compared with 27 nonsubstance-abusing control subjects. All subjects underwent functional magnetic resonance imaging while performing the Stroop task, which allowed us to measure the relationship between IIV and tau to functional brain activity. Elevated IIV in the MA compared with the control group did not reach significance; however, when the MA group was divided into those subjects who had experienced MA-induced psychosis (MAP+) (n = 19) and those who had not (n = 11), the MAP+ group had higher average IIV compared with the other groups (p < .03). In addition, although control subjects displayed a relationship between IIV and conflict-related brain activity in bilateral prefrontal cortex such that increased IIV was associated with increased activity, the MAP+ group displayed this relationship in right prefrontal cortex only, perhaps reflecting elevated vigilance in the MAP+ group. Greater IIV did not correlate with severity of use or months MA abstinent. No group differences emerged in tau values. These results suggest increased cognitive instability in those MA-dependent subjects who had experienced MA-induced psychosis. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
Initial constructs for patient-centered outcome measures to evaluate brain-computer interfaces.
Andresen, Elena M; Fried-Oken, Melanie; Peters, Betts; Patrick, Donald L
2016-10-01
The authors describe preliminary work toward the creation of patient-centered outcome (PCO) measures to evaluate brain-computer interface (BCI) as an assistive technology (AT) for individuals with severe speech and physical impairments (SSPI). In Phase 1, 591 items from 15 existing measures were mapped to the International Classification of Functioning, Disability and Health (ICF). In Phase 2, qualitative interviews were conducted with eight people with SSPI and seven caregivers. Resulting text data were coded in an iterative analysis. Most items (79%) were mapped to the ICF environmental domain; over half (53%) were mapped to more than one domain. The ICF framework was well suited for mapping items related to body functions and structures, but less so for items in other areas, including personal factors. Two constructs emerged from qualitative data: quality of life (QOL) and AT. Component domains and themes were identified for each. Preliminary constructs, domains and themes were generated for future PCO measures relevant to BCI. Existing instruments are sufficient for initial items but do not adequately match the values of people with SSPI and their caregivers. Field methods for interviewing people with SSPI were successful, and support the inclusion of these individuals in PCO research. Implications for Rehabilitation Adapted interview methods allow people with severe speech and physical impairments to participate in patient-centered outcomes research. Patient-centered outcome measures are needed to evaluate the clinical implementation of brain-computer interface as an assistive technology.
Hogstrom, L. J.; Guo, S. M.; Murugadoss, K.; Bathe, M.
2016-01-01
Brain function emerges from hierarchical neuronal structure that spans orders of magnitude in length scale, from the nanometre-scale organization of synaptic proteins to the macroscopic wiring of neuronal circuits. Because the synaptic electrochemical signal transmission that drives brain function ultimately relies on the organization of neuronal circuits, understanding brain function requires an understanding of the principles that determine hierarchical neuronal structure in living or intact organisms. Recent advances in fluorescence imaging now enable quantitative characterization of neuronal structure across length scales, ranging from single-molecule localization using super-resolution imaging to whole-brain imaging using light-sheet microscopy on cleared samples. These tools, together with correlative electron microscopy and magnetic resonance imaging at the nanoscopic and macroscopic scales, respectively, now facilitate our ability to probe brain structure across its full range of length scales with cellular and molecular specificity. As these imaging datasets become increasingly accessible to researchers, novel statistical and computational frameworks will play an increasing role in efforts to relate hierarchical brain structure to its function. In this perspective, we discuss several prominent experimental advances that are ushering in a new era of quantitative fluorescence-based imaging in neuroscience along with novel computational and statistical strategies that are helping to distil our understanding of complex brain structure. PMID:26855758
Mapping the human brain during a specific Vojta's tactile input: the ipsilateral putamen's role
Sanz-Esteban, Ismael; Calvo-Lobo, Cesar; Ríos-Lago, Marcos; Álvarez-Linera, Juan; Muñoz-García, Daniel; Rodríguez-Sanz, David
2018-01-01
Abstract A century of research in human brain parcellation has demonstrated that different brain areas are associated with functional tasks. New neuroscientist perspectives to achieve the parcellation of the human brain have been developed to know the brain areas activation and its relationship with different stimuli. This descriptive study aimed to compare brain regions activation by specific tactile input (STI) stimuli according to the Vojta protocol (STI-group) to a non-STI stimulation (non-STI-group). An exploratory functional magnetic resonance imaging (fMRI) study was performed. The 2 groups of participants were passively stimulated by an expert physical therapist using the same paradigm structure, although differing in the place of stimulation. The stimulation was presented to participants using a block design in all cases. A sample of 16 healthy participants, 5 men and 11 women, with mean age 31.31 ± 8.13 years was recruited. Indeed, 12 participants were allocated in the STI-group and 4 participants in the non-STI-group. fMRI was used to map the human brain in vivo while these tactile stimuli were being applied. Data were analyzed using a general linear model in SPM12 implemented in MATLAB. Differences between groups showed a greater activation in the right cortical areas (temporal and frontal lobes), subcortical regions (thalamus, brainstem, and basal nuclei), and in the cerebellum (anterior lobe). STI-group had specific difference brain activation areas, such as the ipsilateral putamen. Future studies should study clinical implications in neurorehabilitation patients. PMID:29595683
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.
Initial constructs for patient-centered outcome measures to evaluate brain-computer interfaces
Andresen, Elena M.; Fried-Oken, Melanie; Peters, Betts; Patrick, Donald L.
2016-01-01
Purpose The authors describe preliminary work toward the creation of patient-centered outcome (PCO) measures to evaluate brain-computer interface (BCI) as an assistive technology for individuals with severe speech and physical impairments (SSPI). Method In Phase 1, 591 items from 15 existing measures were mapped to the International Classification of Functioning, Disability and Health (ICF). In Phase 2, qualitative interviews were conducted with eight people with SSPI and seven caregivers. Resulting text data were coded in an iterative analysis. Results Most items (79%) mapped to the ICF environmental domain; over half (53%) mapped to more than one domain. The ICF framework was well suited for mapping items related to body functions and structures, but less so for items in other areas, including personal factors. Two constructs emerged from qualitative data: Quality of Life (QOL) and Assistive Technology. Component domains and themes were identified for each. Conclusions Preliminary constructs, domains, and themes were generated for future PCO measures relevant to BCI. Existing instruments are sufficient for initial items but do not adequately match the values of people with SSPI and their caregivers. Field methods for interviewing people with SSPI were successful, and support the inclusion of these individuals in PCO research. PMID:25806719
Park, Sung-Hong; Wang, Danny J J; Duong, Timothy Q
2013-09-01
We implemented pseudo-continuous ASL (pCASL) with 2D and 3D balanced steady state free precession (bSSFP) readout for mapping blood flow in the human brain, retina, and kidney, free of distortion and signal dropout, which are typically observed in the most commonly used echo-planar imaging acquisition. High resolution functional brain imaging in the human visual cortex was feasible with 3D bSSFP pCASL. Blood flow of the human retina could be imaged with pCASL and bSSFP in conjunction with a phase cycling approach to suppress the banding artifacts associated with bSSFP. Furthermore, bSSFP based pCASL enabled us to map renal blood flow within a single breath hold. Control and test-retest experiments suggested that the measured blood flow values in retina and kidney were reliable. Because there is no specific imaging tool for mapping human retina blood flow and the standard contrast agent technique for mapping renal blood flow can cause problems for patients with kidney dysfunction, bSSFP based pCASL may provide a useful tool for the diagnosis of retinal and renal diseases and can complement existing imaging techniques. Copyright © 2013 Elsevier Inc. All rights reserved.
Adaptation, perceptual learning, and plasticity of brain functions.
Horton, Jonathan C; Fahle, Manfred; Mulder, Theo; Trauzettel-Klosinski, Susanne
2017-03-01
The capacity for functional restitution after brain damage is quite different in the sensory and motor systems. This series of presentations highlights the potential for adaptation, plasticity, and perceptual learning from an interdisciplinary perspective. The chances for restitution in the primary visual cortex are limited. Some patterns of visual field loss and recovery after stroke are common, whereas others are impossible, which can be explained by the arrangement and plasticity of the cortical map. On the other hand, compensatory mechanisms are effective, can occur spontaneously, and can be enhanced by training. In contrast to the human visual system, the motor system is highly flexible. This is based on special relationships between perception and action and between cognition and action. In addition, the healthy adult brain can learn new functions, e.g. increasing resolution above the retinal one. The significance of these studies for rehabilitation after brain damage will be discussed.
Whole-brain activity maps reveal stereotyped, distributed networks for visuomotor behavior.
Portugues, Ruben; Feierstein, Claudia E; Engert, Florian; Orger, Michael B
2014-03-19
Most behaviors, even simple innate reflexes, are mediated by circuits of neurons spanning areas throughout the brain. However, in most cases, the distribution and dynamics of firing patterns of these neurons during behavior are not known. We imaged activity, with cellular resolution, throughout the whole brains of zebrafish performing the optokinetic response. We found a sparse, broadly distributed network that has an elaborate but ordered pattern, with a bilaterally symmetrical organization. Activity patterns fell into distinct clusters reflecting sensory and motor processing. By correlating neuronal responses with an array of sensory and motor variables, we find that the network can be clearly divided into distinct functional modules. Comparing aligned data from multiple fish, we find that the spatiotemporal activity dynamics and functional organization are highly stereotyped across individuals. These experiments systematically reveal the functional architecture of neural circuits underlying a sensorimotor behavior in a vertebrate brain. Copyright © 2014 Elsevier Inc. All rights reserved.
A dedicated network for social interaction processing in the primate brain.
Sliwa, J; Freiwald, W A
2017-05-19
Primate cognition requires interaction processing. Interactions can reveal otherwise hidden properties of intentional agents, such as thoughts and feelings, and of inanimate objects, such as mass and material. Where and how interaction analyses are implemented in the brain is unknown. Using whole-brain functional magnetic resonance imaging in macaque monkeys, we discovered a network centered in the medial and ventrolateral prefrontal cortex that is exclusively engaged in social interaction analysis. Exclusivity of specialization was found for no other function anywhere in the brain. Two additional networks, a parieto-premotor and a temporal one, exhibited both social and physical interaction preference, which, in the temporal lobe, mapped onto a fine-grain pattern of object, body, and face selectivity. Extent and location of a dedicated system for social interaction analysis suggest that this function is an evolutionary forerunner of human mind-reading capabilities. Copyright © 2017, American Association for the Advancement of Science.
Network localization of neurological symptoms from focal brain lesions
Prasad, Sashank; Liu, Hesheng; Liu, Qi; Pascual-Leone, Alvaro; Caviness, Verne S.; Fox, Michael D.
2015-01-01
A traditional and widely used approach for linking neurological symptoms to specific brain regions involves identifying overlap in lesion location across patients with similar symptoms, termed lesion mapping. This approach is powerful and broadly applicable, but has limitations when symptoms do not localize to a single region or stem from dysfunction in regions connected to the lesion site rather than the site itself. A newer approach sensitive to such network effects involves functional neuroimaging of patients, but this requires specialized brain scans beyond routine clinical data, making it less versatile and difficult to apply when symptoms are rare or transient. In this article we show that the traditional approach to lesion mapping can be expanded to incorporate network effects into symptom localization without the need for specialized neuroimaging of patients. Our approach involves three steps: (i) transferring the three-dimensional volume of a brain lesion onto a reference brain; (ii) assessing the intrinsic functional connectivity of the lesion volume with the rest of the brain using normative connectome data; and (iii) overlapping lesion-associated networks to identify regions common to a clinical syndrome. We first tested our approach in peduncular hallucinosis, a syndrome of visual hallucinations following subcortical lesions long hypothesized to be due to network effects on extrastriate visual cortex. While the lesions themselves were heterogeneously distributed with little overlap in lesion location, 22 of 23 lesions were negatively correlated with extrastriate visual cortex. This network overlap was specific compared to other subcortical lesions (P < 10−5) and relative to other cortical regions (P < 0.01). Next, we tested for generalizability of our technique by applying it to three additional lesion syndromes: central post-stroke pain, auditory hallucinosis, and subcortical aphasia. In each syndrome, heterogeneous lesions that themselves had little overlap showed significant network overlap in cortical areas previously implicated in symptom expression (P < 10−4). These results suggest that (i) heterogeneous lesions producing similar symptoms share functional connectivity to specific brain regions involved in symptom expression; and (ii) publically available human connectome data can be used to incorporate these network effects into traditional lesion mapping approaches. Because the current technique requires no specialized imaging of patients it may prove a versatile and broadly applicable approach for localizing neurological symptoms in the setting of brain lesions. PMID:26264514
Trevisi, Gianluca; Roujeau, Thomas; Duffau, Hugues
2016-10-01
Brain mapping through a direct cortical and subcortical electrical stimulation during an awake craniotomy has gained an increasing popularity as a powerful tool to prevent neurological deficit while increasing extent of resection of hemispheric diffuse low-grade gliomas in adults. However, few case reports or very limited series of awake surgery in children are currently available in the literature. In this paper, we review the oncological and functional differences between pediatric and adult populations, and the methodological specificities that may limit the use of awake mapping in pediatric low-grade glioma surgery. This could be explained by the fact that pediatric low-grade gliomas have a different epidemiology and biologic behavior in comparison to adults, with pilocytic astrocytomas (WHO grade I glioma) as the most frequent histotype, and with WHO grade II gliomas less prone to anaplastic transformation than their adult counterparts. In addition, aside from the issue of poor collaboration of younger children under 10 years of age, some anatomical and functional peculiarities of children developing brain (cortical and subcortical myelination, maturation of neural networks and of specialized cortical areas) can influence direct electrical stimulation methodology and sensitivity, limiting its use in children. Therefore, even though awake procedure with cortical and axonal stimulation mapping can be adapted in a specific subgroup of children with a diffuse glioma from the age of 10 years, only few pediatric patients are nonetheless candidates for awake brain surgery.
Cortical Bases of Speech Perception: Evidence from Functional Lesion Studies
ERIC Educational Resources Information Center
Boatman, Dana
2004-01-01
Functional lesion studies have yielded new information about the cortical organization of speech perception in the human brain. We will review a number of recent findings, focusing on studies of speech perception that use the techniques of electrocortical mapping by cortical stimulation and hemispheric anesthetization by intracarotid amobarbital.…
Richards, Todd; Webb, Sara Jane; Murias, Michael; Merkle, Kristen; Kleinhans, Natalia M.; Johnson, L. Clark; Poliakov, Andrew; Aylward, Elizabeth; Dawson, Geraldine
2013-01-01
Brain activity patterns during face processing have been extensively explored with functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs). ERP source localization adds a spatial dimension to the ERP time series recordings, which allows for a more direct comparison and integration with fMRI findings. The goals for this study were (1) to compare the spatial descriptions of neuronal activity during face processing obtained with fMRI and ERP source localization using low-resolution electro-magnetic tomography (LORETA), and (2) to use the combined information from source localization and fMRI to explore how the temporal sequence of brain activity during face processing is summarized in fMRI activation maps. fMRI and high-density ERP data were acquired in separate sessions for 17 healthy adult males for a face and object processing task. LORETA statistical maps for the comparison of viewing faces and viewing houses were coregistered and compared to fMRI statistical maps for the same conditions. The spatial locations of face processing-sensitive activity measured by fMRI and LORETA were found to overlap in a number of areas including the bilateral fusiform gyri, the right superior, middle and inferior temporal gyri, and the bilateral precuneus. Both the fMRI and LORETA solutions additionally demon-strated activity in regions that did not overlap. fMRI and LORETA statistical maps of face processing-sensitive brain activity were found to converge spatially primarily at LORETA solution latencies that were within 18 ms of the N170 latency. The combination of data from these techniques suggested that electrical brain activity at the latency of the N170 is highly represented in fMRI statistical maps. PMID:19322649
Structural connectivity asymmetry in the neonatal brain.
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.
Mapping and reconstruction of domoic acid-induced neurodegeneration in the mouse brain.
Colman, J R; Nowocin, K J; Switzer, R C; Trusk, T C; Ramsdell, J S
2005-01-01
Domoic acid, a potent neurotoxin and glutamate analog produced by certain species of the marine diatom Pseudonitzschia, is responsible for several human and wildlife intoxication events. The toxin characteristically damages the hippocampus in exposed humans, rodents, and marine mammals. Histochemical studies have identified this, and other regions of neurodegeneration, though none have sought to map all brain regions affected by domoic acid. In this study, mice exposed (i.p.) to 4 mg/kg domoic acid for 72 h exhibited behavioral and pathological signs of neurotoxicity. Brains were fixed by intracardial perfusion and processed for histochemical analysis. Serial coronal sections (50 microm) were stained using the degeneration-sensitive cupric silver staining method of DeOlmos. Degenerated axons, terminals, and cell bodies, which stained black, were identified and the areas of degeneration were mapped onto Paxinos mouse atlas brain plates using Adobe Illustrator CS. The plates were then combined to reconstruct a 3-dimensional image of domoic acid-induced neurodegeneration using Amira 3.1 software. Affected regions included the olfactory bulb, septal area, and limbic system. These findings are consistent with behavioral and pathological studies demonstrating the effects of domoic acid on cognitive function and neurodegeneration in rodents.
Ouyang, Austin; Jeon, Tina; Sunkin, Susan M.; Pletikos, Mihovil; Sedmak, Goran; Sestan, Nenad; Lein, Ed S.; Huang, Hao
2014-01-01
During human brain development from fetal stage to adulthood, the white matter (WM) tracts undergo dramatic changes. Diffusion tensor imaging (DTI), a widely used magnetic resonance imaging (MRI) modality, offers insight into the dynamic changes of WM fibers as these fibers can be noninvasively traced and three-dimensionally (3D) reconstructed with DTI tractography. The DTI and conventional T1 weighted MRI images also provide sufficient cortical anatomical details for mapping the cortical regions of interests (ROIs). In this paper, we described basic concepts and methods of DTI techniques that can be used to trace major WM tracts noninvasively from fetal brain of 14 postconceptional weeks (pcw) to adult brain. We applied these techniques to acquire DTI data and trace, reconstruct and visualize major WM tracts during development. After categorizing major WM fiber bundles into five unique functional tract groups, namely limbic, brain stem, projection, commissural and association tracts, we revealed formation and maturation of these 3D reconstructed WM tracts of the developing human brain. The structural and connectional imaging data offered by DTI provides the anatomical backbone of transcriptional atlas of the developing human brain. PMID:25448302
Colom, Roberto; Solomon, Jeffrey; Krueger, Frank; Forbes, Chad; Grafman, Jordan
2012-01-01
Although cognitive neuroscience has made remarkable progress in understanding the involvement of the prefrontal cortex in executive control, the broader functional networks that support high-level cognition and give rise to general intelligence remain to be well characterized. Here, we investigated the neural substrates of the general factor of intelligence (g) and executive function in 182 patients with focal brain damage using voxel-based lesion–symptom mapping. The Wechsler Adult Intelligence Scale and Delis–Kaplan Executive Function System were used to derive measures of g and executive function, respectively. Impaired performance on these measures was associated with damage to a distributed network of left lateralized brain areas, including regions of frontal and parietal cortex and white matter association tracts, which bind these areas into a coordinated system. The observed findings support an integrative framework for understanding the architecture of general intelligence and executive function, supporting their reliance upon a shared fronto-parietal network for the integration and control of cognitive representations and making specific recommendations for the application of the Wechsler Adult Intelligence Scale and Delis–Kaplan Executive Function System to the study of high-level cognition in health and disease. PMID:22396393
Park, Chang-Hyun; Choi, Yun Seo; Jung, A-Reum; Chung, Hwa-Kyoung; Kim, Hyeon Jin; Yoo, Jeong Hyun; Lee, Hyang Woon
2017-01-01
Brain functional integration can be disrupted in patients with temporal lobe epilepsy (TLE), but the clinical relevance of this disruption is not completely understood. The authors hypothesized that disrupted functional integration over brain regions remote from, as well as adjacent to, the seizure focus could be related to clinical severity in terms of seizure control and memory impairment. Using resting-state functional MRI data acquired from 48 TLE patients and 45 healthy controls, the authors mapped functional brain networks and assessed changes in a network parameter of brain functional integration, efficiency, to examine the distribution of disrupted functional integration within and between brain regions. The authors assessed whether the extent of altered efficiency was influenced by seizure control status and whether the degree of altered efficiency was associated with the severity of memory impairment. Alterations in the efficiency were observed primarily near the subcortical region ipsilateral to the seizure focus in TLE patients. The extent of regional involvement was greater in patients with poor seizure control: it reached the frontal, temporal, occipital, and insular cortices in TLE patients with poor seizure control, whereas it was limited to the limbic and parietal cortices in TLE patients with good seizure control. Furthermore, TLE patients with poor seizure control experienced more severe memory impairment, and this was associated with lower efficiency in the brain regions with altered efficiency. These findings indicate that the distribution of disrupted brain functional integration is clinically relevant, as it is associated with seizure control status and comorbid memory impairment.
Stimulation Mapping of Myelinated Tracts in Awake Patients
Duffau, Hugues
2016-01-01
For a long time, although the functional anatomy of human cortex has extensively been studied, subcortical white matter tracts have received little consideration. Recent advances in tractography have opened the door to a non-invasive investigation of the subcortical fibers in vivo. However, this method cannot study directly the function of the bundles. Interestingly, for the first time in the history of cognitive neurosciences, direct axonal electrostimulation (DES) mapping of the neural pathways offers the unique opportunity to investigate the function of the connectomal anatomy. Indeed, this technique is able to perform real-time anatomo-functional correlations in awake patients who undergo brain surgery, especially at the level of the subcortical fibers. Here, the aim is to review original data issued from DES of myelinated tracts in adults, with regard to the functional connectivity mediating the sensorimotor, visuo-spatial, language, cognitive and emotional functions, as well as the interactions between these different sub-networks, leading ultimately to explore consciousness. Therefore, axonal stimulation is a valuable tool in the field of connectomics, that is, the map of neural connections, in order to switch from the traditional localizationist view of brain processing to a networking model in which cerebral functions are underpinned by the dynamic interactions of large-scale distributed and parallel sub-circuits. Such connectomal account should integrate the anatomic constraint represented by the subcortical fascicles. Indeed, post-lesional neuroplasticity is possible only on the condition that the white matter fibers are preserved, to allow communication and temporal synchronization among delocalized inter-connected networks. PMID:29765851
Alimohamadi, Maysam; Shirani, Mohammad; Shariat Moharari, Reza; Pour-Rashidi, Ahmad; Ketabchi, Mehdi; Khajavi, Mohammadreza; Arami, Mohamadali; Amirjamshidi, Abbas
2016-08-01
Radical resection of dominant insular gliomas is difficult because of their close vicinity with internal capsule, basal ganglia, and speech centers. Brain mapping techniques can be used to maximize the extent of tumor removal and to minimize postoperative morbidities by precise localization of eloquent cortical and subcortical areas. Patients with newly diagnosed gliomas of dominant insula were enrolled. The exclusion criteria were severe cognitive disturbances, communication difficulty, age greater than 75 years, severe obesity, difficult airways for intubation and severe cardiopulmonary diseases. All were evaluated preoperatively with contrast-enhanced brain magnetic resonance imaging (MRI), functional brain MRI, and diffusion tensor tractography of language and motor systems. All underwent awake craniotomy with the same anesthesiology protocol. Intraoperative monitoring included continuous motor-evoked potential, electromyography, electrocorticography, direct electrical stimulation of cortex, and subcortical tracts. The patients were followed with serial neurologic examination and imaging. Ten patients were enrolled (4 men, 6 women) with a mean age of 43.6 years. Seven patients suffered from low-grade glioma, and 3 patients had high-grade glioma. The most common clinical presentation was seizure followed by speech disturbance, hemiparesis, and memory loss. Extent of tumor resection ranged from 73% to 100%. No mortality or new major postoperative neurologic deficit was encountered. Seizure control improved in three fourths of patients with medical refractory epilepsy. In one patient with speech disorder at presentation, the speech problem became worse after surgery. Brain mapping during awake craniotomy helps to maximize extent of tumor resection while preserving neurologic function in patients with dominant insular lobe glioma. Copyright © 2016. Published by Elsevier Inc.
Surface-Constrained Volumetric Brain Registration Using Harmonic Mappings
Joshi, Anand A.; Shattuck, David W.; Thompson, Paul M.; Leahy, Richard M.
2015-01-01
In order to compare anatomical and functional brain imaging data across subjects, the images must first be registered to a common coordinate system in which anatomical features are aligned. Intensity-based volume registration methods can align subcortical structures well, but the variability in sulcal folding patterns typically results in misalignment of the cortical surface. Conversely, surface-based registration using sulcal features can produce excellent cortical alignment but the mapping between brains is restricted to the cortical surface. Here we describe a method for volumetric registration that also produces an accurate one-to-one point correspondence between cortical surfaces. This is achieved by first parameterizing and aligning the cortical surfaces using sulcal landmarks. We then use a constrained harmonic mapping to extend this surface correspondence to the entire cortical volume. Finally, this mapping is refined using an intensity-based warp. We demonstrate the utility of the method by applying it to T1-weighted magnetic resonance images (MRI). We evaluate the performance of our proposed method relative to existing methods that use only intensity information; for this comparison we compute the inter-subject alignment of expert-labeled sub-cortical structures after registration. PMID:18092736
Yu, Lianchun; De Mazancourt, Marine; Hess, Agathe; Ashadi, Fakhrul R; Klein, Isabelle; Mal, Hervé; Courbage, Maurice; Mangin, Laurence
2016-08-01
Breathing involves a complex interplay between the brainstem automatic network and cortical voluntary command. How these brain regions communicate at rest or during inspiratory loading is unknown. This issue is crucial for several reasons: (i) increased respiratory loading is a major feature of several respiratory diseases, (ii) failure of the voluntary motor and cortical sensory processing drives is among the mechanisms that precede acute respiratory failure, (iii) several cerebral structures involved in responding to inspiratory loading participate in the perception of dyspnea, a distressing symptom in many disease. We studied functional connectivity and Granger causality of the respiratory network in controls and patients with chronic obstructive pulmonary disease (COPD), at rest and during inspiratory loading. Compared with those of controls, the motor cortex area of patients exhibited decreased connectivity with their contralateral counterparts and no connectivity with the brainstem. In the patients, the information flow was reversed at rest with the source of the network shifted from the medulla towards the motor cortex. During inspiratory loading, the system was overwhelmed and the motor cortex became the sink of the network. This major finding may help to understand why some patients with COPD are prone to acute respiratory failure. Network connectivity and causality were related to lung function and illness severity. We validated our connectivity and causality results with a mathematical model of neural network. Our findings suggest a new therapeutic strategy involving the modulation of brain activity to increase motor cortex functional connectivity and improve respiratory muscles performance in patients. Hum Brain Mapp 37:2736-2754, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
Probing the brain with molecular fMRI.
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.
Three-Dimensional Computer Graphics Brain-Mapping Project.
1987-03-15
NEUROQUANT . This package was directed towards quantitative microneuroanatomic data acquisition and analysis. Using this interface, image frames captured...populations of brains. This would have been aprohibitive task if done manually with a densitometer and film, due to user error and bias. NEUROQUANT functioned...of cells were of interest. NEUROQUANT is presently being implemented with a more fully automatic method of localizing the cell bodies directly
Decrease in fMRI brain activation during working memory performed after sleeping under 10 lux light.
Kang, Seung-Gul; Yoon, Ho-Kyoung; Cho, Chul-Hyun; Kwon, Soonwook; Kang, June; Park, Young-Min; Lee, Eunil; Kim, Leen; Lee, Heon-Jeong
2016-11-09
The aim of this study was to investigate the effect of exposure to dim light at night (dLAN) when sleeping on functional brain activation during a working-memory tasks. We conducted the brain functional magnetic resonance imaging (fMRI) analysis on 20 healthy male subjects. All participants slept in a polysomnography laboratory without light exposure on the first and second nights and under a dim-light condition of either 5 or 10 lux on the third night. The fMRI scanning was conducted during n-back tasks after second and third nights. Statistical parametric maps revealed less activation in the right inferior frontal gyrus (IFG) after exposure to 10-lux light. The brain activity in the right and left IFG areas decreased more during the 2-back task than during the 1- or 0-back task in the 10-lux group. The exposure to 5-lux light had no significant effect on brain activities. The exposure to dLAN might influence the brain function which is related to the cognition.
O’Connell, Caitlin; Ho, Leon C.; Murphy, Matthew C.; Conner, Ian P.; Wollstein, Gadi; Cham, Rakie; Chan, Kevin C.
2016-01-01
Human visual performance has been observed to exhibit superiority in localized regions of the visual field across many classes of stimuli. However, the underlying neural mechanisms remain unclear. This study aims to determine if the visual information processing in the human brain is dependent on the location of stimuli in the visual field and the corresponding neuroarchitecture using blood-oxygenation-level-dependent functional MRI (fMRI) and diffusion kurtosis MRI (DKI), respectively in 15 healthy individuals at 3 Tesla. In fMRI, visual stimulation to the lower hemifield showed stronger brain responses and larger brain activation volumes than the upper hemifield, indicative of the differential sensitivity of the human brain across the visual field. In DKI, the brain regions mapping to the lower visual field exhibited higher mean kurtosis but not fractional anisotropy or mean diffusivity when compared to the upper visual field. These results suggested the different distributions of microstructural organization across visual field brain representations. There was also a strong positive relationship between diffusion kurtosis and fMRI responses in the lower field brain representations. In summary, this study suggested the structural and functional brain involvements in the asymmetry of visual field responses in humans, and is important to the neurophysiological and psychological understanding of human visual information processing. PMID:27631541
Chery, Romain; L'Heureux, Barbara; Bendahmane, Mounir; Renaud, Rémi; Martin, Claire; Pain, Frédéric; Gurden, Hirac
2011-01-01
In the brain, sensory stimulation activates distributed populations of neurons among functional modules which participate to the coding of the stimulus. Functional optical imaging techniques are advantageous to visualize the activation of these modules in sensory cortices with high spatial resolution. In this context, endogenous optical signals that arise from molecular mechanisms linked to neuroenergetics are valuable sources of contrast to record spatial maps of sensory stimuli over wide fields in the rodent brain. Here, we present two techniques based on changes of endogenous optical properties of the brain tissue during activation. First the intrinsic optical signals (IOS) are produced by a local alteration in red light reflectance due to: (i) absorption by changes in blood oxygenation level and blood volume (ii) photon scattering. The use of in vivo IOS to record spatial maps started in the mid 1980's with the observation of optical maps of whisker barrels in the rat and the orientation columns in the cat visual cortex1. IOS imaging of the surface of the rodent main olfactory bulb (OB) in response to odorants was later demonstrated by Larry Katz's group2. The second approach relies on flavoprotein autofluorescence signals (FAS) due to changes in the redox state of these mitochondrial metabolic intermediates. More precisely, the technique is based on the green fluorescence due to oxidized state of flavoproteins when the tissue is excited with blue light. Although such signals were probably among the first fluorescent molecules recorded for the study of brain activity by the pioneer studies of Britton Chances and colleagues3, it was not until recently that they have been used for mapping of brain activation in vivo. FAS imaging was first applied to the somatosensory cortex in rodents in response to hindpaw stimulation by Katsuei Shibuki's group4. The olfactory system is of central importance for the survival of the vast majority of living species because it allows efficient detection and identification of chemical substances in the environment (food, predators). The OB is the first relay of olfactory information processing in the brain. It receives afferent projections from the olfactory primary sensory neurons that detect volatile odorant molecules. Each sensory neuron expresses only one type of odorant receptor and neurons carrying the same type of receptor send their nerve processes to the same well-defined microregions of ˜100μm3 constituted of discrete neuropil, the olfactory glomerulus (Fig. 1). In the last decade, IOS imaging has fostered the functional exploration of the OB5, 6, 7 which has become one of the most studied sensory structures. The mapping of OB activity with FAS imaging has not been performed yet. Here, we show the successive steps of an efficient protocol for IOS and FAS imaging to map odor-evoked activities in the mouse OB. PMID:22064685
Advanced lesion symptom mapping analyses and implementation as BCBtoolkit
Foulon, Chris; Cerliani, Leonardo; Kinkingnéhun, Serge; Levy, Richard; Rosso, Charlotte; Urbanski, Marika
2018-01-01
Abstract Background Patients with brain lesions provide a unique opportunity to understand the functioning of the human mind. However, even when focal, brain lesions have local and remote effects that impact functionally and structurally connected circuits. Similarly, function emerges from the interaction between brain areas rather than their sole activity. For instance, category fluency requires the associations between executive, semantic, and language production functions. Findings Here, we provide, for the first time, a set of complementary solutions for measuring the impact of a given lesion on the neuronal circuits. Our methods, which were applied to 37 patients with a focal frontal brain lesions, revealed a large set of directly and indirectly disconnected brain regions that had significantly impacted category fluency performance. The directly disconnected regions corresponded to areas that are classically considered as functionally engaged in verbal fluency and categorization tasks. These regions were also organized into larger directly and indirectly disconnected functional networks, including the left ventral fronto-parietal network, whose cortical thickness correlated with performance on category fluency. Conclusions The combination of structural and functional connectivity together with cortical thickness estimates reveal the remote effects of brain lesions, provide for the identification of the affected networks, and strengthen our understanding of their relationship with cognitive and behavioral measures. The methods presented are available and freely accessible in the BCBtoolkit as supplementary software [1]. PMID:29432527
Lin, Zi-Jing; Li, Lin; Cazzell, Mary; Liu, Hanli
2014-08-01
Diffuse optical tomography (DOT) is a variant of functional near infrared spectroscopy and has the capability of mapping or reconstructing three dimensional (3D) hemodynamic changes due to brain activity. Common methods used in DOT image analysis to define brain activation have limitations because the selection of activation period is relatively subjective. General linear model (GLM)-based analysis can overcome this limitation. In this study, we combine the atlas-guided 3D DOT image reconstruction with GLM-based analysis (i.e., voxel-wise GLM analysis) to investigate the brain activity that is associated with risk decision-making processes. Risk decision-making is an important cognitive process and thus is an essential topic in the field of neuroscience. The Balloon Analog Risk Task (BART) is a valid experimental model and has been commonly used to assess human risk-taking actions and tendencies while facing risks. We have used the BART paradigm with a blocked design to investigate brain activations in the prefrontal and frontal cortical areas during decision-making from 37 human participants (22 males and 15 females). Voxel-wise GLM analysis was performed after a human brain atlas template and a depth compensation algorithm were combined to form atlas-guided DOT images. In this work, we wish to demonstrate the excellence of using voxel-wise GLM analysis with DOT to image and study cognitive functions in response to risk decision-making. Results have shown significant hemodynamic changes in the dorsal lateral prefrontal cortex (DLPFC) during the active-choice mode and a different activation pattern between genders; these findings correlate well with published literature in functional magnetic resonance imaging (fMRI) and fNIRS studies. Copyright © 2014 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.
Mapping neurotransmitter networks with PET: an example on serotonin and opioid systems.
Tuominen, Lauri; Nummenmaa, Lauri; Keltikangas-Järvinen, Liisa; Raitakari, Olli; Hietala, Jarmo
2014-05-01
All functions of the human brain are consequences of altered activity of specific neural pathways and neurotransmitter systems. Although the knowledge of "system level" connectivity in the brain is increasing rapidly, we lack "molecular level" information on brain networks and connectivity patterns. We introduce novel voxel-based positron emission tomography (PET) methods for studying internal neurotransmitter network structure and intercorrelations of different neurotransmitter systems in the human brain. We chose serotonin transporter and μ-opioid receptor for this analysis because of their functional interaction at the cellular level and similar regional distribution in the brain. Twenty-one healthy subjects underwent two consecutive PET scans using [(11)C]MADAM, a serotonin transporter tracer, and [(11)C]carfentanil, a μ-opioid receptor tracer. First, voxel-by-voxel "intracorrelations" (hub and seed analyses) were used to study the internal structure of opioid and serotonin systems. Second, voxel-level opioid-serotonin intercorrelations (between neurotransmitters) were computed. Regional μ-opioid receptor binding potentials were uniformly correlated throughout the brain. However, our analyses revealed nonuniformity in the serotonin transporter intracorrelations and identified a highly connected local network (midbrain-striatum-thalamus-amygdala). Regionally specific intercorrelations between the opioid and serotonin tracers were found in anteromedial thalamus, amygdala, anterior cingulate cortex, dorsolateral prefrontal cortex, and left parietal cortex, i.e., in areas relevant for several neuropsychiatric disorders, especially affective disorders. This methodology enables in vivo mapping of connectivity patterns within and between neurotransmitter systems. Quantification of functional neurotransmitter balances may be a useful approach in etiological studies of neuropsychiatric disorders and also in drug development as a biomarker-based rationale for targeted modulation of neurotransmitter networks. Copyright © 2013 Wiley Periodicals, Inc.
Groppe, David M; Bickel, Stephan; Dykstra, Andrew R; Wang, Xiuyuan; Mégevand, Pierre; Mercier, Manuel R; Lado, Fred A; Mehta, Ashesh D; Honey, Christopher J
2017-04-01
Intracranial electrical recordings (iEEG) and brain stimulation (iEBS) are invaluable human neuroscience methodologies. However, the value of such data is often unrealized as many laboratories lack tools for localizing electrodes relative to anatomy. To remedy this, we have developed a MATLAB toolbox for intracranial electrode localization and visualization, iELVis. NEW METHOD: iELVis uses existing tools (BioImage Suite, FSL, and FreeSurfer) for preimplant magnetic resonance imaging (MRI) segmentation, neuroimaging coregistration, and manual identification of electrodes in postimplant neuroimaging. Subsequently, iELVis implements methods for correcting electrode locations for postimplant brain shift with millimeter-scale accuracy and provides interactive visualization on 3D surfaces or in 2D slices with optional functional neuroimaging overlays. iELVis also localizes electrodes relative to FreeSurfer-based atlases and can combine data across subjects via the FreeSurfer average brain. It takes 30-60min of user time and 12-24h of computer time to localize and visualize electrodes from one brain. We demonstrate iELVis's functionality by showing that three methods for mapping primary hand somatosensory cortex (iEEG, iEBS, and functional MRI) provide highly concordant results. COMPARISON WITH EXISTING METHODS: iELVis is the first public software for electrode localization that corrects for brain shift, maps electrodes to an average brain, and supports neuroimaging overlays. Moreover, its interactive visualizations are powerful and its tutorial material is extensive. iELVis promises to speed the progress and enhance the robustness of intracranial electrode research. The software and extensive tutorial materials are freely available as part of the EpiSurg software project: https://github.com/episurg/episurg. Copyright © 2017 Elsevier B.V. All rights reserved.
A high-resolution computational localization method for transcranial magnetic stimulation mapping.
Aonuma, Shinta; Gomez-Tames, Jose; Laakso, Ilkka; Hirata, Akimasa; Takakura, Tomokazu; Tamura, Manabu; Muragaki, Yoshihiro
2018-05-15
Transcranial magnetic stimulation (TMS) is used for the mapping of brain motor functions. The complexity of the brain deters determining the exact localization of the stimulation site using simplified methods (e.g., the region below the center of the TMS coil) or conventional computational approaches. This study aimed to present a high-precision localization method for a specific motor area by synthesizing computed non-uniform current distributions in the brain for multiple sessions of TMS. Peritumoral mapping by TMS was conducted on patients who had intra-axial brain neoplasms located within or close to the motor speech area. The electric field induced by TMS was computed using realistic head models constructed from magnetic resonance images of patients. A post-processing method was implemented to determine a TMS hotspot by combining the computed electric fields for the coil orientations and positions that delivered high motor-evoked potentials during peritumoral mapping. The method was compared to the stimulation site localized via intraoperative direct brain stimulation and navigated TMS. Four main results were obtained: 1) the dependence of the computed hotspot area on the number of peritumoral measurements was evaluated; 2) the estimated localization of the hand motor area in eight non-affected hemispheres was in good agreement with the position of a so-called "hand-knob"; 3) the estimated hotspot areas were not sensitive to variations in tissue conductivity; and 4) the hand motor areas estimated by this proposal and direct electric stimulation (DES) were in good agreement in the ipsilateral hemisphere of four glioma patients. The TMS localization method was validated by well-known positions of the "hand-knob" in brains for the non-affected hemisphere, and by a hotspot localized via DES during awake craniotomy for the tumor-containing hemisphere. Copyright © 2018 Elsevier Inc. All rights reserved.
Emoto, M C; Yamato, M; Sato-Akaba, H; Yamada, K; Matsuoka, Y; Fujii, H G
2015-01-01
Methamphetamine (METH)-induced neurotoxicity is associated with mitochondrial dysfunction and enhanced oxidative stress. The aims of the present study conducted in the mouse brain repetitively treated with METH were to (1) examine the redox status using the redox-sensitive imaging probe 3-methoxycarbonyl-2,2,5,5-tetramethylpiperidine-1-oxyl (MCP) and (2) non-invasively visualize the brain redox status with electron paramagnetic resonance (EPR) imaging. The rate of reduction of MCP was measured from a series of temporal EPR images of mouse heads, and this rate was used to construct a two-dimensional map of rate constants called a "redox map." The obtained redox map clearly illustrated the change in redox balance in the METH-treated mouse brain that is a known result of oxidative damage. Biochemical assays also showed that the level of thiobarbituric acid-reactive substance, an index of lipid peroxidation, was increased in mouse brains by METH. The enhanced reduction in MCP observed in mouse brains was remarkably suppressed by treatment with the dopamine synthase inhibitor, α-methyl-p-tyrosine, suggesting that enhancement of the reduction reaction of MCP resulted from enzymatic reduction in the mitochondrial respiratory chain. Furthermore, magnetic resonance imaging (MRI) of METH-treated mice using a blood-brain barrier (BBB)-impermeable paramagnetic contrast agent revealed BBB dysfunction after treatment with METH for 7 days. MRI also indicated that the impaired BBB recovered after withdrawal of METH. EPR imaging and MRI are useful tools not only for following changes in the redox status and BBB dysfunction in mouse brains repeatedly administered METH, but also for tracing the drug effect after withdrawal of METH.
SPED light sheet microscopy: fast mapping of biological system structure and function
Tomer, Raju; Lovett-Barron, Matthew; Kauvar, Isaac; Andalman, Aaron; Burns, Vanessa M.; Sankaran, Sethuraman; Grosenick, Logan; Broxton, Michael; Yang, Samuel; Deisseroth, Karl
2016-01-01
The goal of understanding living nervous systems has driven interest in high-speed and large field-of-view volumetric imaging at cellular resolution. Light-sheet microscopy approaches have emerged for cellular-resolution functional brain imaging in small organisms such as larval zebrafish, but remain fundamentally limited in speed. Here we have developed SPED light sheet microscopy, which combines large volumetric field-of-view via an extended depth of field with the optical sectioning of light sheet microscopy, thereby eliminating the need to physically scan detection objectives for volumetric imaging. SPED enables scanning of thousands of volumes-per-second, limited only by camera acquisition rate, through the harnessing of optical mechanisms that normally result in unwanted spherical aberrations. We demonstrate capabilities of SPED microscopy by performing fast sub-cellular resolution imaging of CLARITY mouse brains and cellular-resolution volumetric Ca2+ imaging of entire zebrafish nervous systems. Together, SPED light sheet methods enable high-speed cellular-resolution volumetric mapping of biological system structure and function. PMID:26687363
Anwar, A R; Muthalib, M; Perrey, S; Galka, A; Granert, O; Wolff, S; Deuschl, G; Raethjen, J; Heute, U; Muthuraman, M
2012-01-01
Directionality analysis of signals originating from different parts of brain during motor tasks has gained a lot of interest. Since brain activity can be recorded over time, methods of time series analysis can be applied to medical time series as well. Granger Causality is a method to find a causal relationship between time series. Such causality can be referred to as a directional connection and is not necessarily bidirectional. The aim of this study is to differentiate between different motor tasks on the basis of activation maps and also to understand the nature of connections present between different parts of the brain. In this paper, three different motor tasks (finger tapping, simple finger sequencing, and complex finger sequencing) are analyzed. Time series for each task were extracted from functional magnetic resonance imaging (fMRI) data, which have a very good spatial resolution and can look into the sub-cortical regions of the brain. Activation maps based on fMRI images show that, in case of complex finger sequencing, most parts of the brain are active, unlike finger tapping during which only limited regions show activity. Directionality analysis on time series extracted from contralateral motor cortex (CMC), supplementary motor area (SMA), and cerebellum (CER) show bidirectional connections between these parts of the brain. In case of simple finger sequencing and complex finger sequencing, the strongest connections originate from SMA and CMC, while connections originating from CER in either direction are the weakest ones in magnitude during all paradigms.
Wang, Yumei; Zhao, Xiaochuan; Xu, Shunjiang; Yu, Lulu; Wang, Lan; Song, Mei; Yang, Linlin; Wang, Xueyi
2015-01-01
Most patients with mild cognitive impairment (MCI) are thought to be in an early stage of Alzheimer's disease (AD). Resting-state functional magnetic resonance imaging reflects spontaneous brain activity and/or the endogenous/background neurophysiological process of the human brain. Regional homogeneity (ReHo) rapidly maps regional brain activity across the whole brain. In the present study, we used the ReHo index to explore whole brain spontaneous activity pattern in MCI. Our results showed that MCI subjects displayed an increased ReHo index in the paracentral lobe, precuneus, and postcentral and a decreased ReHo index in the medial temporal gyrus and hippocampus. Impairments in the medial temporal gyrus and hippocampus may serve as important markers distinguishing MCI from healthy aging. Moreover, the increased ReHo index observed in the postcentral and paracentral lobes might indicate compensation for the cognitive function losses in individuals with MCI.
Wang, Yumei; Zhao, Xiaochuan; Xu, Shunjiang; Yu, Lulu; Wang, Lan; Song, Mei; Yang, Linlin; Wang, Xueyi
2015-01-01
Most patients with mild cognitive impairment (MCI) are thought to be in an early stage of Alzheimer's disease (AD). Resting-state functional magnetic resonance imaging reflects spontaneous brain activity and/or the endogenous/background neurophysiological process of the human brain. Regional homogeneity (ReHo) rapidly maps regional brain activity across the whole brain. In the present study, we used the ReHo index to explore whole brain spontaneous activity pattern in MCI. Our results showed that MCI subjects displayed an increased ReHo index in the paracentral lobe, precuneus, and postcentral and a decreased ReHo index in the medial temporal gyrus and hippocampus. Impairments in the medial temporal gyrus and hippocampus may serve as important markers distinguishing MCI from healthy aging. Moreover, the increased ReHo index observed in the postcentral and paracentral lobes might indicate compensation for the cognitive function losses in individuals with MCI. PMID:25738156
NASA Astrophysics Data System (ADS)
Córdova-Palomera, Aldo; Kaufmann, Tobias; Persson, Karin; Alnæs, Dag; Doan, Nhat Trung; Moberget, Torgeir; Lund, Martina Jonette; Barca, Maria Lage; Engvig, Andreas; Brækhus, Anne; Engedal, Knut; Andreassen, Ole A.; Selbæk, Geir; Westlye, Lars T.
2017-01-01
As findings on the neuropathological and behavioral components of Alzheimer’s disease (AD) continue to accrue, converging evidence suggests that macroscale brain functional disruptions may mediate their association. Recent developments on theoretical neuroscience indicate that instantaneous patterns of brain connectivity and metastability may be a key mechanism in neural communication underlying cognitive performance. However, the potential significance of these patterns across the AD spectrum remains virtually unexplored. We assessed the clinical sensitivity of static and dynamic functional brain disruptions across the AD spectrum using resting-state fMRI in a sample consisting of AD patients (n = 80) and subjects with either mild (n = 44) or subjective (n = 26) cognitive impairment (MCI, SCI). Spatial maps constituting the nodes in the functional brain network and their associated time-series were estimated using spatial group independent component analysis and dual regression, and whole-brain oscillatory activity was analyzed both globally (metastability) and locally (static and dynamic connectivity). Instantaneous phase metrics showed functional coupling alterations in AD compared to MCI and SCI, both static (putamen, dorsal and default-mode) and dynamic (temporal, frontal-superior and default-mode), along with decreased global metastability. The results suggest that brains of AD patients display altered oscillatory patterns, in agreement with theoretical premises on cognitive dynamics.
NASA Astrophysics Data System (ADS)
Lee, Jae-Seung; Im, In-Chul; Kang, Su-Man; Goo, Eun-Hoe; Kwak, Byung-Joon
2013-07-01
This study aimed to quantitatively analyze data from diffusion tensor imaging (DTI) using statistical parametric mapping (SPM) in patients with brain disorders and to assess its potential utility for analyzing brain function. DTI was obtained by performing 3.0-T magnetic resonance imaging for patients with Alzheimer's disease (AD) and vascular dementia (VD), and the data were analyzed using Matlab-based SPM software. The two-sample t-test was used for error analysis of the location of the activated pixels. We compared regions of white matter where the fractional anisotropy (FA) values were low and the apparent diffusion coefficients (ADCs) were increased. In the AD group, the FA values were low in the right superior temporal gyrus, right inferior temporal gyrus, right sub-lobar insula, and right occipital lingual gyrus whereas the ADCs were significantly increased in the right inferior frontal gyrus and right middle frontal gyrus. In the VD group, the FA values were low in the right superior temporal gyrus, right inferior temporal gyrus, right limbic cingulate gyrus, and right sub-lobar caudate tail whereas the ADCs were significantly increased in the left lateral globus pallidus and left medial globus pallidus. In conclusion by using DTI and SPM analysis, we were able to not only determine the structural state of the regions affected by brain disorders but also quantitatively analyze and assess brain function.
Structural covariance mapping delineates medial and medio-lateral temporal networks in déjà vu.
Shaw, Daniel Joel; Mareček, Radek; Brázdil, Milan
2016-12-01
Déjà vu (DV) is an eerie phenomenon experienced frequently as an aura of temporal lobe epilepsy, but also reported commonly by healthy individuals. The former pathological manifestation appears to result from aberrant neural activity among brain structures within the medial temporal lobes. Recent studies also implicate medial temporal brain structures in the non-pathological experience of DV, but as one element of a diffuse neuroanatomical correlate; it remains to be seen if neural activity among the medial temporal lobes also underlies this benign manifestation. The present study set out to investigate this. Due to its unpredictable and infrequent occurrence, however, non-pathological DV does not lend itself easily to functional neuroimaging. Instead, we draw on research showing that brain structure covaries among regions that interact frequently as nodes of functional networks. Specifically, we assessed whether grey-matter covariance among structures implicated in non-pathological DV differs according to the frequency with which the phenomenon is experienced. This revealed two diverging patterns of structural covariation: Among the first, comprised primarily of medial temporal structures and the caudate, grey-matter volume becomes more positively correlated with higher frequency of DV experience. The second pattern encompasses medial and lateral temporal structures, among which greater DV frequency is associated with more negatively correlated grey matter. Using a meta-analytic method of co-activation mapping, we demonstrate a higher probability of functional interactions among brain structures constituting the former pattern, particularly during memory-related processes. Our findings suggest that altered neural signalling within memory-related medial temporal brain structures underlies both pathological and non-pathological DV.
Planar implantable sensor for in vivo measurement of cellular oxygen metabolism in brain tissue.
Tsytsarev, Vassiliy; Akkentli, Fatih; Pumbo, Elena; Tang, Qinggong; Chen, Yu; Erzurumlu, Reha S; Papkovsky, Dmitri B
2017-04-01
Brain imaging methods are continually improving. Imaging of the cerebral cortex is widely used in both animal experiments and charting human brain function in health and disease. Among the animal models, the rodent cerebral cortex has been widely used because of patterned neural representation of the whiskers on the snout and relative ease of activating cortical tissue with whisker stimulation. We tested a new planar solid-state oxygen sensor comprising a polymeric film with a phosphorescent oxygen-sensitive coating on the working side, to monitor dynamics of oxygen metabolism in the cerebral cortex following sensory stimulation. Sensory stimulation led to changes in oxygenation and deoxygenation processes of activated areas in the barrel cortex. We demonstrate the possibility of dynamic mapping of relative changes in oxygenation in live mouse brain tissue with such a sensor. Oxygenation-based functional magnetic resonance imaging (fMRI) is very effective method for functional brain mapping but have high costs and limited spatial resolution. Optical imaging of intrinsic signal (IOS) does not provide the required sensitivity, and voltage-sensitive dye optical imaging (VSDi) has limited applicability due to significant toxicity of the voltage-sensitive dye. Our planar solid-state oxygen sensor imaging approach circumvents these limitations, providing a simple optical contrast agent with low toxicity and rapid application. The planar solid-state oxygen sensor described here can be used as a tool in visualization and real-time analysis of sensory-evoked neural activity in vivo. Further, this approach allows visualization of local neural activity with high temporal and spatial resolution. Copyright © 2017 Elsevier B.V. All rights reserved.
[Three-dimensional reconstruction of functional brain images].
Inoue, M; Shoji, K; Kojima, H; Hirano, S; Naito, Y; Honjo, I
1999-08-01
We consider PET (positron emission tomography) measurement with SPM (Statistical Parametric Mapping) analysis to be one of the most useful methods to identify activated areas of the brain involved in language processing. SPM is an effective analytical method that detects markedly activated areas over the whole brain. However, with the conventional presentations of these functional brain images, such as horizontal slices, three directional projection, or brain surface coloring, makes understanding and interpreting the positional relationships among various brain areas difficult. Therefore, we developed three-dimensionally reconstructed images from these functional brain images to improve the interpretation. The subjects were 12 normal volunteers. The following three types of images were constructed: 1) routine images by SPM, 2) three-dimensional static images, and 3) three-dimensional dynamic images, after PET images were analyzed by SPM during daily dialog listening. The creation of images of both the three-dimensional static and dynamic types employed the volume rendering method by VTK (The Visualization Toolkit). Since the functional brain images did not include original brain images, we synthesized SPM and MRI brain images by self-made C++ programs. The three-dimensional dynamic images were made by sequencing static images with available software. Images of both the three-dimensional static and dynamic types were processed by a personal computer system. Our newly created images showed clearer positional relationships among activated brain areas compared to the conventional method. To date, functional brain images have been employed in fields such as neurology or neurosurgery, however, these images may be useful even in the field of otorhinolaryngology, to assess hearing and speech. Exact three-dimensional images based on functional brain images are important for exact and intuitive interpretation, and may lead to new developments in brain science. Currently, the surface model is the most common method of three-dimensional display. However, the volume rendering method may be more effective for imaging regions such as the brain.
Network localization of neurological symptoms from focal brain lesions.
Boes, Aaron D; Prasad, Sashank; Liu, Hesheng; Liu, Qi; Pascual-Leone, Alvaro; Caviness, Verne S; Fox, Michael D
2015-10-01
A traditional and widely used approach for linking neurological symptoms to specific brain regions involves identifying overlap in lesion location across patients with similar symptoms, termed lesion mapping. This approach is powerful and broadly applicable, but has limitations when symptoms do not localize to a single region or stem from dysfunction in regions connected to the lesion site rather than the site itself. A newer approach sensitive to such network effects involves functional neuroimaging of patients, but this requires specialized brain scans beyond routine clinical data, making it less versatile and difficult to apply when symptoms are rare or transient. In this article we show that the traditional approach to lesion mapping can be expanded to incorporate network effects into symptom localization without the need for specialized neuroimaging of patients. Our approach involves three steps: (i) transferring the three-dimensional volume of a brain lesion onto a reference brain; (ii) assessing the intrinsic functional connectivity of the lesion volume with the rest of the brain using normative connectome data; and (iii) overlapping lesion-associated networks to identify regions common to a clinical syndrome. We first tested our approach in peduncular hallucinosis, a syndrome of visual hallucinations following subcortical lesions long hypothesized to be due to network effects on extrastriate visual cortex. While the lesions themselves were heterogeneously distributed with little overlap in lesion location, 22 of 23 lesions were negatively correlated with extrastriate visual cortex. This network overlap was specific compared to other subcortical lesions (P < 10(-5)) and relative to other cortical regions (P < 0.01). Next, we tested for generalizability of our technique by applying it to three additional lesion syndromes: central post-stroke pain, auditory hallucinosis, and subcortical aphasia. In each syndrome, heterogeneous lesions that themselves had little overlap showed significant network overlap in cortical areas previously implicated in symptom expression (P < 10(-4)). These results suggest that (i) heterogeneous lesions producing similar symptoms share functional connectivity to specific brain regions involved in symptom expression; and (ii) publically available human connectome data can be used to incorporate these network effects into traditional lesion mapping approaches. Because the current technique requires no specialized imaging of patients it may prove a versatile and broadly applicable approach for localizing neurological symptoms in the setting of brain lesions. © 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.
High-density diffuse optical tomography of term infant visual cortex in the nursery
NASA Astrophysics Data System (ADS)
Liao, Steve M.; Ferradal, Silvina L.; White, Brian R.; Gregg, Nicholas; Inder, Terrie E.; Culver, Joseph P.
2012-08-01
Advancements in antenatal and neonatal medicine over the last few decades have led to significant improvement in the survival rates of sick newborn infants. However, this improvement in survival has not been matched by a reduction in neurodevelopmental morbidities with increasing recognition of the diverse cognitive and behavioral challenges that preterm infants face in childhood. Conventional neuroimaging modalities, such as cranial ultrasound and magnetic resonance imaging, provide an important definition of neuroanatomy with recognition of brain injury. However, they fail to define the functional integrity of the immature brain, particularly during this critical developmental period. Diffuse optical tomography methods have established success in imaging adult brain function; however, few studies exist to demonstrate their feasibility in the neonatal population. We demonstrate the feasibility of using recently developed high-density diffuse optical tomography (HD-DOT) to map functional activation of the visual cortex in healthy term-born infants. The functional images show high contrast-to-noise ratio obtained in seven neonates. These results illustrate the potential for HD-DOT and provide a foundation for investigations of brain function in more vulnerable newborns, such as preterm infants.
De Martin, Elena; Duran, Dunja; Ghielmetti, Francesco; Visani, Elisa; Aquino, Domenico; Marchetti, Marcello; Sebastiano, Davide Rossi; Cusumano, Davide; Bruzzone, Maria Grazia; Panzica, Ferruccio; Fariselli, Laura
2017-12-01
Magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) provide noninvasive localization of eloquent brain areas for presurgical planning. The aim of this study is the integration of MEG and fMRI maps into a CyberKnife (CK) system to optimize dose planning. Four patients with brain metastases in the motor area underwent functional imaging study of the hand motor cortex before radiosurgery. MEG data were acquired during a visually cued hand motor task. Motor activations were identified also using an fMRI block-designed paradigm. MEG and fMRI maps were then integrated into a CK system and contoured as organs at risk for treatment planning optimization. The integration of fMRI data into the CK system was achieved for all patients by means of a standardized protocol. We also implemented an ad hoc pipeline to convert the MEG signal into a DICOM standard, to make sure that it was readable by our CK treatment planning system. Inclusion of the activation areas into the optimization plan allowed the creation of treatment plans that reduced the irradiation of the motor cortex yet not affecting the brain peripheral dose. The availability of advanced neuroimaging techniques is playing an increasingly important role in radiosurgical planning strategy. We successfully imported MEG and fMRI activations into a CK system. This additional information can improve dose sparing of eloquent areas, allowing a more comprehensive investigation of the related dose-volume constraints that in theory could translate into a gain in tumor local control, and a reduction of neurological complications. Copyright © 2017 Elsevier Inc. All rights reserved.
Tadić, Bosiljka; Andjelković, Miroslav; Boshkoska, Biljana Mileva; Levnajić, Zoran
2016-01-01
Human behaviour in various circumstances mirrors the corresponding brain connectivity patterns, which are suitably represented by functional brain networks. While the objective analysis of these networks by graph theory tools deepened our understanding of brain functions, the multi-brain structures and connections underlying human social behaviour remain largely unexplored. In this study, we analyse the aggregate graph that maps coordination of EEG signals previously recorded during spoken communications in two groups of six listeners and two speakers. Applying an innovative approach based on the algebraic topology of graphs, we analyse higher-order topological complexes consisting of mutually interwoven cliques of a high order to which the identified functional connections organise. Our results reveal that the topological quantifiers provide new suitable measures for differences in the brain activity patterns and inter-brain synchronisation between speakers and listeners. Moreover, the higher topological complexity correlates with the listener’s concentration to the story, confirmed by self-rating, and closeness to the speaker’s brain activity pattern, which is measured by network-to-network distance. The connectivity structures of the frontal and parietal lobe consistently constitute distinct clusters, which extend across the listener’s group. Formally, the topology quantifiers of the multi-brain communities exceed the sum of those of the participating individuals and also reflect the listener’s rated attributes of the speaker and the narrated subject. In the broader context, the presented study exposes the relevance of higher topological structures (besides standard graph measures) for characterising functional brain networks under different stimuli. PMID:27880802
Whole-brain activity mapping onto a zebrafish brain atlas.
Randlett, Owen; Wee, Caroline L; Naumann, Eva A; Nnaemeka, Onyeka; Schoppik, David; Fitzgerald, James E; Portugues, Ruben; Lacoste, Alix M B; Riegler, Clemens; Engert, Florian; Schier, Alexander F
2015-11-01
In order to localize the neural circuits involved in generating behaviors, it is necessary to assign activity onto anatomical maps of the nervous system. Using brain registration across hundreds of larval zebrafish, we have built an expandable open-source atlas containing molecular labels and definitions of anatomical regions, the Z-Brain. Using this platform and immunohistochemical detection of phosphorylated extracellular signal–regulated kinase (ERK) as a readout of neural activity, we have developed a system to create and contextualize whole-brain maps of stimulus- and behavior-dependent neural activity. This mitogen-activated protein kinase (MAP)-mapping assay is technically simple, and data analysis is completely automated. Because MAP-mapping is performed on freely swimming fish, it is applicable to studies of nearly any stimulus or behavior. Here we demonstrate our high-throughput approach using pharmacological, visual and noxious stimuli, as well as hunting and feeding. The resultant maps outline hundreds of areas associated with behaviors.
Tomaiuolo, F; MacDonald, J D; Caramanos, Z; Posner, G; Chiavaras, M; Evans, A C; Petrides, M
1999-09-01
The pars opercularis occupies the posterior part of the inferior frontal gyrus. Electrical stimulation or damage of this region interferes with language production. The present study investigated the morphology and morphometry of the pars opercularis in 108 normal adult human cerebral hemispheres by means of magnetic resonance imaging. The brain images were transformed into a standardized proportional steoreotaxic space (i.e. that of Talairach and Tournoux) in order to minimize interindividual brain size variability. There was considerable variability in the shape and location of the pars opercularis across brains and between cerebral hemispheres. There was no significant difference or correlation between left and right hemisphere grey matter volumes. There was also no significant difference between sex and side of asymmetry of the pars opercularis. A probability map of the pars opercularis was constructed by averaging its location and extent in each individual normalized brain into Talairach space to aid in localization of activity changes in functional neuroimaging studies.
Mapping Epileptic Activity: Sources or Networks for the Clinicians?
Pittau, Francesca; Mégevand, Pierre; Sheybani, Laurent; Abela, Eugenio; Grouiller, Frédéric; Spinelli, Laurent; Michel, Christoph M.; Seeck, Margitta; Vulliemoz, Serge
2014-01-01
Epileptic seizures of focal origin are classically considered to arise from a focal epileptogenic zone and then spread to other brain regions. This is a key concept for semiological electro-clinical correlations, localization of relevant structural lesions, and selection of patients for epilepsy surgery. Recent development in neuro-imaging and electro-physiology and combinations, thereof, have been validated as contributory tools for focus localization. In parallel, these techniques have revealed that widespread networks of brain regions, rather than a single epileptogenic region, are implicated in focal epileptic activity. Sophisticated multimodal imaging and analysis strategies of brain connectivity patterns have been developed to characterize the spatio-temporal relationships within these networks by combining the strength of both techniques to optimize spatial and temporal resolution with whole-brain coverage and directional connectivity. In this paper, we review the potential clinical contribution of these functional mapping techniques as well as invasive electrophysiology in human beings and animal models for characterizing network connectivity. PMID:25414692
Mongeau, R; Casu, M A; Pani, L; Pillolla, G; Lianas, L; Giachetti, A
2008-05-01
The vast amount of heterogeneous data generated in various fields of neurosciences such as neuropsychopharmacology can hardly be classified using traditional databases. We present here the concept of a virtual archive, spatially referenced over a simplified 3D brain map and accessible over the Internet. A simple prototype (available at http://aquatics.crs4.it/neuropsydat3d) has been realized using current Web-based virtual reality standards and technologies. It illustrates how primary literature or summary information can easily be retrieved through hyperlinks mapped onto a 3D schema while navigating through neuroanatomy. Furthermore, 3D navigation and visualization techniques are used to enhance the representation of brain's neurotransmitters, pathways and the involvement of specific brain areas in any particular physiological or behavioral functions. The system proposed shows how the use of a schematic spatial organization of data, widely exploited in other fields (e.g. Geographical Information Systems) can be extremely useful to develop efficient tools for research and teaching in neurosciences.
Prospective study of awake craniotomy used routinely and nonselectively for supratentorial tumors.
Serletis, Demitre; Bernstein, Mark
2007-07-01
The authors prospectively assessed the value of awake craniotomy used nonselectively in patients undergoing resection of supratentorial tumors. The demographic features, presenting symptoms, tumor location, histological diagnosis, outcomes, and complications were documented for 610 patients who underwent awake craniotomy for supratentorial tumor resection. Intraoperative brain mapping was used in 511 cases (83.8%). Mapping identified eloquent cortex in 115 patients (22.5%) and no eloquent cortex in 396 patients (77.5%). Neurological deficits occurred in 89 patients (14.6%). In the subset of 511 patients in whom brain mapping was performed, 78 (15.3%) experienced postoperative neurological worsening. This phenomenon was more common in patients with preoperative neurological deficits or in those individuals in whom mapping successfully identified eloquent tissue. Twenty-five (4.9%) of the 511 patients suffered intraoperative seizures, and two of these individuals required intubation and induction of general anesthesia after generalized seizures occurred. Four (0.7%) of the 610 patients developed wound complications. Postoperative hematomas developed in seven patients (1.1%), four of whom urgently required a repeated craniotomy to allow evacuation of the clot. Two patients (0.3%) required readmission to the hospital soon after being discharged. There were three deaths (0.5%). Awake craniotomy is safe, practical, and effective during resection of supratentorial lesions of diverse pathological range and location. It allows for intraoperative brain mapping that helps identify and protect functional cortex. It also avoids the complications inherent in the induction of general anesthesia. Awake craniotomy provides an excellent alternative to surgery of supratentorial brain lesions in patients in whom general anesthesia has been induced.
An Improved Representation of Regional Boundaries on Parcellated Morphological Surfaces
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
Zhang, Shu; Zhao, Yu; Jiang, Xi; Shen, Dinggang; Liu, Tianming
2018-06-01
In the brain mapping field, there have been significant interests in representation of structural/functional profiles to establish structural/functional landmark correspondences across individuals and populations. For example, from the structural perspective, our previous studies have identified hundreds of consistent DICCCOL (dense individualized and common connectivity-based cortical landmarks) landmarks across individuals and populations, each of which possess consistent DTI-derived fiber connection patterns. From the functional perspective, a large collection of well-characterized HAFNI (holistic atlases of functional networks and interactions) networks based on sparse representation of whole-brain fMRI signals have been identified in our prior studies. However, due to the remarkable variability of structural and functional architectures in the human brain, it is challenging for earlier studies to jointly represent the connectome-scale structural and functional profiles for establishing a common cortical architecture which can comprehensively encode both structural and functional characteristics across individuals. To address this challenge, we propose an effective computational framework to jointly represent the structural and functional profiles for identification of consistent and common cortical landmarks with both structural and functional correspondences across different brains based on DTI and fMRI data. Experimental results demonstrate that 55 structurally and functionally common cortical landmarks can be successfully identified.
NASA Astrophysics Data System (ADS)
Silvestri, Ludovico; Rudinskiy, Nikita; Paciscopi, Marco; Müllenbroich, Marie Caroline; Costantini, Irene; Sacconi, Leonardo; Frasconi, Paolo; Hyman, Bradley T.; Pavone, Francesco S.
2016-03-01
Mapping neuronal activity patterns across the whole brain with cellular resolution is a challenging task for state-of-the-art imaging methods. Indeed, despite a number of technological efforts, quantitative cellular-resolution activation maps of the whole brain have not yet been obtained. Many techniques are limited by coarse resolution or by a narrow field of view. High-throughput imaging methods, such as light sheet microscopy, can be used to image large specimens with high resolution and in reasonable times. However, the bottleneck is then moved from image acquisition to image analysis, since many TeraBytes of data have to be processed to extract meaningful information. Here, we present a full experimental pipeline to quantify neuronal activity in the entire mouse brain with cellular resolution, based on a combination of genetics, optics and computer science. We used a transgenic mouse strain (Arc-dVenus mouse) in which neurons which have been active in the last hours before brain fixation are fluorescently labelled. Samples were cleared with CLARITY and imaged with a custom-made confocal light sheet microscope. To perform an automatic localization of fluorescent cells on the large images produced, we used a novel computational approach called semantic deconvolution. The combined approach presented here allows quantifying the amount of Arc-expressing neurons throughout the whole mouse brain. When applied to cohorts of mice subject to different stimuli and/or environmental conditions, this method helps finding correlations in activity between different neuronal populations, opening the possibility to infer a sort of brain-wide 'functional connectivity' with cellular resolution.
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.
Improving Functional MRI Registration Using Whole-Brain Functional Correlation Tensors.
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.
Vilasboas, Tatiana; Herbet, Guillaume; Duffau, Hugues
2017-07-01
For many years, the right hemisphere (RH) was considered as nondominant, especially in right-handers. In neurosurgical practice, this dogma resulted in the selection of awake procedure with language mapping only for lesions of the left dominant hemisphere. Conversely, surgery under general anesthesia (possibly with motor mapping) was usually proposed for right lesions. However, when objective neuropsychological assessments were performed, they frequently showed cognitive and behavioral deficits after brain surgery, even in the RH. Therefore, to preserve an optimal quality of life, especially in patients with a long survival expectancy (as in low-grade gliomas), awake surgery with cortical and axonal electrostimulation mapping has recently been proposed for resection of right tumors. Here, we review new insights gained from intraoperative stimulation into the pivotal role of the RH in movement execution and control, visual processes and spatial cognition, language and nonverbal semantic processing, executive functions (e.g., attention), and social cognition (mentalizing and emotion recognition). These original findings, which break with the myth of a nondominant RH, may have important implications in cognitive neurosciences, by improving our knowledge of the functional connectivity of the RH, as well as for the clinical management of patients with a right lesion. In brain surgery, awake mapping should be considered more systematically in the RH. Moreover, neuropsychological examination must be achieved in a more systematic manner before and after surgery within the RH, to optimize care by predicting the likelihood of functional recovery and by elaborating specific programs of rehabilitation. Copyright © 2017 Elsevier Inc. All rights reserved.
Wu, Jinsong; Lu, Junfeng; Zhang, Han; Zhang, Jie; Yao, Chengjun; Zhuang, Dongxiao; Qiu, Tianming; Guo, Qihao; Hu, Xiaobing; Mao, Ying; Zhou, Liangfu
2015-12-01
Chinese processing has been suggested involving distinct brain areas from English. However, current functional localization studies on Chinese speech processing use mostly "indirect" techniques such as functional magnetic resonance imaging and electroencephalography, lacking direct evidence by means of electrocortical recording. In this study, awake craniotomies in 66 Chinese-speaking glioma patients provide a unique opportunity to directly map eloquent language areas. Intraoperative electrocortical stimulation was conducted and the positive sites for speech arrest, anomia, and alexia were identified separately. With help of stereotaxic neuronavigation system and computational modeling, all positive sites elicited by stimulation were integrated and a series of two- and three-dimension Chinese language probability maps were built. We performed statistical comparisons between the Chinese maps and previously derived English maps. While most Chinese speech arrest areas located at typical language production sites (i.e., 50% positive sites in ventral precentral gyrus, 28% in pars opercularis and pars triangularis), which also serve English production, an additional brain area, the left middle frontal gyrus (Brodmann's areas 6/9), was found to be unique in Chinese production (P < 0.05). Moreover, Chinese speakers' inferior ventral precentral gyrus (Brodmann's area 6) was used more than that in English speakers. Our finding suggests that Chinese involves more perisylvian region (extending to left middle frontal gyrus) than English. This is the first time that direct evidence supports cross-cultural neurolinguistics differences in human beings. The Chinese language atlas will also helpful in brain surgery planning for Chinese-speakers. Copyright © 2015 Wiley Periodicals, Inc.
Sha, Fern; Johenning, Friedrich W.; Schreiter, Eric R.; Looger, Loren L.; Larkum, Matthew E.
2016-01-01
Key points The genetically encoded fluorescent calcium integrator calcium‐modulated photoactivatable ratiobetric integrator (CaMPARI) reports calcium influx induced by synaptic and neural activity. Its fluorescence is converted from green to red in the presence of violet light and calcium.The rate of conversion – the sensitivity to activity – is tunable and depends on the intensity of violet light.Synaptic activity and action potentials can independently initiate significant CaMPARI conversion.The level of conversion by subthreshold synaptic inputs is correlated to the strength of input, enabling optical readout of relative synaptic strength.When combined with optogenetic activation of defined presynaptic neurons, CaMPARI provides an all‐optical method to map synaptic connectivity. Abstract The calcium‐modulated photoactivatable ratiometric integrator (CaMPARI) is a genetically encoded calcium integrator that facilitates the study of neural circuits by permanently marking cells active during user‐specified temporal windows. Permanent marking enables measurement of signals from large swathes of tissue and easy correlation of activity with other structural or functional labels. One potential application of CaMPARI is labelling neurons postsynaptic to specific populations targeted for optogenetic stimulation, giving rise to all‐optical functional connectivity mapping. Here, we characterized the response of CaMPARI to several common types of neuronal calcium signals in mouse acute cortical brain slices. Our experiments show that CaMPARI is effectively converted by both action potentials and subthreshold synaptic inputs, and that conversion level is correlated to synaptic strength. Importantly, we found that conversion rate can be tuned: it is linearly related to light intensity. At low photoconversion light levels CaMPARI offers a wide dynamic range due to slower conversion rate; at high light levels conversion is more rapid and more sensitive to activity. Finally, we employed CaMPARI and optogenetics for functional circuit mapping in ex vivo acute brain slices, which preserve in vivo‐like connectivity of axon terminals. With a single light source, we stimulated channelrhodopsin‐2‐expressing long‐range posteromedial (POm) thalamic axon terminals in cortex and induced CaMPARI conversion in recipient cortical neurons. We found that POm stimulation triggers robust photoconversion of layer 5 cortical neurons and weaker conversion of layer 2/3 neurons. Thus, CaMPARI enables network‐wide, tunable, all‐optical functional circuit mapping that captures supra‐ and subthreshold depolarization. PMID:27861906
Effects of age of acquisition on brain activation during Chinese character recognition.
Weekes, Brendan Stuart; Chan, Alice H D; Tan, Li Hai
2008-01-01
The age of acquisition of a word (AoA) has a specific effect on brain activation during word identification in English and German. However, the neural locus of AoA effects differs across studies. According to Hernandez and Fiebach [Hernandez, A., & Fiebach, C. (2006). The brain bases of reading late-learned words: Evidence from functional MRI. Visual Cognition, 13(8), 1027-1043], the effects of AoA on brain activation depend on the predictability of the connections between input (orthography) and output (phonology) in a lexical network. We tested this hypothesis by examining AoA effects in a non-alphabetic script with relatively arbitrary mappings between orthography and phonology--Chinese. Our results showed that the effects of AoA in Chinese speakers are located in brain regions that are spatially distinctive including the bilateral middle temporal gyrus and the left inferior parietal cortex. An additional finding was that word frequency had an independent effect on brain activation in the right middle occipital gyrus only. We conclude that spatially distinctive effects of AoA on neural activity depend on the predictability of the mappings between orthography and phonology and reflect a division of labour towards greater lexical-semantic retrieval in non-alphabetic scripts.
Mandonnet, Emmanuel; Winkler, Peter A; Duffau, Hugues
2010-02-01
While the fundamental and clinical contribution of direct electrical stimulation (DES) of the brain is now well acknowledged, its advantages and limitations have not been re-evaluated for a long time. Here, we critically review exactly what DES can tell us about cerebral function. First, we show that DES is highly sensitive for detecting the cortical and axonal eloquent structures. Moreover, DES also provides a unique opportunity to study brain connectivity, since each area responsive to stimulation is in fact an input gate into a large-scale network rather than an isolated discrete functional site. DES, however, also has a limitation: its specificity is suboptimal. Indeed, DES may lead to interpretations that a structure is crucial because of the induction of a transient functional response when stimulated, whereas (1) this effect is caused by the backward spreading of the electro-stimulation along the network to an essential area and/or (2) the stimulated region can be functionally compensated owing to long-term brain plasticity mechanisms. In brief, although DES is still the gold standard for brain mapping, its combination with new methods such as perioperative neurofunctional imaging and biomathematical modeling is now mandatory, in order to clearly differentiate those networks that are actually indispensable to function from those that can be compensated.
Whole-brain activity mapping onto a zebrafish brain atlas
Randlett, Owen; Wee, Caroline L.; Naumann, Eva A.; Nnaemeka, Onyeka; Schoppik, David; Fitzgerald, James E.; Portugues, Ruben; Lacoste, Alix M.B.; Riegler, Clemens; Engert, Florian; Schier, Alexander F.
2015-01-01
In order to localize the neural circuits involved in generating behaviors, it is necessary to assign activity onto anatomical maps of the nervous system. Using brain registration across hundreds of larval zebrafish, we have built an expandable open source atlas containing molecular labels and anatomical region definitions, the Z-Brain. Using this platform and immunohistochemical detection of phosphorylated-Extracellular signal-regulated kinase (ERK/MAPK) as a readout of neural activity, we have developed a system to create and contextualize whole brain maps of stimulus- and behavior-dependent neural activity. This MAP-Mapping (Mitogen Activated Protein kinase – Mapping) assay is technically simple, fast, inexpensive, and data analysis is completely automated. Since MAP-Mapping is performed on fish that are freely swimming, it is applicable to nearly any stimulus or behavior. We demonstrate the utility of our high-throughput approach using hunting/feeding, pharmacological, visual and noxious stimuli. The resultant maps outline hundreds of areas associated with behaviors. PMID:26778924
Brun, Caroline; Leporé, Natasha; Pennec, Xavier; Lee, Agatha D.; Barysheva, Marina; Madsen, Sarah K.; Avedissian, Christina; Chou, Yi-Yu; de Zubicaray, Greig I.; McMahon, Katie; Wright, Margaret; Toga, Arthur W.; Thompson, Paul M.
2010-01-01
Genetic and environmental factors influence brain structure and function profoundly The search for heritable anatomical features and their influencing genes would be accelerated with detailed 3D maps showing the degree to which brain morphometry is genetically determined. As part of an MRI study that will scan 1150 twins, we applied Tensor-Based Morphometry to compute morphometric differences in 23 pairs of identical twins and 23 pairs of same-sex fraternal twins (mean age: 23.8 ± 1.8 SD years). All 92 twins’ 3D brain MRI scans were nonlinearly registered to a common space using a Riemannian fluid-based warping approach to compute volumetric differences across subjects. A multi-template method was used to improve volume quantification. Vector fields driving each subject’s anatomy onto the common template were analyzed to create maps of local volumetric excesses and deficits relative to the standard template. Using a new structural equation modeling method, we computed the voxelwise proportion of variance in volumes attributable to additive (A) or dominant (D) genetic factors versus shared environmental (C) or unique environmental factors (E). The method was also applied to various anatomical regions of interest (ROIs). As hypothesized, the overall volumes of the brain, basal ganglia, thalamus, and each lobe were under strong genetic control; local white matter volumes were mostly controlled by common environment. After adjusting for individual differences in overall brain scale, genetic influences were still relatively high in the corpus callosum and in early-maturing brain regions such as the occipital lobes, while environmental influences were greater in frontal brain regions which have a more protracted maturational time-course. PMID:19446645
Aleem Bhatti, Atta Ul; Jakhrani, Nasir Khan; Parekh, Maria Adnan
2018-01-01
The past few years have seen increasing support for gross total resection in the management of low-grade gliomas (LGGs), with a greater extent of resection correlated with better overall survival, progression-free survival, and time to malignant transformation. There is consistent evidence in literature supporting extent of safe resection as a good prognostic indicator as well as positively affecting seizure control, symptomatic relief in pressure symptoms, and longer progression-free and total survival. The operative goal in most LGG cases is to maximize the extent of resection for these benefits while avoiding postoperative neurologic deficits. Several advanced invasive and noninvasive surgical techniques such as intraoperative magnetic resonance imaging (MRI), fluorescence-guided surgery, intraoperative functional pathway mapping, and neuronavigation have been developed in an attempt to better achieve maximal safe resection. We present a case of LGG in a young patient with a 5-year history of refractory seizures and gradual onset walking difficulty. Serial MRI brain scans revealed a progressive increase in right frontal tumor size with substantial edema and parafalcine herniation. Noninvasive brain mapping by functional MRI (fMRI) and sleep-awake-sleep type of anesthesia with endotracheal tube insertion was utilized during an awake craniotomy. Histopathology confirmed a Grade II oligodendroglioma, and genetic analysis revealed no codeletion at 1p/19q. Neurological improvement was remarkable in terms of immediate motor improvement, and the patient remained completely seizure free on a single antiepileptic drug. There is no radiologic or clinical evidence of recurrence 6 months postoperatively. This is the first published report of an awake craniotomy for LGG in Pakistan. The contemporary concept of supratotal resection in LGGs advocates generous functional resection even beyond MRI findings rather than mere excision of oncological boundaries. This relatively aggressive approach is only possible with an awake craniotomy, which ensures preservation of functional status and thus less postoperative morbidity and better outcomes. Noninvasive mapping for intracranial space-occupying lesions, including fMRI and blood-oxygen-level dependent (BOLD) imaging modality, is an essential tool in a resource-limited setting such as Pakistan.
Brain Connectivity and Functional Recovery in Patients With Ischemic Stroke.
Almeida, Sara Regina Meira; Vicentini, Jessica; Bonilha, Leonardo; De Campos, Brunno M; Casseb, Raphael F; Min, Li Li
2017-01-01
Brain mapping studies have demonstrated that functional poststroke brain reorganization is associated with recovery of motor function. Nonetheless, the specific mechanisms associated with functional reorganization leading to motor recovery are still partly unknown. In this study, we performed a cross-sectional evaluation of poststroke subjects with the following goals: (1) To assess intra- and interhemispheric functional brain activation patterns associated with motor function in poststroke patients with variable degrees of recovery; (2) to investigate the involvement of other nonmotor functional networks in relationship with recovery. We studied 59 individuals: 13 patients with function Rankin > 1 and Barthel < 100; 19 patients with preserved function with Rankin 0-1 and Barthel = 100; and 27 healthy controls. All subjects underwent structural and functional magnetic resonance imaging (3T Philips Achieva, Holland) using the same protocol (TR = 2 seconds, TE = 30 ms, FOV = 240 × 240 × 117, slice = 39). Resting state functional connectivity was used by in-house software, based on SPM12. Among patients with and without preserved function, the functional connectivity between the primary motor region (M1) and the contralateral hemisphere was increased compared with controls. Nonetheless, only patients with decreased function exhibited decreased functional connectivity between executive control, sensorimotor and visuospatial networks. Functional recovery after stroke is associated with preserved functional connectivity of motor to nonmotor networks. Copyright © 2016 by the American Society of Neuroimaging.
Liu, Quanying; Ganzetti, Marco; Wenderoth, Nicole; Mantini, Dante
2018-01-01
Resting state networks (RSNs) in the human brain were recently detected using high-density electroencephalography (hdEEG). This was done by using an advanced analysis workflow to estimate neural signals in the cortex and to assess functional connectivity (FC) between distant cortical regions. FC analyses were conducted either using temporal (tICA) or spatial independent component analysis (sICA). Notably, EEG-RSNs obtained with sICA were very similar to RSNs retrieved with sICA from functional magnetic resonance imaging data. It still remains to be clarified, however, what technological aspects of hdEEG acquisition and analysis primarily influence this correspondence. Here we examined to what extent the detection of EEG-RSN maps by sICA depends on the electrode density, the accuracy of the head model, and the source localization algorithm employed. Our analyses revealed that the collection of EEG data using a high-density montage is crucial for RSN detection by sICA, but also the use of appropriate methods for head modeling and source localization have a substantial effect on RSN reconstruction. Overall, our results confirm the potential of hdEEG for mapping the functional architecture of the human brain, and highlight at the same time the interplay between acquisition technology and innovative solutions in data analysis. PMID:29551969
Avram, Alexandru V; Sarlls, Joelle E; Barnett, Alan S; Özarslan, Evren; Thomas, Cibu; Irfanoglu, M Okan; Hutchinson, Elizabeth; Pierpaoli, Carlo; Basser, Peter J
2016-02-15
Diffusion tensor imaging (DTI) is the most widely used method for characterizing noninvasively structural and architectural features of brain tissues. However, the assumption of a Gaussian spin displacement distribution intrinsic to DTI weakens its ability to describe intricate tissue microanatomy. Consequently, the biological interpretation of microstructural parameters, such as fractional anisotropy or mean diffusivity, is often equivocal. We evaluate the clinical feasibility of assessing brain tissue microstructure with mean apparent propagator (MAP) MRI, a powerful analytical framework that efficiently measures the probability density function (PDF) of spin displacements and quantifies useful metrics of this PDF indicative of diffusion in complex microstructure (e.g., restrictions, multiple compartments). Rotation invariant and scalar parameters computed from the MAP show consistent variation across neuroanatomical brain regions and increased ability to differentiate tissues with distinct structural and architectural features compared with DTI-derived parameters. The return-to-origin probability (RTOP) appears to reflect cellularity and restrictions better than MD, while the non-Gaussianity (NG) measures diffusion heterogeneity by comprehensively quantifying the deviation between the spin displacement PDF and its Gaussian approximation. Both RTOP and NG can be decomposed in the local anatomical frame for reference determined by the orientation of the diffusion tensor and reveal additional information complementary to DTI. The propagator anisotropy (PA) shows high tissue contrast even in deep brain nuclei and cortical gray matter and is more uniform in white matter than the FA, which drops significantly in regions containing crossing fibers. Orientational profiles of the propagator computed analytically from the MAP MRI series coefficients allow separation of different fiber populations in regions of crossing white matter pathways, which in turn improves our ability to perform whole-brain fiber tractography. Reconstructions from subsampled data sets suggest that MAP MRI parameters can be computed from a relatively small number of DWIs acquired with high b-value and good signal-to-noise ratio in clinically achievable scan durations of less than 10min. The neuroanatomical consistency across healthy subjects and reproducibility in test-retest experiments of MAP MRI microstructural parameters further substantiate the robustness and clinical feasibility of this technique. The MAP MRI metrics could potentially provide more sensitive clinical biomarkers with increased pathophysiological specificity compared to microstructural measures derived using conventional diffusion MRI techniques. Published by Elsevier Inc.
Large-scale topology and the default mode network in the mouse connectome
Stafford, James M.; Jarrett, Benjamin R.; Miranda-Dominguez, Oscar; Mills, Brian D.; Cain, Nicholas; Mihalas, Stefan; Lahvis, Garet P.; Lattal, K. Matthew; Mitchell, Suzanne H.; David, Stephen V.; Fryer, John D.; Nigg, Joel T.; Fair, Damien A.
2014-01-01
Noninvasive functional imaging holds great promise for serving as a translational bridge between human and animal models of various neurological and psychiatric disorders. However, despite a depth of knowledge of the cellular and molecular underpinnings of atypical processes in mouse models, little is known about the large-scale functional architecture measured by functional brain imaging, limiting translation to human conditions. Here, we provide a robust processing pipeline to generate high-resolution, whole-brain resting-state functional connectivity MRI (rs-fcMRI) images in the mouse. Using a mesoscale structural connectome (i.e., an anterograde tracer mapping of axonal projections across the mouse CNS), we show that rs-fcMRI in the mouse has strong structural underpinnings, validating our procedures. We next directly show that large-scale network properties previously identified in primates are present in rodents, although they differ in several ways. Last, we examine the existence of the so-called default mode network (DMN)—a distributed functional brain system identified in primates as being highly important for social cognition and overall brain function and atypically functionally connected across a multitude of disorders. We show the presence of a potential DMN in the mouse brain both structurally and functionally. Together, these studies confirm the presence of basic network properties and functional networks of high translational importance in structural and functional systems in the mouse brain. This work clears the way for an important bridge measurement between human and rodent models, enabling us to make stronger conclusions about how regionally specific cellular and molecular manipulations in mice relate back to humans. PMID:25512496
Using Data-Driven Model-Brain Mappings to Constrain Formal Models of Cognition
Borst, Jelmer P.; Nijboer, Menno; Taatgen, Niels A.; van Rijn, Hedderik; Anderson, John R.
2015-01-01
In this paper we propose a method to create data-driven mappings from components of cognitive models to brain regions. Cognitive models are notoriously hard to evaluate, especially based on behavioral measures alone. Neuroimaging data can provide additional constraints, but this requires a mapping from model components to brain regions. Although such mappings can be based on the experience of the modeler or on a reading of the literature, a formal method is preferred to prevent researcher-based biases. In this paper we used model-based fMRI analysis to create a data-driven model-brain mapping for five modules of the ACT-R cognitive architecture. We then validated this mapping by applying it to two new datasets with associated models. The new mapping was at least as powerful as an existing mapping that was based on the literature, and indicated where the models were supported by the data and where they have to be improved. We conclude that data-driven model-brain mappings can provide strong constraints on cognitive models, and that model-based fMRI is a suitable way to create such mappings. PMID:25747601
Pre-seizure state identified by diffuse optical tomography
Zhang, Tao; Zhou, Junli; Jiang, Ruixin; Yang, Hao; Carney, Paul R.; Jiang, Huabei
2014-01-01
In epilepsy it has been challenging to detect early changes in brain activity that occurs prior to seizure onset and to map their origin and evolution for possible intervention. Here we demonstrate using a rat model of generalized epilepsy that diffuse optical tomography (DOT) provides a unique functional neuroimaging modality for noninvasively and continuously tracking such brain activities with high spatiotemporal resolution. We detected early hemodynamic responses with heterogeneous patterns, along with intracranial electroencephalogram gamma power changes, several minutes preceding the electroencephalographic seizure onset, supporting the presence of a “pre-seizure” state. We also observed the decoupling between local hemodynamic and neural activities. We found widespread hemodynamic changes evolving from local regions of the bilateral cortex and thalamus to the entire brain, indicating that the onset of generalized seizures may originate locally rather than diffusely. Together, these findings suggest DOT represents a powerful tool for mapping early seizure onset and propagation pathways. PMID:24445927
Intrinsic connectivity in the human brain does not reveal networks for ‘basic’ emotions
Lindquist, Kristen A.; Dickerson, Bradford C.; Barrett, Lisa Feldman
2015-01-01
We tested two competing models for the brain basis of emotion, the basic emotion theory and the conceptual act theory of emotion, using resting-state functional connectivity magnetic resonance imaging (rs-fcMRI). The basic emotion view hypothesizes that anger, sadness, fear, disgust and happiness each arise from a brain network that is innate, anatomically constrained and homologous in other animals. The conceptual act theory of emotion hypothesizes that an instance of emotion is a brain state constructed from the interaction of domain-general, core systems within the brain such as the salience, default mode and frontoparietal control networks. Using peak coordinates derived from a meta-analysis of task-evoked emotion fMRI studies, we generated a set of whole-brain rs-fcMRI ‘discovery’ maps for each emotion category and examined the spatial overlap in their conjunctions. Instead of discovering a specific network for each emotion category, variance in the discovery maps was accounted for by the known domain-general network. Furthermore, the salience network is observed as part of every emotion category. These results indicate that specific networks for each emotion do not exist within the intrinsic architecture of the human brain and instead support the conceptual act theory of emotion. PMID:25680990
Mills, D. L.; Dai, L.; Fishman, I.; Yam, A.; Appelbaum, L. G.; Galaburda, A.; Bellugi, U.; Korenberg, J. R.
2014-01-01
In Williams Syndrome (WS), a known genetic deletion results in atypical brain function with strengths in face and language processing. We examined how genetic influences on brain activity change with development. In three studies, ERPs from large samples of children, adolescents, and adults with the full genetic deletion for WS were compared to typically developing controls, and two adults with partial deletions for WS. Studies 1 and 2 identified ERP markers of brain plasticity in WS across development. Study 3 suggested that in adults with partial deletions for WS, specific genes may be differentially implicated in face and language processing. PMID:24219698
Slice-to-Volume Nonrigid Registration of Histological Sections to MR Images of the Human Brain
Osechinskiy, Sergey; Kruggel, Frithjof
2011-01-01
Registration of histological images to three-dimensional imaging modalities is an important step in quantitative analysis of brain structure, in architectonic mapping of the brain, and in investigation of the pathology of a brain disease. Reconstruction of histology volume from serial sections is a well-established procedure, but it does not address registration of individual slices from sparse sections, which is the aim of the slice-to-volume approach. This study presents a flexible framework for intensity-based slice-to-volume nonrigid registration algorithms with a geometric transformation deformation field parametrized by various classes of spline functions: thin-plate splines (TPS), Gaussian elastic body splines (GEBS), or cubic B-splines. Algorithms are applied to cross-modality registration of histological and magnetic resonance images of the human brain. Registration performance is evaluated across a range of optimization algorithms and intensity-based cost functions. For a particular case of histological data, best results are obtained with a TPS three-dimensional (3D) warp, a new unconstrained optimization algorithm (NEWUOA), and a correlation-coefficient-based cost function. PMID:22567290
Hu, Zhishan; Zhang, Juan; Couto, Tania Alexandra; Xu, Shiyang; Luan, Ping; Yuan, Zhen
2018-06-22
In this study, functional near-infrared spectroscopy (fNIRS) was used to examine the brain activation and connectivity in occipitotemporal cortex during Chinese character recognition (CCR). Eighteen healthy participants were recruited to perform a well-designed task with three categories of stimuli (real characters, pseudo characters, and checkerboards). By inspecting the brain activation difference and its relationship with behavioral data, the left laterality during CCR was clearly identified in the Brodmann area (BA) 18 and 19. In addition, our novel findings also demonstrated that the bilateral superior temporal gyrus (STG), bilateral BA 19, and left fusiform gyrus were also involved in high-level lexical information processing such as semantic and phonological ones. Meanwhile, by examining functional brain networks, we discovered that the right BA 19 exhibited enhanced brain connectivity. In particular, the connectivity in the right fusiform gyrus, right BA 19, and left STG showed significant correlation with the performance of CCR. Consequently, the combination of fNIRS technique with functional network analysis paves a new avenue for improved understanding of the cognitive mechanism underlying CCR.
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.
Soman, S; Liu, Z; Kim, G; Nemec, U; Holdsworth, S J; Main, K; Lee, B; Kolakowsky-Hayner, S; Selim, M; Furst, A J; Massaband, P; Yesavage, J; Adamson, M M; Spincemallie, P; Moseley, M; Wang, Y
2018-04-01
Identifying cerebral microhemorrhage burden can aid in the diagnosis and management of traumatic brain injury, stroke, hypertension, and cerebral amyloid angiopathy. MR imaging susceptibility-based methods are more sensitive than CT for detecting cerebral microhemorrhage, but methods other than quantitative susceptibility mapping provide results that vary with field strength and TE, require additional phase maps to distinguish blood from calcification, and depict cerebral microhemorrhages as bloom artifacts. Quantitative susceptibility mapping provides universal quantification of tissue magnetic property without these constraints but traditionally requires a mask generated by skull-stripping, which can pose challenges at tissue interphases. We evaluated the preconditioned quantitative susceptibility mapping MR imaging method, which does not require skull-stripping, for improved depiction of brain parenchyma and pathology. Fifty-six subjects underwent brain MR imaging with a 3D multiecho gradient recalled echo acquisition. Mask-based quantitative susceptibility mapping images were created using a commonly used mask-based quantitative susceptibility mapping method, and preconditioned quantitative susceptibility images were made using precondition-based total field inversion. All images were reviewed by a neuroradiologist and a radiology resident. Ten subjects (18%), all with traumatic brain injury, demonstrated blood products on 3D gradient recalled echo imaging. All lesions were visible on preconditioned quantitative susceptibility mapping, while 6 were not visible on mask-based quantitative susceptibility mapping. Thirty-one subjects (55%) demonstrated brain parenchyma and/or lesions that were visible on preconditioned quantitative susceptibility mapping but not on mask-based quantitative susceptibility mapping. Six subjects (11%) demonstrated pons artifacts on preconditioned quantitative susceptibility mapping and mask-based quantitative susceptibility mapping; they were worse on preconditioned quantitative susceptibility mapping. Preconditioned quantitative susceptibility mapping MR imaging can bring the benefits of quantitative susceptibility mapping imaging to clinical practice without the limitations of mask-based quantitative susceptibility mapping, especially for evaluating cerebral microhemorrhage-associated pathologies, such as traumatic brain injury. © 2018 by American Journal of Neuroradiology.
Cell type-specific long-range connections of basal forebrain circuit.
Do, Johnny Phong; Xu, Min; Lee, Seung-Hee; Chang, Wei-Cheng; Zhang, Siyu; Chung, Shinjae; Yung, Tyler J; Fan, Jiang Lan; Miyamichi, Kazunari; Luo, Liqun; Dan, Yang
2016-09-19
The basal forebrain (BF) plays key roles in multiple brain functions, including sleep-wake regulation, attention, and learning/memory, but the long-range connections mediating these functions remain poorly characterized. Here we performed whole-brain mapping of both inputs and outputs of four BF cell types - cholinergic, glutamatergic, and parvalbumin-positive (PV+) and somatostatin-positive (SOM+) GABAergic neurons - in the mouse brain. Using rabies virus -mediated monosynaptic retrograde tracing to label the inputs and adeno-associated virus to trace axonal projections, we identified numerous brain areas connected to the BF. The inputs to different cell types were qualitatively similar, but the output projections showed marked differences. The connections to glutamatergic and SOM+ neurons were strongly reciprocal, while those to cholinergic and PV+ neurons were more unidirectional. These results reveal the long-range wiring diagram of the BF circuit with highly convergent inputs and divergent outputs and point to both functional commonality and specialization of different BF cell types.
Expanding efforts to address Alzheimer’s disease: The Healthy Brain Initiative
Anderson, Lynda A.; Egge, Robert
2015-01-01
The growing burden of Alzheimer’s disease underscores the importance of enhancing current public health efforts to address dementia. Public health organizations and entities have substantial opportunities to contribute to efforts underway and to add innovations to the field. The Alzheimer’s Association and the Centers for Disease Control and Prevention worked with a 15-member leadership committee and hundreds of stakeholders to create The Healthy Brain Initiative: The Public Health Road Map for State and National Partnerships, 2013–2018 (Road Map). The actions in the Road Map provide a foundation for the public health community to anticipate and respond to emerging innovations and developments. It will be a challenge to harness the increasingly complex nature of public- and private-sector collaborations. We must strengthen the capacity of public health agencies, leverage partnerships, and find new ways to integrate cognitive functioning into public health efforts. PMID:25088658
Rosario, Wilfredo; Singh, Inderroop; Wautlet, Arnaud; Patterson, Christa; Flak, Jonathan; Becker, Thomas C; Ali, Almas; Tamarina, Natalia; Philipson, Louis H; Enquist, Lynn W; Myers, Martin G; Rhodes, Christopher J
2016-09-01
The brain influences glucose homeostasis, partly by supplemental control over insulin and glucagon secretion. Without this central regulation, diabetes and its complications can ensue. Yet, the neuronal network linking to pancreatic islets has never been fully mapped. Here, we refine this map using pseudorabies virus (PRV) retrograde tracing, indicating that the pancreatic islets are innervated by efferent circuits that emanate from the hypothalamus. We found that the hypothalamic arcuate nucleus (ARC), ventromedial nucleus (VMN), and lateral hypothalamic area (LHA) significantly overlap PRV and the physiological glucose-sensing enzyme glucokinase. Then, experimentally lowering glucose sensing, specifically in the ARC, resulted in glucose intolerance due to deficient insulin secretion and no significant effect in the VMN, but in the LHA it resulted in a lowering of the glucose threshold that improved glucose tolerance and/or improved insulin sensitivity, with an exaggerated counter-regulatory response for glucagon secretion. No significant effect on insulin sensitivity or metabolic homeostasis was noted. Thus, these data reveal novel direct neuronal effects on pancreatic islets and also render a functional validation of the brain-to-islet neuronal map. They also demonstrate that distinct regions of the hypothalamus differentially control insulin and glucagon secretion, potentially in partnership to help maintain glucose homeostasis and guard against hypoglycemia. © 2016 by the American Diabetes Association.
Whole head quantitative susceptibility mapping using a least-norm direct dipole inversion method.
Sun, Hongfu; Ma, Yuhan; MacDonald, M Ethan; Pike, G Bruce
2018-06-15
A new dipole field inversion method for whole head quantitative susceptibility mapping (QSM) is proposed. Instead of performing background field removal and local field inversion sequentially, the proposed method performs dipole field inversion directly on the total field map in a single step. To aid this under-determined and ill-posed inversion process and obtain robust QSM images, Tikhonov regularization is implemented to seek the local susceptibility solution with the least-norm (LN) using the L-curve criterion. The proposed LN-QSM does not require brain edge erosion, thereby preserving the cerebral cortex in the final images. This should improve its applicability for QSM-based cortical grey matter measurement, functional imaging and venography of full brain. Furthermore, LN-QSM also enables susceptibility mapping of the entire head without the need for brain extraction, which makes QSM reconstruction more automated and less dependent on intermediate pre-processing methods and their associated parameters. It is shown that the proposed LN-QSM method reduced errors in a numerical phantom simulation, improved accuracy in a gadolinium phantom experiment, and suppressed artefacts in nine subjects, as compared to two-step and other single-step QSM methods. Measurements of deep grey matter and skull susceptibilities from LN-QSM are consistent with established reconstruction methods. Copyright © 2018 Elsevier Inc. All rights reserved.
Quantifying Mesoscale Neuroanatomy Using X-Ray Microtomography
Gray Roncal, William; Prasad, Judy A.; Fernandes, Hugo L.; Gürsoy, Doga; De Andrade, Vincent; Fezzaa, Kamel; Xiao, Xianghui; Vogelstein, Joshua T.; Jacobsen, Chris; Körding, Konrad P.
2017-01-01
Methods for resolving the three-dimensional (3D) microstructure of the brain typically start by thinly slicing and staining the brain, followed by imaging numerous individual sections with visible light photons or electrons. In contrast, X-rays can be used to image thick samples, providing a rapid approach for producing large 3D brain maps without sectioning. Here we demonstrate the use of synchrotron X-ray microtomography (µCT) for producing mesoscale (∼1 µm 3 resolution) brain maps from millimeter-scale volumes of mouse brain. We introduce a pipeline for µCT-based brain mapping that develops and integrates methods for sample preparation, imaging, and automated segmentation of cells, blood vessels, and myelinated axons, in addition to statistical analyses of these brain structures. Our results demonstrate that X-ray tomography achieves rapid quantification of large brain volumes, complementing other brain mapping and connectomics efforts. PMID:29085899
Prakash, Neal; Uhleman, Falk; Sheth, Sameer A.; Bookheimer, Susan; Martin, Neil; Toga, Arthur W.
2009-01-01
Resection of a cerebral arteriovenous malformation (AVM), epileptic focus, or glioma, ideally has a prerequisite of microscopic delineation of the lesion borders in relation to the normal gray and white matter that mediate critical functions. Currently, Wada testing and functional magnetic resonance imaging (fMRI) are used for preoperative mapping of critical function, whereas electrical stimulation mapping (ESM) is used for intraoperative mapping. For lesion delineation, MRI and positron emission tomography (PET) are used preoperatively, whereas microscopy and histological sectioning are used intraoperatively. However, for lesions near eloquent cortex, these imaging techniques may lack sufficient resolution to define the relationship between the lesion and language function, and thus not accurately determine which patients will benefit from neurosurgical resection of the lesion without iatrogenic aphasia. Optical techniques such as intraoperative optical imaging of intrinsic signals (iOIS) show great promise for the precise functional mapping of cortices, as well as delineation of the borders of AVMs, epileptic foci, and gliomas. Here we first review the physiology of neuroimaging, and then progress towards the validation and justification of using intraoperative optical techniques, especially in relation to neurosurgical planning of resection AVMs, epileptic foci, and gliomas near or in eloquent cortex. We conclude with a short description of potential novel intraoperative optical techniques. PMID:18786643
Jiang, Xi; Li, Xiang; Lv, Jinglei; Zhao, Shijie; Zhang, Shu; Zhang, Wei; Zhang, Tuo; Han, Junwei; Guo, Lei; Liu, Tianming
2018-06-01
Various studies in the brain mapping field have demonstrated that there exist multiple concurrent functional networks that are spatially overlapped and interacting with each other during specific task performance to jointly realize the total brain function. Assessing such spatial overlap patterns of functional networks (SOPFNs) based on functional magnetic resonance imaging (fMRI) has thus received increasing interest for brain function studies. However, there are still two crucial issues to be addressed. First, the SOPFNs are assessed over the entire fMRI scan assuming the temporal stationarity, while possibly time-dependent dynamics of the SOPFNs is not sufficiently explored. Second, the SOPFNs are assessed within individual subjects, while group-wise consistency of the SOPFNs is largely unknown. To address the two issues, we propose a novel computational framework of group-wise sparse representation of whole-brain fMRI temporal segments to assess the temporal dynamic spatial patterns of SOPFNs that are consistent across different subjects. Experimental results based on the recently publicly released Human Connectome Project grayordinate task fMRI data demonstrate that meaningful SOPFNs exhibiting dynamic spatial patterns across different time periods are effectively and robustly identified based on the reconstructed concurrent functional networks via the proposed framework. Specifically, those SOPFNs locate significantly more on gyral regions than on sulcal regions across different time periods. These results reveal novel functional architecture of cortical gyri and sulci. Moreover, these results help better understand functional dynamics mechanisms of cerebral cortex in the future.
Farzan, Faranak; Pascual-Leone, Alvaro; Schmahmann, Jeremy D.; Halko, Mark
2016-01-01
Growing evidence suggests that sensory, motor, cognitive and affective processes map onto specific, distributed neural networks. Cerebellar subregions are part of these networks, but how the cerebellum is involved in this wide range of brain functions remains poorly understood. It is postulated that the cerebellum contributes a basic role in brain functions, helping to shape the complexity of brain temporal dynamics. We therefore hypothesized that stimulating cerebellar nodes integrated in different networks should have the same impact on the temporal complexity of cortical signals. In healthy humans, we applied intermittent theta burst stimulation (iTBS) to the vermis lobule VII or right lateral cerebellar Crus I/II, subregions that prominently couple to the dorsal-attention/fronto-parietal and default-mode networks, respectively. Cerebellar iTBS increased the complexity of brain signals across multiple time scales in a network-specific manner identified through electroencephalography (EEG). We also demonstrated a region-specific shift in power of cortical oscillations towards higher frequencies consistent with the natural frequencies of targeted cortical areas. Our findings provide a novel mechanism and evidence by which the cerebellum contributes to multiple brain functions: specific cerebellar subregions control the temporal dynamics of the networks they are engaged in. PMID:27009405
Novel Neuroimaging Methods to Understand How HIV Affects the Brain
Thompson, Paul
2015-01-01
In much of the developed world, the HIV epidemic has largely been controlled by anti-retroviral treatment. Even so, there is growing concern that HIV-infected individuals may be at risk for accelerated brain aging, and a range of cognitive impairments. What promotes or resists these changes is largely unknown. There is also interest in discovering factors that promote resilience to HIV, and combat its adverse effects in children. Here we review recent developments in brain imaging that reveal how the virus affects the brain. We relate these brain changes to changes in blood markers, cognitive function, and other patient outcomes or symptoms, such as apathy or neuropathic pain. We focus on new and emerging techniques, including new variants of brain MRI. Diffusion tensor imaging, for example, can map the brain’s structural connections while fMRI can uncover functional connections. Finally, we suggest how large-scale global research alliances, such as ENIGMA, may resolve controversies over effects where evidence is now lacking. These efforts pool scans from tens of thousands of individuals, and offer a source of power not previously imaginable for brain imaging studies. PMID:25902966
Brain Functional Connectivity in MS: An EEG-NIRS Study
2015-10-01
electrical (EEG) and blood volume and blood oxygen-based (NIRS and fMRI ) signals, and to use the results to help optimize blood oxygen level...dependent (BOLD) fMRI analyses of brain activity. Participants will be patients with MS (n=25) and healthy demographically matched controls (n=25) who will...undergo standardized evaluations and imaging using combined EEG-NIRS- fMRI . EEG-NIRS data will be used to construct maps of neurovascular coupling
Fusing DTI and FMRI Data: A Survey of Methods and Applications
Zhu, Dajiang; Zhang, Tuo; Jiang, Xi; Hu, Xintao; Chen, Hanbo; Yang, Ning; Lv, Jinglei; Han, Junwei; Guo, Lei; Liu, Tianming
2014-01-01
The relationship between brain structure and function has been one of the centers of research in neuroimaging for decades. In recent years, diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) techniques have been widely available and popular in cognitive and clinical neurosciences for examining the brain’s white matter (WM) micro-structures and gray matter (GM) functions, respectively. Given the intrinsic integration of WM/GM and the complementary information embedded in DTI/fMRI data, it is natural and well-justified to combine these two neuroimaging modalities together to investigate brain structure and function and their relationships simultaneously. In the past decade, there have been remarkable achievements of DTI/fMRI fusion methods and applications in neuroimaging and human brain mapping community. This survey paper aims to review recent advancements on methodologies and applications in incorporating multimodal DTI and fMRI data, and offer our perspectives on future research directions. We envision that effective fusion of DTI/fMRI techniques will play increasingly important roles in neuroimaging and brain sciences in the years to come. PMID:24103849
Moriguchi, Yoshiya; Noda, Takamasa; Nakayashiki, Kosei; Takata, Yohei; Setoyama, Shiori; Kawasaki, Shingo; Kunisato, Yoshihiko; Mishima, Kazuo; Nakagome, Kazuyuki; Hanakawa, Takashi
2017-10-01
Near-infrared spectroscopy (NIRS) is a convenient and safe brain-mapping tool. However, its inevitable confounding with hemodynamic responses outside the brain, especially in the frontotemporal head, has questioned its validity. Some researchers attempted to validate NIRS signals through concurrent measurements with functional magnetic resonance imaging (fMRI), but, counterintuitively, NIRS signals rarely correlate with local fMRI signals in NIRS channels, although both mapping techniques should measure the same hemoglobin concentration. Here, we tested a novel hypothesis that different voxels within the scalp and the brain tissues might have substantially different hemoglobin absorption rates of near-infrared light, which might differentially contribute to NIRS signals across channels. Therefore, we newly applied a multivariate approach, a partial least squares regression, to explain NIRS signals with multivoxel information from fMRI within the brain and soft tissues in the head. We concurrently obtained fMRI and NIRS signals in 9 healthy human subjects engaging in an n-back task. The multivariate fMRI model was quite successfully able to predict the NIRS signals by cross-validation (interclass correlation coefficient = ∼0.85). This result confirmed that fMRI and NIRS surely measure the same hemoglobin concentration. Additional application of Monte-Carlo permutation tests confirmed that the model surely reflects temporal and spatial hemodynamic information, not random noise. After this thorough validation, we calculated the ratios of the contributions of the brain and soft-tissue hemodynamics to the NIRS signals, and found that the contribution ratios were quite different across different NIRS channels in reality, presumably because of the structural complexity of the frontotemporal regions. Hum Brain Mapp 38:5274-5291, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Gorgolewski, Krzysztof J; Varoquaux, Gael; Rivera, Gabriel; Schwartz, Yannick; Sochat, Vanessa V; Ghosh, Satrajit S; Maumet, Camille; Nichols, Thomas E; Poline, Jean-Baptiste; Yarkoni, Tal; Margulies, Daniel S; Poldrack, Russell A
2016-01-01
NeuroVault.org is dedicated to storing outputs of analyses in the form of statistical maps, parcellations and atlases, a unique strategy that contrasts with most neuroimaging repositories that store raw acquisition data or stereotaxic coordinates. Such maps are indispensable for performing meta-analyses, validating novel methodology, and deciding on precise outlines for regions of interest (ROIs). NeuroVault is open to maps derived from both healthy and clinical populations, as well as from various imaging modalities (sMRI, fMRI, EEG, MEG, PET, etc.). The repository uses modern web technologies such as interactive web-based visualization, cognitive decoding, and comparison with other maps to provide researchers with efficient, intuitive tools to improve the understanding of their results. Each dataset and map is assigned a permanent Universal Resource Locator (URL), and all of the data is accessible through a REST Application Programming Interface (API). Additionally, the repository supports the NIDM-Results standard and has the ability to parse outputs from popular FSL and SPM software packages to automatically extract relevant metadata. This ease of use, modern web-integration, and pioneering functionality holds promise to improve the workflow for making inferences about and sharing whole-brain statistical maps. Copyright © 2015 Elsevier Inc. All rights reserved.
Canolty, Ryan T.; Ganguly, Karunesh; Carmena, Jose M.
2012-01-01
Understanding the principles governing the dynamic coordination of functional brain networks remains an important unmet goal within neuroscience. How do distributed ensembles of neurons transiently coordinate their activity across a variety of spatial and temporal scales? While a complete mechanistic account of this process remains elusive, evidence suggests that neuronal oscillations may play a key role in this process, with different rhythms influencing both local computation and long-range communication. To investigate this question, we recorded multiple single unit and local field potential (LFP) activity from microelectrode arrays implanted bilaterally in macaque motor areas. Monkeys performed a delayed center-out reach task either manually using their natural arm (Manual Control, MC) or under direct neural control through a brain-machine interface (Brain Control, BC). In accord with prior work, we found that the spiking activity of individual neurons is coupled to multiple aspects of the ongoing motor beta rhythm (10–45 Hz) during both MC and BC, with neurons exhibiting a diversity of coupling preferences. However, here we show that for identified single neurons, this beta-to-rate mapping can change in a reversible and task-dependent way. For example, as beta power increases, a given neuron may increase spiking during MC but decrease spiking during BC, or exhibit a reversible shift in the preferred phase of firing. The within-task stability of coupling, combined with the reversible cross-task changes in coupling, suggest that task-dependent changes in the beta-to-rate mapping play a role in the transient functional reorganization of neural ensembles. We characterize the range of task-dependent changes in the mapping from beta amplitude, phase, and inter-hemispheric phase differences to the spike rates of an ensemble of simultaneously-recorded neurons, and discuss the potential implications that dynamic remapping from oscillatory activity to spike rate and timing may hold for models of computation and communication in distributed functional brain networks. PMID:23284276
Diffusion-tensor imaging of white matter tracts in patients with cerebral neoplasm.
Witwer, Brian P; Moftakhar, Roham; Hasan, Khader M; Deshmukh, Praveen; Haughton, Victor; Field, Aaron; Arfanakis, Konstantinos; Noyes, Jane; Moritz, Chad H; Meyerand, M Elizabeth; Rowley, Howard A; Alexander, Andrew L; Badie, Behnam
2002-09-01
Preserving vital cerebral function while maximizing tumor resection is a principal goal in surgical neurooncology. Although functional magnetic resonance imaging has been useful in the localization of eloquent cerebral cortex, this method does not provide information about the white matter tracts that may be involved in invasive, intrinsic brain tumors. Recently, diffusion-tensor (DT) imaging techniques have been used to map white matter tracts in the normal brain. The aim of this study was to demonstrate the role of DT imaging in preoperative mapping of white matter tracts in relation to cerebral neoplasms. Nine patients with brain malignancies (one pilocytic astrocytoma, five oligodendrogliomas, one low-grade oligoastrocytoma, one Grade 4 astrocytoma, and one metastatic adenocarcinoma) underwent DT imaging examinations prior to tumor excision. Anatomical information about white matter tract location, orientation, and projections was obtained in every patient. Depending on the tumor type and location, evidence of white matter tract edema (two patients), infiltration (two patients), displacement (five patients), and disruption (two patients) could be assessed with the aid of DT imaging in each case. Diffusion-tensor imaging allowed for visualization of white matter tracts and was found to be beneficial in the surgical planning for patients with intrinsic brain tumors. The authors' experience with DT imaging indicates that anatomically intact fibers may be present in abnormal-appearing areas of the brain. Whether resection of these involved fibers results in subtle postoperative neurological deficits requires further systematic study.
Kasabov, Nikola K
2014-04-01
The brain functions as a spatio-temporal information processing machine. Spatio- and spectro-temporal brain data (STBD) are the most commonly collected data for measuring brain response to external stimuli. An enormous amount of such data has been already collected, including brain structural and functional data under different conditions, molecular and genetic data, in an attempt to make a progress in medicine, health, cognitive science, engineering, education, neuro-economics, Brain-Computer Interfaces (BCI), and games. Yet, there is no unifying computational framework to deal with all these types of data in order to better understand this data and the processes that generated it. Standard machine learning techniques only partially succeeded and they were not designed in the first instance to deal with such complex data. Therefore, there is a need for a new paradigm to deal with STBD. This paper reviews some methods of spiking neural networks (SNN) and argues that SNN are suitable for the creation of a unifying computational framework for learning and understanding of various STBD, such as EEG, fMRI, genetic, DTI, MEG, and NIRS, in their integration and interaction. One of the reasons is that SNN use the same computational principle that generates STBD, namely spiking information processing. This paper introduces a new SNN architecture, called NeuCube, for the creation of concrete models to map, learn and understand STBD. A NeuCube model is based on a 3D evolving SNN that is an approximate map of structural and functional areas of interest of the brain related to the modeling STBD. Gene information is included optionally in the form of gene regulatory networks (GRN) if this is relevant to the problem and the data. A NeuCube model learns from STBD and creates connections between clusters of neurons that manifest chains (trajectories) of neuronal activity. Once learning is applied, a NeuCube model can reproduce these trajectories, even if only part of the input STBD or the stimuli data is presented, thus acting as an associative memory. The NeuCube framework can be used not only to discover functional pathways from data, but also as a predictive system of brain activities, to predict and possibly, prevent certain events. Analysis of the internal structure of a model after training can reveal important spatio-temporal relationships 'hidden' in the data. NeuCube will allow the integration in one model of various brain data, information and knowledge, related to a single subject (personalized modeling) or to a population of subjects. The use of NeuCube for classification of STBD is illustrated in a case study problem of EEG data. NeuCube models result in a better accuracy of STBD classification than standard machine learning techniques. They are robust to noise (so typical in brain data) and facilitate a better interpretation of the results and understanding of the STBD and the brain conditions under which data was collected. Future directions for the use of SNN for STBD are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.
Zeharia, Noa; Hertz, Uri; Flash, Tamar; Amedi, Amir
2015-02-18
Topographic organization is one of the main principles of organization in the human brain. Specifically, whole-brain topographic mapping using spectral analysis is responsible for one of the greatest advances in vision research. Thus, it is intriguing that although topography is a key feature also in the motor system, whole-body somatosensory-motor mapping using spectral analysis has not been conducted in humans outside M1/SMA. Here, using this method, we were able to map a homunculus in the globus pallidus, a key target area for deep brain stimulation, which has not been mapped noninvasively or in healthy subjects. The analysis clarifies contradictory and partial results regarding somatotopy in the caudal-cingulate zone and rostral-cingulate zone in the medial wall and in the putamen. Most of the results were confirmed at the single-subject level and were found to be compatible with results from animal studies. Using multivoxel pattern analysis, we could predict movements of individual body parts in these homunculi, thus confirming that they contain somatotopic information. Using functional connectivity, we demonstrate interhemispheric functional somatotopic connectivity of these homunculi, such that the somatotopy in one hemisphere could have been found given the connectivity pattern of the corresponding regions of interest in the other hemisphere. When inspecting the somatotopic and nonsomatotopic connectivity patterns, a similarity index indicated that the pattern of connected and nonconnected regions of interest across different homunculi is similar for different body parts and hemispheres. The results show that topographical gradients are even more widespread than previously assumed in the somatosensory-motor system. Spectral analysis can thus potentially serve as a gold standard for defining somatosensory-motor system areas for basic research and clinical applications. Copyright © 2015 the authors 0270-6474/15/352845-15$15.00/0.
Gibson, William S.; Jo, Hang Joon; Testini, Paola; Cho, Shinho; Felmlee, Joel P.; Welker, Kirk M.; Klassen, Bryan T.; Min, Hoon-Ki
2016-01-01
Deep brain stimulation is an established neurosurgical therapy for movement disorders including essential tremor and Parkinson’s disease. While typically highly effective, deep brain stimulation can sometimes yield suboptimal therapeutic benefit and can cause adverse effects. In this study, we tested the hypothesis that intraoperative functional magnetic resonance imaging could be used to detect deep brain stimulation-evoked changes in functional and effective connectivity that would correlate with the therapeutic and adverse effects of stimulation. Ten patients receiving deep brain stimulation of the ventralis intermedius thalamic nucleus for essential tremor underwent functional magnetic resonance imaging during stimulation applied at a series of stimulation localizations, followed by evaluation of deep brain stimulation-evoked therapeutic and adverse effects. Correlations between the therapeutic effectiveness of deep brain stimulation (3 months postoperatively) and deep brain stimulation-evoked changes in functional and effective connectivity were assessed using region of interest-based correlation analysis and dynamic causal modelling, respectively. Further, we investigated whether brain regions might exist in which activation resulting from deep brain stimulation might correlate with the presence of paraesthesias, the most common deep brain stimulation-evoked adverse effect. Thalamic deep brain stimulation resulted in activation within established nodes of the tremor circuit: sensorimotor cortex, thalamus, contralateral cerebellar cortex and deep cerebellar nuclei (FDR q < 0.05). Stimulation-evoked activation in all these regions of interest, as well as activation within the supplementary motor area, brainstem, and inferior frontal gyrus, exhibited significant correlations with the long-term therapeutic effectiveness of deep brain stimulation (P < 0.05), with the strongest correlation (P < 0.001) observed within the contralateral cerebellum. Dynamic causal modelling revealed a correlation between therapeutic effectiveness and attenuated within-region inhibitory connectivity in cerebellum. Finally, specific subregions of sensorimotor cortex were identified in which deep brain stimulation-evoked activation correlated with the presence of unwanted paraesthesias. These results suggest that thalamic deep brain stimulation in tremor likely exerts its effects through modulation of both olivocerebellar and thalamocortical circuits. In addition, our findings indicate that deep brain stimulation-evoked functional activation maps obtained intraoperatively may contain predictive information pertaining to the therapeutic and adverse effects induced by deep brain stimulation. PMID:27329768
The heritability of the functional connectome is robust to common nonlinear registration methods
NASA Astrophysics Data System (ADS)
Hafzalla, George W.; Prasad, Gautam; Baboyan, Vatche G.; Faskowitz, Joshua; Jahanshad, Neda; McMahon, Katie L.; de Zubicaray, Greig I.; Wright, Margaret J.; Braskie, Meredith N.; Thompson, Paul M.
2016-03-01
Nonlinear registration algorithms are routinely used in brain imaging, to align data for inter-subject and group comparisons, and for voxelwise statistical analyses. To understand how the choice of registration method affects maps of functional brain connectivity in a sample of 611 twins, we evaluated three popular nonlinear registration methods: Advanced Normalization Tools (ANTs), Automatic Registration Toolbox (ART), and FMRIB's Nonlinear Image Registration Tool (FNIRT). Using both structural and functional MRI, we used each of the three methods to align the MNI152 brain template, and 80 regions of interest (ROIs), to each subject's T1-weighted (T1w) anatomical image. We then transformed each subject's ROIs onto the associated resting state functional MRI (rs-fMRI) scans and computed a connectivity network or functional connectome for each subject. Given the different degrees of genetic similarity between pairs of monozygotic (MZ) and same-sex dizygotic (DZ) twins, we used structural equation modeling to estimate the additive genetic influences on the elements of the function networks, or their heritability. The functional connectome and derived statistics were relatively robust to nonlinear registration effects.
Urgesi, Cosimo; Candidi, Matteo; Avenanti, Alessio
2014-01-01
Several neurophysiologic and neuroimaging studies suggested that motor and perceptual systems are tightly linked along a continuum rather than providing segregated mechanisms supporting different functions. Using correlational approaches, these studies demonstrated that action observation activates not only visual but also motor brain regions. On the other hand, brain stimulation and brain lesion evidence allows tackling the critical question of whether our action representations are necessary to perceive and understand others’ actions. In particular, recent neuropsychological studies have shown that patients with temporal, parietal, and frontal lesions exhibit a number of possible deficits in the visual perception and the understanding of others’ actions. The specific anatomical substrates of such neuropsychological deficits however, are still a matter of debate. Here we review the existing literature on this issue and perform an anatomic likelihood estimation meta-analysis of studies using lesion-symptom mapping methods on the causal relation between brain lesions and non-linguistic action perception and understanding deficits. The meta-analysis encompassed data from 361 patients tested in 11 studies and identified regions in the inferior frontal cortex, the inferior parietal cortex and the middle/superior temporal cortex, whose damage is consistently associated with poor performance in action perception and understanding tasks across studies. Interestingly, these areas correspond to the three nodes of the action observation network that are strongly activated in response to visual action perception in neuroimaging research and that have been targeted in previous brain stimulation studies. Thus, brain lesion mapping research provides converging causal evidence that premotor, parietal and temporal regions play a crucial role in action recognition and understanding. PMID:24910603
Measuring Brain Connectivity: Diffusion Tensor Imaging Validates Resting State Temporal Correlations
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
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.
Beck, Anne; Wüstenberg, Torsten; Genauck, Alexander; Wrase, Jana; Schlagenhauf, Florian; Smolka, Michael N; Mann, Karl; Heinz, Andreas
2012-08-01
In alcohol-dependent patients, brain atrophy and functional brain activation elicited by alcohol-associated stimuli may predict relapse. However, to date, the interaction between both factors has not been studied. To determine whether results from structural and functional magnetic resonance imaging are associated with relapse in detoxified alcohol-dependent patients. A cue-reactivity functional magnetic resonance experiment with alcohol-associated and neutral stimuli. After a follow-up period of 3 months, the group of 46 detoxified alcohol-dependent patients was subdivided into 16 abstainers and 30 relapsers. Faculty for Clinical Medicine Mannheim at the University of Heidelberg, Germany. A total of 46 detoxified alcohol-dependent patients and 46 age- and sex-matched healthy control subjects Local gray matter volume, local stimulus-related functional magnetic resonance imaging activation, joint analyses of structural and functional data with Biological Parametric Mapping, and connectivity analyses adopting the psychophysiological interaction approach. Subsequent relapsers showed pronounced atrophy in the bilateral orbitofrontal cortex and in the right medial prefrontal and anterior cingulate cortex, compared with healthy controls and patients who remained abstinent. The local gray matter volume-corrected brain response elicited by alcohol-associated vs neutral stimuli in the left medial prefrontal cortex was enhanced for subsequent relapsers, whereas abstainers displayed an increased neural response in the midbrain (the ventral tegmental area extending into the subthalamic nucleus) and ventral striatum. For alcohol-associated vs neutral stimuli in abstainers compared with relapsers, the analyses of the psychophysiological interaction showed a stronger functional connectivity between the midbrain and the left amygdala and between the midbrain and the left orbitofrontal cortex. Subsequent relapsers displayed increased brain atrophy in brain areas associated with error monitoring and behavioral control. Correcting for gray matter reductions, we found that, in these patients, alcohol-related cues elicited increased activation in brain areas associated with attentional bias toward these cues and that, in patients who remained abstinent, increased activation and connectivity were observed in brain areas associated with processing of salient or aversive stimuli.
Brain systems underlying susceptibility to helplessness and depression.
Shumake, J; Gonzalez-Lima, F
2003-09-01
There has been a relative lack of research into the neurobiological predispositions that confer vulnerability to depression. This article reviews functional brain mappings from a genetic animal model, the congenitally helpless rat, which is predisposed to develop learned helplessness. Neurometabolic findings from this model are integrated with the neuroscientific literature from other animal models of depression as well as depressed humans. Changes in four major brain systems are suggested to underlie susceptibility to helplessness and possibly depression: (a) an unbalanced prefrontal-cingulate cortical system, (b) a dissociated hypothalamic-pituitary-adrenal axis, (c) a dissociated septal-hippocampal system, and (d) a hypoactive brain reward system, as exemplified by a hypermetabolic habenula-interpeduncular nucleus pathway and a hypometabolic ventral tegmental area-striatum pathway. Functional interconnections and causal relationships among these systems are considered and further experiments are suggested, with theoretical attention to how an abnormality in any one system could affect the others.
Imaging functional and structural brain connectomics in attention-deficit/hyperactivity disorder.
Cao, Miao; Shu, Ni; Cao, Qingjiu; Wang, Yufeng; He, Yong
2014-12-01
Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopment disorders in childhood. Clinically, the core symptoms of this disorder include inattention, hyperactivity, and impulsivity. Previous studies have documented that these behavior deficits in ADHD children are associated with not only regional brain abnormalities but also changes in functional and structural connectivity among regions. In the past several years, our understanding of how ADHD affects the brain's connectivity has been greatly advanced by mapping topological alterations of large-scale brain networks (i.e., connectomes) using noninvasive neurophysiological and neuroimaging techniques (e.g., electroencephalograph, functional MRI, and diffusion MRI) in combination with graph theoretical approaches. In this review, we summarize the recent progresses of functional and structural brain connectomics in ADHD, focusing on graphic analysis of large-scale brain systems. Convergent evidence suggests that children with ADHD had abnormal small-world properties in both functional and structural brain networks characterized by higher local clustering and lower global integrity, suggesting a disorder-related shift of network topology toward regular configurations. Moreover, ADHD children showed the redistribution of regional nodes and connectivity involving the default-mode, attention, and sensorimotor systems. Importantly, these ADHD-associated alterations significantly correlated with behavior disturbances (e.g., inattention and hyperactivity/impulsivity symptoms) and exhibited differential patterns between clinical subtypes. Together, these connectome-based studies highlight brain network dysfunction in ADHD, thus opening up a new window into our understanding of the pathophysiological mechanisms of this disorder. These works might also have important implications on the development of imaging-based biomarkers for clinical diagnosis and treatment evaluation in ADHD.
Mackey, Scott; Olafsson, Valur; Aupperle, Robin L; Lu, Kun; Fonzo, Greg A; Parnass, Jason; Liu, Thomas; Paulus, Martin P
2016-09-01
The significance of why a similar set of brain regions are associated with the default mode network and value-related neural processes remains to be clarified. Here, we examined i) whether brain regions exhibiting willingness-to-pay (WTP) task-related activity are intrinsically connected when the brain is at rest, ii) whether these regions overlap spatially with the default mode network, and iii) whether individual differences in choice behavior during the WTP task are reflected in functional brain connectivity at rest. Blood-oxygen-level dependent (BOLD) signal was measured by functional magnetic resonance imaging while subjects performed the WTP task and at rest with eyes open. Brain regions that tracked the value of bids during the WTP task were used as seed regions in an analysis of functional connectivity in the resting state data. The seed in the ventromedial prefrontal cortex was functionally connected to core regions of the WTP task-related network. Brain regions within the WTP task-related network, namely the ventral precuneus, ventromedial prefrontal and posterior cingulate cortex overlapped spatially with publically available maps of the default mode network. Also, those individuals with higher functional connectivity during rest between the ventromedial prefrontal cortex and the ventral striatum showed greater preference consistency during the WTP task. Thus, WTP task-related regions are an intrinsic network of the brain that corresponds spatially with the default mode network, and individual differences in functional connectivity within the WTP network at rest may reveal a priori biases in choice behavior.
Mackey, Scott; Olafsson, Valur; Aupperle, Robin; Lu, Kun; Fonzo, Greg; Parnass, Jason; Liu, Thomas; Paulus, Martin P.
2015-01-01
The significance of why a similar set of brain regions are associated with the default mode network and value-related neural processes remains to be clarified. Here, we examined i) whether brain regions exhibiting willingness-to-pay (WTP) task-related activity are intrinsically connected when the brain is at rest, ii) whether these regions overlap spatially with the default mode network, and iii) whether individual differences in choice behavior during the WTP task are reflected in functional brain connectivity at rest. Blood-oxygen-level dependent (BOLD) signal was measured by functional magnetic resonance imaging while subjects performed the WTP task and at rest with eyes open. Brain regions that tracked the value of bids during the WTP task were used as seed regions in an analysis of functional connectivity in the resting state data. The seed in the ventromedial prefrontal cortex was functionally connected to core regions of the WTP task-related network. Brain regions within the WTP task-related network, namely the ventral precuneus, ventromedial prefrontal and posterior cingulate cortex overlapped spatially with publically available maps of the default mode network. Also, those individuals with higher functional connectivity during rest between the ventromedial prefrontal cortex and the ventral striatum showed greater preference consistency during the WTP task. Thus, WTP task-related regions are an intrinsic network of the brain that corresponds spatially with the default mode network, and individual differences in functional connectivity within the WTP network at rest may reveal a priori biases in choice behavior. PMID:26271206
Comparing consistency of R2* and T2*-weighted BOLD analysis of resting state fetal fMRI
NASA Astrophysics Data System (ADS)
Seshamani, Sharmishtaa; Blazejewska, Anna I.; Gatenby, Christopher; Mckown, Susan; Caucutt, Jason; Dighe, Manjiri; Studholme, Colin
2015-03-01
Understanding when and how resting state brain functional activity begins in the human brain is an increasing area of interest in both basic neuroscience and in the clinical evaluation of the brain during pregnancy and after premature birth. Although fMRI studies have been carried out on pregnant women since the 1990's, reliable mapping of brain function in utero is an extremely challenging problem due to the unconstrained fetal head motion. Recent studies have employed scrubbing to exclude parts of the time series and whole subjects from studies in order to control the confounds of motion. Fundamentally, even after correction of the location of signals due to motion, signal intensity variations are a fundamental limitation, due to coil sensitivity and spin history effects. An alternative technique is to use a more parametric MRI signal derived from multiple echoes that provides a level of independence from basic MRI signal variation. Here we examine the use of R2* mapping combined with slice based multi echo geometric distortion correction for in-utero studies. The challenges for R2* mapping arise from the relatively low signal strength of in-utero data. In this paper we focus on comparing activation detection in-utero using T2W and R2* approaches. We make use a subset of studies with relatively limited motion to compare the activation patterns without the additional confound of significant motion. Results at different gestational ages indicate comparable agreement in many activation patterns when limited motion is present, and the detection of some additional networks in the R2* data, not seen in the T2W results.
Structural and Maturational Covariance in Early Childhood Brain Development.
Geng, Xiujuan; Li, Gang; Lu, Zhaohua; Gao, Wei; Wang, Li; Shen, Dinggang; Zhu, Hongtu; Gilmore, John H
2017-03-01
Brain structural covariance networks (SCNs) composed of regions with correlated variation are altered in neuropsychiatric disease and change with age. Little is known about the development of SCNs in early childhood, a period of rapid cortical growth. We investigated the development of structural and maturational covariance networks, including default, dorsal attention, primary visual and sensorimotor networks in a longitudinal population of 118 children after birth to 2 years old and compared them with intrinsic functional connectivity networks. We found that structural covariance of all networks exhibit strong correlations mostly limited to their seed regions. By Age 2, default and dorsal attention structural networks are much less distributed compared with their functional maps. The maturational covariance maps, however, revealed significant couplings in rates of change between distributed regions, which partially recapitulate their functional networks. The structural and maturational covariance of the primary visual and sensorimotor networks shows similar patterns to the corresponding functional networks. Results indicate that functional networks are in place prior to structural networks, that correlated structural patterns in adult may arise in part from coordinated cortical maturation, and that regional co-activation in functional networks may guide and refine the maturation of SCNs over childhood development. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Functional imaging with low-resolution brain electromagnetic tomography (LORETA): a review.
Pascual-Marqui, R D; Esslen, M; Kochi, K; Lehmann, D
2002-01-01
This paper reviews several recent publications that have successfully used the functional brain imaging method known as LORETA. Emphasis is placed on the electrophysiological and neuroanatomical basis of the method, on the localization properties of the method, and on the validation of the method in real experimental human data. Papers that criticize LORETA are briefly discussed. LORETA publications in the 1994-1997 period based localization inference on images of raw electric neuronal activity. In 1998, a series of papers appeared that based localization inference on the statistical parametric mapping methodology applied to high-time resolution LORETA images. Starting in 1999, quantitative neuroanatomy was added to the methodology, based on the digitized Talairach atlas provided by the Brain Imaging Centre, Montreal Neurological Institute. The combination of these methodological developments has placed LORETA at a level that compares favorably to the more classical functional imaging methods, such as PET and fMRI.
Whole-brain activity maps reveal stereotyped, distributed networks for visuomotor behavior
Portugues, Ruben; Feierstein, Claudia E.; Engert, Florian; Orger, Michael B.
2014-01-01
Summary Most behaviors, even simple innate reflexes, are mediated by circuits of neurons spanning areas throughout the brain. However, in most cases, the distribution and dynamics of firing patterns of these neurons during behavior are not known. We imaged activity, with cellular resolution, throughout the whole brains of zebrafish performing the optokinetic response. We found a sparse, broadly distributed network that has an elaborate, but ordered, pattern, with a bilaterally symmetrical organization. Activity patterns fell into distinct clusters reflecting sensory and motor processing. By correlating neuronal responses with an array of sensory and motor variables, we find that the network can be clearly divided into distinct functional modules. Comparing aligned data from multiple fish, we find that the spatiotemporal activity dynamics and functional organization are highly stereotyped across individuals. These experiments reveal, for the first time in a vertebrate, the comprehensive functional architecture of the neural circuits underlying a sensorimotor behavior. PMID:24656252
The Specialization of Function: Cognitive and Neural Perspectives
Mahon, Bradford Z.; Cantlon, Jessica F.
2014-01-01
A unifying theme that cuts across all research areas and techniques in the cognitive and brain sciences is whether there is specialization of function at levels of processing that are ‘abstracted away’ from sensory inputs and motor outputs. Any theory that articulates claims about specialization of function in the mind/brain confronts the following types of interrelated questions, each of which carries with it certain theoretical commitments. What methods are appropriate for decomposing complex cognitive and neural processes into their constituent parts? How do cognitive processes map onto neural processes, and at what resolution are they related? What types of conclusions can be drawn about the structure of mind from dissociations observed at the neural level, and vice versa? The contributions that form this Special Issue of Cognitive Neuropsychology represent recent reflections on these and other issues from leading researchers in different areas of the cognitive and brain sciences. PMID:22185234
Cao, Shenglong; Hua, Ya; Keep, Richard F; Chaudhary, Neeraj; Xi, Guohua
2018-04-01
Brain iron overload is a key factor causing brain injury after intracerebral hemorrhage (ICH). This study quantified brain iron levels after ICH with magnetic resonance imaging R2* mapping. The effect of minocycline on iron overload and ICH-induced brain injury in aged rats was also determined. Aged (18 months old) male Fischer 344 rats had an intracerebral injection of autologous blood or saline, and brain iron levels were measured by magnetic resonance imaging R2* mapping. Some ICH rats were treated with minocycline or vehicle. The rats were euthanized at days 7 and 28 after ICH, and brains were used for immunohistochemistry and Western blot analyses. Magnetic resonance imaging (T2-weighted, T2* gradient-echo, and R2* mapping) sequences were performed at different time points. ICH-induced brain iron overload in the perihematomal area could be quantified by R2* mapping. Minocycline treatment reduced brain iron accumulation, T2* lesion volume, iron-handling protein upregulation, neuronal cell death, and neurological deficits ( P <0.05). Magnetic resonance imaging R2* mapping is a reliable and noninvasive method, which can quantitatively measure brain iron levels after ICH. Minocycline reduced ICH-related perihematomal iron accumulation and brain injury in aged rats. © 2018 American Heart Association, Inc.
Investigating the Efficacy of Novel TrkB Agonists to Augment Stroke Recovery
NASA Astrophysics Data System (ADS)
Warraich, Zuha
Stroke remains the leading cause of adult disability in developed countries. Most survivors live with residual motor impairments that severely diminish independence and quality of life. After stroke, the only accepted treatment for these patients is motor rehabilitation. However, the amount and kind of rehabilitation required to induce clinically significant improvements in motor function is rarely given due to the constraints of our current health care system. Research reported in this dissertation contributes towards developing adjuvant therapies that may augment the impact of motor rehabilitation and improve functional outcome. These studies have demonstrated reorganization of maps within motor cortex as a function of experience in both healthy and brain-injured animals by using intracortical microstimulation technique. Furthermore, synaptic plasticity has been identified as a key neural mechanism in directing motor map plasticity, evidenced by restoration of movement representations within the spared cortical tissue accompanied by increase in synapse number translating into motor improvement after stroke. There is increasing evidence that brain-derived neurotrophic factor (BDNF) modulates synaptic and morphological plasticity in the developing and mature nervous system. Unfortunately, BDNF itself is a poor candidate because of its short half-life, low penetration through the blood brain barrier, and activating multiple receptor units, p75 and TrkB on the neuronal membrane. In order to circumvent this problem efficacy of two recently developed novel TrkB agonists, LM22A-4 and 7,8-dihydroxyflavone, that actively penetrate the blood brain barrier and enhance functional recovery. Findings from these dissertation studies indicate that administration of these pharmacological compounds, accompanied by motor rehabilitation provide a powerful therapeutic tool for stroke recovery.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Elrod, D.W.
1992-01-01
Computational neural networks (CNNs) are a computational paradigm inspired by the brain's massively parallel network of highly interconnected neurons. The power of computational neural networks derives not so much from their ability to model the brain as from their ability to learn by example and to map highly complex, nonlinear functions, without the need to explicitly specify the functional relationship. Two central questions about CNNs were investigated in the context of predicting chemical reactions: (1) the mapping properties of neural networks and (2) the representation of chemical information for use in CNNs. Chemical reactivity is here considered an example ofmore » a complex, nonlinear function of molecular structure. CNN's were trained using modifications of the back propagation learning rule to map a three dimensional response surface similar to those typically observed in quantitative structure-activity and structure-property relationships. The computational neural network's mapping of the response surface was found to be robust to the effects of training sample size, noisy data and intercorrelated input variables. The investigation of chemical structure representation led to the development of a molecular structure-based connection-table representation suitable for neural network training. An extension of this work led to a BE-matrix structure representation that was found to be general for several classes of reactions. The CNN prediction of chemical reactivity and regiochemistry was investigated for electrophilic aromatic substitution reactions, Markovnikov addition to alkenes, Saytzeff elimination from haloalkanes, Diels-Alder cycloaddition, and retro Diels-Alder ring opening reactions using these connectivity-matrix derived representations. The reaction predictions made by the CNNs were more accurate than those of an expert system and were comparable to predictions made by chemists.« less
Kia, Seyed Mostafa; Vega Pons, Sandro; Weisz, Nathan; Passerini, Andrea
2016-01-01
Brain decoding is a popular multivariate approach for hypothesis testing in neuroimaging. Linear classifiers are widely employed in the brain decoding paradigm to discriminate among experimental conditions. Then, the derived linear weights are visualized in the form of multivariate brain maps to further study spatio-temporal patterns of underlying neural activities. It is well known that the brain maps derived from weights of linear classifiers are hard to interpret because of high correlations between predictors, low signal to noise ratios, and the high dimensionality of neuroimaging data. Therefore, improving the interpretability of brain decoding approaches is of primary interest in many neuroimaging studies. Despite extensive studies of this type, at present, there is no formal definition for interpretability of multivariate brain maps. As a consequence, there is no quantitative measure for evaluating the interpretability of different brain decoding methods. In this paper, first, we present a theoretical definition of interpretability in brain decoding; we show that the interpretability of multivariate brain maps can be decomposed into their reproducibility and representativeness. Second, as an application of the proposed definition, we exemplify a heuristic for approximating the interpretability in multivariate analysis of evoked magnetoencephalography (MEG) responses. Third, we propose to combine the approximated interpretability and the generalization performance of the brain decoding into a new multi-objective criterion for model selection. Our results, for the simulated and real MEG data, show that optimizing the hyper-parameters of the regularized linear classifier based on the proposed criterion results in more informative multivariate brain maps. More importantly, the presented definition provides the theoretical background for quantitative evaluation of interpretability, and hence, facilitates the development of more effective brain decoding algorithms in the future.
Kia, Seyed Mostafa; Vega Pons, Sandro; Weisz, Nathan; Passerini, Andrea
2017-01-01
Brain decoding is a popular multivariate approach for hypothesis testing in neuroimaging. Linear classifiers are widely employed in the brain decoding paradigm to discriminate among experimental conditions. Then, the derived linear weights are visualized in the form of multivariate brain maps to further study spatio-temporal patterns of underlying neural activities. It is well known that the brain maps derived from weights of linear classifiers are hard to interpret because of high correlations between predictors, low signal to noise ratios, and the high dimensionality of neuroimaging data. Therefore, improving the interpretability of brain decoding approaches is of primary interest in many neuroimaging studies. Despite extensive studies of this type, at present, there is no formal definition for interpretability of multivariate brain maps. As a consequence, there is no quantitative measure for evaluating the interpretability of different brain decoding methods. In this paper, first, we present a theoretical definition of interpretability in brain decoding; we show that the interpretability of multivariate brain maps can be decomposed into their reproducibility and representativeness. Second, as an application of the proposed definition, we exemplify a heuristic for approximating the interpretability in multivariate analysis of evoked magnetoencephalography (MEG) responses. Third, we propose to combine the approximated interpretability and the generalization performance of the brain decoding into a new multi-objective criterion for model selection. Our results, for the simulated and real MEG data, show that optimizing the hyper-parameters of the regularized linear classifier based on the proposed criterion results in more informative multivariate brain maps. More importantly, the presented definition provides the theoretical background for quantitative evaluation of interpretability, and hence, facilitates the development of more effective brain decoding algorithms in the future. PMID:28167896
From brain maps to cognitive ontologies: informatics and the search for mental structure
Poldrack, Russell A.; Yarkoni, Tal
2015-01-01
A major goal of cognitive neuroscience is to delineate how brain systems give rise to mental function. Here we review the increasingly large role informatics-driven approaches are playing in such efforts. We begin by reviewing a number of challenges conventional neuroimaging approaches face in trying to delineate brain-cognition mappings—for example, the difficulty in establishing the specificity of postulated associations. Next, we demonstrate how these limitations can potentially be overcome using complementary approaches that emphasize large-scale analysis—including meta-analytic methods that synthesize hundreds or thousands of studies at a time; latent-variable approaches that seek to extract structure from data in a bottom-up manner; and predictive modeling approaches capable of quantitatively inferring mental states from patterns of brain activity. We highlight the underappreciated but critical role for formal cognitive ontologies in helping to clarify, refine, and test theories of brain and cognitive function. Finally, we conclude with a speculative discussion of what future informatics developments may hold for cognitive neuroscience. PMID:26393866
Effect of Experimental Thyrotoxicosis on Brain Gray Matter: A Voxel-Based Morphometry Study.
Göbel, Anna; Heldmann, Marcus; Göttlich, Martin; Dirk, Anna-Luise; Brabant, Georg; Münte, Thomas F
2015-09-01
Hyper-as well hypothyroidism have an effect on behavior and brain function. Moreover, during development thyroid hormones influence brain structure. This study aimed to demonstrate an effect of experimentally induced hyperthyroidism on brain gray matter in healthy adult humans. High-resolution 3D T1-weighted images were acquired in 29 healthy young subjects prior to as well as after receiving 250 µg of T4 per day for 8 weeks. Voxel-based morphometry analysis was performed using Statistical Parametric Mapping 8 (SPM8). Laboratory testing confirmed the induction of hyperthyroidism. In the hyperthyroid condition, gray matter volumes were increased in the right posterior cerebellum (lobule VI) and decreased in the bilateral visual cortex and anterior cerebellum (lobules I-IV) compared to the euthyroid condition. Our study provides evidence that short periods of hyperthyroidism induce distinct alterations in brain structures of cerebellar regions that have been associated with sensorimotor functions as well as working memory in the literature.
Genomic distribution and possible functions of DNA hydroxymethylation in the brain.
Wen, Lu; Tang, Fuchou
2014-11-01
DNA methylation (5-methylcytosine, 5mC) is involved in many cellular processes and emerges as an important epigenetic player in brain development and memory formation. The recent discovery that 5mC can be oxidized to 5-hydroxymethylcytosine (5hmC) by TET (Ten-Eleven-Translocation) proteins provides novel insights into the dynamic character of 5mC in the brain. The content of 5hmC is remarkably high in the brain, adding further complexity. In this review, we discuss how recent advances have improved our understanding of the possible biological roles of 5hmC and TET proteins in the brain. These advances attribute to various approaches, including the genome-wide approach to map 5hmC in different genomic contexts, the gene knockout/knockdown approach to elucidate the functions of TET proteins and 5hmC, and the biochemical approach to uncover potential 5hmC readers. Copyright © 2014 Elsevier Inc. All rights reserved.
Yu, Qiang; Reutens, David; O'Brien, Kieran; Vegh, Viktor
2017-02-01
Tissue microstructure features, namely axon radius and volume fraction, provide important information on the function of white matter pathways. These parameters vary on the scale much smaller than imaging voxels (microscale) yet influence the magnetic resonance imaging diffusion signal at the image voxel scale (macroscale) in an anomalous manner. Researchers have already mapped anomalous diffusion parameters from magnetic resonance imaging data, but macroscopic variations have not been related to microscale influences. With the aid of a tissue model, we aimed to connect anomalous diffusion parameters to axon radius and volume fraction using diffusion-weighted magnetic resonance imaging measurements. An ex vivo human brain experiment was performed to directly validate axon radius and volume fraction measurements in the human brain. These findings were validated using electron microscopy. Additionally, we performed an in vivo study on nine healthy participants to map axon radius and volume fraction along different regions of the corpus callosum projecting into various cortical areas identified using tractography. We found a clear relationship between anomalous diffusion parameters and axon radius and volume fraction. We were also able to map accurately the trend in axon radius along the corpus callosum, and in vivo findings resembled the low-high-low-high behaviour in axon radius demonstrated previously. Axon radius and volume fraction measurements can potentially be used in brain connectivity studies and to understand the implications of white matter structure in brain diseases and disorders. Hum Brain Mapp 38:1068-1081, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
White Matter Fiber-based Analysis of T1w/T2w Ratio Map.
Chen, Haiwei; Budin, Francois; Noel, Jean; Prieto, Juan Carlos; Gilmore, John; Rasmussen, Jerod; Wadhwa, Pathik D; Entringer, Sonja; Buss, Claudia; Styner, Martin
2017-02-01
To develop, test, evaluate and apply a novel tool for the white matter fiber-based analysis of T1w/T2w ratio maps quantifying myelin content. The cerebral white matter in the human brain develops from a mostly non-myelinated state to a nearly fully mature white matter myelination within the first few years of life. High resolution T1w/T2w ratio maps are believed to be effective in quantitatively estimating myelin content on a voxel-wise basis. We propose the use of a fiber-tract-based analysis of such T1w/T2w ratio data, as it allows us to separate fiber bundles that a common regional analysis imprecisely groups together, and to associate effects to specific tracts rather than large, broad regions. We developed an intuitive, open source tool to facilitate such fiber-based studies of T1w/T2w ratio maps. Via its Graphical User Interface (GUI) the tool is accessible to non-technical users. The framework uses calibrated T1w/T2w ratio maps and a prior fiber atlas as an input to generate profiles of T1w/T2w values. The resulting fiber profiles are used in a statistical analysis that performs along-tract functional statistical analysis. We applied this approach to a preliminary study of early brain development in neonates. We developed an open-source tool for the fiber based analysis of T1w/T2w ratio maps and tested it in a study of brain development.
White matter fiber-based analysis of T1w/T2w ratio map
NASA Astrophysics Data System (ADS)
Chen, Haiwei; Budin, Francois; Noel, Jean; Prieto, Juan Carlos; Gilmore, John; Rasmussen, Jerod; Wadhwa, Pathik D.; Entringer, Sonja; Buss, Claudia; Styner, Martin
2017-02-01
Purpose: To develop, test, evaluate and apply a novel tool for the white matter fiber-based analysis of T1w/T2w ratio maps quantifying myelin content. Background: The cerebral white matter in the human brain develops from a mostly non-myelinated state to a nearly fully mature white matter myelination within the first few years of life. High resolution T1w/T2w ratio maps are believed to be effective in quantitatively estimating myelin content on a voxel-wise basis. We propose the use of a fiber-tract-based analysis of such T1w/T2w ratio data, as it allows us to separate fiber bundles that a common regional analysis imprecisely groups together, and to associate effects to specific tracts rather than large, broad regions. Methods: We developed an intuitive, open source tool to facilitate such fiber-based studies of T1w/T2w ratio maps. Via its Graphical User Interface (GUI) the tool is accessible to non-technical users. The framework uses calibrated T1w/T2w ratio maps and a prior fiber atlas as an input to generate profiles of T1w/T2w values. The resulting fiber profiles are used in a statistical analysis that performs along-tract functional statistical analysis. We applied this approach to a preliminary study of early brain development in neonates. Results: We developed an open-source tool for the fiber based analysis of T1w/T2w ratio maps and tested it in a study of brain development.
Bolton, Thomas A W; Jochaut, Delphine; Giraud, Anne-Lise; Van De Ville, Dimitri
2018-06-01
To refine our understanding of autism spectrum disorders (ASD), studies of the brain in dynamic, multimodal and ecological experimental settings are required. One way to achieve this is to compare the neural responses of ASD and typically developing (TD) individuals when viewing a naturalistic movie, but the temporal complexity of the stimulus hampers this task, and the presence of intrinsic functional connectivity (FC) may overshadow movie-driven fluctuations. Here, we detected inter-subject functional correlation (ISFC) transients to disentangle movie-induced functional changes from underlying resting-state activity while probing FC dynamically. When considering the number of significant ISFC excursions triggered by the movie across the brain, connections between remote functional modules were more heterogeneously engaged in the ASD population. Dynamically tracking the temporal profiles of those ISFC changes and tying them to specific movie subparts, this idiosyncrasy in ASD responses was then shown to involve functional integration and segregation mechanisms such as response inhibition, background suppression, or multisensory integration, while low-level visual processing was spared. Through the application of a new framework for the study of dynamic experimental paradigms, our results reveal a temporally localized idiosyncrasy in ASD responses, specific to short-lived episodes of long-range functional interplays. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
Optical mapping of the brain activity in children with Down's syndrome
NASA Astrophysics Data System (ADS)
Yuan, Zhen; Lu, Fengmei
2018-02-01
Down's syndrome (DS) has been shown to be associated with many neurological complications, including cognitive deficits, seizures, early-onset dementia that resembles Alzheimer's disease, and neurological complications of systemic disorders. DS patients show to have poor performance in executive functions (EF) and fine motor skills. In this study, we examined the brain hemodynamic responses and brain activation patterns of DS children during the completion of EF tasks. Revealing its neural mechanism of DS is not only able to contribute to the early intervention of this children with DS, but also increase understanding of developmental cascades in childhood.
NASA Astrophysics Data System (ADS)
Nelson, G. A.; Cns Nscor Team
A new NASA-sponsored program project (NSCOR) has been organized to conduct the first comprehensive investigation of the response of a mammalian brain structure (mouse hippocampus) to charged-particle radiation. The NSCOR collaboration has three main goals. The first goal is to quantify the time- and dose-dependent changes in cellular composition and architecture. By using stereology on preserved brains, subsets of cells (neurons, glia, endothelia and stem cells) will be quantified out to 2 years after irradiation with accelerated protons and iron ions. To further characterize changes in vasculature architecture a polymer infusion technique will be used to produce a three-dimensional vasculature cast that then will be mapped by x-ray tomography to determine topological changes, and microscopic infarcts associated with amyloid protein deposits. The 2nd goal is to quantify hippocampal function(s). The primary measurement of function will be extracellular electrical recordings from hippocampal ``brain slices'' that reflect underlying functions such as connectivity, action potential generation & conduction, and neurotransmitter formation, secretion, and uptake. Individual nerve membrane properties will be assessed by ``patch clamp'' recordings. Two non-invasive methods will evaluate brain function and the evolution of changes with time. Electroencephalograms will map macroscopic spontaneous electrical activity while two state-of-the-art MRI magnetization sequences will visualize and quantify local oxygen utilization and white matter fiber tracts structural integrity. To quantify the brains' overall performance under stress, animals will receive a systemic shock mediated by the immune system in the form of a reaction to lipopolysaccharide. A second strategy will employ the APP23 transgenic mouse that develops the pathological changes associated with Alzheimer's disease. Measurements of irradiated mice will determine whether radiation exposure affects the latency and severity of the disease-associated pathological changes. The third goal is to quantify molecular markers that underly cellular and system changes. The team will quantify the frequency and structural spectrum of mutations in hippocampal samples using the E. coli β -galactosidase gene present in a transgenic mouse's tissues. Finally, by using transcription profiling hybridization, the status of a set of 96 genes involved in cytokine signaling during inflammation will be assessed.
Nakayama, N; Okumura, A; Shinoda, J; Nakashima, T; Iwama, T
2006-07-01
The cerebral metabolism of patients in the chronic stage of traumatic diffuse brain injury (TDBI) has not been fully investigated. To study the relationship between regional cerebral metabolism (rCM) and consciousness disturbance in patients with TDBI. 52 patients with TDBI in the chronic stage without large focal lesions were enrolled, and rCM was evaluated by fluorine-18-fluorodeoxyglucose positron emission tomography (FDG-PET) with statistical parametric mapping (SPM). All the patients were found to have disturbed consciousness or cognitive function and were divided into the following three groups: group A (n = 22), patients in a state with higher brain dysfunction; group B (n = 13), patients in a minimally conscious state; and group C (n = 17), patients in a vegetative state. rCM patterns on FDG-PET among these groups were evaluated and compared with those of normal control subjects on statistical parametric maps. Hypometabolism was consistently indicated bilaterally in the medial prefrontal regions, the medial frontobasal regions, the cingulate gyrus and the thalamus. Hypometabolism in these regions was the most widespread and prominent in group C, and that in group B was more widespread and prominent than that in group A. Bilateral hypometabolism in the medial prefrontal regions, the medial frontobasal regions, the cingulate gyrus and the thalamus may reflect the clinical deterioration of TDBI, which is due to functional and structural disconnections of neural networks rather than due to direct cerebral focal contusion.
In situ FTIR microspectroscopy of extravasated blood-damaged brain tissue
NASA Astrophysics Data System (ADS)
Wetzel, David L.; Le Vine, Steven M.
1994-01-01
Fourier transform infrared (FT-IR) microspectroscopy enables the collection of infrared spectra from microscopic regions of tissue sections. The objectives of this study were to utilize FT-IR microspectroscopy to analyze the spatial distribution of chemical changes that result from the extravasation of blood into the brain and to determine if products of free radical damage are associated with the damaged areas. An animal model that involves the injection of blood into the white matter of rat brains was used. Maps depicting the relative concentrations of chemical functional groups of lesioned sites and surrounding areas were made. Significant decreases were observed for CH2, C equals O, P equals O, and HO-C-H functional groups at the lesioned site and penumbra regions compared to the neighboring normal tissue areas.
atonal regulates neurite arborization but does not act as a proneural gene in the Drosophila brain
NASA Technical Reports Server (NTRS)
Hassan, B. A.; Bermingham, N. A.; He, Y.; Sun, Y.; Jan, Y. N.; Zoghbi, H. Y.; Bellen, H. J.
2000-01-01
Drosophila atonal (ato) is the proneural gene of the chordotonal organs (CHOs) in the peripheral nervous system (PNS) and the larval and adult photoreceptor organs. Here, we show that ato is expressed at multiple stages during the development of a lineage of central brain neurons that innervate the optic lobes and are required for eclosion. A novel fate mapping approach shows that ato is expressed in the embryonic precursors of these neurons and that its expression is reactivated in third instar larvae (L3). In contrast to its function in the PNS, ato does not act as a proneural gene in the embryonic brain. Instead, ato performs a novel function, regulating arborization during larval and pupal development by interacting with Notch.
Women's clitoris, vagina and cervix mapped on the sensory cortex: fMRI evidence
Komisaruk, Barry R.; Wise, Nan; Frangos, Eleni; Liu, Wen-Ching; Allen, Kachina; Brody, Stuart
2011-01-01
Introduction The projection of vagina, uterine cervix, and nipple to the sensory cortex in humans has not been reported. Aims To map the sensory cortical fields of the clitoris, vagina, cervix and nipple, toward an elucidation of the neural systems underlying sexual response. Methods Using functional Magnetic Resonance Imaging (fMRI) we mapped sensory cortical responses to clitoral, vaginal, cervical, and nipple self-stimulation. For points of reference on the homunculus, we also mapped responses to the thumb and great toe (hallux) stimulation. Main Outcome Measures fMRI of brain regions activated by the various sensory stimuli. Results Clitoral, vaginal, and cervical self-stimulation activate differentiable sensory cortical regions, all clustered in the medial cortex (medial paracentral lobule). Nipple self-stimulation activated the genital sensory cortex (as well as the thoracic) region of the homuncular map. Conclusion The genital sensory cortex, identified in the classical Penfield homunculus based on electrical stimulation of the brain only in men, was confirmed for the first time in the literature by the present study in women, applying clitoral, vaginal, and cervical self-stimulation, and observing their regional brain responses using fMRI. Vaginal, clitoral, and cervical regions of activation were differentiable, consistent with innervation by different afferent nerves and different behavioral correlates. Activation of the genital sensory cortex by nipple self-stimulation was unexpected, but suggests a neurological basis for women’s reports of its erotogenic quality. PMID:21797981
HDAC6 Brain Mapping with [ 18 F]Bavarostat Enabled by a Ru-Mediated Deoxyfluorination
DOE Office of Scientific and Technical Information (OSTI.GOV)
Strebl, Martin G.; Campbell, Arthur J.; Zhao, Wen -Ning
Histone deacetylase 6 (HDAC6) function and dysregulation have been implicated in the etiology of certain cancers and more recently in central nervous system (CNS) disorders including Rett syndrome, Alzheimer’s and Parkinson’s diseases, and major depressive disorder. HDAC6-selective inhibitors have therapeutic potential, but in the CNS drug space the development of highly brain penetrant HDAC inhibitors has been a persistent challenge. Moreover, no tool exists to directly characterize HDAC6 and its related biology in the living human brain. Here, we report a highly brain penetrant HDAC6 inhibitor, Bavarostat, that exhibits excellent HDAC6 selectivity (>80-fold over all other Zn-containing HDAC paralogues), modulatesmore » tubulin acetylation selectively over histone acetylation, and has excellent brain penetrance. We further demonstrate that Bavarostat can be radiolabeled with 18F by deoxyfluorination through in situ formation of a ruthenium π-complex of the corresponding phenol precursor: the only method currently suitable for synthesis of [ 18F]Bavarostat. In conclusion, by using [ 18F]Bavarostat in a series of rodent and nonhuman primate imaging experiments, we demonstrate its utility for mapping HDAC6 in the living brain, which sets the stage for first-in-human neurochemical imaging of this important target.« less
HDAC6 Brain Mapping with [ 18 F]Bavarostat Enabled by a Ru-Mediated Deoxyfluorination
Strebl, Martin G.; Campbell, Arthur J.; Zhao, Wen -Ning; ...
2017-09-06
Histone deacetylase 6 (HDAC6) function and dysregulation have been implicated in the etiology of certain cancers and more recently in central nervous system (CNS) disorders including Rett syndrome, Alzheimer’s and Parkinson’s diseases, and major depressive disorder. HDAC6-selective inhibitors have therapeutic potential, but in the CNS drug space the development of highly brain penetrant HDAC inhibitors has been a persistent challenge. Moreover, no tool exists to directly characterize HDAC6 and its related biology in the living human brain. Here, we report a highly brain penetrant HDAC6 inhibitor, Bavarostat, that exhibits excellent HDAC6 selectivity (>80-fold over all other Zn-containing HDAC paralogues), modulatesmore » tubulin acetylation selectively over histone acetylation, and has excellent brain penetrance. We further demonstrate that Bavarostat can be radiolabeled with 18F by deoxyfluorination through in situ formation of a ruthenium π-complex of the corresponding phenol precursor: the only method currently suitable for synthesis of [ 18F]Bavarostat. In conclusion, by using [ 18F]Bavarostat in a series of rodent and nonhuman primate imaging experiments, we demonstrate its utility for mapping HDAC6 in the living brain, which sets the stage for first-in-human neurochemical imaging of this important target.« less
D'Ambrosio, Alessandro; Pagani, Elisabetta; Riccitelli, Gianna C; Colombo, Bruno; Rodegher, Mariaemma; Falini, Andrea; Comi, Giancarlo; Filippi, Massimo; Rocca, Maria A
2017-08-01
To investigate the role of cerebellar sub-regions on motor and cognitive performance in multiple sclerosis (MS) patients. Whole and sub-regional cerebellar volumes, brain volumes, T2 hyperintense lesion volumes (LV), and motor performance scores were obtained from 95 relapse-onset MS patients and 32 healthy controls (HC). MS patients also underwent an evaluation of working memory and processing speed functions. Cerebellar anterior and posterior lobes were segmented using the Spatially Unbiased Infratentorial Toolbox (SUIT) from Statistical Parametric Mapping (SPM12). Multivariate linear regression models assessed the relationship between magnetic resonance imaging (MRI) measures and motor/cognitive scores. Compared to HC, only secondary progressive multiple sclerosis (SPMS) patients had lower cerebellar volumes (total and posterior cerebellum). In MS patients, lower anterior cerebellar volume and brain T2 LV predicted worse motor performance, whereas lower posterior cerebellar volume and brain T2 LV predicted poor cognitive performance. Global measures of brain volume and infratentorial T2 LV were not selected by the final multivariate models. Cerebellar volumetric abnormalities are likely to play an important contribution to explain motor and cognitive performance in MS patients. Consistently with functional mapping studies, cerebellar posterior-inferior volume accounted for variance in cognitive measures, whereas anterior cerebellar volume accounted for variance in motor performance, supporting the assessment of cerebellar damage at sub-regional level.
Jaspers, Ellen; Balsters, Joshua H; Kassraian Fard, Pegah; Mantini, Dante; Wenderoth, Nicole
2017-03-01
Over the last decade, structure-function relationships have begun to encompass networks of brain areas rather than individual structures. For example, corticostriatal circuits have been associated with sensorimotor, limbic, and cognitive information processing, and damage to these circuits has been shown to produce unique behavioral outcomes in Autism, Parkinson's Disease, Schizophrenia and healthy ageing. However, it remains an open question how abnormal or absent connectivity can be detected at the individual level. Here, we provide a method for clustering gross morphological structures into subregions with unique functional connectivity fingerprints, and generate network probability maps usable as a baseline to compare individual cases against. We used connectivity metrics derived from resting-state fMRI (N = 100), in conjunction with hierarchical clustering methods, to parcellate the striatum into functionally distinct clusters. We identified three highly reproducible striatal subregions, across both hemispheres and in an independent replication dataset (N = 100) (dice-similarity values 0.40-1.00). Each striatal seed region resulted in a highly reproducible distinct connectivity fingerprint: the putamen showed predominant connectivity with cortical and cerebellar sensorimotor and language processing areas; the ventromedial striatum cluster had a distinct limbic connectivity pattern; the caudate showed predominant connectivity with the thalamus, frontal and occipital areas, and the cerebellum. Our corticostriatal probability maps agree with existing connectivity data in humans and non-human primates, and showed a high degree of replication. We believe that these maps offer an efficient tool to further advance hypothesis driven research and provide important guidance when investigating deviant connectivity in neurological patient populations suffering from e.g., stroke or cerebral palsy. Hum Brain Mapp 38:1478-1491, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Spatial working memory in heavy cannabis users: a functional magnetic resonance imaging study.
Kanayama, Gen; Rogowska, Jadwiga; Pope, Harrison G; Gruber, Staci A; Yurgelun-Todd, Deborah A
2004-11-01
Many neuropsychological studies have documented deficits in working memory among recent heavy cannabis users. However, little is known about the effects of cannabis on brain activity. We assessed brain function among recent heavy cannabis users while they performed a working memory task. Functional magnetic resonance imaging was used to examine brain activity in 12 long-term heavy cannabis users, 6-36 h after last use, and in 10 control subjects while they performed a spatial working memory task. Regional brain activation was analyzed and compared using statistical parametric mapping techniques. Compared with controls, cannabis users exhibited increased activation of brain regions typically used for spatial working memory tasks (such as prefrontal cortex and anterior cingulate). Users also recruited additional regions not typically used for spatial working memory (such as regions in the basal ganglia). These findings remained essentially unchanged when re-analyzed using subjects' ages as a covariate. Brain activation showed little or no significant correlation with subjects' years of education, verbal IQ, lifetime episodes of cannabis use, or urinary cannabinoid levels at the time of scanning. Recent cannabis users displayed greater and more widespread brain activation than normal subjects when attempting to perform a spatial working memory task. This observation suggests that recent cannabis users may experience subtle neurophysiological deficits, and that they compensate for these deficits by "working harder"-calling upon additional brain regions to meet the demands of the task.
Osmanski, Bruno-Félix; Pezet, Sophie; Ricobaraza, Ana; Lenkei, Zsolt; Tanter, Mickael
2014-01-01
Long-range coherences in spontaneous brain activity reflect functional connectivity. Here we propose a novel, highly resolved connectivity mapping approach, using ultrafast functional ultrasound (fUS), which enables imaging of cerebral microvascular haemodynamics deep in the anaesthetized rodent brain, through a large thinned-skull cranial window, with pixel dimensions of 100 μm × 100 μm in-plane. The millisecond-range temporal resolution allows unambiguous cancellation of low-frequency cardio-respiratory noise. Both seed-based and singular value decomposition analysis of spatial coherences in the low-frequency (<0.1 Hz) spontaneous fUS signal fluctuations reproducibly report, at different coronal planes, overlapping high-contrast, intrinsic functional connectivity patterns. These patterns are similar to major functional networks described in humans by resting-state fMRI, such as the lateral task-dependent network putatively anticorrelated with the midline default-mode network. These results introduce fUS as a powerful novel neuroimaging method, which could be extended to portable systems for three-dimensional functional connectivity imaging in awake and freely moving rodents. PMID:25277668
Huang, Huiyuan; Ding, Zhongxiang; Mao, Dewang; Yuan, Jianhua; Zhu, Fangmei; Chen, Shuda; Xu, Yan; Lou, Lin; Feng, Xiaoyan; Qi, Le; Qiu, Wusi; Zhang, Han; Zang, Yu-Feng
2016-10-01
The main goal of brain tumor surgery is to maximize tumor resection while minimizing the risk of irreversible postoperative functional sequelae. Eloquent functional areas should be delineated preoperatively, particularly for patients with tumors near eloquent areas. Functional magnetic resonance imaging (fMRI) is a noninvasive technique that demonstrates great promise for presurgical planning. However, specialized data processing toolkits for presurgical planning remain lacking. Based on several functions in open-source software such as Statistical Parametric Mapping (SPM), Resting-State fMRI Data Analysis Toolkit (REST), Data Processing Assistant for Resting-State fMRI (DPARSF) and Multiple Independent Component Analysis (MICA), here, we introduce an open-source MATLAB toolbox named PreSurgMapp. This toolbox can reveal eloquent areas using comprehensive methods and various complementary fMRI modalities. For example, PreSurgMapp supports both model-based (general linear model, GLM, and seed correlation) and data-driven (independent component analysis, ICA) methods and processes both task-based and resting-state fMRI data. PreSurgMapp is designed for highly automatic and individualized functional mapping with a user-friendly graphical user interface (GUI) for time-saving pipeline processing. For example, sensorimotor and language-related components can be automatically identified without human input interference using an effective, accurate component identification algorithm using discriminability index. All the results generated can be further evaluated and compared by neuro-radiologists or neurosurgeons. This software has substantial value for clinical neuro-radiology and neuro-oncology, including application to patients with low- and high-grade brain tumors and those with epilepsy foci in the dominant language hemisphere who are planning to undergo a temporal lobectomy.
Fukushima, Makoto; Saunders, Richard C; Leopold, David A; Mishkin, Mortimer; Averbeck, Bruno B
2012-06-07
In the absence of sensory stimuli, spontaneous activity in the brain has been shown to exhibit organization at multiple spatiotemporal scales. In the macaque auditory cortex, responses to acoustic stimuli are tonotopically organized within multiple, adjacent frequency maps aligned in a caudorostral direction on the supratemporal plane (STP) of the lateral sulcus. Here, we used chronic microelectrocorticography to investigate the correspondence between sensory maps and spontaneous neural fluctuations in the auditory cortex. We first mapped tonotopic organization across 96 electrodes spanning approximately two centimeters along the primary and higher auditory cortex. In separate sessions, we then observed that spontaneous activity at the same sites exhibited spatial covariation that reflected the tonotopic map of the STP. This observation demonstrates a close relationship between functional organization and spontaneous neural activity in the sensory cortex of the awake monkey. Copyright © 2012 Elsevier Inc. All rights reserved.
Fukushima, Makoto; Saunders, Richard C.; Leopold, David A.; Mishkin, Mortimer; Averbeck, Bruno B.
2012-01-01
Summary In the absence of sensory stimuli, spontaneous activity in the brain has been shown to exhibit organization at multiple spatiotemporal scales. In the macaque auditory cortex, responses to acoustic stimuli are tonotopically organized within multiple, adjacent frequency maps aligned in a caudorostral direction on the supratemporal plane (STP) of the lateral sulcus. Here we used chronic micro-electrocorticography to investigate the correspondence between sensory maps and spontaneous neural fluctuations in the auditory cortex. We first mapped tonotopic organization across 96 electrodes spanning approximately two centimeters along the primary and higher auditory cortex. In separate sessions we then observed that spontaneous activity at the same sites exhibited spatial covariation that reflected the tonotopic map of the STP. This observation demonstrates a close relationship between functional organization and spontaneous neural activity in the sensory cortex of the awake monkey. PMID:22681693
Natural speech reveals the semantic maps that tile human cerebral cortex
Huth, Alexander G.; de Heer, Wendy A.; Griffiths, Thomas L.; Theunissen, Frédéric E.; Gallant, Jack L.
2016-01-01
The meaning of language is represented in regions of the cerebral cortex collectively known as the “semantic system”. However, little of the semantic system has been mapped comprehensively, and the semantic selectivity of most regions is unknown. Here we systematically map semantic selectivity across the cortex using voxel-wise modeling of fMRI data collected while subjects listened to hours of narrative stories. We show that the semantic system is organized into intricate patterns that appear consistent across individuals. We then use a novel generative model to create a detailed semantic atlas. Our results suggest that most areas within the semantic system represent information about specific semantic domains, or groups of related concepts, and our atlas shows which domains are represented in each area. This study demonstrates that data-driven methods—commonplace in studies of human neuroanatomy and functional connectivity—provide a powerful and efficient means for mapping functional representations in the brain. PMID:27121839
Large-scale brain networks are distinctly affected in right and left mesial temporal lobe epilepsy.
de Campos, Brunno Machado; Coan, Ana Carolina; Lin Yasuda, Clarissa; Casseb, Raphael Fernandes; Cendes, Fernando
2016-09-01
Mesial temporal lobe epilepsy (MTLE) with hippocampus sclerosis (HS) is associated with functional and structural alterations extending beyond the temporal regions and abnormal pattern of brain resting state networks (RSNs) connectivity. We hypothesized that the interaction of large-scale RSNs is differently affected in patients with right- and left-MTLE with HS compared to controls. We aimed to determine and characterize these alterations through the analysis of 12 RSNs, functionally parceled in 70 regions of interest (ROIs), from resting-state functional-MRIs of 99 subjects (52 controls, 26 right- and 21 left-MTLE patients with HS). Image preprocessing and statistical analysis were performed using UF(2) C-toolbox, which provided ROI-wise results for intranetwork and internetwork connectivity. Intranetwork abnormalities were observed in the dorsal default mode network (DMN) in both groups of patients and in the posterior salience network in right-MTLE. Both groups showed abnormal correlation between the dorsal-DMN and the posterior salience, as well as between the dorsal-DMN and the executive-control network. Patients with left-MTLE also showed reduced correlation between the dorsal-DMN and visuospatial network and increased correlation between bilateral thalamus and the posterior salience network. The ipsilateral hippocampus stood out as a central area of abnormalities. Alterations on left-MTLE expressed a low cluster coefficient, whereas the altered connections on right-MTLE showed low cluster coefficient in the DMN but high in the posterior salience regions. Both right- and left-MTLE patients with HS have widespread abnormal interactions of large-scale brain networks; however, all parameters evaluated indicate that left-MTLE has a more intricate bihemispheric dysfunction compared to right-MTLE. Hum Brain Mapp 37:3137-3152, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
Wang, Nancy X. R.; Olson, Jared D.; Ojemann, Jeffrey G.; Rao, Rajesh P. N.; Brunton, Bingni W.
2016-01-01
Fully automated decoding of human activities and intentions from direct neural recordings is a tantalizing challenge in brain-computer interfacing. Implementing Brain Computer Interfaces (BCIs) outside carefully controlled experiments in laboratory settings requires adaptive and scalable strategies with minimal supervision. Here we describe an unsupervised approach to decoding neural states from naturalistic human brain recordings. We analyzed continuous, long-term electrocorticography (ECoG) data recorded over many days from the brain of subjects in a hospital room, with simultaneous audio and video recordings. We discovered coherent clusters in high-dimensional ECoG recordings using hierarchical clustering and automatically annotated them using speech and movement labels extracted from audio and video. To our knowledge, this represents the first time techniques from computer vision and speech processing have been used for natural ECoG decoding. Interpretable behaviors were decoded from ECoG data, including moving, speaking and resting; the results were assessed by comparison with manual annotation. Discovered clusters were projected back onto the brain revealing features consistent with known functional areas, opening the door to automated functional brain mapping in natural settings. PMID:27148018
Small-world human brain networks: Perspectives and challenges.
Liao, Xuhong; Vasilakos, Athanasios V; He, Yong
2017-06-01
Modelling the human brain as a complex network has provided a powerful mathematical framework to characterize the structural and functional architectures of the brain. In the past decade, the combination of non-invasive neuroimaging techniques and graph theoretical approaches enable us to map human structural and functional connectivity patterns (i.e., connectome) at the macroscopic level. One of the most influential findings is that human brain networks exhibit prominent small-world organization. Such a network architecture in the human brain facilitates efficient information segregation and integration at low wiring and energy costs, which presumably results from natural selection under the pressure of a cost-efficiency balance. Moreover, the small-world organization undergoes continuous changes during normal development and ageing and exhibits dramatic alterations in neurological and psychiatric disorders. In this review, we survey recent advances regarding the small-world architecture in human brain networks and highlight the potential implications and applications in multidisciplinary fields, including cognitive neuroscience, medicine and engineering. Finally, we highlight several challenging issues and areas for future research in this rapidly growing field. Copyright © 2017 Elsevier Ltd. All rights reserved.
Uga, Minako; Saito, Toshiyuki; Sano, Toshifumi; Yokota, Hidenori; Oguro, Keiji; Rizki, Edmi Edison; Mizutani, Tsutomu; Katura, Takusige; Dan, Ippeita; Watanabe, Eiju
2014-05-01
Functional near-infrared spectroscopy (fNIRS) is a neuroimaging technique for the noninvasive monitoring of human brain activation states utilizing the coupling between neural activity and regional cerebral hemodynamics. Illuminators and detectors, together constituting optodes, are placed on the scalp, but due to the presence of head tissues, an inter-optode distance of more than 2.5cm is necessary to detect cortical signals. Although direct cortical monitoring with fNIRS has been pursued, a high-resolution visualization of hemodynamic changes associated with sensory, motor and cognitive neural responses directly from the cortical surface has yet to be realized. To acquire robust information on the hemodynamics of the cortex, devoid of signal complications in transcranial measurement, we devised a functional near-infrared cortical imaging (fNCI) technique. Here we demonstrate the first direct functional measurement of temporal and spatial patterns of cortical hemodynamics using the fNCI technique. For fNCI, inter-optode distance was set at 5mm, and light leakage from illuminators was prevented by a special optode holder made of a light-shielding rubber sheet. fNCI successfully detected the somatotopy of pig nostril sensation, as assessed in comparison with concurrent and sequential somatosensory-evoked potential (SEP) measurements on the same stimulation sites. Accordingly, the fNCI system realized a direct cortical hemodynamic measurement with a spatial resolution comparable to that of SEP mapping on the rostral region of the pig brain. This study provides an important initial step toward realizing functional cortical hemodynamic monitoring during neurosurgery of human brains. Copyright © 2014. Published by Elsevier Inc.
Kristo, Gert; Raemaekers, Mathijs; Rutten, Geert-Jan; de Gelder, Beatrice; Ramsey, Nick F
2015-03-01
Despite many claims of functional reorganization following tumour surgery, empirical studies that investigate changes in functional activation patterns are rare. This study investigates whether functional recovery following surgical treatment in patients with a low-grade glioma in the left hemisphere is linked to inter-hemispheric reorganization. Based on literature, we hypothesized that reorganization would induce changes in the spatial pattern of activation specifically in tumour homologue brain areas in the healthy right hemisphere. An experimental group (EG) of 14 patients with a glioma in the left hemisphere near language related brain areas, and a control group of 6 patients with a glioma in the right, non-language dominant hemisphere were scanned before and after resection. In addition, an age and gender matched second control group of 18 healthy volunteers was scanned twice. A verb generation task was used to map language related areas and a novel technique was used for data analysis. Contrary to our hypothesis, we found that functional recovery following surgery of low-grade gliomas cannot be linked to functional reorganization in language homologue brain areas in the healthy, right hemisphere. Although elevated changes in the activation pattern were found in patients after surgery, these were largest in brain areas in proximity to the surgical resection, and were very similar to the spatial pattern of the brain shift following surgery. This suggests that the apparent perilesional functional reorganization is mostly caused by the brain shift as a consequence of surgery. Perilesional functional reorganization can however not be excluded. The study suggests that language recovery after transient post-surgical language deficits involves recovery of functioning of the presurgical language system. Copyright © 2014 Elsevier Ltd. All rights reserved.
Technological Advances in the Study of Reading: An Introduction.
ERIC Educational Resources Information Center
Henk, William A.
1991-01-01
Describes the purpose and functional operation of new computer-driven technologies such as computerized axial tomography, positron emissions transaxial tomography, regional cerebral blood flow monitoring, magnetic resonance imaging, and brain electrical activity mapping. Outlines their current contribution to the knowledge base. Speculates on the…
Testosterone affects language areas of the adult human brain.
Hahn, Andreas; Kranz, Georg S; Sladky, Ronald; Kaufmann, Ulrike; Ganger, Sebastian; Hummer, Allan; Seiger, Rene; Spies, Marie; Vanicek, Thomas; Winkler, Dietmar; Kasper, Siegfried; Windischberger, Christian; Swaab, Dick F; Lanzenberger, Rupert
2016-05-01
Although the sex steroid hormone testosterone is integrally involved in the development of language processing, ethical considerations mostly limit investigations to single hormone administrations. To circumvent this issue we assessed the influence of continuous high-dose hormone application in adult female-to-male transsexuals. Subjects underwent magnetic resonance imaging before and after 4 weeks of testosterone treatment, with each scan including structural, diffusion weighted and functional imaging. Voxel-based morphometry analysis showed decreased gray matter volume with increasing levels of bioavailable testosterone exclusively in Broca's and Wernicke's areas. Particularly, this may link known sex differences in language performance to the influence of testosterone on relevant brain regions. Using probabilistic tractography, we further observed that longitudinal changes in testosterone negatively predicted changes in mean diffusivity of the corresponding structural connection passing through the extreme capsule. Considering a related increase in myelin staining in rodents, this potentially reflects a strengthening of the fiber tract particularly involved in language comprehension. Finally, functional images at resting-state were evaluated, showing increased functional connectivity between the two brain regions with increasing testosterone levels. These findings suggest testosterone-dependent neuroplastic adaptations in adulthood within language-specific brain regions and connections. Importantly, deteriorations in gray matter volume seem to be compensated by enhancement of corresponding structural and functional connectivity. Hum Brain Mapp 37:1738-1748, 2016. © 2016 Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
Sodium 3D COncentration MApping (COMA 3D) using 23Na and proton MRI
NASA Astrophysics Data System (ADS)
Truong, Milton L.; Harrington, Michael G.; Schepkin, Victor D.; Chekmenev, Eduard Y.
2014-10-01
Functional changes of sodium 3D MRI signals were converted into millimolar concentration changes using an open-source fully automated MATLAB toolbox. These concentration changes are visualized via 3D sodium concentration maps, and they are overlaid over conventional 3D proton images to provide high-resolution co-registration for easy correlation of functional changes to anatomical regions. Nearly 5000/h concentration maps were generated on a personal computer (ca. 2012) using 21.1 T 3D sodium MRI brain images of live rats with spatial resolution of 0.8 × 0.8 × 0.8 mm3 and imaging matrices of 60 × 60 × 60. The produced concentration maps allowed for non-invasive quantitative measurement of in vivo sodium concentration in the normal rat brain as a functional response to migraine-like conditions. The presented work can also be applied to sodium-associated changes in migraine, cancer, and other metabolic abnormalities that can be sensed by molecular imaging. The MATLAB toolbox allows for automated image analysis of the 3D images acquired on the Bruker platform and can be extended to other imaging platforms. The resulting images are presented in a form of series of 2D slices in all three dimensions in native MATLAB and PDF formats. The following is provided: (a) MATLAB source code for image processing, (b) the detailed processing procedures, (c) description of the code and all sub-routines, (d) example data sets of initial and processed data. The toolbox can be downloaded at: http://www.vuiis.vanderbilt.edu/ truongm/COMA3D/.
Dysbindin modulates brain function during visual processing in children.
Mechelli, A; Viding, E; Kumar, A; Pettersson-Yeo, W; Fusar-Poli, P; Tognin, S; O'Donovan, M C; McGuire, P
2010-01-01
Schizophrenia is a neurodevelopmental disorder, and risk genes are thought to act through disruption of brain development. Several genetic studies have identified dystrobrevin binding protein 1 (DTNBP1, also known as dysbindin) as a potential susceptibility gene for schizophrenia, but its impact on brain function is poorly understood. It has been proposed that DTNBP1 may be associated with differences in visual processing. To test this, we examined the impact on visual processing in 61 healthy children aged 10-12 years of a genetic variant in DTNBP1 (rs2619538) that was common to all schizophrenia associated haplotypes in an earlier UK-Irish study. We tested the hypothesis that carriers of the risk allele would show altered occipital cortical function relative to noncarriers. Functional Magnetic Resonance Imaging (fMRI) was used to measure brain responses during a visual matching task. The data were analysed using statistical parametric mapping and statistical inferences were made at p<0.05 (corrected for multiple comparisons). Relative to noncarriers, carriers of the risk allele had greater activation in the lingual, fusiform gyrus and inferior occipital gyri. In these regions DTNBP1 genotype accounted for 19%, 20% and 14% of the inter-individual variance, respectively. Our results suggest that that genetic variation in DTNBP1 is associated with differences in the function of brain areas that mediate visual processing, and that these effects are evident in young children. These findings are consistent with the notion that the DTNBP1 gene influences brain development and can thereby modulate vulnerability to schizophrenia.
2002-12-01
sections of formalin-fixed guinea pig brains using different MAP-2 monoclonal antibodies. Brain sections were boiled in sodium citrate, citric acid...citric acid solution at pH 6.0 is the optimal microwave-assisted AR method for immunolabeling MAP-2 in formalin-fixed, paraffin-processed guinea pig brain...studies on archival guinea pig brain paraffin blocks, ultimately relaxing the use of additional animals to evaluate changes in MAP-2 expression between chemical warfare nerve agent-treated and control samples.
TRACTOGRAPHY DENSITY AND NETWORK MEASURES IN ALZHEIMER'S DISEASE.
Prasad, Gautam; Nir, Talia M; Toga, Arthur W; Thompson, Paul M
2013-04-01
Brain connectivity declines in Alzheimer's disease (AD), both functionally and structurally. Connectivity maps and networks derived from diffusion-based tractography offer new ways to track disease progression and to understand how AD affects the brain. Here we set out to identify (1) which fiber network measures show greatest differences between AD patients and controls, and (2) how these effects depend on the density of fibers extracted by the tractography algorithm. We computed brain networks from diffusion-weighted images (DWI) of the brain, in 110 subjects (28 normal elderly, 56 with early and 11 with late mild cognitive impairment, and 15 with AD). We derived connectivity matrices and network topology measures, for each subject, from whole-brain tractography and cortical parcellations. We used an ODF lookup table to speed up fiber extraction, and to exploit the full information in the orientation distribution function (ODF). This made it feasible to compute high density connectivity maps. We used accelerated tractography to compute a large number of fibers to understand what effect fiber density has on network measures and in distinguishing different disease groups in our data. We focused on global efficiency, transitivity, path length, mean degree, density, modularity, small world, and assortativity measures computed from weighted and binary undirected connectivity matrices. Of all these measures, the mean nodal degree best distinguished diagnostic groups. High-density fiber matrices were most helpful for picking up the more subtle clinical differences, e.g. between mild cognitively impaired (MCI) and normals, or for distinguishing subtypes of MCI (early versus late). Care is needed in clinical analyses of brain connectivity, as the density of extracted fibers may affect how well a network measure can pick up differences between patients and controls.
Functional expression of SGLTs in rat brain.
Yu, Amy S; Hirayama, Bruce A; Timbol, Gerald; Liu, Jie; Basarah, Ernest; Kepe, Vladimir; Satyamurthy, Nagichettiar; Huang, Sung-Cheng; Wright, Ernest M; Barrio, Jorge R
2010-12-01
This work provides evidence of previously unrecognized uptake of glucose via sodium-coupled glucose transporters (SGLTs) in specific regions of the brain. The current understanding of functional glucose utilization in brain is largely based on studies using positron emission tomography (PET) with the glucose tracer 2-deoxy-2-[F-18]fluoro-D-glucose (2-FDG). However, 2-FDG is only a good substrate for facilitated-glucose transporters (GLUTs), not for SGLTs. Thus, glucose accumulation measured by 2-FDG omits the role of SGLTs. We designed and synthesized two high-affinity tracers: one, α-methyl-4-[F-18]fluoro-4-deoxy-D-glucopyranoside (Me-4FDG), is a highly specific SGLT substrate and not transported by GLUTs; the other one, 4-[F-18]fluoro-4-deoxy-D-glucose (4-FDG), is transported by both SGLTs and GLUTs and will pass through the blood brain barrier (BBB). In vitro Me-4FDG autoradiography was used to map the distribution of uptake by functional SGLTs in brain slices with a comparable result from in vitro 4-FDG autoradiography. Immunohistochemical assays showed that uptake was consistent with the distribution of SGLT protein. Ex vivo 4-FDG autoradiography showed that SGLTs in these areas are functionally active in the normal in vivo brain. The results establish that SGLTs are a normal part of the physiology of specific areas of the brain, including hippocampus, amygdala, hypothalamus, and cerebral cortices. 4-FDG PET imaging also established that this BBB-permeable SGLT tracer now offers a functional imaging approach in humans to assess regulation of SGLT activity in health and disease.
Maggioni, Eleonora; Tana, Maria Gabriella; Arrigoni, Filippo; Zucca, Claudio; Bianchi, Anna Maria
2014-05-15
Functional Magnetic Resonance Imaging (fMRI) is used for exploring brain functionality, and recently it was applied for mapping the brain connection patterns. To give a meaningful neurobiological interpretation to the connectivity network, it is fundamental to properly define the network framework. In particular, the choice of the network nodes may affect the final connectivity results and the consequent interpretation. We introduce a novel method for the intra subject topological characterization of the nodes of fMRI brain networks, based on a whole brain parcellation scheme. The proposed whole brain parcellation algorithm divides the brain into clusters that are homogeneous from the anatomical and functional point of view, each of which constitutes a node. The functional parcellation described is based on the Tononi's cluster index, which measures instantaneous correlation in terms of intrinsic and extrinsic statistical dependencies. The method performance and reliability were first tested on simulated data, then on a real fMRI dataset acquired on healthy subjects during visual stimulation. Finally, the proposed algorithm was applied to epileptic patients' fMRI data recorded during seizures, to verify its usefulness as preparatory step for effective connectivity analysis. For each patient, the nodes of the network involved in ictal activity were defined according to the proposed parcellation scheme and Granger Causality Analysis (GCA) was applied to infer effective connectivity. We showed that the algorithm 1) performed well on simulated data, 2) was able to produce reliable inter subjects results and 3) led to a detailed definition of the effective connectivity pattern. Copyright © 2014 Elsevier B.V. All rights reserved.
Functional brain networks associated with eating behaviors in obesity.
Park, Bo-Yong; Seo, Jongbum; Park, Hyunjin
2016-03-31
Obesity causes critical health problems including diabetes and hypertension that affect billions of people worldwide. Obesity and eating behaviors are believed to be closely linked but their relationship through brain networks has not been fully explored. We identified functional brain networks associated with obesity and examined how the networks were related to eating behaviors. Resting state functional magnetic resonance imaging (MRI) scans were obtained for 82 participants. Data were from an equal number of people of healthy weight (HW) and non-healthy weight (non-HW). Connectivity matrices were computed with spatial maps derived using a group independent component analysis approach. Brain networks and associated connectivity parameters with significant group-wise differences were identified and correlated with scores on a three-factor eating questionnaire (TFEQ) describing restraint, disinhibition, and hunger eating behaviors. Frontoparietal and cerebellum networks showed group-wise differences between HW and non-HW groups. Frontoparietal network showed a high correlation with TFEQ disinhibition scores. Both frontoparietal and cerebellum networks showed a high correlation with body mass index (BMI) scores. Brain networks with significant group-wise differences between HW and non-HW groups were identified. Parts of the identified networks showed a high correlation with eating behavior scores.
A Four-Dimensional Probabilistic Atlas of the Human Brain
Mazziotta, John; Toga, Arthur; Evans, Alan; Fox, Peter; Lancaster, Jack; Zilles, Karl; Woods, Roger; Paus, Tomas; Simpson, Gregory; Pike, Bruce; Holmes, Colin; Collins, Louis; Thompson, Paul; MacDonald, David; Iacoboni, Marco; Schormann, Thorsten; Amunts, Katrin; Palomero-Gallagher, Nicola; Geyer, Stefan; Parsons, Larry; Narr, Katherine; Kabani, Noor; Le Goualher, Georges; Feidler, Jordan; Smith, Kenneth; Boomsma, Dorret; Pol, Hilleke Hulshoff; Cannon, Tyrone; Kawashima, Ryuta; Mazoyer, Bernard
2001-01-01
The authors describe the development of a four-dimensional atlas and reference system that includes both macroscopic and microscopic information on structure and function of the human brain in persons between the ages of 18 and 90 years. Given the presumed large but previously unquantified degree of structural and functional variance among normal persons in the human population, the basis for this atlas and reference system is probabilistic. Through the efforts of the International Consortium for Brain Mapping (ICBM), 7,000 subjects will be included in the initial phase of database and atlas development. For each subject, detailed demographic, clinical, behavioral, and imaging information is being collected. In addition, 5,800 subjects will contribute DNA for the purpose of determining genotype– phenotype–behavioral correlations. The process of developing the strategies, algorithms, data collection methods, validation approaches, database structures, and distribution of results is described in this report. Examples of applications of the approach are described for the normal brain in both adults and children as well as in patients with schizophrenia. This project should provide new insights into the relationship between microscopic and macroscopic structure and function in the human brain and should have important implications in basic neuroscience, clinical diagnostics, and cerebral disorders. PMID:11522763
Current technical approaches to brain energy metabolism.
Barros, L Felipe; Bolaños, Juan P; Bonvento, Gilles; Bouzier-Sore, Anne-Karine; Brown, Angus; Hirrlinger, Johannes; Kasparov, Sergey; Kirchhoff, Frank; Murphy, Anne N; Pellerin, Luc; Robinson, Michael B; Weber, Bruno
2018-06-01
Neuroscience is a technology-driven discipline and brain energy metabolism is no exception. Once satisfied with mapping metabolic pathways at organ level, we are now looking to learn what it is exactly that metabolic enzymes and transporters do and when, where do they reside, how are they regulated, and how do they relate to the specific functions of neurons, glial cells, and their subcellular domains and organelles, in different areas of the brain. Moreover, we aim to quantify the fluxes of metabolites within and between cells. Energy metabolism is not just a necessity for proper cell function and viability but plays specific roles in higher brain functions such as memory processing and behavior, whose mechanisms need to be understood at all hierarchical levels, from isolated proteins to whole subjects, in both health and disease. To this aim, the field takes advantage of diverse disciplines including anatomy, histology, physiology, biochemistry, bioenergetics, cellular biology, molecular biology, developmental biology, neurology, and mathematical modeling. This article presents a well-referenced synopsis of the technical side of brain energy metabolism research. Detail and jargon are avoided whenever possible and emphasis is given to comparative strengths, limitations, and weaknesses, information that is often not available in regular articles. © 2017 Wiley Periodicals, Inc.
2014-01-01
Background Repetitive navigated transcranial magnetic stimulation (rTMS) was recently described for mapping of human language areas. However, its capability of detecting language plasticity in brain tumor patients was not proven up to now. Thus, this study was designed to evaluate such data in order to compare rTMS language mapping to language mapping during repeated awake surgery during follow-up in patients suffering from language-eloquent gliomas. Methods Three right-handed patients with left-sided gliomas (2 opercular glioblastomas, 1 astrocytoma WHO grade III of the angular gyrus) underwent preoperative language mapping by rTMS as well as intraoperative language mapping provided via direct cortical stimulation (DCS) for initial as well as for repeated Resection 7, 10, and 15 months later. Results Overall, preoperative rTMS was able to elicit clear language errors in all mappings. A good correlation between initial rTMS and DCS results was observed. As a consequence of brain plasticity, initial DCS and rTMS findings only corresponded with the results obtained during the second examination in one out of three patients thus suggesting changes of language organization in two of our three patients. Conclusions This report points out the usefulness but also the limitations of preoperative rTMS language mapping to detect plastic changes in language function or for long-term follow-up prior to DCS even in recurrent gliomas. However, DCS still has to be regarded as gold standard. PMID:24479694
ConnectViz: Accelerated Approach for Brain Structural Connectivity Using Delaunay Triangulation.
Adeshina, A M; Hashim, R
2016-03-01
Stroke is a cardiovascular disease with high mortality and long-term disability in the world. Normal functioning of the brain is dependent on the adequate supply of oxygen and nutrients to the brain complex network through the blood vessels. Stroke, occasionally a hemorrhagic stroke, ischemia or other blood vessel dysfunctions can affect patients during a cerebrovascular incident. Structurally, the left and the right carotid arteries, and the right and the left vertebral arteries are responsible for supplying blood to the brain, scalp and the face. However, a number of impairment in the function of the frontal lobes may occur as a result of any decrease in the flow of the blood through one of the internal carotid arteries. Such impairment commonly results in numbness, weakness or paralysis. Recently, the concepts of brain's wiring representation, the connectome, was introduced. However, construction and visualization of such brain network requires tremendous computation. Consequently, previously proposed approaches have been identified with common problems of high memory consumption and slow execution. Furthermore, interactivity in the previously proposed frameworks for brain network is also an outstanding issue. This study proposes an accelerated approach for brain connectomic visualization based on graph theory paradigm using compute unified device architecture, extending the previously proposed SurLens Visualization and computer aided hepatocellular carcinoma frameworks. The accelerated brain structural connectivity framework was evaluated with stripped brain datasets from the Department of Surgery, University of North Carolina, Chapel Hill, USA. Significantly, our proposed framework is able to generate and extract points and edges of datasets, displays nodes and edges in the datasets in form of a network and clearly maps data volume to the corresponding brain surface. Moreover, with the framework, surfaces of the dataset were simultaneously displayed with the nodes and the edges. The framework is very efficient in providing greater interactivity as a way of representing the nodes and the edges intuitively, all achieved at a considerably interactive speed for instantaneous mapping of the datasets' features. Uniquely, the connectomic algorithm performed remarkably fast with normal hardware requirement specifications.
ConnectViz: Accelerated approach for brain structural connectivity using Delaunay triangulation.
Adeshina, A M; Hashim, R
2015-02-06
Stroke is a cardiovascular disease with high mortality and long-term disability in the world. Normal functioning of the brain is dependent on the adequate supply of oxygen and nutrients to the brain complex network through the blood vessels. Stroke, occasionally a hemorrhagic stroke, ischemia or other blood vessel dysfunctions can affect patients during a cerebrovascular incident. Structurally, the left and the right carotid arteries, and the right and the left vertebral arteries are responsible for supplying blood to the brain, scalp and the face. However, a number of impairment in the function of the frontal lobes may occur as a result of any decrease in the flow of the blood through one of the internal carotid arteries. Such impairment commonly results in numbness, weakness or paralysis. Recently, the concepts of brain's wiring representation, the connectome, was introduced. However, construction and visualization of such brain network requires tremendous computation. Consequently, previously proposed approaches have been identified with common problems of high memory consumption and slow execution. Furthermore, interactivity in the previously proposed frameworks for brain network is also an outstanding issue. This study proposes an accelerated approach for brain connectomic visualization based on graph theory paradigm using Compute Unified Device Architecture (CUDA), extending the previously proposed SurLens Visualization and Computer Aided Hepatocellular Carcinoma (CAHECA) frameworks. The accelerated brain structural connectivity framework was evaluated with stripped brain datasets from the Department of Surgery, University of North Carolina, Chapel Hill, United States. Significantly, our proposed framework is able to generates and extracts points and edges of datasets, displays nodes and edges in the datasets in form of a network and clearly maps data volume to the corresponding brain surface. Moreover, with the framework, surfaces of the dataset were simultaneously displayed with the nodes and the edges. The framework is very efficient in providing greater interactivity as a way of representing the nodes and the edges intuitively, all achieved at a considerably interactive speed for instantaneous mapping of the datasets' features. Uniquely, the connectomic algorithm performed remarkably fast with normal hardware requirement specifications.
Increased resting-state brain entropy in Alzheimer's disease.
Xue, Shao-Wei; Guo, Yonghu
2018-03-07
Entropy analysis of resting-state functional MRI (R-fMRI) is a novel approach to characterize brain temporal dynamics and facilitates the identification of abnormal brain activity caused by several disease conditions. However, Alzheimer's disease (AD)-related brain entropy mapping based on R-fMRI has not been assessed. Here, we measured the sample entropy and voxel-wise connectivity of the network degree centrality (DC) of the intrinsic brain activity acquired by R-fMRI in 26 patients with AD and 26 healthy controls. Compared with the controls, AD patients showed increased entropy in the middle temporal gyrus and the precentral gyrus and also showed decreased DC in the precuneus. Moreover, the magnitude of the negative correlation between local brain activity (entropy) and network connectivity (DC) was increased in AD patients in comparison with healthy controls. These findings provide new evidence on AD-related brain entropy alterations.
Neuroscience thinks big (and collaboratively).
Kandel, Eric R; Markram, Henry; Matthews, Paul M; Yuste, Rafael; Koch, Christof
2013-09-01
Despite cash-strapped times for research, several ambitious collaborative neuroscience projects have attracted large amounts of funding and media attention. In Europe, the Human Brain Project aims to develop a large-scale computer simulation of the brain, whereas in the United States, the Brain Activity Map is working towards establishing a functional connectome of the entire brain, and the Allen Institute for Brain Science has embarked upon a 10-year project to understand the mouse visual cortex (the MindScope project). US President Barack Obama's announcement of the BRAIN Initiative (Brain Research through Advancing Innovative Neurotechnologies Initiative) in April 2013 highlights the political commitment to neuroscience and is expected to further foster interdisciplinary collaborations, accelerate the development of new technologies and thus fuel much needed medical advances. In this Viewpoint article, five prominent neuroscientists explain the aims of the projects and how they are addressing some of the questions (and criticisms) that have arisen.
In search of the motor engram: motor map plasticity as a mechanism for encoding motor experience.
Monfils, Marie-H; Plautz, Erik J; Kleim, Jeffrey A
2005-10-01
Motor skill acquisition occurs through modification and organization of muscle synergies into effective movement sequences. The learning process is reflected neurophysiologically as a reorganization of movement representations within the primary motor cortex, suggesting that the motor map is a motor engram. However, the specific neural mechanisms underlying map plasticity are unknown. Here the authors review evidence that 1) motor map topography reflects the capacity for skilled movement, 2) motor skill learning induces reorganization of motor maps in a manner that reflects the kinematics of acquired skilled movement, 3) map plasticity is supported by a reorganization of cortical microcircuitry involving changes in synaptic efficacy, and 4) motor map integrity and topography are influenced by various neurochemical signals that coordinate changes in cortical circuitry to encode motor experience. Finally, the role of motor map plasticity in recovery of motor function after brain damage is discussed.
George, S Thomas; Balakrishnan, R; Johnson, J Stanly; Jayakumar, J
2017-07-01
EEG records the spontaneous electrical activity of the brain using multiple electrodes placed on the scalp, and it provides a wealth of information related to the functions of brain. Nevertheless, the signals from the electrodes cannot be directly applied to a diagnostic tool like brain mapping as they undergo a "mixing" process because of the volume conduction effect in the scalp. A pervasive problem in neuroscience is determining which regions of the brain are active, given voltage measurements at the scalp. Because of which, there has been a surge of interest among the biosignal processing community to investigate the process of mixing and unmixing to identify the underlying active sources. According to the assumptions of independent component analysis (ICA) algorithms, the resultant mixture obtained from the scalp can be closely approximated by a linear combination of the "actual" EEG signals emanating from the underlying sources of electrical activity in the brain. As a consequence, using these well-known ICA techniques in preprocessing of the EEG signals prior to clinical applications could result in development of diagnostic tool like quantitative EEG which in turn can assist the neurologists to gain noninvasive access to patient-specific cortical activity, which helps in treating neuropathologies like seizure disorders. The popular and proven ICA schemes mentioned in various literature and applications were selected (which includes Infomax, JADE, and SOBI) and applied on generalized seizure disorder samples using EEGLAB toolbox in MATLAB environment to see their usefulness in source separations; and they were validated by the expert neurologist for clinical relevance in terms of pathologies on brain functionalities. The performance of Infomax method was found to be superior when compared with other ICA schemes applied on EEG and it has been established based on the validations carried by expert neurologist for generalized seizure and its clinical correlation. The results are encouraging for furthering the studies in the direction of developing useful brain mapping tools using ICA methods.
Quantitative susceptibility mapping of human brain at 3T: a multisite reproducibility study.
Lin, P-Y; Chao, T-C; Wu, M-L
2015-03-01
Quantitative susceptibility mapping of the human brain has demonstrated strong potential in examining iron deposition, which may help in investigating possible brain pathology. This study assesses the reproducibility of quantitative susceptibility mapping across different imaging sites. In this study, the susceptibility values of 5 regions of interest in the human brain were measured on 9 healthy subjects following calibration by using phantom experiments. Each of the subjects was imaged 5 times on 1 scanner with the same procedure repeated on 3 different 3T systems so that both within-site and cross-site quantitative susceptibility mapping precision levels could be assessed. Two quantitative susceptibility mapping algorithms, similar in principle, one by using iterative regularization (iterative quantitative susceptibility mapping) and the other with analytic optimal solutions (deterministic quantitative susceptibility mapping), were implemented, and their performances were compared. Results show that while deterministic quantitative susceptibility mapping had nearly 700 times faster computation speed, residual streaking artifacts seem to be more prominent compared with iterative quantitative susceptibility mapping. With quantitative susceptibility mapping, the putamen, globus pallidus, and caudate nucleus showed smaller imprecision on the order of 0.005 ppm, whereas the red nucleus and substantia nigra, closer to the skull base, had a somewhat larger imprecision of approximately 0.01 ppm. Cross-site errors were not significantly larger than within-site errors. Possible sources of estimation errors are discussed. The reproducibility of quantitative susceptibility mapping in the human brain in vivo is regionally dependent, and the precision levels achieved with quantitative susceptibility mapping should allow longitudinal and multisite studies such as aging-related changes in brain tissue magnetic susceptibility. © 2015 by American Journal of Neuroradiology.
Zvyagintsev, M; Klasen, M; Weber, R; Sarkheil, P; Esposito, F; Mathiak, K A; Schwenzer, M; Mathiak, K
2016-04-21
In violent video games, players engage in virtual aggressive behaviors. Exposure to virtual aggressive behavior induces short-term changes in players' behavior. In a previous study, a violence-related version of the racing game "Carmageddon TDR2000" increased aggressive affects, cognitions, and behaviors compared to its non-violence-related version. This study investigates the differences in neural network activity during the playing of both versions of the video game. Functional magnetic resonance imaging (fMRI) recorded ongoing brain activity of 18 young men playing the violence-related and the non-violence-related version of the video game Carmageddon. Image time series were decomposed into functional connectivity (FC) patterns using independent component analysis (ICA) and template-matching yielded a mapping to established functional brain networks. The FC patterns revealed a decrease in connectivity within 6 brain networks during the violence-related compared to the non-violence-related condition: three sensory-motor networks, the reward network, the default mode network (DMN), and the right-lateralized frontoparietal network. Playing violent racing games may change functional brain connectivity, in particular and even after controlling for event frequency, in the reward network and the DMN. These changes may underlie the short-term increase of aggressive affects, cognitions, and behaviors as observed after playing violent video games. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.
Wolf, R C; Sambataro, F; Vasic, N; Depping, M S; Thomann, P A; Landwehrmeyer, G B; Süssmuth, S D; Orth, M
2014-11-01
Functional magnetic resonance imaging (fMRI) of multiple neural networks during the brain's 'resting state' could facilitate biomarker development in patients with Huntington's disease (HD) and may provide new insights into the relationship between neural dysfunction and clinical symptoms. To date, however, very few studies have examined the functional integrity of multiple resting state networks (RSNs) in manifest HD, and even less is known about whether concomitant brain atrophy affects neural activity in patients. Using MRI, we investigated brain structure and RSN function in patients with early HD (n = 20) and healthy controls (n = 20). For resting-state fMRI data a group-independent component analysis identified spatiotemporally distinct patterns of motor and prefrontal RSNs of interest. We used voxel-based morphometry to assess regional brain atrophy, and 'biological parametric mapping' analyses to investigate the impact of atrophy on neural activity. Compared with controls, patients showed connectivity changes within distinct neural systems including lateral prefrontal, supplementary motor, thalamic, cingulate, temporal and parietal regions. In patients, supplementary motor area and cingulate cortex connectivity indices were associated with measures of motor function, whereas lateral prefrontal connectivity was associated with cognition. This study provides evidence for aberrant connectivity of RSNs associated with motor function and cognition in early manifest HD when controlling for brain atrophy. This suggests clinically relevant changes of RSN activity in the presence of HD-associated cortical and subcortical structural abnormalities.
Structured Illumination Diffuse Optical Tomography for Mouse Brain Imaging
NASA Astrophysics Data System (ADS)
Reisman, Matthew David
As advances in functional magnetic resonance imaging (fMRI) have transformed the study of human brain function, they have also widened the divide between standard research techniques used in humans and those used in mice, where high quality images are difficult to obtain using fMRI given the small volume of the mouse brain. Optical imaging techniques have been developed to study mouse brain networks, which are highly valuable given the ability to study brain disease treatments or development in a controlled environment. A planar imaging technique known as optical intrinsic signal (OIS) imaging has been a powerful tool for capturing functional brain hemodynamics in rodents. Recent wide field-of-view implementations of OIS have provided efficient maps of functional connectivity from spontaneous brain activity in mice. However, OIS requires scalp retraction and is limited to imaging a 2-dimensional view of superficial cortical tissues. Diffuse optical tomography (DOT) is a non-invasive, volumetric neuroimaging technique that has been valuable for bedside imaging of patients in the clinic, but previous DOT systems for rodent neuroimaging have been limited by either sparse spatial sampling or by slow speed. My research has been to develop diffuse optical tomography for whole brain mouse neuroimaging by expanding previous techniques to achieve high spatial sampling using multiple camera views for detection and high speed using structured illumination sources. I have shown the feasibility of this method to perform non-invasive functional neuroimaging in mice and its capabilities of imaging the entire volume of the brain. Additionally, the system has been built with a custom, flexible framework to accommodate the expansion to imaging multiple dynamic contrasts in the brain and populations that were previously difficult or impossible to image, such as infant mice and awake mice. I have contributed to preliminary feasibility studies of these more advanced techniques using OIS, which can now be carried out using the structured illumination diffuse optical tomography technique to perform longitudinal, non-invasive studies of the whole volume of the mouse brain.
Roux, F; Boulanouar, K; Ibarrola, D; Tremoulet, M; Chollet, F; Berry, I
2000-01-01
OBJECTIVE—To support the hypothesis about the potential compensatory role of ipsilateral corticofugal pathways when the contralateral pathways are impaired by brain tumours. METHODS—Retrospective analysis was carried out on the results of functional MRI (fMRI) of a selected group of five paretic patients with Rolandic brain tumours who exhibited an abnormally high ipsilateral/contralateral ratio of activation—that is, movements of the paretic hand activated predominately the ipsilateral cortex. Brain activation was achieved with a flexion extension of the fingers. Statistical parametric activation was obtained using a t test and a threshold of p<0.001. These patients, candidates for tumour resection, also underwent cortical intraoperative stimulation that was correlated to the fMRI spatial data using three dimensional reconstructions of the brain. Three patients also had postoperative control fMRI. RESULTS—The absence of fMRI activation of the primary sensorimotor cortex normally innervating the paretic hand for the threshold chosen, was correlated with completely negative cortical responses of the cortical hand area during the operation. The preoperative fMRI activation of these patients predominantly found in the ipsilateral frontal and primary sensorimotor cortices could be related to the residual ipsilateral hand function. Postoperatively, the fMRI activation returned to more classic patterns of activation, reflecting the consequences of therapy. CONCLUSION—In paretic patients with brain tumours, ipsilateral control could be implicated in the residual hand function, when the normal primary pathways are impaired. The possibility that functional tissue still remains in the peritumorous sensorimotor cortex even when the preoperative fMRI and the cortical intraoperative stimulations are negative, should be taken into account when planning the tumour resection and during the operation. PMID:10990503
Direct and accelerated parameter mapping using the unscented Kalman filter.
Zhao, Li; Feng, Xue; Meyer, Craig H
2016-05-01
To accelerate parameter mapping using a new paradigm that combines image reconstruction and model regression as a parameter state-tracking problem. In T2 mapping, the T2 map is first encoded in parameter space by multi-TE measurements and then encoded by Fourier transformation with readout/phase encoding gradients. Using a state transition function and a measurement function, the unscented Kalman filter can describe T2 mapping as a dynamic system and directly estimate the T2 map from the k-space data. The proposed method was validated with a numerical brain phantom and volunteer experiments with a multiple-contrast spin echo sequence. Its performance was compared with a conjugate-gradient nonlinear inversion method at undersampling factors of 2 to 8. An accelerated pulse sequence was developed based on this method to achieve prospective undersampling. Compared with the nonlinear inversion reconstruction, the proposed method had higher precision, improved structural similarity and reduced normalized root mean squared error, with acceleration factors up to 8 in numerical phantom and volunteer studies. This work describes a new perspective on parameter mapping by state tracking. The unscented Kalman filter provides a highly accelerated and efficient paradigm for T2 mapping. © 2015 Wiley Periodicals, Inc.
Kundu, Bornali; Penwarden, Amy; Wood, Joel M; Gallagher, Thomas A; Andreoli, Matthew J; Voss, Jed; Meier, Timothy; Nair, Veena A; Kuo, John S; Field, Aaron S; Moritz, Chad; Meyerand, M Elizabeth; Prabhakaran, Vivek
2013-04-01
Functional MRI (fMRI) has the potential to be a useful presurgical planning tool to treat patients with primary brain tumor. In this study the authors retrospectively explored relationships between language-related postoperative outcomes in such patients and multiple factors, including measures estimated from task fMRI maps (proximity of lesion to functional activation area, or lesion-to-activation distance [LAD], and activation-based language lateralization, or lateralization index [LI]) used in the clinical setting for presurgical planning, as well as other factors such as patient age, patient sex, tumor grade, and tumor volume. Patient information was drawn from a database of patients with brain tumors who had undergone preoperative fMRI-based language mapping of the Broca and Wernicke areas. Patients had performed a battery of tasks, including word-generation tasks and a text-versus-symbols reading task, as part of a clinical fMRI protocol. Individually thresholded task fMRI activation maps had been provided for use in the clinical setting. These clinical imaging maps were used to retrospectively estimate LAD and LI for the Broca and Wernicke areas. There was a relationship between postoperative language deficits and the proximity between tumor and Broca area activation (the LAD estimate), where shorter LADs were related to the presence of postoperative aphasia. Stratification by tumor location further showed that for posterior tumors within the temporal and parietal lobes, more bilaterally oriented Broca area activation (LI estimate close to 0) and a shorter Wernicke area LAD were associated with increased postoperative aphasia. Furthermore, decreasing LAD was related to decreasing LI for both Broca and Wernicke areas. Preoperative deficits were related to increasing patient age and a shorter Wernicke area LAD. Overall, LAD and LI, as determined using fMRI in the context of these paradigms, may be useful indicators of postsurgical outcomes. Whereas tumor location may influence postoperative deficits, the results indicated that tumor proximity to an activation area might also interact with how the language network is affected as a whole by the lesion. Although the derivation of LI must be further validated in individual patients by using spatially specific statistical methods, the current results indicated that fMRI is a useful tool for predicting postoperative outcomes in patients with a single brain tumor.
Viader, Andreu; Ogasawara, Daisuke; Joslyn, Christopher M; Sanchez-Alavez, Manuel; Mori, Simone; Nguyen, William; Conti, Bruno; Cravatt, Benjamin F
2016-01-01
Metabolic specialization among major brain cell types is central to nervous system function and determined in large part by the cellular distribution of enzymes. Serine hydrolases are a diverse enzyme class that plays fundamental roles in CNS metabolism and signaling. Here, we perform an activity-based proteomic analysis of primary mouse neurons, astrocytes, and microglia to furnish a global portrait of the cellular anatomy of serine hydrolases in the brain. We uncover compelling evidence for the cellular compartmentalization of key chemical transmission pathways, including the functional segregation of endocannabinoid (eCB) biosynthetic enzymes diacylglycerol lipase-alpha (DAGLα) and –beta (DAGLβ) to neurons and microglia, respectively. Disruption of DAGLβ perturbed eCB-eicosanoid crosstalk specifically in microglia and suppressed neuroinflammatory events in vivo independently of broader effects on eCB content. Mapping the cellular distribution of metabolic enzymes thus identifies pathways for regulating specialized inflammatory responses in the brain while avoiding global alterations in CNS function. DOI: http://dx.doi.org/10.7554/eLife.12345.001 PMID:26779719
Grinvald, A
1992-01-01
Long standing questions related to brain mechanisms underlying perception can finally be resolved by direct visualization of the architecture and function of mammalian cortex. This advance has been accomplished with the aid of two optical imaging techniques with which one can literally see how the brain functions. The upbringing of this technology required a multi-disciplinary approach integrating brain research with organic chemistry, spectroscopy, biophysics, computer sciences, optics and image processing. Beyond the technological ramifications, recent research shed new light on cortical mechanisms underlying sensory perception. Clinical applications of this technology for precise mapping of the cortical surface of patients during neurosurgery have begun. Below is a brief summary of our own research and a description of the technical specifications of the two optical imaging techniques. Like every technique, optical imaging also suffers from severe limitations. Here we mostly emphasize some of its advantages relative to all alternative imaging techniques currently in use. The limitations are critically discussed in our recent reviews. For a series of other reviews, see Cohen (1989).
Optical Coherence Tomography for Brain Imaging
NASA Astrophysics Data System (ADS)
Liu, Gangjun; Chen, Zhongping
Recently, there has been growing interest in using OCT for brain imaging. A feasibility study of OCT for guiding deep brain probes has found that OCT can differentiate the white matter and gray matter because the white matter tends to have a higher peak reflectivity and steeper attenuation rate compared to gray matter. In vivo 3D visualization of the layered organization of a rat olfactory bulb with OCT has been demonstrated. OCT has been used for single myelin fiber imaging in living rodents without labeling. The refractive index in the rat somatosensory cortex has also been measured with OCT. In addition, functional extension of OCT, such as Doppler-OCT (D-OCT), polarization sensitive-OCT (PS-OCT), and phase-resolved-OCT (PR-OCT), can image and quantify physiological parameters in addition to the morphological structure image. Based on the scattering changes during neural activity, OCT has been used to measure the functional activation in neuronal tissues. PS-OCT, which combines polarization sensitive detection with OCT to determine tissue birefringence, has been used for the localization of nerve fiber bundles and the mapping of micrometer-scale fiber pathways in the brain. D-OCT, also named optical Doppler tomography (ODT), combines the Doppler principle with OCT to obtain high resolution tomographic images of moving constituents in highly scattering biological tissues. D-OCT has been successfully used to image cortical blood flow and map the blood vessel network for brain research. In this chapter, the principle and technology of OCT and D-OCT are reviewed and examples of potential applications are described.
Winchester, Catherine L; Ohzeki, Hiromitsu; Vouyiouklis, Demetrius A; Thompson, Rhiannon; Penninger, Josef M; Yamagami, Keiji; Norrie, John D; Hunter, Robert; Pratt, Judith A; Morris, Brian J
2012-11-15
Schizophrenia is a debilitating psychiatric disease with a strong genetic contribution, potentially linked to altered glutamatergic function in brain regions such as the prefrontal cortex (PFC). Here, we report converging evidence to support a functional candidate gene for schizophrenia. In post-mortem PFC from patients with schizophrenia, we detected decreased expression of MKK7/MAP2K7-a kinase activated by glutamatergic activity. While mice lacking one copy of the Map2k7 gene were overtly normal in a variety of behavioural tests, these mice showed a schizophrenia-like cognitive phenotype of impaired working memory. Additional support for MAP2K7 as a candidate gene came from a genetic association study. A substantial effect size (odds ratios: ~1.9) was observed for a common variant in a cohort of case and control samples collected in the Glasgow area and also in a replication cohort of samples of Northern European descent (most significant P-value: 3 × 10(-4)). While some caution is warranted until these association data are further replicated, these results are the first to implicate the candidate gene MAP2K7 in genetic risk for schizophrenia. Complete sequencing of all MAP2K7 exons did not reveal any non-synonymous mutations. However, the MAP2K7 haplotype appeared to have functional effects, in that it influenced the level of expression of MAP2K7 mRNA in human PFC. Taken together, the results imply that reduced function of the MAP2K7-c-Jun N-terminal kinase (JNK) signalling cascade may underlie some of the neurochemical changes and core symptoms in schizophrenia.
Spinal Cord Injury Disrupts Resting-State Networks in the Human Brain.
Hawasli, Ammar H; Rutlin, Jerrel; Roland, Jarod L; Murphy, Rory K J; Song, Sheng-Kwei; Leuthardt, Eric C; Shimony, Joshua S; Ray, Wilson Z
2018-03-15
Despite 253,000 spinal cord injury (SCI) patients in the United States, little is known about how SCI affects brain networks. Spinal MRI provides only structural information with no insight into functional connectivity. Resting-state functional MRI (RS-fMRI) quantifies network connectivity through the identification of resting-state networks (RSNs) and allows detection of functionally relevant changes during disease. Given the robust network of spinal cord afferents to the brain, we hypothesized that SCI produces meaningful changes in brain RSNs. RS-fMRIs and functional assessments were performed on 10 SCI subjects. Blood oxygen-dependent RS-fMRI sequences were acquired. Seed-based correlation mapping was performed using five RSNs: default-mode (DMN), dorsal-attention (DAN), salience (SAL), control (CON), and somatomotor (SMN). RSNs were compared with normal control subjects using false-discovery rate-corrected two way t tests. SCI reduced brain network connectivity within the SAL, SMN, and DMN and disrupted anti-correlated connectivity between CON and SMN. When divided into separate cohorts, complete but not incomplete SCI disrupted connectivity within SAL, DAN, SMN and DMN and between CON and SMN. Finally, connectivity changed over time after SCI: the primary motor cortex decreased connectivity with the primary somatosensory cortex, the visual cortex decreased connectivity with the primary motor cortex, and the visual cortex decreased connectivity with the sensory parietal cortex. These unique findings demonstrate the functional network plasticity that occurs in the brain as a result of injury to the spinal cord. Connectivity changes after SCI may serve as biomarkers to predict functional recovery following an SCI and guide future therapy.
Mapping oxygen concentration in the awake mouse brain
Lyons, Declan G; Parpaleix, Alexandre; Roche, Morgane; Charpak, Serge
2016-01-01
Although critical for brain function, the physiological values of cerebral oxygen concentration have remained elusive because high-resolution measurements have only been performed during anesthesia, which affects two major parameters modulating tissue oxygenation: neuronal activity and blood flow. Using measurements of capillary erythrocyte-associated transients, fluctuations of oxygen partial pressure (Po2) associated with individual erythrocytes, to infer Po2 in the nearby neuropil, we report the first non-invasive micron-scale mapping of cerebral Po2 in awake, resting mice. Interstitial Po2 has similar values in the olfactory bulb glomerular layer and the somatosensory cortex, whereas there are large capillary hematocrit and erythrocyte flux differences. Awake tissue Po2 is about half that under isoflurane anesthesia, and within the cortex, vascular and interstitial Po2 values display layer-specific differences which dramatically contrast with those recorded under anesthesia. Our findings emphasize the importance of measuring energy parameters non-invasively in physiological conditions to precisely quantify and model brain metabolism. DOI: http://dx.doi.org/10.7554/eLife.12024.001 PMID:26836304
Mapping oxygen concentration in the awake mouse brain.
Lyons, Declan G; Parpaleix, Alexandre; Roche, Morgane; Charpak, Serge
2016-02-02
Although critical for brain function, the physiological values of cerebral oxygen concentration have remained elusive because high-resolution measurements have only been performed during anesthesia, which affects two major parameters modulating tissue oxygenation: neuronal activity and blood flow. Using measurements of capillary erythrocyte-associated transients, fluctuations of oxygen partial pressure (Po2) associated with individual erythrocytes, to infer Po2 in the nearby neuropil, we report the first non-invasive micron-scale mapping of cerebral Po2 in awake, resting mice. Interstitial Po2 has similar values in the olfactory bulb glomerular layer and the somatosensory cortex, whereas there are large capillary hematocrit and erythrocyte flux differences. Awake tissue Po2 is about half that under isoflurane anesthesia, and within the cortex, vascular and interstitial Po2 values display layer-specific differences which dramatically contrast with those recorded under anesthesia. Our findings emphasize the importance of measuring energy parameters non-invasively in physiological conditions to precisely quantify and model brain metabolism.
Nathan, Dominic E; Oakes, Terrence R; Yeh, Ping Hong; French, Louis M; Harper, Jamie F; Liu, Wei; Wolfowitz, Rachel D; Wang, Bin Quan; Graner, John L; Riedy, Gerard
2015-03-01
A definitive diagnosis of mild traumatic brain injury (mTBI) is difficult due to the absence of biomarkers in standard clinical imaging. The brain is a complex network of interconnected neurons and subtle changes can modulate key networks of cognitive function. The resting state default mode network (DMN) has been shown to be sensitive to changes induced by pathology. This study seeks to determine whether quantitative measures of the DMN are sensitive in distinguishing mTBI subjects. Resting state functional magnetic resonance imaging data were obtained for healthy (n=12) and mTBI subjects (n=15). DMN maps were computed using dual-regression Independent Component Analysis (ICA). A goodness-of-fit (GOF) index was calculated to assess the degree of spatial specificity and sensitivity between healthy controls and mTBI subjects. DMN regions and neuropsychological assessments were examined to identify potential relationships. The resting state DMN maps indicate an increase in spatial coactivity in mTBI subjects within key regions of the DMN. Significant coactivity within the cerebellum and supplementary motor areas of mTBI subjects were also observed. This has not been previously reported in seed-based resting state network analysis. The GOF suggested the presence of high variability within the mTBI subject group, with poor sensitivity and specificity. The neuropsychological data showed correlations between areas of coactivity within the resting state network in the brain with a number of measures of emotion and cognitive functioning. The poor performance of the GOF highlights the key challenge associated with mTBI injury: the high variability in injury mechanisms and subsequent recovery. However, the quantification of the DMN using dual-regression ICA has potential to distinguish mTBI from healthy subjects, and provide information on the relationship of aspects of cognitive and emotional functioning with their potential neural correlates.
Southwell, Derek G; Hervey-Jumper, Shawn L; Perry, David W; Berger, Mitchel S
2016-05-01
OBJECT To avoid iatrogenic injury during the removal of intrinsic cerebral neoplasms such as gliomas, direct electrical stimulation (DES) is used to identify cortical and subcortical white matter pathways critical for language, motor, and sensory function. When a patient undergoes more than 1 brain tumor resection as in the case of tumor recurrence, the use of DES provides an unusual opportunity to examine brain plasticity in the setting of neurological disease. METHODS The authors examined 561 consecutive cases in which patients underwent DES mapping during surgery forglioma resection. "Positive" and "negative" sites-discrete cortical regions where electrical stimulation did (positive) or did not (negative) produce transient sensory, motor, or language disturbance-were identified prior to tumor resection and documented by intraoperative photography for categorization into functional maps. In this group of 561 patients, 18 were identified who underwent repeat surgery in which 1 or more stimulation sites overlapped with those tested during the initial surgery. The authors compared intraoperative sensory, motor, or language mapping results between initial and repeat surgeries, and evaluated the clinical outcomes for these patients. RESULTS A total of 117 sites were tested for sensory (7 sites, 6.0%), motor (9 sites, 7.7%), or language (101 sites, 86.3%) function during both initial and repeat surgeries. The mean interval between surgical procedures was 4.1 years. During initial surgeries, 95 (81.2%) of 117 sites were found to be negative and 22 (18.8%) of 117 sites were found to be positive. During repeat surgeries, 103 (88.0%) of 117 sites were negative and 14 (12.0%) of 117 were positive. Of the 95 sites that were negative at the initial surgery, 94 (98.9%) were also negative at the repeat surgery, while 1 (1.1%) site was found to be positive. Of the 22 sites that were initially positive, 13 (59.1%) remained positive at repeat surgery, while 9 (40.9%) had become negative for function. Overall, 6 (33.3%) of 18 patients exhibited loss of function at 1 or more motor or language sites between surgeries. Loss of function at these sites was not associated with neurological impairment at the time of repeat surgery, suggesting that neurological function was preserved through neural circuit reorganization or activation of latent functional pathways. CONCLUSIONS The adult central nervous system reorganizes motor and language areas in patients with glioma. Ultimately, adult neural plasticity may help to preserve motor and language function in the presence of evolving structural lesions. The insight gained from this subset of patients has implications for our understanding of brain plasticity in clinical settings.
Mapping Language Problems in the Brain
... issue Health Capsule Mapping Language Problems in the Brain En español Send us your comments We often ... more about how language is organized in the brain, an NIH-funded research team studied people with ...
NASA Astrophysics Data System (ADS)
Khadka, Sabin; Chityala, Srujan R.; Tian, Fenghua; Liu, Hanli
2011-03-01
Stroop test is commonly used as a behavior-testing tool for psychological examinations that are related to attention and cognitive control of the human brain. Studies have shown activations in Broadmann area 10 (BA10) of prefrontal cortex (PFC) during attention and cognitive process. The use of diffuse optical tomography (DOT) for human brain mapping is becoming more prevalent. In this study we expect to find neural correlates between the performed cognitive tasks and hemodynamic signals detected by a DOT system. Our initial observation showed activation of oxy-hemoglobin concentration in BA 10, which is consistent with some results seen by positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). Our study demonstrates the possibility of combining DOT with Stroop test to quantitatively investigate cognitive functions of the human brain at the prefrontal cortex.
Using Brain Electrical Activity Mapping to Diagnose Learning Disabilities.
ERIC Educational Resources Information Center
Torello, Michael, W.; Duffy, Frank H.
1985-01-01
Cognitive neuroscience assumes that measurement of brain electrical activity should relate to cognition. Brain Electrical Activity Mapping (BEAM), a non-invasive technique, is used to record changes in activity from one brain area to another and is 80 to 90 percent successful in classifying subjects as dyslexic or normal. (MT)
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
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.
Functional parcellation using time courses of instantaneous connectivity.
van Oort, Erik S B; Mennes, Maarten; Navarro Schröder, Tobias; Kumar, Vinod J; Zaragoza Jimenez, Nestor I; Grodd, Wolfgang; Doeller, Christian F; Beckmann, Christian F
2018-04-15
Functional neuroimaging studies have led to understanding the brain as a collection of spatially segregated functional networks. It is thought that each of these networks is in turn composed of a set of distinct sub-regions that together support each network's function. Considering the sub-regions to be an essential part of the brain's functional architecture, several strategies have been put forward that aim at identifying the functional sub-units of the brain by means of functional parcellations. Current parcellation strategies typically employ a bottom-up strategy, creating a parcellation by clustering smaller units. We propose a novel top-down parcellation strategy, using time courses of instantaneous connectivity to subdivide an initial region of interest into sub-regions. We use split-half reproducibility to choose the optimal number of sub-regions. We apply our Instantaneous Connectivity Parcellation (ICP) strategy on high-quality resting-state FMRI data, and demonstrate the ability to generate parcellations for thalamus, entorhinal cortex, motor cortex, and subcortex including brainstem and striatum. We evaluate the subdivisions against available cytoarchitecture maps to show that our parcellation strategy recovers biologically valid subdivisions that adhere to known cytoarchitectural features. Copyright © 2017 Elsevier Inc. All rights reserved.
Tsuchiya, Mariko; Amano, Kojiro; Abe, Masaya; Seki, Misato; Hase, Sumitaka; Sato, Kengo; Sakakibara, Yasubumi
2016-06-15
Deep sequencing of the transcripts of regulatory non-coding RNA generates footprints of post-transcriptional processes. After obtaining sequence reads, the short reads are mapped to a reference genome, and specific mapping patterns can be detected called read mapping profiles, which are distinct from random non-functional degradation patterns. These patterns reflect the maturation processes that lead to the production of shorter RNA sequences. Recent next-generation sequencing studies have revealed not only the typical maturation process of miRNAs but also the various processing mechanisms of small RNAs derived from tRNAs and snoRNAs. We developed an algorithm termed SHARAKU to align two read mapping profiles of next-generation sequencing outputs for non-coding RNAs. In contrast with previous work, SHARAKU incorporates the primary and secondary sequence structures into an alignment of read mapping profiles to allow for the detection of common processing patterns. Using a benchmark simulated dataset, SHARAKU exhibited superior performance to previous methods for correctly clustering the read mapping profiles with respect to 5'-end processing and 3'-end processing from degradation patterns and in detecting similar processing patterns in deriving the shorter RNAs. Further, using experimental data of small RNA sequencing for the common marmoset brain, SHARAKU succeeded in identifying the significant clusters of read mapping profiles for similar processing patterns of small derived RNA families expressed in the brain. The source code of our program SHARAKU is available at http://www.dna.bio.keio.ac.jp/sharaku/, and the simulated dataset used in this work is available at the same link. Accession code: The sequence data from the whole RNA transcripts in the hippocampus of the left brain used in this work is available from the DNA DataBank of Japan (DDBJ) Sequence Read Archive (DRA) under the accession number DRA004502. yasu@bio.keio.ac.jp Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.
Systems Neuroscience of Psychosis: Mapping Schizophrenia Symptoms onto Brain Systems.
Strik, Werner; Stegmayer, Katharina; Walther, Sebastian; Dierks, Thomas
2017-01-01
Schizophrenia research has been in a deadlock for many decades. Despite important advances in clinical treatment, there are still major concerns regarding long-term psychosocial reintegration and disease management, biological heterogeneity, unsatisfactory predictors of individual course and treatment strategies, and a confusing variety of controversial theories about its etiology and pathophysiological mechanisms. In the present perspective on schizophrenia research, we first discuss a methodological pitfall in contemporary schizophrenia research inherent in the attempt to link mental phenomena with the brain: we claim that the time-honored phenomenological method of defining mental symptoms should not be contaminated with the naturalistic approach of modern neuroscience. We then describe our Systems Neuroscience of Psychosis (SyNoPsis) project, which aims to overcome this intrinsic problem of psychiatric research. Considering schizophrenia primarily as a disorder of interindividual communication, we developed a neurobiologically informed semiotics of psychotic disorders, as well as an operational clinical rating scale. The novel psychopathology allows disentangling the clinical manifestations of schizophrenia into behavioral domains matching the functions of three well-described higher-order corticobasal brain systems involved in interindividual human communication, namely, the limbic, associative, and motor loops, including their corticocortical sensorimotor connections. The results of several empirical studies support the hypothesis that the proposed three-dimensional symptom structure, segregated into the affective, the language, and the motor domain, can be specifically mapped onto structural and functional abnormalities of the respective brain systems. New pathophysiological hypotheses derived from this brain system-oriented approach have helped to develop and improve novel treatment strategies with noninvasive brain stimulation and practicable clinical parameters. In clinical practice, the novel psychopathology allows confining the communication deficits of the individual patient, shifting attention from the symptoms to the intact resources. We have studied this approach and observed important advantages for therapeutic alliances, personalized treatment, and de-escalation strategies. Future studies will further conjoin clinical definitions of psychotic symptoms with brain structures and functions, and disentangle structural and functional deficit patterns within these systems to identify neurobiologically distinct subsyndromes. Neurobiologically homogeneous patient groups may provide new momentum for treatment research. Finally, lessons learned from schizophrenia research may contribute to developing a comprehensive perspective on human experience and behavior that integrates methodologically distinct, but internally consistent, insights from humanities and neuroscience. © 2017 S. Karger AG, Basel.
Marshall, Peter J.; Meltzoff, Andrew N.
2015-01-01
Researchers have examined representations of the body in the adult brain, but relatively little attention has been paid to ontogenetic aspects of neural body maps in human infants. Novel applications of methods for recording brain activity in infants are delineating cortical body maps in the first months of life. Body maps may facilitate infants’ registration of similarities between self and other—an ability that is foundational to developing social cognition. Alterations in interpersonal aspects of body representations might also contribute to social deficits in certain neurodevelopmental disorders. PMID:26231760
Hyperbrain features of team mental models within a juggling paradigm: a proof of concept
Filho, Edson; Tamburro, Gabriella; Schinaia, Lorenzo; Chatel-Goldman, Jonas; di Fronso, Selenia; Robazza, Claudio
2016-01-01
Background Research on cooperative behavior and the social brain exists, but little research has focused on real-time motor cooperative behavior and its neural correlates. In this proof of concept study, we explored the conceptual notion of shared and complementary mental models through EEG mapping of two brains performing a real-world interactive motor task of increasing difficulty. We used the recently introduced participative “juggling paradigm,” and collected neuro-physiological and psycho-social data. We were interested in analyzing the between-brains coupling during a dyadic juggling task, and in exploring the relationship between the motor task execution, the jugglers’skill level and the task difficulty. We also investigated how this relationship could be mirrored in the coupled functional organization of the interacting brains. Methods To capture the neural schemas underlying the notion of shared and complementary mental models, we examined the functional connectivity patterns and hyperbrain features of a juggling dyad involved in cooperative motor tasks of increasing difficulty. Jugglers’ cortical activity was measured using two synchronized 32-channel EEG systems during dyadic juggling performed with 3, 4, 5 and 6 balls. Individual and hyperbrain functional connections were quantified through coherence maps calculated across all electrode pairs in the theta and alpha bands (4–8 and 8–12 Hz). Graph metrics were used to typify the global topology and efficiency of the functional networks for the four difficulty levels in the theta and alpha bands. Results Results indicated that, as task difficulty increased, the cortical functional organization of the more skilled juggler became progressively more segregated in both frequency bands, with a small-world organization in the theta band during easier tasks, indicative of a flow-like state in line with the neural efficiency hypothesis. Conversely, more integrated functional patterns were observed for the less skilled juggler in both frequency bands, possibly related to cognitive overload due to the difficulty of the task at hand (reinvestment hypothesis). At the hyperbrain level, a segregated functional organization involving areas of the visuo-attentional networks of both jugglers was observed in both frequency bands and for the easier task only. Discussion These results suggest that cooperative juggling is supported by integrated activity of specialized cortical areas from both brains only during easier tasks, whereas it relies on individual skills, mirrored in uncorrelated individual brain activations, during more difficult tasks. These findings suggest that task difficulty and jugglers’ personal skills may influence the features of the hyperbrain network in its shared/integrative and complementary/segregative tendencies. PMID:27688968
Wilson, Maximiliano A; Joubert, Sven; Ferré, Perrine; Belleville, Sylvie; Ansaldo, Ana Inés; Joanette, Yves; Rouleau, Isabelle; Brambati, Simona Maria
2012-05-01
Semantic dementia (SD) is a neurodegenerative disease that occurs following the atrophy of the anterior temporal lobes (ATLs). It is characterised by the degradation of semantic knowledge and difficulties in reading exception words (surface dyslexia). This disease has highlighted the role of the ATLs in the process of exception word reading. However, imaging studies in healthy subjects have failed to detect activation of the ATLs during exception word reading. The aim of the present study was to test whether the functional brain regions that mediate exception word reading in normal readers overlap those brain regions atrophied in SD. In Study One, we map the brain regions of grey matter atrophy in AF, a patient with mild SD and surface dyslexia profile. In Study Two, we map the activation pattern associated with exception word compared to pseudoword reading in young, healthy participants using fMRI. The results revealed areas of significant activation in healthy subjects engaged in the exception word reading task in the left anterior middle temporal gyrus, in a region observed to be atrophic in the patient AF. These results reconcile neuropsychological and functional imaging data, revealing the critical role of the left ATL in exception word reading. Copyright © 2012 Elsevier Inc. All rights reserved.
Bahrami, Sheyda; Shamsi, Mousa
2017-01-01
Functional magnetic resonance imaging (fMRI) is a popular method to probe the functional organization of the brain using hemodynamic responses. In this method, volume images of the entire brain are obtained with a very good spatial resolution and low temporal resolution. However, they always suffer from high dimensionality in the face of classification algorithms. In this work, we combine a support vector machine (SVM) with a self-organizing map (SOM) for having a feature-based classification by using SVM. Then, a linear kernel SVM is used for detecting the active areas. Here, we use SOM for feature extracting and labeling the datasets. SOM has two major advances: (i) it reduces dimension of data sets for having less computational complexity and (ii) it is useful for identifying brain regions with small onset differences in hemodynamic responses. Our non-parametric model is compared with parametric and non-parametric methods. We use simulated fMRI data sets and block design inputs in this paper and consider the contrast to noise ratio (CNR) value equal to 0.6 for simulated datasets. fMRI simulated dataset has contrast 1-4% in active areas. The accuracy of our proposed method is 93.63% and the error rate is 6.37%.
fMRI mapping of the visual system in the mouse brain with interleaved snapshot GE-EPI.
Niranjan, Arun; Christie, Isabel N; Solomon, Samuel G; Wells, Jack A; Lythgoe, Mark F
2016-10-01
The use of functional magnetic resonance imaging (fMRI) in mice is increasingly prevalent, providing a means to non-invasively characterise functional abnormalities associated with genetic models of human diseases. The predominant stimulus used in task-based fMRI in the mouse is electrical stimulation of the paw. Task-based fMRI in mice using visual stimuli remains underexplored, despite visual stimuli being common in human fMRI studies. In this study, we map the mouse brain visual system with BOLD measurements at 9.4T using flashing light stimuli with medetomidine anaesthesia. BOLD responses were observed in the lateral geniculate nucleus, the superior colliculus and the primary visual area of the cortex, and were modulated by the flashing frequency, diffuse vs focussed light and stimulus context. Negative BOLD responses were measured in the visual cortex at 10Hz flashing frequency; but turned positive below 5Hz. In addition, the use of interleaved snapshot GE-EPI improved fMRI image quality without diminishing the temporal contrast-noise-ratio. Taken together, this work demonstrates a novel methodological protocol in which the mouse brain visual system can be non-invasively investigated using BOLD fMRI. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Quantile rank maps: a new tool for understanding individual brain development.
Chen, Huaihou; Kelly, Clare; Castellanos, F Xavier; He, Ye; Zuo, Xi-Nian; Reiss, Philip T
2015-05-01
We propose a novel method for neurodevelopmental brain mapping that displays how an individual's values for a quantity of interest compare with age-specific norms. By estimating smoothly age-varying distributions at a set of brain regions of interest, we derive age-dependent region-wise quantile ranks for a given individual, which can be presented in the form of a brain map. Such quantile rank maps could potentially be used for clinical screening. Bootstrap-based confidence intervals are proposed for the quantile rank estimates. We also propose a recalibrated Kolmogorov-Smirnov test for detecting group differences in the age-varying distribution. This test is shown to be more robust to model misspecification than a linear regression-based test. The proposed methods are applied to brain imaging data from the Nathan Kline Institute Rockland Sample and from the Autism Brain Imaging Data Exchange (ABIDE) sample. Copyright © 2015 Elsevier Inc. All rights reserved.
Typical and atypical brain development: a review of neuroimaging studies
Dennis, Emily L.; Thompson, Paul M.
2013-01-01
In the course of development, the brain undergoes a remarkable process of restructuring as it adapts to the environment and becomes more efficient in processing information. A variety of brain imaging methods can be used to probe how anatomy, connectivity, and function change in the developing brain. Here we review recent discoveries regarding these brain changes in both typically developing individuals and individuals with neurodevelopmental disorders. We begin with typical development, summarizing research on changes in regional brain volume and tissue density, cortical thickness, white matter integrity, and functional connectivity. Space limits preclude the coverage of all neurodevelopmental disorders; instead, we cover a representative selection of studies examining neural correlates of autism, attention deficit/hyperactivity disorder, Fragile X, 22q11.2 deletion syndrome, Williams syndrome, Down syndrome, and Turner syndrome. Where possible, we focus on studies that identify an age by diagnosis interaction, suggesting an altered developmental trajectory. The studies we review generally cover the developmental period from infancy to early adulthood. Great progress has been made over the last 20 years in mapping how the brain matures with MR technology. With ever-improving technology, we expect this progress to accelerate, offering a deeper understanding of brain development, and more effective interventions for neurodevelopmental disorders. PMID:24174907
Typical and atypical brain development: a review of neuroimaging studies.
Dennis, Emily L; Thompson, Paul M
2013-09-01
In the course of development, the brain undergoes a remarkable process of restructuring as it adapts to the environment and becomes more efficient in processing information. A variety of brain imaging methods can be used to probe how anatomy, connectivity, and function change in the developing brain. Here we review recent discoveries regarding these brain changes in both typically developing individuals and individuals with neurodevelopmental disorders. We begin with typical development, summarizing research on changes in regional brain volume and tissue density, cortical thickness, white matter integrity, and functional connectivity. Space limits preclude the coverage of all neurodevelopmental disorders; instead, we cover a representative selection of studies examining neural correlates of autism, attention deficit/hyperactivity disorder, Fragile X, 22q11.2 deletion syndrome, Williams syndrome, Down syndrome, and Turner syndrome. Where possible, we focus on studies that identify an age by diagnosis interaction, suggesting an altered developmental trajectory. The studies we review generally cover the developmental period from infancy to early adulthood. Great progress has been made over the last 20 years in mapping how the brain matures with MR technology. With ever-improving technology, we expect this progress to accelerate, offering a deeper understanding of brain development, and more effective interventions for neurodevelopmental disorders.
Resting state cerebral blood flow with arterial spin labeling MRI in developing human brains.
Liu, Feng; Duan, Yunsuo; Peterson, Bradley S; Asllani, Iris; Zelaya, Fernando; Lythgoe, David; Kangarlu, Alayar
2018-07-01
The development of brain circuits is coupled with changes in neurovascular coupling, which refers to the close relationship between neural activity and cerebral blood flow (CBF). Studying the characteristics of CBF during resting state in developing brain can be a complementary way to understand the functional connectivity of the developing brain. Arterial spin labeling (ASL), as a noninvasive MR technique, is particularly attractive for studying cerebral perfusion in children and even newborns. We have collected pulsed ASL data in resting state for 47 healthy subjects from young children to adolescence (aged from 6 to 20 years old). In addition to studying the developmental change of static CBF maps during resting state, we also analyzed the CBF time series to reveal the dynamic characteristics of CBF in differing age groups. We used the seed-based correlation analysis to examine the temporal relationship of CBF time series between the selected ROIs and other brain regions. We have shown the developmental patterns in both static CBF maps and dynamic characteristics of CBF. While higher CBF of default mode network (DMN) in all age groups supports that DMN is the prominent active network during the resting state, the CBF connectivity patterns of some typical resting state networks show distinct patterns of metabolic activity during the resting state in the developing brains. Copyright © 2018 European Paediatric Neurology Society. All rights reserved.
Lan, Chen-Chia; Tsai, Shih-Jen; Huang, Chu-Chung; Wang, Ying-Hsiu; Chen, Tong-Ru; Yeh, Heng-Liang; Liu, Mu-En; Lin, Ching-Po; Yang, Albert C.
2016-01-01
Background: Depression and loneliness are prevalent and highly correlated phenomena among the elderly and influence both physical and mental health. Brain functional connectivity changes associated with depressive symptoms and loneliness are not fully understood. Methods: A cross-sectional functional MRI study was conducted among 85 non-demented male elders. Geriatric depression scale-short form (GDS) and loneliness scale were used to evaluate the severity of depressive symptoms and loneliness, respectively. Whole brain voxel-wise resting-state functional connectivity density (FCD) mapping was performed to delineate short-range FCD (SFCD) and long-range FCD (LFCD). Regional correlations between depressive symptoms or loneliness and SFCD or LFCD were examined using general linear model (GLM), with age incorporated as a covariate and depressive symptoms and loneliness as predictors. Results: Positive correlations between depressive symptoms and LFCD were observed in left rectal gyrus, left superior frontal gyrus, right supraorbital gyrus, and left inferior temporal gyrus. Positive correlations between depressive symptoms and SFCD were observed in left middle frontal gyrus, left superior frontal gyrus, bilateral superior medial frontal gyrus, left inferior temporal gyrus, and left middle occipital region. Positive correlations between SFCD and loneliness were centered over bilateral lingual gyrus. Conclusion: Depressive symptoms are associated with FCD changes over frontal and temporal regions, which may involve the cognitive control, affective regulation, and default mode networks. Loneliness is associated with FCD changes in bilateral lingual gyri that are known to be important in social cognition. Depressive symptoms and loneliness may be associated with different brain regions in non-demented elderly male. PMID:26793101
Yamaguchi, Shinji; Katagiri, Sachiko; Aoki, Naoya; Iikubo, Eiji; Kitajima, Takaaki; Matsushima, Toshiya; Homma, Koichi J
2011-01-01
RNA interference (RNAi)-mediated gene-silencing can be a tool for elucidating the role of genes in the neural basis of behavioral plasticity. Previously, we reported that exogenous DNA could be successfully delivered into newly-hatched chick brains via electroporation. Here, we used this in vivo gene-transfer technique and showed that transfected microRNA vectors preferentially silence exogenous DNA expression in neuronal cells. Using this system, the up-regulation of microtubule-associated protein 2 (MAP2) accompanying filial imprinting was suppressed in vivo, which impaired the filial imprinting in chicks. In addition, the phosphorylation of MAP2 was found to increase in parallel with filial imprinting, and lithium chloride, an inhibitor of glycogen synthase kinase 3 (GSK3), was found to impair filial imprinting. Our results suggest that the regulation of MAP2 expression and its phosphorylation are required for filial imprinting and may modify microtubule stability, thereby leading to cytoskeletal reorganization during imprinting. This in vivo RNAi-mediated gene-silencing system will facilitate the analysis of gene function in the living chick brain and provides further clues regarding the molecular mechanisms underpinning avian learning. Copyright © 2010 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.