Is the spatial distribution of brain lesions associated with closed-head injury predictive of subsequent development of attention-deficit/hyperactivity disorder? Analysis with brain-image database

NASA Technical Reports Server (NTRS)

Herskovits, E. H.; Megalooikonomou, V.; Davatzikos, C.; Chen, A.; Bryan, R. N.; Gerring, J. P.

1999-01-01

PURPOSE: To determine whether there is an association between the spatial distribution of lesions detected at magnetic resonance (MR) imaging of the brain in children after closed-head injury and the development of secondary attention-deficit/hyperactivity disorder (ADHD). MATERIALS AND METHODS: Data obtained from 76 children without prior history of ADHD were analyzed. MR images were obtained 3 months after closed-head injury. After manual delineation of lesions, images were registered to the Talairach coordinate system. For each subject, registered images and secondary ADHD status were integrated into a brain-image database, which contains depiction (visualization) and statistical analysis software. Using this database, we assessed visually the spatial distributions of lesions and performed statistical analysis of image and clinical variables. RESULTS: Of the 76 children, 15 developed secondary ADHD. Depiction of the data suggested that children who developed secondary ADHD had more lesions in the right putamen than children who did not develop secondary ADHD; this impression was confirmed statistically. After Bonferroni correction, we could not demonstrate significant differences between secondary ADHD status and lesion burdens for the right caudate nucleus or the right globus pallidus. CONCLUSION: Closed-head injury-induced lesions in the right putamen in children are associated with subsequent development of secondary ADHD. Depiction software is useful in guiding statistical analysis of image data.

Harmonic Brain Modes: A Unifying Framework for Linking Space and Time in Brain Dynamics.

PubMed

Atasoy, Selen; Deco, Gustavo; Kringelbach, Morten L; Pearson, Joel

2018-06-01

A fundamental characteristic of spontaneous brain activity is coherent oscillations covering a wide range of frequencies. Interestingly, these temporal oscillations are highly correlated among spatially distributed cortical areas forming structured correlation patterns known as the resting state networks, although the brain is never truly at "rest." Here, we introduce the concept of harmonic brain modes-fundamental building blocks of complex spatiotemporal patterns of neural activity. We define these elementary harmonic brain modes as harmonic modes of structural connectivity; that is, connectome harmonics, yielding fully synchronous neural activity patterns with different frequency oscillations emerging on and constrained by the particular structure of the brain. Hence, this particular definition implicitly links the hitherto poorly understood dimensions of space and time in brain dynamics and its underlying anatomy. Further we show how harmonic brain modes can explain the relationship between neurophysiological, temporal, and network-level changes in the brain across different mental states ( wakefulness, sleep, anesthesia, psychedelic). Notably, when decoded as activation of connectome harmonics, spatial and temporal characteristics of neural activity naturally emerge from the interplay between excitation and inhibition and this critical relation fits the spatial, temporal, and neurophysiological changes associated with different mental states. Thus, the introduced framework of harmonic brain modes not only establishes a relation between the spatial structure of correlation patterns and temporal oscillations (linking space and time in brain dynamics), but also enables a new dimension of tools for understanding fundamental principles underlying brain dynamics in different states of consciousness.

Three-dimensional distribution of cortical synapses: a replicated point pattern-based analysis

PubMed Central

Anton-Sanchez, Laura; Bielza, Concha; Merchán-Pérez, Angel; Rodríguez, José-Rodrigo; DeFelipe, Javier; Larrañaga, Pedro

2014-01-01

The biggest problem when analyzing the brain is that its synaptic connections are extremely complex. Generally, the billions of neurons making up the brain exchange information through two types of highly specialized structures: chemical synapses (the vast majority) and so-called gap junctions (a substrate of one class of electrical synapse). Here we are interested in exploring the three-dimensional spatial distribution of chemical synapses in the cerebral cortex. Recent research has showed that the three-dimensional spatial distribution of synapses in layer III of the neocortex can be modeled by a random sequential adsorption (RSA) point process, i.e., synapses are distributed in space almost randomly, with the only constraint that they cannot overlap. In this study we hypothesize that RSA processes can also explain the distribution of synapses in all cortical layers. We also investigate whether there are differences in both the synaptic density and spatial distribution of synapses between layers. Using combined focused ion beam milling and scanning electron microscopy (FIB/SEM), we obtained three-dimensional samples from the six layers of the rat somatosensory cortex and identified and reconstructed the synaptic junctions. A total volume of tissue of approximately 4500μm3 and around 4000 synapses from three different animals were analyzed. Different samples, layers and/or animals were aggregated and compared using RSA replicated spatial point processes. The results showed no significant differences in the synaptic distribution across the different rats used in the study. We found that RSA processes described the spatial distribution of synapses in all samples of each layer. We also found that the synaptic distribution in layers II to VI conforms to a common underlying RSA process with different densities per layer. Interestingly, the results showed that synapses in layer I had a slightly different spatial distribution from the other layers. PMID:25206325

Three-dimensional distribution of cortical synapses: a replicated point pattern-based analysis.

PubMed

Anton-Sanchez, Laura; Bielza, Concha; Merchán-Pérez, Angel; Rodríguez, José-Rodrigo; DeFelipe, Javier; Larrañaga, Pedro

2014-01-01

The biggest problem when analyzing the brain is that its synaptic connections are extremely complex. Generally, the billions of neurons making up the brain exchange information through two types of highly specialized structures: chemical synapses (the vast majority) and so-called gap junctions (a substrate of one class of electrical synapse). Here we are interested in exploring the three-dimensional spatial distribution of chemical synapses in the cerebral cortex. Recent research has showed that the three-dimensional spatial distribution of synapses in layer III of the neocortex can be modeled by a random sequential adsorption (RSA) point process, i.e., synapses are distributed in space almost randomly, with the only constraint that they cannot overlap. In this study we hypothesize that RSA processes can also explain the distribution of synapses in all cortical layers. We also investigate whether there are differences in both the synaptic density and spatial distribution of synapses between layers. Using combined focused ion beam milling and scanning electron microscopy (FIB/SEM), we obtained three-dimensional samples from the six layers of the rat somatosensory cortex and identified and reconstructed the synaptic junctions. A total volume of tissue of approximately 4500μm(3) and around 4000 synapses from three different animals were analyzed. Different samples, layers and/or animals were aggregated and compared using RSA replicated spatial point processes. The results showed no significant differences in the synaptic distribution across the different rats used in the study. We found that RSA processes described the spatial distribution of synapses in all samples of each layer. We also found that the synaptic distribution in layers II to VI conforms to a common underlying RSA process with different densities per layer. Interestingly, the results showed that synapses in layer I had a slightly different spatial distribution from the other layers.

AP-MALDI Mass Spectrometry Imaging of Gangliosides Using 2,6-Dihydroxyacetophenone

NASA Astrophysics Data System (ADS)

Jackson, Shelley N.; Muller, Ludovic; Roux, Aurelie; Oktem, Berk; Moskovets, Eugene; Doroshenko, Vladimir M.; Woods, Amina S.

2018-03-01

Matrix-assisted laser/desorption ionization (MALDI) mass spectrometry imaging (MSI) is widely used as a unique tool to record the distribution of a large range of biomolecules in tissues. 2,6-Dihydroxyacetophenone (DHA) matrix has been shown to provide efficient ionization of lipids, especially gangliosides. The major drawback for DHA as it applies to MS imaging is that it sublimes under vacuum (low pressure) at the extended time necessary to complete both high spatial and mass resolution MSI studies of whole organs. To overcome the problem of sublimation, we used an atmospheric pressure (AP)-MALDI source to obtain high spatial resolution images of lipids in the brain using a high mass resolution mass spectrometer. Additionally, the advantages of atmospheric pressure and DHA for imaging gangliosides are highlighted. The imaging of [M-H]- and [M-H2O-H]- mass peaks for GD1 gangliosides showed different distribution, most likely reflecting the different spatial distribution of GD1a and GD1b species in the brain. [Figure not available: see fulltext.

Distribution of RF energy emitted by mobile phones in anatomical structures of the brain.

PubMed

Cardis, E; Deltour, I; Mann, S; Moissonnier, M; Taki, M; Varsier, N; Wake, K; Wiart, J

2008-06-07

The rapid worldwide increase in mobile phone use in the last decade has generated considerable interest in possible carcinogenic effects of radio frequency (RF). Because exposure to RF from phones is localized, if a risk exists it is likely to be greatest for tumours in regions with greatest energy absorption. The objective of the current paper was to characterize the spatial distribution of RF energy in the brain, using results of measurements made in two laboratories on 110 phones used in Europe or Japan. Most (97-99% depending on frequency) appears to be absorbed in the brain hemisphere on the side where the phone is used, mainly (50-60%) in the temporal lobe. The average relative SAR is highest in the temporal lobe (6-15%, depending on frequency, of the spatial peak SAR in the most exposed region of the brain) and the cerebellum (2-10%) and decreases very rapidly with increasing depth, particularly at higher frequencies. The SAR distribution appears to be fairly similar across phone models, between older and newer phones and between phones with different antenna types and positions. Analyses of risk by location of tumour are therefore important for the interpretation of results of studies of brain tumours in relation to mobile phone use.

Anatomical and functional assemblies of brain BOLD oscillations

PubMed Central

Baria, Alexis T.; Baliki, Marwan N.; Parrish, Todd; Apkarian, A. Vania

2011-01-01

Brain oscillatory activity has long been thought to have spatial properties, the details of which are unresolved. Here we examine spatial organizational rules for the human brain oscillatory activity as measured by blood oxygen level-dependent (BOLD). Resting state BOLD signal was transformed into frequency space (Welch’s method), averaged across subjects, and its spatial distribution studied as a function of four frequency bands, spanning the full bandwidth of BOLD. The brain showed anatomically constrained distribution of power for each frequency band. This result was replicated on a repository dataset of 195 subjects. Next, we examined larger-scale organization by parceling the neocortex into regions approximating Brodmann Areas (BAs). This indicated that BAs of simple function/connectivity (unimodal), vs. complex properties (transmodal), are dominated by low frequency BOLD oscillations, and within the visual ventral stream we observe a graded shift of power to higher frequency bands for BAs further removed from the primary visual cortex (increased complexity), linking frequency properties of BOLD to hodology. Additionally, BOLD oscillation properties for the default mode network demonstrated that it is composed of distinct frequency dependent regions. When the same analysis was performed on a visual-motor task, frequency-dependent global and voxel-wise shifts in BOLD oscillations could be detected at brain sites mostly outside those identified with general linear modeling. Thus, analysis of BOLD oscillations in full bandwidth uncovers novel brain organizational rules, linking anatomical structures and functional networks to characteristic BOLD oscillations. The approach also identifies changes in brain intrinsic properties in relation to responses to external inputs. PMID:21613505

A mass spectrometry imaging approach for investigating how drug-drug interactions influence drug blood-brain barrier permeability.

PubMed

Vallianatou, Theodosia; Strittmatter, Nicole; Nilsson, Anna; Shariatgorji, Mohammadreza; Hamm, Gregory; Pereira, Marcela; Källback, Patrik; Svenningsson, Per; Karlgren, Maria; Goodwin, Richard J A; Andrén, Per E

2018-05-15

There is a high need to develop quantitative imaging methods capable of providing detailed brain localization information of several molecular species simultaneously. In addition, extensive information on the effect of the blood-brain barrier on the penetration, distribution and efficacy of neuroactive compounds is required. Thus, we have developed a mass spectrometry imaging method to visualize and quantify the brain distribution of drugs with varying blood-brain barrier permeability. With this approach, we were able to determine blood-brain barrier transport of different drugs and define the drug distribution in very small brain structures (e.g., choroid plexus) due to the high spatial resolution provided. Simultaneously, we investigated the effect of drug-drug interactions by inhibiting the membrane transporter multidrug resistance 1 protein. We propose that the described approach can serve as a valuable analytical tool during the development of neuroactive drugs, as it can provide physiologically relevant information often neglected by traditional imaging technologies. Copyright © 2018. Published by Elsevier Inc.

P300 event-related potentials in children with dyslexia.

PubMed

Papagiannopoulou, Eleni A; Lagopoulos, Jim

2017-04-01

To elucidate the timing and the nature of neural disturbances in dyslexia and to further understand the topographical distribution of these, we examined entire brain regions employing the non-invasive auditory oddball P300 paradigm in children with dyslexia and neurotypical controls. Our findings revealed abnormalities for the dyslexia group in (i) P300 latency, globally, but greatest in frontal brain regions and (ii) decreased P300 amplitude confined to the central brain regions (Fig. 1). These findings reflect abnormalities associated with a diminished capacity to process mental workload as well as delayed processing of this information in children with dyslexia. Furthermore, the topographical distribution of these findings suggests a distinct spatial distribution for the observed P300 abnormalities. This information may be useful in future therapeutic or brain stimulation intervention trials.

Neural Correlates of Music Recognition in Down Syndrome

ERIC Educational Resources Information Center

Virji-Babul, N.; Moiseev, A.; Sun, W.; Feng, T.; Moiseeva, N.; Watt, K. J.; Huotilainen, M.

2013-01-01

The brain mechanisms that subserve music recognition remain unclear despite increasing interest in this process. Here we report the results of a magnetoencephalography experiment to determine the temporal dynamics and spatial distribution of brain regions activated during listening to a familiar and unfamiliar instrumental melody in control adults…

Electrophysiological Source Imaging: A Noninvasive Window to Brain Dynamics.

PubMed

He, Bin; Sohrabpour, Abbas; Brown, Emery; Liu, Zhongming

2018-06-04

Brain activity and connectivity are distributed in the three-dimensional space and evolve in time. It is important to image brain dynamics with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive measurements associated with complex neural activations and interactions that encode brain functions. Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. It offers increasingly improved spatial resolution and intrinsically high temporal resolution for imaging large-scale brain activity and connectivity on a wide range of timescales. Integration of electrophysiological source imaging and functional magnetic resonance imaging could further enhance spatiotemporal resolution and specificity to an extent that is not attainable with either technique alone. We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic and clinical neuroscience applications.

Techniques for the Cellular and Subcellular Localization of Endocannabinoid Receptors and Enzymes in the Mammalian Brain.

PubMed

Cristino, Luigia; Imperatore, Roberta; Di Marzo, Vincenzo

2017-01-01

This chapter attempts to piece together knowledge about new advanced microscopy techniques to study the neuroanatomical distribution of endocannabinoid receptors and enzymes at the level of cellular and subcellular structures and organelles in the brain. Techniques ranging from light to electron microscopy up to the new advanced LBM, PALM, and STORM super-resolution microscopy will be discussed in the context of their contribution to define the spatial distribution and organization of receptors and enzymes of the endocannabinoid system (ECS), and to better understand ECS brain functions. © 2017 Elsevier Inc. All rights reserved.

Tissue distribution of pretomanid in rat brain via mass spectrometry imaging.

PubMed

Shobo, Adeola; Bratkowska, Dominika; Baijnath, Sooraj; Naiker, Suhashni; Somboro, Anou M; Bester, Linda A; Singh, Sanil D; Naicker, Tricia; Kruger, Hendrik G; Govender, Thavendran

2016-01-01

1. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) combines the sensitivity and selectivity of mass spectrometry with spatial analysis to provide a new dimension for histological analyses of the distribution of drugs in tissue. Pretomanid is a pro-drug belonging to a class of antibiotics known as nitroimidizoles, which have been proven to be active under hypoxic conditions and to the best of our knowledge there have been no studies investigating the distribution and localisation of this class of compounds in the brain using MALDI MSI. 2. Herein, we report on the distribution of pretomanid in the healthy rat brain after intraperitoneal administration (20 mg/kg) using MALDI MSI. Our findings showed that the drug localises in specific compartments of the rat brain viz. the corpus callosum, a dense network of neurons connecting left and right cerebral hemispheres. 3. This study proves that MALDI MSI technique has great potential for mapping the pretomanid distribution in uninfected tissue samples, without the need for molecular labelling.

Distribution of RF energy emitted by mobile phones in anatomical structures of the brain

NASA Astrophysics Data System (ADS)

Cardis, E.; Deltour, I.; Mann, S.; Moissonnier, M.; Taki, M.; Varsier, N.; Wake, K.; Wiart, J.

2008-06-01

The rapid worldwide increase in mobile phone use in the last decade has generated considerable interest in possible carcinogenic effects of radio frequency (RF). Because exposure to RF from phones is localized, if a risk exists it is likely to be greatest for tumours in regions with greatest energy absorption. The objective of the current paper was to characterize the spatial distribution of RF energy in the brain, using results of measurements made in two laboratories on 110 phones used in Europe or Japan. Most (97-99% depending on frequency) appears to be absorbed in the brain hemisphere on the side where the phone is used, mainly (50-60%) in the temporal lobe. The average relative SARSAR is the specific energy absorption rate i.e. energy absorption rate per unit mass (measured in W kg-1). is highest in the temporal lobe (6-15%, depending on frequency, of the spatial peak SAR in the most exposed region of the brain) and the cerebellum (2-10%) and decreases very rapidly with increasing depth, particularly at higher frequencies. The SAR distribution appears to be fairly similar across phone models, between older and newer phones and between phones with different antenna types and positions. Analyses of risk by location of tumour are therefore important for the interpretation of results of studies of brain tumours in relation to mobile phone use.

Trace element distribution in the rat cerebellum

NASA Astrophysics Data System (ADS)

Kwiatek, W. M.; Long, G. J.; Pounds, J. G.; Reuhl, K. R.; Hanson, A. L.; Jones, K. W.

1990-04-01

Spatial distributions and concentrations of trace elements (TE) in the brain are important because TE perform catalytic and structural functions in enzymes which regulate brain function and development. We have investigated the distributions of TE in rat cerebellum. Structures were sectioned and analyzed by the Synchrotron Radiation Induced X-ray Emission (SRIXE) method using the NSLS X-26 white-light microprobe facility. Advantages important for TE analysis of biological specimens with X-ray microscopy include short time of measurement, high brightness and flux, good spatial resolution, multielemental detection, good sensitivity, and nondestructive irradiation. Trace elements were measured in thin rat brain sections of 20 μm thickness. The analyses were performed on sample volumes as small as 0.2 nl with Minimum Detectable Limits (MDL) of 50 ppb wet weight for Fe, 100 ppb wet weight for Cu, and Zn, and 1 ppm wet weight for Pb. The distribution of TE in the molecular cell layer, granule cell layer and fiber tract of rat cerebella was investigated. Both point analyses and two-dimensional semiquantitative mapping of the TE distribution in a section were used. All analyzed elements were observed in each structure of the cerebellum except mercury which was not observed in granule cell layer or fiber tract. This approach permits an exacting correlation of the TE distribution in complex structure with the diet, toxic elements, and functional status of the animal.

Breakdown in the temporal and spatial organization of spontaneous brain activity during general anesthesia.

PubMed

Zhang, Jianfeng; Huang, Zirui; Chen, Yali; Zhang, Jun; Ghinda, Diana; Nikolova, Yuliya; Wu, Jinsong; Xu, Jianghui; Bai, Wenjie; Mao, Ying; Yang, Zhong; Duncan, Niall; Qin, Pengmin; Wang, Hao; Chen, Bing; Weng, Xuchu; Northoff, Georg

2018-05-01

Which temporal features that can characterize different brain states (i.e., consciousness or unconsciousness) is a fundamental question in the neuroscience of consciousness. Using resting-state functional magnetic resonance imaging (rs-fMRI), we investigated the spatial patterns of two temporal features: the long-range temporal correlations (LRTCs), measured by power-law exponent (PLE), and temporal variability, measured by standard deviation (SD) during wakefulness and anesthetic-induced unconsciousness. We found that both PLE and SD showed global reductions across the whole brain during anesthetic state comparing to wakefulness. Importantly, the relationship between PLE and SD was altered in anesthetic state, in terms of a spatial "decoupling." This decoupling was mainly driven by a spatial pattern alteration of the PLE, rather than the SD, in the anesthetic state. Our results suggest differential physiological grounds of PLE and SD and highlight the functional importance of the topographical organization of LRTCs in maintaining an optimal spatiotemporal configuration of the neural dynamics during normal level of consciousness. The central role of the spatial distribution of LRTCs, reflecting temporo-spatial nestedness, may support the recently introduced temporo-spatial theory of consciousness (TTC). © 2018 Wiley Periodicals, Inc.

[Brain mapping in verbal and spatial thinking].

PubMed

Ivanitskiĭ, A M; Portnova, G V; Martynova, O V; Maĭorova, L A; Fedina, O N; Petrushevskiĭ, A G

2013-01-01

The goal of this study was to describe the topography of the active cortical areas and subcortical structuresin verbal and spatial thinking. The method of functional magnetic resonance imaging (fMRI) was used. 18 right-handed subjects participated in the study. Four types of tasks were presented: two experimental tasks--verbal (anagram) and spatial (search for a piece to complement a square), and two types of control tasks (written words and a spatial task, where all the pieces are identical). In solving verbal tasks the greater volume of activation was observed in the left hemisphere involving Broca's area, while the right middle frontal gyrus was activated in solving the spatial tasks. For occipital region an activation of the visual field 18 was more explicitin solving spatial problems, while the solution of anagrams caused an activation of the field 19 associated with higher levels of visual processing. The cerebellum was active bilaterally in both tasks with predominance in the second. The obtained fMRI data indicate that the verbal and spatial types of thinking are provided by an activation of narrow specific sets of brain structures, while the previous electrophysiological studies indicate the distributed nature of the brain processes in thinking. Combining these two approaches, it can be concluded that cognitive functions are supported by the systemic brain processes with a distinct location of the particular salient structures.

Use of Synchrotron X-ray Fluorescence to Measure Trace Metal Distribution in the Brain

NASA Astrophysics Data System (ADS)

Linkous, D.; Flinn, J. M.; Lanzirotti, A.; Frederickson, C.; Jones, B. F.; Bertsch, P. M.

2002-12-01

X26A, National Synchrotron Light Source, was used to quantitatively evaluate the spatial distribution of trace metals, such as Zn and Cu, in brain tissue. X-ray microprobe techniques offer distinct advantages over other analytical methods by allowing analyses to be done in-situ with little or no chemical pretreatment and low detection limits (about 1 ppm). In the context of neuroscience, SXRF can provide non-destructive measurements of specific metal concentrations and distribution within nerve (brain) tissue. Neuronal tissue from organisms having undergone different normal or experimental conditions may be compared, with analytical capacities not limited by binding states of the metal (i.e., vesicular or enzymatic), as is the case with staining techniques.. Whole regions of tissue may be scanned for detectable trace metals at spatial resolutions of 10um or less using focused monochromatic x-ray beams. Here special attention has been given to zinc because it is the most common trace metal in the brain, and levels have been increasing in the environment. In this investigation, zinc concentrations present within the hilus of a rat hippocampus, and to a lesser extent in the cortex, have been shown to increase following long-term ingestion of zinc-enhanced drinking water that was associated with deficits in spatial memory. Concomitantly, copper concentrations in the internal capsule were comparatively lower. Other first order transition metals, Cr, V, Mn, and Co were not detected. In contrast, elevated levels of Zn, Cu, and Fe have been seen in amyloid plaques associated with Alzheimer's disease.

Neural network configuration and efficiency underlies individual differences in spatial orientation ability.

PubMed

Arnold, Aiden E G F; Protzner, Andrea B; Bray, Signe; Levy, Richard M; Iaria, Giuseppe

2014-02-01

Spatial orientation is a complex cognitive process requiring the integration of information processed in a distributed system of brain regions. Current models on the neural basis of spatial orientation are based primarily on the functional role of single brain regions, with limited understanding of how interaction among these brain regions relates to behavior. In this study, we investigated two sources of variability in the neural networks that support spatial orientation--network configuration and efficiency--and assessed whether variability in these topological properties relates to individual differences in orientation accuracy. Participants with higher accuracy were shown to express greater activity in the right supramarginal gyrus, the right precentral cortex, and the left hippocampus, over and above a core network engaged by the whole group. Additionally, high-performing individuals had increased levels of global efficiency within a resting-state network composed of brain regions engaged during orientation and increased levels of node centrality in the right supramarginal gyrus, the right primary motor cortex, and the left hippocampus. These results indicate that individual differences in the configuration of task-related networks and their efficiency measured at rest relate to the ability to spatially orient. Our findings advance systems neuroscience models of orientation and navigation by providing insight into the role of functional integration in shaping orientation behavior.

Electroconvulsive therapy-induced brain plasticity determines therapeutic outcome in mood disorders

PubMed Central

Dukart, Juergen; Regen, Francesca; Kherif, Ferath; Colla, Michael; Bajbouj, Malek; Heuser, Isabella; Frackowiak, Richard S.; Draganski, Bogdan

2014-01-01

There remains much scientific, clinical, and ethical controversy concerning the use of electroconvulsive therapy (ECT) for psychiatric disorders stemming from a lack of information and knowledge about how such treatment might work, given its nonspecific and spatially unfocused nature. The mode of action of ECT has even been ascribed to a “barbaric” form of placebo effect. Here we show differential, highly specific, spatially distributed effects of ECT on regional brain structure in two populations: patients with unipolar or bipolar disorder. Unipolar and bipolar disorders respond differentially to ECT and the associated local brain-volume changes, which occur in areas previously associated with these diseases, correlate with symptom severity and the therapeutic effect. Our unique evidence shows that electrophysical therapeutic effects, although applied generally, take on regional significance through interactions with brain pathophysiology. PMID:24379394

Analysis of brain patterns using temporal measures

DOEpatents

Georgopoulos, Apostolos

2015-08-11

A set of brain data representing a time series of neurophysiologic activity acquired by spatially distributed sensors arranged to detect neural signaling of a brain (such as by the use of magnetoencephalography) is obtained. The set of brain data is processed to obtain a dynamic brain model based on a set of statistically-independent temporal measures, such as partial cross correlations, among groupings of different time series within the set of brain data. The dynamic brain model represents interactions between neural populations of the brain occurring close in time, such as with zero lag, for example. The dynamic brain model can be analyzed to obtain the neurophysiologic assessment of the brain. Data processing techniques may be used to assess structural or neurochemical brain pathologies.

Differentially categorized structural brain hubs are involved in different microstructural, functional, and cognitive characteristics and contribute to individual identification.

PubMed

Wang, Xindi; Lin, Qixiang; Xia, Mingrui; He, Yong

2018-04-01

Very little is known regarding whether structural hubs of human brain networks that enable efficient information communication may be classified into different categories. Using three multimodal neuroimaging data sets, we construct individual structural brain networks and further identify hub regions based on eight widely used graph-nodal metrics, followed by comprehensive characteristics and reproducibility analyses. We show the three categories of structural hubs in the brain network, namely, aggregated, distributed, and connector hubs. Spatially, these distinct categories of hubs are primarily located in the default-mode system and additionally in the visual and limbic systems for aggregated hubs, in the frontoparietal system for distributed hubs, and in the sensorimotor and ventral attention systems for connector hubs. These categorized hubs exhibit various distinct characteristics to support their differentiated roles, involving microstructural organization, wiring costs, topological vulnerability, functional modular integration, and cognitive flexibility; moreover, these characteristics are better in the hubs than nonhubs. Finally, all three categories of hubs display high across-session spatial similarities and act as structural fingerprints with high predictive rates (100%, 100%, and 84.2%) for individual identification. Collectively, we highlight three categories of brain hubs with differential microstructural, functional and, cognitive associations, which shed light on topological mechanisms of the human connectome. © 2018 Wiley Periodicals, Inc.

Spatiotemporal Distribution of β-Amyloid in Alzheimer Disease Is the Result of Heterogeneous Regional Carrying Capacities.

PubMed

Whittington, Alex; Sharp, David J; Gunn, Roger N

2018-05-01

β-amyloid (Aβ) accumulation in the brain is 1 of 2 pathologic hallmarks of Alzheimer disease (AD), and the spatial distribution of Aβ has been studied extensively ex vivo. Methods: We applied mathematical modeling to Aβ in vivo PET imaging data to investigate competing theories of Aβ spread in AD. Results: Our results provided evidence that Aβ accumulation starts in all brain regions simultaneously and that its spatiotemporal distribution is due to heterogeneous regional carrying capacities (regional maximum possible concentration of Aβ) for the aggregated protein rather than to longer-term spreading from seed regions. Conclusion: The in vivo spatiotemporal distribution of Aβ in AD can be mathematically modeled using a logistic growth model in which the Aβ carrying capacity is heterogeneous across the brain but the exponential growth rate and time of half maximal Aβ concentration are constant. © 2018 by the Society of Nuclear Medicine and Molecular Imaging.

Brain MR image segmentation based on an improved active contour model

PubMed Central

Meng, Xiangrui; Gu, Wenya; Zhang, Jianwei

2017-01-01

It is often a difficult task to accurately segment brain magnetic resonance (MR) images with intensity in-homogeneity and noise. This paper introduces a novel level set method for simultaneous brain MR image segmentation and intensity inhomogeneity correction. To reduce the effect of noise, novel anisotropic spatial information, which can preserve more details of edges and corners, is proposed by incorporating the inner relationships among the neighbor pixels. Then the proposed energy function uses the multivariate Student's t-distribution to fit the distribution of the intensities of each tissue. Furthermore, the proposed model utilizes Hidden Markov random fields to model the spatial correlation between neigh-boring pixels/voxels. The means of the multivariate Student's t-distribution can be adaptively estimated by multiplying a bias field to reduce the effect of intensity inhomogeneity. In the end, we reconstructed the energy function to be convex and calculated it by using the Split Bregman method, which allows our framework for random initialization, thereby allowing fully automated applications. Our method can obtain the final result in less than 1 second for 2D image with size 256 × 256 and less than 300 seconds for 3D image with size 256 × 256 × 171. The proposed method was compared to other state-of-the-art segmentation methods using both synthetic and clinical brain MR images and increased the accuracies of the results more than 3%. PMID:28854235

Towards real-time diffuse optical tomography for imaging brain functions cooperated with Kalman estimator

NASA Astrophysics Data System (ADS)

Wang, Bingyuan; Zhang, Yao; Liu, Dongyuan; Ding, Xuemei; Dan, Mai; Pan, Tiantian; Wang, Yihan; Li, Jiao; Zhou, Zhongxing; Zhang, Limin; Zhao, Huijuan; Gao, Feng

2018-02-01

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging method to monitor the cerebral hemodynamic through the optical changes measured at the scalp surface. It has played a more and more important role in psychology and medical imaging communities. Real-time imaging of brain function using NIRS makes it possible to explore some sophisticated human brain functions unexplored before. Kalman estimator has been frequently used in combination with modified Beer-Lamber Law (MBLL) based optical topology (OT), for real-time brain function imaging. However, the spatial resolution of the OT is low, hampering the application of OT in exploring some complicated brain functions. In this paper, we develop a real-time imaging method combining diffuse optical tomography (DOT) and Kalman estimator, much improving the spatial resolution. Instead of only presenting one spatially distributed image indicating the changes of the absorption coefficients at each time point during the recording process, one real-time updated image using the Kalman estimator is provided. Its each voxel represents the amplitude of the hemodynamic response function (HRF) associated with this voxel. We evaluate this method using some simulation experiments, demonstrating that this method can obtain more reliable spatial resolution images. Furthermore, a statistical analysis is also conducted to help to decide whether a voxel in the field of view is activated or not.

Neural correlates of reward-based spatial learning in persons with cocaine dependence.

PubMed

Tau, Gregory Z; Marsh, Rachel; Wang, Zhishun; Torres-Sanchez, Tania; Graniello, Barbara; Hao, Xuejun; Xu, Dongrong; Packard, Mark G; Duan, Yunsuo; Kangarlu, Alayar; Martinez, Diana; Peterson, Bradley S

2014-02-01

Dysfunctional learning systems are thought to be central to the pathogenesis of and impair recovery from addictions. The functioning of the brain circuits for episodic memory or learning that support goal-directed behavior has not been studied previously in persons with cocaine dependence (CD). Thirteen abstinent CD and 13 healthy participants underwent MRI scanning while performing a task that requires the use of spatial cues to navigate a virtual-reality environment and find monetary rewards, allowing the functional assessment of the brain systems for spatial learning, a form of episodic memory. Whereas both groups performed similarly on the reward-based spatial learning task, we identified disturbances in brain regions involved in learning and reward in CD participants. In particular, CD was associated with impaired functioning of medial temporal lobe (MTL), a brain region that is crucial for spatial learning (and episodic memory) with concomitant recruitment of striatum (which normally participates in stimulus-response, or habit, learning), and prefrontal cortex. CD was also associated with enhanced sensitivity of the ventral striatum to unexpected rewards but not to expected rewards earned during spatial learning. We provide evidence that spatial learning in CD is characterized by disturbances in functioning of an MTL-based system for episodic memory and a striatum-based system for stimulus-response learning and reward. We have found additional abnormalities in distributed cortical regions. Consistent with findings from animal studies, we provide the first evidence in humans describing the disruptive effects of cocaine on the coordinated functioning of multiple neural systems for learning and memory.

Resting State Brain Entropy Alterations in Relapsing Remitting Multiple Sclerosis.

PubMed

Zhou, Fuqing; Zhuang, Ying; Gong, Honghan; Zhan, Jie; Grossman, Murray; Wang, Ze

2016-01-01

Brain entropy (BEN) mapping provides a novel approach to characterize brain temporal dynamics, a key feature of human brain. Using resting state functional magnetic resonance imaging (rsfMRI), reliable and spatially distributed BEN patterns have been identified in normal brain, suggesting a potential use in clinical populations since temporal brain dynamics and entropy may be altered in disease conditions. The purpose of this study was to characterize BEN in multiple sclerosis (MS), a neurodegenerative disease that affects millions of people. Since currently there is no cure for MS, developing treatment or medication that can slow down its progression represents a high research priority, for which validating a brain marker sensitive to disease and the related functional impairments is essential. Because MS can start long time before any measurable symptoms and structural deficits, assessing the dynamic brain activity and correspondingly BEN may provide a critical way to study MS and its progression. Because BEN is new to MS, we aimed to assess BEN alterations in the relapsing-remitting MS (RRMS) patients using a patient versus control design, to examine the correlation of BEN to clinical measurements, and to check the correlation of BEN to structural brain measures which have been more often used in MS studies. As compared to controls, RRMS patients showed increased BEN in motor areas, executive control area, spatial coordinating area, and memory system. Increased BEN was related to greater disease severity as measured by the expanded disability status scale (EDSS) and greater tissue damage as indicated by the mean diffusivity. Patients also showed decreased BEN in other places, which was associated with less disability or fatigue, indicating a disease-related BEN re-distribution. Our results suggest BEN as a novel and useful tool for characterizing RRMS.

Spatial sexual dimorphism of X and Y homolog gene expression in the human central nervous system during early male development.

PubMed

Johansson, Martin M; Lundin, Elin; Qian, Xiaoyan; Mirzazadeh, Mohammadreza; Halvardson, Jonatan; Darj, Elisabeth; Feuk, Lars; Nilsson, Mats; Jazin, Elena

2016-01-01

Renewed attention has been directed to the functions of the Y chromosome in the central nervous system during early human male development, due to the recent proposed involvement in neurodevelopmental diseases. PCDH11Y and NLGN4Y are of special interest because they belong to gene families involved in cell fate determination and formation of dendrites and axon. We used RNA sequencing, immunocytochemistry and a padlock probing and rolling circle amplification strategy, to distinguish the expression of X and Y homologs in situ in the human brain for the first time. To minimize influence of androgens on the sex differences in the brain, we focused our investigation to human embryos at 8-11 weeks post-gestation. We found that the X- and Y-encoded genes are expressed in specific and heterogeneous cellular sub-populations of both glial and neuronal origins. More importantly, we found differential distribution patterns of X and Y homologs in the male developing central nervous system. This study has visualized the spatial distribution of PCDH11X/Y and NLGN4X/Y in human developing nervous tissue. The observed spatial distribution patterns suggest the existence of an additional layer of complexity in the development of the male CNS.

Spatially distributed effects of mental exhaustion on resting-state FMRI networks.

PubMed

Esposito, Fabrizio; Otto, Tobias; Zijlstra, Fred R H; Goebel, Rainer

2014-01-01

Brain activity during rest is spatially coherent over functional connectivity networks called resting-state networks. In resting-state functional magnetic resonance imaging, independent component analysis yields spatially distributed network representations reflecting distinct mental processes, such as intrinsic (default) or extrinsic (executive) attention, and sensory inhibition or excitation. These aspects can be related to different treatments or subjective experiences. Among these, exhaustion is a common psychological state induced by prolonged mental performance. Using repeated functional magnetic resonance imaging sessions and spatial independent component analysis, we explored the effect of several hours of sustained cognitive performances on the resting human brain. Resting-state functional magnetic resonance imaging was performed on the same healthy volunteers in two days, with and without, and before, during and after, an intensive psychological treatment (skill training and sustained practice with a flight simulator). After each scan, subjects rated their level of exhaustion and performed an N-back task to evaluate eventual decrease in cognitive performance. Spatial maps of selected resting-state network components were statistically evaluated across time points to detect possible changes induced by the sustained mental performance. The intensive treatment had a significant effect on exhaustion and effort ratings, but no effects on N-back performances. Significant changes in the most exhausted state were observed in the early visual processing and the anterior default mode networks (enhancement) and in the fronto-parietal executive networks (suppression), suggesting that mental exhaustion is associated with a more idling brain state and that internal attention processes are facilitated to the detriment of more extrinsic processes. The described application may inspire future indicators of the level of fatigue in the neural attention system.

Spatiotemporal patterns of ERP based on combined ICA-LORETA analysis

NASA Astrophysics Data System (ADS)

Zhang, Jiacai; Guo, Taomei; Xu, Yaqin; Zhao, Xiaojie; Yao, Li

2007-03-01

In contrast to the FMRI methods widely used up to now, this method try to understand more profoundly how the brain systems work under sentence processing task map accurately the spatiotemporal patterns of activity of the large neuronal populations in the human brain from the analysis of ERP data recorded on the brain scalp. In this study, an event-related brain potential (ERP) paradigm to record the on-line responses to the processing of sentences is chosen as an example. In order to give attention to both utilizing the ERPs' temporal resolution of milliseconds and overcoming the insensibility of cerebral location ERP sources, we separate these sources in space and time based on a combined method of independent component analysis (ICA) and low-resolution tomography (LORETA) algorithms. ICA blindly separate the input ERP data into a sum of temporally independent and spatially fixed components arising from distinct or overlapping brain or extra-brain sources. And then the spatial maps associated with each ICA component are analyzed, with use of LORETA to uniquely locate its cerebral sources throughout the full brain according to the assumption that neighboring neurons are simultaneously and synchronously activated. Our results show that the cerebral computation mechanism underlies content words reading is mediated by the orchestrated activity of several spatially distributed brain sources located in the temporal, frontal, and parietal areas, and activate at distinct time intervals and are grouped into different statistically independent components. Thus ICA-LORETA analysis provides an encouraging and effective method to study brain dynamics from ERP.

A Heavy Tailed Expectation Maximization Hidden Markov Random Field Model with Applications to Segmentation of MRI

PubMed Central

Castillo-Barnes, Diego; Peis, Ignacio; Martínez-Murcia, Francisco J.; Segovia, Fermín; Illán, Ignacio A.; Górriz, Juan M.; Ramírez, Javier; Salas-Gonzalez, Diego

2017-01-01

A wide range of segmentation approaches assumes that intensity histograms extracted from magnetic resonance images (MRI) have a distribution for each brain tissue that can be modeled by a Gaussian distribution or a mixture of them. Nevertheless, intensity histograms of White Matter and Gray Matter are not symmetric and they exhibit heavy tails. In this work, we present a hidden Markov random field model with expectation maximization (EM-HMRF) modeling the components using the α-stable distribution. The proposed model is a generalization of the widely used EM-HMRF algorithm with Gaussian distributions. We test the α-stable EM-HMRF model in synthetic data and brain MRI data. The proposed methodology presents two main advantages: Firstly, it is more robust to outliers. Secondly, we obtain similar results than using Gaussian when the Gaussian assumption holds. This approach is able to model the spatial dependence between neighboring voxels in tomographic brain MRI. PMID:29209194

MEG source localization of spatially extended generators of epileptic activity: comparing entropic and hierarchical bayesian approaches.

PubMed

Chowdhury, Rasheda Arman; Lina, Jean Marc; Kobayashi, Eliane; Grova, Christophe

2013-01-01

Localizing the generators of epileptic activity in the brain using Electro-EncephaloGraphy (EEG) or Magneto-EncephaloGraphy (MEG) signals is of particular interest during the pre-surgical investigation of epilepsy. Epileptic discharges can be detectable from background brain activity, provided they are associated with spatially extended generators. Using realistic simulations of epileptic activity, this study evaluates the ability of distributed source localization methods to accurately estimate the location of the generators and their sensitivity to the spatial extent of such generators when using MEG data. Source localization methods based on two types of realistic models have been investigated: (i) brain activity may be modeled using cortical parcels and (ii) brain activity is assumed to be locally smooth within each parcel. A Data Driven Parcellization (DDP) method was used to segment the cortical surface into non-overlapping parcels and diffusion-based spatial priors were used to model local spatial smoothness within parcels. These models were implemented within the Maximum Entropy on the Mean (MEM) and the Hierarchical Bayesian (HB) source localization frameworks. We proposed new methods in this context and compared them with other standard ones using Monte Carlo simulations of realistic MEG data involving sources of several spatial extents and depths. Detection accuracy of each method was quantified using Receiver Operating Characteristic (ROC) analysis and localization error metrics. Our results showed that methods implemented within the MEM framework were sensitive to all spatial extents of the sources ranging from 3 cm(2) to 30 cm(2), whatever were the number and size of the parcels defining the model. To reach a similar level of accuracy within the HB framework, a model using parcels larger than the size of the sources should be considered.

MEG Source Localization of Spatially Extended Generators of Epileptic Activity: Comparing Entropic and Hierarchical Bayesian Approaches

PubMed Central

Chowdhury, Rasheda Arman; Lina, Jean Marc; Kobayashi, Eliane; Grova, Christophe

2013-01-01

Localizing the generators of epileptic activity in the brain using Electro-EncephaloGraphy (EEG) or Magneto-EncephaloGraphy (MEG) signals is of particular interest during the pre-surgical investigation of epilepsy. Epileptic discharges can be detectable from background brain activity, provided they are associated with spatially extended generators. Using realistic simulations of epileptic activity, this study evaluates the ability of distributed source localization methods to accurately estimate the location of the generators and their sensitivity to the spatial extent of such generators when using MEG data. Source localization methods based on two types of realistic models have been investigated: (i) brain activity may be modeled using cortical parcels and (ii) brain activity is assumed to be locally smooth within each parcel. A Data Driven Parcellization (DDP) method was used to segment the cortical surface into non-overlapping parcels and diffusion-based spatial priors were used to model local spatial smoothness within parcels. These models were implemented within the Maximum Entropy on the Mean (MEM) and the Hierarchical Bayesian (HB) source localization frameworks. We proposed new methods in this context and compared them with other standard ones using Monte Carlo simulations of realistic MEG data involving sources of several spatial extents and depths. Detection accuracy of each method was quantified using Receiver Operating Characteristic (ROC) analysis and localization error metrics. Our results showed that methods implemented within the MEM framework were sensitive to all spatial extents of the sources ranging from 3 cm2 to 30 cm2, whatever were the number and size of the parcels defining the model. To reach a similar level of accuracy within the HB framework, a model using parcels larger than the size of the sources should be considered. PMID:23418485

Regional volumes and spatial volumetric distribution of gray matter in the gender dysphoric brain.

PubMed

Hoekzema, Elseline; Schagen, Sebastian E E; Kreukels, Baudewijntje P C; Veltman, Dick J; Cohen-Kettenis, Peggy T; Delemarre-van de Waal, Henriette; Bakker, Julie

2015-05-01

The sexual differentiation of the brain is primarily driven by gonadal hormones during fetal development. Leading theories on the etiology of gender dysphoria (GD) involve deviations herein. To examine whether there are signs of a sex-atypical brain development in GD, we quantified regional neural gray matter (GM) volumes in 55 female-to-male and 38 male-to-female adolescents, 44 boys and 52 girls without GD and applied both univariate and multivariate analyses. In girls, more GM volume was observed in the left superior medial frontal cortex, while boys had more volume in the bilateral superior posterior hemispheres of the cerebellum and the hypothalamus. Regarding the GD groups, at whole-brain level they differed only from individuals sharing their gender identity but not from their natal sex. Accordingly, using multivariate pattern recognition analyses, the GD groups could more accurately be automatically discriminated from individuals sharing their gender identity than those sharing their natal sex based on spatially distributed GM patterns. However, region of interest analyses indicated less GM volume in the right cerebellum and more volume in the medial frontal cortex in female-to-males in comparison to girls without GD, while male-to-females had less volume in the bilateral cerebellum and hypothalamus than natal boys. Deviations from the natal sex within sexually dimorphic structures were also observed in the untreated subsamples. Our findings thus indicate that GM distribution and regional volumes in GD adolescents are largely in accordance with their respective natal sex. However, there are subtle deviations from the natal sex in sexually dimorphic structures, which can represent signs of a partial sex-atypical differentiation of the brain. Copyright © 2015 Elsevier Ltd. All rights reserved.

Localization of extended brain sources from EEG/MEG: the ExSo-MUSIC approach.

PubMed

Birot, Gwénaël; Albera, Laurent; Wendling, Fabrice; Merlet, Isabelle

2011-05-01

We propose a new MUSIC-like method, called 2q-ExSo-MUSIC (q ≥ 1). This method is an extension of the 2q-MUSIC (q ≥ 1) approach for solving the EEG/MEG inverse problem, when spatially-extended neocortical sources ("ExSo") are considered. It introduces a novel ExSo-MUSIC principle. The novelty is two-fold: i) the parameterization of the spatial source distribution that leads to an appropriate metric in the context of distributed brain sources and ii) the introduction of an original, efficient and low-cost way of optimizing this metric. In 2q-ExSo-MUSIC, the possible use of higher order statistics (q ≥ 2) offers a better robustness with respect to Gaussian noise of unknown spatial coherence and modeling errors. As a result we reduced the penalizing effects of both the background cerebral activity that can be seen as a Gaussian and spatially correlated noise, and the modeling errors induced by the non-exact resolution of the forward problem. Computer results on simulated EEG signals obtained with physiologically-relevant models of both the sources and the volume conductor show a highly increased performance of our 2q-ExSo-MUSIC method as compared to the classical 2q-MUSIC algorithms. Copyright © 2011 Elsevier Inc. All rights reserved.

Imaging Metals in Brain Tissue by Laser Ablation - Inductively Coupled Plasma - Mass Spectrometry (LA-ICP-MS)

PubMed Central

Hare, Dominic J.; Kysenius, Kai; Paul, Bence; Knauer, Beate; Hutchinson, Robert W.; O'Connor, Ciaran; Fryer, Fred; Hennessey, Tom P.; Bush, Ashley I.; Crouch, Peter J.; Doble, Philip A.

2017-01-01

Metals are found ubiquitously throughout an organism, with their biological role dictated by both their chemical reactivity and abundance within a specific anatomical region. Within the brain, metals have a highly compartmentalized distribution, depending on the primary function they play within the central nervous system. Imaging the spatial distribution of metals has provided unique insight into the biochemical architecture of the brain, allowing direct correlation between neuroanatomical regions and their known function with regard to metal-dependent processes. In addition, several age-related neurological disorders feature disrupted metal homeostasis, which is often confined to small regions of the brain that are otherwise difficult to analyze. Here, we describe a comprehensive method for quantitatively imaging metals in the mouse brain, using laser ablation - inductively coupled plasma - mass spectrometry (LA-ICP-MS) and specially designed image processing software. Focusing on iron, copper and zinc, which are three of the most abundant and disease-relevant metals within the brain, we describe the essential steps in sample preparation, analysis, quantitative measurements and image processing to produce maps of metal distribution within the low micrometer resolution range. This technique, applicable to any cut tissue section, is capable of demonstrating the highly variable distribution of metals within an organ or system, and can be used to identify changes in metal homeostasis and absolute levels within fine anatomical structures. PMID:28190025

Atlas-Guided Segmentation of Vervet Monkey Brain MRI

PubMed Central

Fedorov, Andriy; Li, Xiaoxing; Pohl, Kilian M; Bouix, Sylvain; Styner, Martin; Addicott, Merideth; Wyatt, Chris; Daunais, James B; Wells, William M; Kikinis, Ron

2011-01-01

The vervet monkey is an important nonhuman primate model that allows the study of isolated environmental factors in a controlled environment. Analysis of monkey MRI often suffers from lower quality images compared with human MRI because clinical equipment is typically used to image the smaller monkey brain and higher spatial resolution is required. This, together with the anatomical differences of the monkey brains, complicates the use of neuroimage analysis pipelines tuned for human MRI analysis. In this paper we developed an open source image analysis framework based on the tools available within the 3D Slicer software to support a biological study that investigates the effect of chronic ethanol exposure on brain morphometry in a longitudinally followed population of male vervets. We first developed a computerized atlas of vervet monkey brain MRI, which was used to encode the typical appearance of the individual brain structures in MRI and their spatial distribution. The atlas was then used as a spatial prior during automatic segmentation to process two longitudinal scans per subject. Our evaluation confirms the consistency and reliability of the automatic segmentation. The comparison of atlas construction strategies reveals that the use of a population-specific atlas leads to improved accuracy of the segmentation for subcortical brain structures. The contribution of this work is twofold. First, we describe an image processing workflow specifically tuned towards the analysis of vervet MRI that consists solely of the open source software tools. Second, we develop a digital atlas of vervet monkey brain MRIs to enable similar studies that rely on the vervet model. PMID:22253661

The Michelin red guide of the brain: role of dopamine in goal-oriented navigation.

PubMed

Retailleau, Aude; Boraud, Thomas

2014-01-01

Spatial learning has been recognized over the years to be under the control of the hippocampus and related temporal lobe structures. Hippocampal damage often causes severe impairments in the ability to learn and remember a location in space defined by distal visual cues. Such cognitive disabilities are found in Parkinsonian patients. We recently investigated the role of dopamine in navigation in the 6-Hydroxy-dopamine (6-OHDA) rat, a model of Parkinson's disease (PD) commonly used to investigate the pathophysiology of dopamine depletion (Retailleau et al., 2013). We demonstrated that dopamine (DA) is essential to spatial learning as its depletion results in spatial impairments. Our results showed that the behavioral effect of DA depletion is correlated with modification of the neural encoding of spatial features and decision making processes in hippocampus. However, the origin of these alterations in the neural processing of the spatial information needs to be clarified. It could result from a local effect: dopamine depletion disturbs directly the processing of relevant spatial information at hippocampal level. Alternatively, it could result from a more distributed network effect: dopamine depletion elsewhere in the brain (entorhinal cortex, striatum, etc.) modifies the way hippocampus processes spatial information. Recent experimental evidence in rodents, demonstrated indeed, that other brain areas are involved in the acquisition of spatial information. Amongst these, the cortex-basal ganglia (BG) loop is known to be involved in reinforcement learning and has been identified as an important contributor to spatial learning. In particular, it has been shown that altered activity of the BG striatal complex can impair the ability to perform spatial learning tasks. The present review provides a glimpse of the findings obtained over the past decade that support a dialog between these two structures during spatial learning under DA control.

Divergent and nonuniform gene expression patterns in mouse brain

PubMed Central

Morris, John A.; Royall, Joshua J.; Bertagnolli, Darren; Boe, Andrew F.; Burnell, Josh J.; Byrnes, Emi J.; Copeland, Cathy; Desta, Tsega; Fischer, Shanna R.; Goldy, Jeff; Glattfelder, Katie J.; Kidney, Jolene M.; Lemon, Tracy; Orta, Geralyn J.; Parry, Sheana E.; Pathak, Sayan D.; Pearson, Owen C.; Reding, Melissa; Shapouri, Sheila; Smith, Kimberly A.; Soden, Chad; Solan, Beth M.; Weller, John; Takahashi, Joseph S.; Overly, Caroline C.; Lein, Ed S.; Hawrylycz, Michael J.; Hohmann, John G.; Jones, Allan R.

2010-01-01

Considerable progress has been made in understanding variations in gene sequence and expression level associated with phenotype, yet how genetic diversity translates into complex phenotypic differences remains poorly understood. Here, we examine the relationship between genetic background and spatial patterns of gene expression across seven strains of mice, providing the most extensive cellular-resolution comparative analysis of gene expression in the mammalian brain to date. Using comprehensive brainwide anatomic coverage (more than 200 brain regions), we applied in situ hybridization to analyze the spatial expression patterns of 49 genes encoding well-known pharmaceutical drug targets. Remarkably, over 50% of the genes examined showed interstrain expression variation. In addition, the variability was nonuniformly distributed across strain and neuroanatomic region, suggesting certain organizing principles. First, the degree of expression variance among strains mirrors genealogic relationships. Second, expression pattern differences were concentrated in higher-order brain regions such as the cortex and hippocampus. Divergence in gene expression patterns across the brain could contribute significantly to variations in behavior and responses to neuroactive drugs in laboratory mouse strains and may help to explain individual differences in human responsiveness to neuroactive drugs. PMID:20956311

Uncertainty quantification in flux balance analysis of spatially lumped and distributed models of neuron-astrocyte metabolism.

PubMed

Calvetti, Daniela; Cheng, Yougan; Somersalo, Erkki

2016-12-01

Identifying feasible steady state solutions of a brain energy metabolism model is an inverse problem that allows infinitely many solutions. The characterization of the non-uniqueness, or the uncertainty quantification of the flux balance analysis, is tantamount to identifying the degrees of freedom of the solution. The degrees of freedom of multi-compartment mathematical models for energy metabolism of a neuron-astrocyte complex may offer a key to understand the different ways in which the energetic needs of the brain are met. In this paper we study the uncertainty in the solution, using techniques of linear algebra to identify the degrees of freedom in a lumped model, and Markov chain Monte Carlo methods in its extension to a spatially distributed case. The interpretation of the degrees of freedom in metabolic terms, more specifically, glucose and oxygen partitioning, is then leveraged to derive constraints on the free parameters to guarantee that the model is energetically feasible. We demonstrate how the model can be used to estimate the stoichiometric energy needs of the cells as well as the household energy based on the measured oxidative cerebral metabolic rate of glucose and glutamate cycling. Moreover, our analysis shows that in the lumped model the net direction of lactate dehydrogenase (LDH) in the cells can be deduced from the glucose partitioning between the compartments. The extension of the lumped model to a spatially distributed multi-compartment setting that includes diffusion fluxes from capillary to tissue increases the number of degrees of freedom, requiring the use of statistical sampling techniques. The analysis of the distributed model reveals that some of the conclusions valid for the spatially lumped model, e.g., concerning the LDH activity and glucose partitioning, may no longer hold.

Investigating Digital Optical Computing with Spatial Light Rebroadcasters

DTIC Science & Technology

1991-10-31

3303, 1991 5 5: I 66. F. Rosenblatt, Principles of neurodynamics : Perceptrons and the theory of brain mechanism, Spartan, Washington, 1961. 67. D. E...eds., Parallel Distributed Processing: Explorations in the Microstructure of Cognition , Vol-I : Foundations, MIT Press, 1986. 68. A. Ayyalusamy

Monte Carlo simulation of near-infrared light propagation in realistic adult head models with hair follicles

NASA Astrophysics Data System (ADS)

Pan, Boan; Fang, Xiang; Liu, Weichao; Li, Nanxi; Zhao, Ke; Li, Ting

2018-02-01

Near infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) has been used to measure brain activation, which are clinically important. Monte Carlo simulation has been applied to the near infrared light propagation model in biological tissue, and has the function of predicting diffusion and brain activation. However, previous studies have rarely considered hair and hair follicles as a contributing factor. Here, we attempt to use MCVM (Monte Carlo simulation based on 3D voxelized media) to examine light transmission, absorption, fluence, spatial sensitivity distribution (SSD) and brain activation judgement in the presence or absence of the hair follicles. The data in this study is a series of high-resolution cryosectional color photograph of a standing Chinse male adult. We found that the number of photons transmitted under the scalp decreases dramatically and the photons exported to detector is also decreasing, as the density of hair follicles increases. If there is no hair follicle, the above data increase and has the maximum value. Meanwhile, the light distribution and brain activation have a stable change along with the change of hair follicles density. The findings indicated hair follicles make influence of NIRS in light distribution and brain activation judgement.

Cyberinfrastructure for the digital brain: spatial standards for integrating rodent brain atlases

PubMed Central

Zaslavsky, Ilya; Baldock, Richard A.; Boline, Jyl

2014-01-01

Biomedical research entails capture and analysis of massive data volumes and new discoveries arise from data-integration and mining. This is only possible if data can be mapped onto a common framework such as the genome for genomic data. In neuroscience, the framework is intrinsically spatial and based on a number of paper atlases. This cannot meet today's data-intensive analysis and integration challenges. A scalable and extensible software infrastructure that is standards based but open for novel data and resources, is required for integrating information such as signal distributions, gene-expression, neuronal connectivity, electrophysiology, anatomy, and developmental processes. Therefore, the International Neuroinformatics Coordinating Facility (INCF) initiated the development of a spatial framework for neuroscience data integration with an associated Digital Atlasing Infrastructure (DAI). A prototype implementation of this infrastructure for the rodent brain is reported here. The infrastructure is based on a collection of reference spaces to which data is mapped at the required resolution, such as the Waxholm Space (WHS), a 3D reconstruction of the brain generated using high-resolution, multi-channel microMRI. The core standards of the digital atlasing service-oriented infrastructure include Waxholm Markup Language (WaxML): XML schema expressing a uniform information model for key elements such as coordinate systems, transformations, points of interest (POI)s, labels, and annotations; and Atlas Web Services: interfaces for querying and updating atlas data. The services return WaxML-encoded documents with information about capabilities, spatial reference systems (SRSs) and structures, and execute coordinate transformations and POI-based requests. Key elements of INCF-DAI cyberinfrastructure have been prototyped for both mouse and rat brain atlas sources, including the Allen Mouse Brain Atlas, UCSD Cell-Centered Database, and Edinburgh Mouse Atlas Project. PMID:25309417

Cyberinfrastructure for the digital brain: spatial standards for integrating rodent brain atlases.

PubMed

Zaslavsky, Ilya; Baldock, Richard A; Boline, Jyl

2014-01-01

Biomedical research entails capture and analysis of massive data volumes and new discoveries arise from data-integration and mining. This is only possible if data can be mapped onto a common framework such as the genome for genomic data. In neuroscience, the framework is intrinsically spatial and based on a number of paper atlases. This cannot meet today's data-intensive analysis and integration challenges. A scalable and extensible software infrastructure that is standards based but open for novel data and resources, is required for integrating information such as signal distributions, gene-expression, neuronal connectivity, electrophysiology, anatomy, and developmental processes. Therefore, the International Neuroinformatics Coordinating Facility (INCF) initiated the development of a spatial framework for neuroscience data integration with an associated Digital Atlasing Infrastructure (DAI). A prototype implementation of this infrastructure for the rodent brain is reported here. The infrastructure is based on a collection of reference spaces to which data is mapped at the required resolution, such as the Waxholm Space (WHS), a 3D reconstruction of the brain generated using high-resolution, multi-channel microMRI. The core standards of the digital atlasing service-oriented infrastructure include Waxholm Markup Language (WaxML): XML schema expressing a uniform information model for key elements such as coordinate systems, transformations, points of interest (POI)s, labels, and annotations; and Atlas Web Services: interfaces for querying and updating atlas data. The services return WaxML-encoded documents with information about capabilities, spatial reference systems (SRSs) and structures, and execute coordinate transformations and POI-based requests. Key elements of INCF-DAI cyberinfrastructure have been prototyped for both mouse and rat brain atlas sources, including the Allen Mouse Brain Atlas, UCSD Cell-Centered Database, and Edinburgh Mouse Atlas Project.

Brain regions that retain the spatial layout of tactile stimuli during working memory - A 'tactospatial sketchpad'?

PubMed

Schmidt, Timo Torsten; Blankenburg, Felix

2018-05-31

Working memory (WM) studies have been essential for ascertaining how the brain flexibly handles mentally represented information in the absence of sensory stimulation. Most studies on the memory of sensory stimulus features have focused, however, on the visual domain. Here, we report a human WM study in the tactile modality where participants had to memorize the spatial layout of patterned Braille-like stimuli presented to the index finger. We used a whole-brain searchlight approach in combination with multi-voxel pattern analysis (MVPA) to investigate tactile WM representations without a priori assumptions about which brain regions code tactospatial information. Our analysis revealed that posterior and parietal cortices, as well as premotor regions, retained information across the twelve-second delay phase. Interestingly, parts of this brain network were previously shown to also contain information of visuospatial WM. Also, by specifically testing somatosensory regions for WM representations, we observed content-specific activation patterns in primary somatosensory cortex (SI). Our findings demonstrate that tactile WM depends on a distributed network of brain regions in analogy to the representation of visuospatial information. Copyright © 2018. Published by Elsevier Inc.

Decoding multiple sound categories in the human temporal cortex using high resolution fMRI.

PubMed

Zhang, Fengqing; Wang, Ji-Ping; Kim, Jieun; Parrish, Todd; Wong, Patrick C M

2015-01-01

Perception of sound categories is an important aspect of auditory perception. The extent to which the brain's representation of sound categories is encoded in specialized subregions or distributed across the auditory cortex remains unclear. Recent studies using multivariate pattern analysis (MVPA) of brain activations have provided important insights into how the brain decodes perceptual information. In the large existing literature on brain decoding using MVPA methods, relatively few studies have been conducted on multi-class categorization in the auditory domain. Here, we investigated the representation and processing of auditory categories within the human temporal cortex using high resolution fMRI and MVPA methods. More importantly, we considered decoding multiple sound categories simultaneously through multi-class support vector machine-recursive feature elimination (MSVM-RFE) as our MVPA tool. Results show that for all classifications the model MSVM-RFE was able to learn the functional relation between the multiple sound categories and the corresponding evoked spatial patterns and classify the unlabeled sound-evoked patterns significantly above chance. This indicates the feasibility of decoding multiple sound categories not only within but across subjects. However, the across-subject variation affects classification performance more than the within-subject variation, as the across-subject analysis has significantly lower classification accuracies. Sound category-selective brain maps were identified based on multi-class classification and revealed distributed patterns of brain activity in the superior temporal gyrus and the middle temporal gyrus. This is in accordance with previous studies, indicating that information in the spatially distributed patterns may reflect a more abstract perceptual level of representation of sound categories. Further, we show that the across-subject classification performance can be significantly improved by averaging the fMRI images over items, because the irrelevant variations between different items of the same sound category are reduced and in turn the proportion of signals relevant to sound categorization increases.

Dynamics of the EEG of human brain in the gradient magnetic fields of geological faults in different geographical and climatic zones

NASA Astrophysics Data System (ADS)

Pobachenko, S. V.; Sokolov, M. V.; Grigoriev, P. E.; Vasilieva, I. V.

2017-11-01

There are presented the results of experimental studies of the dynamics of indices of the functional state of a person located within the zones characterized by anomalous parameters of spatial distribution of magnetic field vector values. It is shown that these geophysical modifications have a pronounced effect on the dynamics of electrical activity indices of the human brain, regardless of geographic and climatic conditions.

Mapping phosphorylation rate of fluoro-deoxy-glucose in rat brain by 19F chemical shift imaging

PubMed Central

Coman, Daniel; Sanganahalli, Basavaraju G.; Cheng, David; McCarthy, Timothy; Rothman, Douglas L.; Hyder, Fahmeed

2014-01-01

19F magnetic resonance spectroscopy (MRS) studies of 2-fluoro-2-deoxy-D-glucose (FDG) and 2-fluoro-2-deoxy-D-glucose-6-phosphate (FDG-6P) can be used for directly assessing total glucose metabolism in vivo. To date, 19F MRS measurements of FDG phosphorylation in the brain have either been achieved ex vivo from extracted tissue or in vivo by unusually long acquisition times. Electrophysiological and functional magnetic resonance imaging (fMRI) measurements indicate that FDG doses up to 500mg/kg can be tolerated with minimal side effects on cerebral physiology and evoked fMRI-BOLD responses to forepaw stimulation. In halothane-anesthetized rats, we report localized in vivo detection and separation of FDG and FDG-6P MRS signals with 19F 2D chemical shift imaging (CSI) at 11.7T. A metabolic model based on reversible transport between plasma and brain tissue, which included a non-saturable plasma to tissue component, was used to calculate spatial distribution of FDG and FDG-6P concentrations in rat brain. In addition, spatial distribution of rate constants and metabolic fluxes of FDG to FDG-6P conversion were estimated. Mapping the rate of FDG to FDG-6P conversion by 19F CSI provides an MR methodology that could impact other in vivo applications such as characterization of tumor pathophysiology. PMID:24581725

Time-reversal acoustics and ultrasound-assisted convection-enhanced drug delivery to the brain.

PubMed

Olbricht, William; Sistla, Manjari; Ghandi, Gaurav; Lewis, George; Sarvazyan, Armen

2013-08-01

Time-reversal acoustics is an effective way of focusing ultrasound deep inside heterogeneous media such as biological tissues. Convection-enhanced delivery is a method of delivering drugs into the brain by infusing them directly into the brain interstitium. These two technologies are combined in a focusing system that uses a "smart needle" to simultaneously infuse fluid into the brain and provide the necessary feedback for focusing ultrasound using time-reversal acoustics. The effects of time-reversal acoustics-focused ultrasound on the spatial distribution of infused low- and high-molecular weight tracer molecules are examined in live, anesthetized rats. Results show that exposing the rat brain to focused ultrasound significantly increases the penetration of infused compounds into the brain. The addition of stabilized microbubbles enhances the effect of ultrasound exposure.

The topology of large Open Connectome networks for the human brain.

PubMed

Gastner, Michael T; Ódor, Géza

2016-06-07

The structural human connectome (i.e. the network of fiber connections in the brain) can be analyzed at ever finer spatial resolution thanks to advances in neuroimaging. Here we analyze several large data sets for the human brain network made available by the Open Connectome Project. We apply statistical model selection to characterize the degree distributions of graphs containing up to nodes and edges. A three-parameter generalized Weibull (also known as a stretched exponential) distribution is a good fit to most of the observed degree distributions. For almost all networks, simple power laws cannot fit the data, but in some cases there is statistical support for power laws with an exponential cutoff. We also calculate the topological (graph) dimension D and the small-world coefficient σ of these networks. While σ suggests a small-world topology, we found that D < 4 showing that long-distance connections provide only a small correction to the topology of the embedding three-dimensional space.

The topology of large Open Connectome networks for the human brain

NASA Astrophysics Data System (ADS)

Gastner, Michael T.; Ódor, Géza

2016-06-01

The structural human connectome (i.e. the network of fiber connections in the brain) can be analyzed at ever finer spatial resolution thanks to advances in neuroimaging. Here we analyze several large data sets for the human brain network made available by the Open Connectome Project. We apply statistical model selection to characterize the degree distributions of graphs containing up to nodes and edges. A three-parameter generalized Weibull (also known as a stretched exponential) distribution is a good fit to most of the observed degree distributions. For almost all networks, simple power laws cannot fit the data, but in some cases there is statistical support for power laws with an exponential cutoff. We also calculate the topological (graph) dimension D and the small-world coefficient σ of these networks. While σ suggests a small-world topology, we found that D < 4 showing that long-distance connections provide only a small correction to the topology of the embedding three-dimensional space.

Is the spatial distribution of brain lesions associated with closed-head injury in children predictive of subsequent development of posttraumatic stress disorder?

NASA Technical Reports Server (NTRS)

Herskovits, Edward H.; Gerring, Joan P.; Davatzikos, Christos; Bryan, R. Nick

2002-01-01

PURPOSE: To determine whether there is an association between the spatial distributions of lesions detected at magnetic resonance (MR) imaging of the brain in children, adolescents, and young adults after closed-head injury (CHI) and development of the reexperiencing symptoms of posttraumatic stress disorder (PTSD). MATERIALS AND METHODS: Data obtained in 94 subjects without a history of PTSD as determined by parental interview were analyzed. MR images were obtained 3 months after CHI. Lesions were manually delineated and registered to the Talairach coordinate system. Mann-Whitney analysis of lesion distribution and PTSD status at 1 year (again, as determined by parental interview) was performed, consisting of an analysis of lesion distribution versus the major symptoms of PTSD: reexperiencing, hyperarousal, and avoidance. RESULTS: Of the 94 subjects, 41 met the PTSD reexperiencing criterion and nine met all three PTSD criteria. Subjects who met the reexperiencing criterion had fewer lesions in limbic system structures (eg, the cingulum) on the right than did subjects who did not meet this criterion (Mann-Whitney, P =.003). CONCLUSION: Lesions induced by CHI in the limbic system on the right may inhibit subsequent manifestation of PTSD reexperiencing symptoms in children, adolescents, and young adults. Copyright RSNA, 2002.

Experimental and theoretical characterization of the voltage distribution generated by deep brain stimulation.

PubMed

Miocinovic, Svjetlana; Lempka, Scott F; Russo, Gary S; Maks, Christopher B; Butson, Christopher R; Sakaie, Ken E; Vitek, Jerrold L; McIntyre, Cameron C

2009-03-01

Deep brain stimulation (DBS) is an established therapy for the treatment of Parkinson's disease and shows great promise for numerous other disorders. While the fundamental purpose of DBS is to modulate neural activity with electric fields, little is known about the actual voltage distribution generated in the brain by DBS electrodes and as a result it is difficult to accurately predict which brain areas are directly affected by the stimulation. The goal of this study was to characterize the spatial and temporal characteristics of the voltage distribution generated by DBS electrodes. We experimentally recorded voltages around active DBS electrodes in either a saline bath or implanted in the brain of a non-human primate. Recordings were made during voltage-controlled and current-controlled stimulation. The experimental findings were compared to volume conductor electric field models of DBS parameterized to match the different experiments. Three factors directly affected the experimental and theoretical voltage measurements: 1) DBS electrode impedance, primarily dictated by a voltage drop at the electrode-electrolyte interface and the conductivity of the tissue medium, 2) capacitive modulation of the stimulus waveform, and 3) inhomogeneity and anisotropy of the tissue medium. While the voltage distribution does not directly predict the neural response to DBS, the results of this study do provide foundational building blocks for understanding the electrical parameters of DBS and characterizing its effects on the nervous system.

Hemispheric Connectivity and the Visual-Spatial Divergent-Thinking Component of Creativity

ERIC Educational Resources Information Center

Moore, Dana W.; Bhadelia, Rafeeque A.; Billings, Rebecca L.; Fulwiler, Carl; Heilman, Kenneth M.; Rood, Kenneth M. J.; Gansler, David A.

2009-01-01

Background/hypothesis: Divergent thinking is an important measurable component of creativity. This study tested the postulate that divergent thinking depends on large distributed inter- and intra-hemispheric networks. Although preliminary evidence supports increased brain connectivity during divergent thinking, the neural correlates of this…

Neuromagnetic Evidence of Spatially Distributed Sources Underlying Epileptiform Spikes in the Human Brain

NASA Astrophysics Data System (ADS)

Barth, Daniel S.; Sutherling, William; Engle, Jerome; Beatty, Jackson

1984-01-01

Neuromagnetic measurements were performed on 17 subjects with focal seizure disorders. In all of the subjects, the interictal spike in the scalp electroencephalogram was associated with an orderly extracranial magnetic field pattern. In eight of these subjects, multiple current sources underlay the magnetic spike complex. The multiple sources within a given subject displayed a fixed chronological sequence of discharge, demonstrating a high degree of spatial and temporal organization within the interictal focus.

Investigation of lithium distribution in the rat brain ex vivo using lithium-7 magnetic resonance spectroscopy and imaging at 17.2 T.

PubMed

Stout, Jacques; Hanak, Anne-Sophie; Chevillard, Lucie; Djemaï, Boucif; Risède, Patricia; Giacomini, Eric; Poupon, Joël; Barrière, David André; Bellivier, Frank; Mégarbane, Bruno; Boumezbeur, Fawzi

2017-11-01

Lithium is the first-line mood stabilizer for the treatment of patients with bipolar disorder. However, its mechanisms of action and transport across the blood-brain barrier remain poorly understood. The contribution of lithium-7 magnetic resonance imaging ( 7 Li MRI) to investigate brain lithium distribution remains limited because of the modest sensitivity of the lithium nucleus and the expected low brain concentrations in humans and animal models. Therefore, we decided to image lithium distribution in the rat brain ex vivo using a turbo-spin-echo imaging sequence at 17.2 T. The estimation of lithium concentrations was performed using a phantom replacement approach accounting for B 1 inhomogeneities and differential T 1 and T 2 weighting. Our MRI-derived lithium concentrations were validated by comparison with inductively coupled plasma-mass spectrometry (ICP-MS) measurements ([Li] MRI  = 1.18[Li] MS , R = 0.95). Overall, a sensitivity of 0.03 mmol/L was achieved for a spatial resolution of 16 μL. Lithium distribution was uneven throughout the brain (normalized lithium content ranged from 0.4 to 1.4) and was mostly symmetrical, with consistently lower concentrations in the metencephalon (cerebellum and brainstem) and higher concentrations in the cortex. Interestingly, low lithium concentrations were also observed close to the lateral ventricles. The average brain-to-plasma lithium ratio was 0.34 ± 0.04, ranging from 0.29 to 0.39. Brain lithium concentrations were reasonably correlated with plasma lithium concentrations, with Pearson correlation factors ranging from 0.63 to 0.90. Copyright © 2017 John Wiley & Sons, Ltd.

Structural whole-brain covariance of the anterior and posterior hippocampus: Associations with age and memory.

PubMed

Nordin, Kristin; Persson, Jonas; Stening, Eva; Herlitz, Agneta; Larsson, Elna-Marie; Söderlund, Hedvig

2018-02-01

The hippocampus (HC) interacts with distributed brain regions to support memory and shows significant volume reductions in aging, but little is known about age effects on hippocampal whole-brain structural covariance. It is also unclear whether the anterior and posterior HC show similar or distinct patterns of whole-brain covariance and to what extent these are related to memory functions organized along the hippocampal longitudinal axis. Using the multivariate approach partial least squares, we assessed structural whole-brain covariance of the HC in addition to regional volume, in young, middle-aged and older adults (n = 221), and assessed associations with episodic and spatial memory. Based on findings of sex differences in both memory and brain aging, we further considered sex as a potential modulating factor of age effects. There were two main covariance patterns: one capturing common anterior and posterior covariance, and one differentiating the two regions by capturing anterior-specific covariance only. These patterns were differentially related to associative memory while unrelated to measures of single-item memory and spatial memory. Although patterns were qualitatively comparable across age groups, participants' expression of both patterns decreased with age, independently of sex. The results suggest that the organization of hippocampal structural whole-brain covariance remains stable across age, but that the integrity of these networks decreases as the brain undergoes age-related alterations. © 2017 Wiley Periodicals, Inc.

An Integrative Platform for Three-dimensional Quantitative Analysis of Spatially Heterogeneous Metastasis Landscapes

NASA Astrophysics Data System (ADS)

Guldner, Ian H.; Yang, Lin; Cowdrick, Kyle R.; Wang, Qingfei; Alvarez Barrios, Wendy V.; Zellmer, Victoria R.; Zhang, Yizhe; Host, Misha; Liu, Fang; Chen, Danny Z.; Zhang, Siyuan

2016-04-01

Metastatic microenvironments are spatially and compositionally heterogeneous. This seemingly stochastic heterogeneity provides researchers great challenges in elucidating factors that determine metastatic outgrowth. Herein, we develop and implement an integrative platform that will enable researchers to obtain novel insights from intricate metastatic landscapes. Our two-segment platform begins with whole tissue clearing, staining, and imaging to globally delineate metastatic landscape heterogeneity with spatial and molecular resolution. The second segment of our platform applies our custom-developed SMART 3D (Spatial filtering-based background removal and Multi-chAnnel forest classifiers-based 3D ReconsTruction), a multi-faceted image analysis pipeline, permitting quantitative interrogation of functional implications of heterogeneous metastatic landscape constituents, from subcellular features to multicellular structures, within our large three-dimensional (3D) image datasets. Coupling whole tissue imaging of brain metastasis animal models with SMART 3D, we demonstrate the capability of our integrative pipeline to reveal and quantify volumetric and spatial aspects of brain metastasis landscapes, including diverse tumor morphology, heterogeneous proliferative indices, metastasis-associated astrogliosis, and vasculature spatial distribution. Collectively, our study demonstrates the utility of our novel integrative platform to reveal and quantify the global spatial and volumetric characteristics of the 3D metastatic landscape with unparalleled accuracy, opening new opportunities for unbiased investigation of novel biological phenomena in situ.

Imaging Nicotine in Rat Brain Tissue by Use of Nanospray Desorption Electrospray Ionization Mass Spectrometry

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

Lanekoff, Ingela T.; Thomas, Mathew; Carson, James P.

Imaging mass spectrometry offers simultaneous detection of drugs, drug metabolites and endogenous substances in a single experiment. This is important when evaluating effects of a drug on a complex organ system such as the brain, where there is a need to understand how regional drug distribution impacts function. Nicotine is an addictive drug and its action in the brain is of high interest. Here we use nanospray desorption electrospray ionization, nano-DESI, imaging to discover the localization of nicotine in rat brain tissue after in vivo administration of nicotine. Nano-DESI is a new ambient technique that enables spatially-resolved analysis of tissuemore » samples without special sample pretreatment. We demonstrate high sensitivity of nano-DESI imaging that enables detection of only 0.7 fmole nicotine per pixel in the complex brain matrix. Furthermore, by adding deuterated nicotine to the solvent, we examined how matrix effects, ion suppression, and normalization affect the observed nicotine distribution. Finally, we provide preliminary results suggesting that nicotine localizes to the hippocampal substructure called dentate gyrus.« less

Cognitive Science Program. Hierarchical Distributed Networks in the Neuropsychology of Selective Attention.

DTIC Science & Technology

1985-05-15

The -. . . . . . . . . . ..- L 12 example, Hughes & Zimba (1985) have argued that attention acts simply by inhibiting the hemifield to which one is...and control of attention. Brain 104, 1981, 861-872. Hughes, H.C. & Zimba , L.D. Spatial maps of directed attention. Paper presented to the Psychonmics

An fMRI study of sex differences in regional activation to a verbal and a spatial task.

PubMed

Gur, R C; Alsop, D; Glahn, D; Petty, R; Swanson, C L; Maldjian, J A; Turetsky, B I; Detre, J A; Gee, J; Gur, R E

2000-09-01

Sex differences in cognitive performance have been documented, women performing better on some phonological tasks and men on spatial tasks. An earlier fMRI study suggested sex differences in distributed brain activation during phonological processing, with bilateral activation seen in women while men showed primarily left-lateralized activation. This blood oxygen level-dependent fMRI study examined sex differences (14 men, 13 women) in activation for a spatial task (judgment of line orientation) compared to a verbal-reasoning task (analogies) that does not typically show sex differences. Task difficulty was manipulated. Hypothesized ROI-based analysis documented the expected left-lateralized changes for the verbal task in the inferior parietal and planum temporal regions in both men and women, but only men showed right-lateralized increase for the spatial task in these regions. Image-based analysis revealed a distributed network of cortical regions activated by the tasks, which consisted of the lateral frontal, medial frontal, mid-temporal, occipitoparietal, and occipital regions. The activation was more left lateralized for the verbal and more right for the spatial tasks, but men also showed some left activation for the spatial task, which was not seen in women. Increased task difficulty produced more distributed activation for the verbal and more circumscribed activation for the spatial task. The results suggest that failure to activate the appropriate hemisphere in regions directly involved in task performance may explain certain sex differences in performance. They also extend, for a spatial task, the principle that bilateral activation in a distributed cognitive system underlies sex differences in performance. Copyright 2000 Academic Press.

Time-reversal acoustics and ultrasound-assisted convection-enhanced drug delivery to the brain

PubMed Central

Olbricht, William; Sistla, Manjari; Ghandi, Gaurav; Lewis, George; Sarvazyan, Armen

2013-01-01

Time-reversal acoustics is an effective way of focusing ultrasound deep inside heterogeneous media such as biological tissues. Convection-enhanced delivery is a method of delivering drugs into the brain by infusing them directly into the brain interstitium. These two technologies are combined in a focusing system that uses a “smart needle” to simultaneously infuse fluid into the brain and provide the necessary feedback for focusing ultrasound using time-reversal acoustics. The effects of time-reversal acoustics-focused ultrasound on the spatial distribution of infused low- and high-molecular weight tracer molecules are examined in live, anesthetized rats. Results show that exposing the rat brain to focused ultrasound significantly increases the penetration of infused compounds into the brain. The addition of stabilized microbubbles enhances the effect of ultrasound exposure. PMID:23927197

Mobile phone types and SAR characteristics of the human brain.

PubMed

Lee, Ae-Kyoung; Hong, Seon-Eui; Kwon, Jong-Hwa; Choi, Hyung-Do; Cardis, Elisabeth

2017-04-07

Mobile phones differ in terms of their operating frequency, outer shape, and form and location of the antennae, all of which affect the spatial distributions of their electromagnetic field and the level of electromagnetic absorption in the human head or brain. For this paper, the specific absorption rate (SAR) was calculated for four anatomical head models at different ages using 11 numerical phone models of different shapes and antenna configurations. The 11 models represent phone types accounting for around 86% of the approximately 1400 commercial phone models released into the Korean market since 2002. Seven of the phone models selected have an internal dual-band antenna, and the remaining four possess an external antenna. Each model was intended to generate an average absorption level equivalent to that of the same type of commercial phone model operating at the maximum available output power. The 1 g peak spatial SAR and ipsilateral and contralateral brain-averaged SARs were reported for all 11 phone models. The effects of the phone type, phone position, operating frequency, and age of head models on the brain SAR were comprehensively determined.

Mobile phone types and SAR characteristics of the human brain

NASA Astrophysics Data System (ADS)

Lee, Ae-Kyoung; Hong, Seon-Eui; Kwon, Jong-Hwa; Choi, Hyung-Do; Cardis, Elisabeth

2017-04-01

Mobile phones differ in terms of their operating frequency, outer shape, and form and location of the antennae, all of which affect the spatial distributions of their electromagnetic field and the level of electromagnetic absorption in the human head or brain. For this paper, the specific absorption rate (SAR) was calculated for four anatomical head models at different ages using 11 numerical phone models of different shapes and antenna configurations. The 11 models represent phone types accounting for around 86% of the approximately 1400 commercial phone models released into the Korean market since 2002. Seven of the phone models selected have an internal dual-band antenna, and the remaining four possess an external antenna. Each model was intended to generate an average absorption level equivalent to that of the same type of commercial phone model operating at the maximum available output power. The 1 g peak spatial SAR and ipsilateral and contralateral brain-averaged SARs were reported for all 11 phone models. The effects of the phone type, phone position, operating frequency, and age of head models on the brain SAR were comprehensively determined.

Robust generative asymmetric GMM for brain MR image segmentation.

PubMed

Ji, Zexuan; Xia, Yong; Zheng, Yuhui

2017-11-01

Accurate segmentation of brain tissues from magnetic resonance (MR) images based on the unsupervised statistical models such as Gaussian mixture model (GMM) has been widely studied during last decades. However, most GMM based segmentation methods suffer from limited accuracy due to the influences of noise and intensity inhomogeneity in brain MR images. To further improve the accuracy for brain MR image segmentation, this paper presents a Robust Generative Asymmetric GMM (RGAGMM) for simultaneous brain MR image segmentation and intensity inhomogeneity correction. First, we develop an asymmetric distribution to fit the data shapes, and thus construct a spatial constrained asymmetric model. Then, we incorporate two pseudo-likelihood quantities and bias field estimation into the model's log-likelihood, aiming to exploit the neighboring priors of within-cluster and between-cluster and to alleviate the impact of intensity inhomogeneity, respectively. Finally, an expectation maximization algorithm is derived to iteratively maximize the approximation of the data log-likelihood function to overcome the intensity inhomogeneity in the image and segment the brain MR images simultaneously. To demonstrate the performances of the proposed algorithm, we first applied the proposed algorithm to a synthetic brain MR image to show the intermediate illustrations and the estimated distribution of the proposed algorithm. The next group of experiments is carried out in clinical 3T-weighted brain MR images which contain quite serious intensity inhomogeneity and noise. Then we quantitatively compare our algorithm to state-of-the-art segmentation approaches by using Dice coefficient (DC) on benchmark images obtained from IBSR and BrainWeb with different level of noise and intensity inhomogeneity. The comparison results on various brain MR images demonstrate the superior performances of the proposed algorithm in dealing with the noise and intensity inhomogeneity. In this paper, the RGAGMM algorithm is proposed which can simply and efficiently incorporate spatial constraints into an EM framework to simultaneously segment brain MR images and estimate the intensity inhomogeneity. The proposed algorithm is flexible to fit the data shapes, and can simultaneously overcome the influence of noise and intensity inhomogeneity, and hence is capable of improving over 5% segmentation accuracy comparing with several state-of-the-art algorithms. Copyright © 2017 Elsevier B.V. All rights reserved.

Nitric Oxide in the Crustacean Brain: Regulation of Neurogenesis and Morphogenesis in the Developing Olfactory Pathway

PubMed Central

Benton, J.L.; Sandeman, D.C.; Beltz, B.S.

2009-01-01

Nitric oxide (NO) plays major roles during development and in adult organisms. We examined the temporal and spatial patterns of nitric oxide synthase (NOS) appearance in the embryonic lobster brain to localize sources of NO activity; potential NO targets were identified by defining the distribution of NO-induced cGMP. Staining patterns are compared with NOS and cyclic 3,5 guanosine monophosphate (cGMP) distribution in adult lobster brains. Manipulation of NO levels influences olfactory glomerular formation and stabilization, as well as levels of neurogenesis among the olfactory projection neurons. In the first 2 days following ablation of the lateral antennular flagella in juvenile lobsters, a wave of increased NOS immunoreactivity and a reduction in neurogenesis occur. These studies implicate nitric oxide as a developmental architect and also support a role for this molecule in the neural response to injury in the olfactory pathway. PMID:17948307

Mapping pharmaceuticals in rat brain sections using MALDI imaging mass spectrometry.

PubMed

Hsieh, Yunsheng; Li, Fangbiao; Korfmacher, Walter A

2010-01-01

Matrix-assisted laser desorption/ionization-tandem mass spectrometric method (MALDI-MS/MS) has proven to be a reliable tool for direct measurement of the disposition of small molecules in animal tissue sections. As example, MALDI-MS/MS imaging system was employed for visualizing the spatial distribution of astemizole and its primary metabolite in rat brain tissues. Astemizole is a second-generation antihistamine, a block peripheral H1 receptor, which was introduced to provide comparable therapeutic benefit but was withdrawn in most countries due to toxicity risks. Astemizole was observed to be heterogeneously distributed to most parts of brain tissue slices including cortex, hippocampus, hypothalamic, thalamus, and ventricle regions while its major metabolite, desmethylastemizole, was only found around ventricle sites. We have shown that astemizole alone is likely to be responsible for the central nervous system (CNS) side effects when its exposures became elevated.

Decoding Multiple Sound Categories in the Human Temporal Cortex Using High Resolution fMRI

PubMed Central

Zhang, Fengqing; Wang, Ji-Ping; Kim, Jieun; Parrish, Todd; Wong, Patrick C. M.

2015-01-01

Perception of sound categories is an important aspect of auditory perception. The extent to which the brain’s representation of sound categories is encoded in specialized subregions or distributed across the auditory cortex remains unclear. Recent studies using multivariate pattern analysis (MVPA) of brain activations have provided important insights into how the brain decodes perceptual information. In the large existing literature on brain decoding using MVPA methods, relatively few studies have been conducted on multi-class categorization in the auditory domain. Here, we investigated the representation and processing of auditory categories within the human temporal cortex using high resolution fMRI and MVPA methods. More importantly, we considered decoding multiple sound categories simultaneously through multi-class support vector machine-recursive feature elimination (MSVM-RFE) as our MVPA tool. Results show that for all classifications the model MSVM-RFE was able to learn the functional relation between the multiple sound categories and the corresponding evoked spatial patterns and classify the unlabeled sound-evoked patterns significantly above chance. This indicates the feasibility of decoding multiple sound categories not only within but across subjects. However, the across-subject variation affects classification performance more than the within-subject variation, as the across-subject analysis has significantly lower classification accuracies. Sound category-selective brain maps were identified based on multi-class classification and revealed distributed patterns of brain activity in the superior temporal gyrus and the middle temporal gyrus. This is in accordance with previous studies, indicating that information in the spatially distributed patterns may reflect a more abstract perceptual level of representation of sound categories. Further, we show that the across-subject classification performance can be significantly improved by averaging the fMRI images over items, because the irrelevant variations between different items of the same sound category are reduced and in turn the proportion of signals relevant to sound categorization increases. PMID:25692885

X-Ray Fluorescence Imaging: A New Tool for Studying Manganese Neurotoxicity

PubMed Central

Robison, Gregory; Zakharova, Taisiya; Fu, Sherleen; Jiang, Wendy; Fulper, Rachael; Barrea, Raul; Marcus, Matthew A.; Zheng, Wei; Pushkar, Yulia

2012-01-01

The neurotoxic effect of manganese (Mn) establishes itself in a condition known as manganism or Mn induced parkinsonism. While this condition was first diagnosed about 170 years ago, the mechanism of the neurotoxic action of Mn remains unknown. Moreover, the possibility that Mn exposure combined with other genetic and environmental factors can contribute to the development of Parkinson's disease has been discussed in the literature and several epidemiological studies have demonstrated a correlation between Mn exposure and an elevated risk of Parkinson's disease. Here, we introduce X-ray fluorescence imaging as a new quantitative tool for analysis of the Mn distribution in the brain with high spatial resolution. The animal model employed mimics deficits observed in affected human subjects. The obtained maps of Mn distribution in the brain demonstrate the highest Mn content in the globus pallidus, the thalamus, and the substantia nigra pars compacta. To test the hypothesis that Mn transport into/distribution within brain cells mimics that of other biologically relevant metal ions, such as iron, copper, or zinc, their distributions were compared. It was demonstrated that the Mn distribution does not follow the distributions of any of these metals in the brain. The majority of Mn in the brain was shown to occur in the mobile state, confirming the relevance of the chelation therapy currently used to treat Mn intoxication. In cells with accumulated Mn, it can cause neurotoxic action by affecting the mitochondrial respiratory chain. This can result in increased susceptibility of the neurons of the globus pallidus, thalamus, and substantia nigra pars compacta to various environmental or genetic insults. The obtained data is the first demonstration of Mn accumulation in the substantia nigra pars compacta, and thus, can represent a link between Mn exposure and its potential effects for development of Parkinson's disease. PMID:23185282

Direct Visualization of Neurotransmitters in Rat Brain Slices by Desorption Electrospray Ionization Mass Spectrometry Imaging (DESI - MS)

NASA Astrophysics Data System (ADS)

Fernandes, Anna Maria A. P.; Vendramini, Pedro H.; Galaverna, Renan; Schwab, Nicolas V.; Alberici, Luciane C.; Augusti, Rodinei; Castilho, Roger F.; Eberlin, Marcos N.

2016-12-01

Mass spectrometry imaging (MSI) of neurotransmitters has so far been mainly performed by matrix-assisted laser desorption/ionization (MALDI) where derivatization reagents, deuterated matrix and/or high resolution, or tandem MS have been applied to circumvent problems with interfering ion peaks from matrix and from isobaric species. We herein describe the application of desorption electrospray ionization mass spectrometry imaging (DESI)-MSI in rat brain coronal and sagittal slices for direct spatial monitoring of neurotransmitters and choline with no need of derivatization reagents and/or deuterated materials. The amino acids γ-aminobutyric (GABA), glutamate, aspartate, serine, as well as acetylcholine, dopamine, and choline were successfully imaged using a commercial DESI source coupled to a hybrid quadrupole-Orbitrap mass spectrometer. The spatial distribution of the analyzed compounds in different brain regions was determined. We conclude that the ambient matrix-free DESI-MSI is suitable for neurotransmitter imaging and could be applied in studies that involve evaluation of imbalances in neurotransmitters levels.

Brain and behaviour phenotyping of a mouse model of neurofibromatosis type-1: an MRI/DTI study on social cognition.

PubMed

Petrella, L I; Cai, Y; Sereno, J V; Gonçalves, S I; Silva, A J; Castelo-Branco, M

2016-09-01

Neurofibromatosis type-1 (NF1) is a common neurogenetic disorder and an important cause of intellectual disability. Brain-behaviour associations can be examined in vivo using morphometric magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) to study brain structure. Here, we studied structural and behavioural phenotypes in heterozygous Nf1 mice (Nf1(+/-) ) using T2-weighted imaging MRI and DTI, with a focus on social recognition deficits. We found that Nf1(+/-) mice have larger volumes than wild-type (WT) mice in regions of interest involved in social cognition, the prefrontal cortex (PFC) and the caudate-putamen (CPu). Higher diffusivity was found across a distributed network of cortical and subcortical brain regions, within and beyond these regions. Significant differences were observed for the social recognition test. Most importantly, significant structure-function correlations were identified concerning social recognition performance and PFC volumes in Nf1(+/-) mice. Analyses of spatial learning corroborated the previously known deficits in the mutant mice, as corroborated by platform crossings, training quadrant time and average proximity measures. Moreover, linear discriminant analysis of spatial performance identified 2 separate sub-groups in Nf1(+/-) mice. A significant correlation between quadrant time and CPu volumes was found specifically for the sub-group of Nf1(+/-) mice with lower spatial learning performance, suggesting additional evidence for reorganization of this region. We found strong evidence that social and spatial cognition deficits can be associated with PFC/CPu structural changes and reorganization in NF1. © 2016 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

A Compressive Sensing Approach for Glioma Margin Delineation Using Mass Spectrometry

PubMed Central

Gholami, Behnood; Agar, Nathalie Y. R.; Jolesz, Ferenc A.; Haddad, Wassim M.; Tannenbaum, Allen R.

2013-01-01

Surgery, and specifically, tumor resection, is the primary treatment for most patients suffering from brain tumors. Medical imaging techniques, and in particular, magnetic resonance imaging are currently used in diagnosis as well as image-guided surgery procedures. However, studies show that computed tomography and magnetic resonance imaging fail to accurately identify the full extent of malignant brain tumors and their microscopic infiltration. Mass spectrometry is a well-known analytical technique used to identify molecules in a given sample based on their mass. In a recent study, it is proposed to use mass spectrometry as an intraoperative tool for discriminating tumor and non-tumor tissue. Integration of mass spectrometry with the resection module allows for tumor resection and immediate molecular analysis. In this paper, we propose a framework for tumor margin delineation using compressive sensing. Specifically, we show that the spatial distribution of tumor cell concentration can be efficiently reconstructed and updated using mass spectrometry information from the resected tissue. In addition, our proposed framework is model-free, and hence, requires no prior information of spatial distribution of the tumor cell concentration. PMID:22255629

The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience.

PubMed

Burns, Randal; Roncal, William Gray; Kleissas, Dean; Lillaney, Kunal; Manavalan, Priya; Perlman, Eric; Berger, Daniel R; Bock, Davi D; Chung, Kwanghun; Grosenick, Logan; Kasthuri, Narayanan; Weiler, Nicholas C; Deisseroth, Karl; Kazhdan, Michael; Lichtman, Jeff; Reid, R Clay; Smith, Stephen J; Szalay, Alexander S; Vogelstein, Joshua T; Vogelstein, R Jacob

2013-01-01

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes - neural connectivity maps of the brain-using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems-reads to parallel disk arrays and writes to solid-state storage-to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization.

Tracking the voluntary control of auditory spatial attention with event-related brain potentials.

PubMed

Störmer, Viola S; Green, Jessica J; McDonald, John J

2009-03-01

A lateralized event-related potential (ERP) component elicited by attention-directing cues (ADAN) has been linked to frontal-lobe control but is often absent when spatial attention is deployed in the auditory modality. Here, we tested the hypothesis that ERP activity associated with frontal-lobe control of auditory spatial attention is distributed bilaterally by comparing ERPs elicited by attention-directing cues and neutral cues in a unimodal auditory task. This revealed an initial ERP positivity over the anterior scalp and a later ERP negativity over the parietal scalp. Distributed source analysis indicated that the anterior positivity was generated primarily in bilateral prefrontal cortices, whereas the more posterior negativity was generated in parietal and temporal cortices. The anterior ERP positivity likely reflects frontal-lobe attentional control, whereas the subsequent ERP negativity likely reflects anticipatory biasing of activity in auditory cortex.

A Mean Field Approach to Self-Organization in Spatially Extended Perception-Action and Psychological Systems

NASA Astrophysics Data System (ADS)

Frank, Till; Beek, Peter

It is argued that perception-action systems should be considered as spatially extended systems on account of (i) the presence of spatially distributed synchronized brain activity during the performance of perceptual-motor tasks, and (ii) the failure of conventional zero-dimensional theoretical approaches to deal with multistable perception-action systems and hysteresis in the presence of noise. It is shown that in spatially extended systems self-organization can arise due to the emergence of mean field attractors. This mean field approach is exemplified for a particular class of perception-action systems, namely, rhythmic movements. In addition, clinical implications of the mean field approach and the notion of spatially extended perception-action systems are briefly discussed in the context of psychotherapy and Parkinson's disease.

Transcranial magnetic stimulation: Improved coil design for deep brain investigation

NASA Astrophysics Data System (ADS)

Crowther, L. J.; Marketos, P.; Williams, P. I.; Melikhov, Y.; Jiles, D. C.; Starzewski, J. H.

2011-04-01

This paper reports on a design for a coil for transcranial magnetic stimulation. The design shows potential for improving the penetration depth of the magnetic field, allowing stimulation of subcortical structures within the brain. The magnetic and induced electric fields in the human head have been calculated with finite element electromagnetic modeling software and compared with empirical measurements. Results show that the coil design used gives improved penetration depth, but also indicates the likelihood of stimulation of additional tissue resulting from the spatial distribution of the magnetic field.

Structure Shapes Dynamics and Directionality in Diverse Brain Networks: Mathematical Principles and Empirical Confirmation in Three Species

NASA Astrophysics Data System (ADS)

Moon, Joon-Young; Kim, Junhyeok; Ko, Tae-Wook; Kim, Minkyung; Iturria-Medina, Yasser; Choi, Jee-Hyun; Lee, Joseph; Mashour, George A.; Lee, Uncheol

2017-04-01

Identifying how spatially distributed information becomes integrated in the brain is essential to understanding higher cognitive functions. Previous computational and empirical studies suggest a significant influence of brain network structure on brain network function. However, there have been few analytical approaches to explain the role of network structure in shaping regional activities and directionality patterns. In this study, analytical methods are applied to a coupled oscillator model implemented in inhomogeneous networks. We first derive a mathematical principle that explains the emergence of directionality from the underlying brain network structure. We then apply the analytical methods to the anatomical brain networks of human, macaque, and mouse, successfully predicting simulation and empirical electroencephalographic data. The results demonstrate that the global directionality patterns in resting state brain networks can be predicted solely by their unique network structures. This study forms a foundation for a more comprehensive understanding of how neural information is directed and integrated in complex brain networks.

Decoding the individual finger movements from single-trial functional magnetic resonance imaging recordings of human brain activity.

PubMed

Shen, Guohua; Zhang, Jing; Wang, Mengxing; Lei, Du; Yang, Guang; Zhang, Shanmin; Du, Xiaoxia

2014-06-01

Multivariate pattern classification analysis (MVPA) has been applied to functional magnetic resonance imaging (fMRI) data to decode brain states from spatially distributed activation patterns. Decoding upper limb movements from non-invasively recorded human brain activation is crucial for implementing a brain-machine interface that directly harnesses an individual's thoughts to control external devices or computers. The aim of this study was to decode the individual finger movements from fMRI single-trial data. Thirteen healthy human subjects participated in a visually cued delayed finger movement task, and only one slight button press was performed in each trial. Using MVPA, the decoding accuracy (DA) was computed separately for the different motor-related regions of interest. For the construction of feature vectors, the feature vectors from two successive volumes in the image series for a trial were concatenated. With these spatial-temporal feature vectors, we obtained a 63.1% average DA (84.7% for the best subject) for the contralateral primary somatosensory cortex and a 46.0% average DA (71.0% for the best subject) for the contralateral primary motor cortex; both of these values were significantly above the chance level (20%). In addition, we implemented searchlight MVPA to search for informative regions in an unbiased manner across the whole brain. Furthermore, by applying searchlight MVPA to each volume of a trial, we visually demonstrated the information for decoding, both spatially and temporally. The results suggest that the non-invasive fMRI technique may provide informative features for decoding individual finger movements and the potential of developing an fMRI-based brain-machine interface for finger movement. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

SPATIAL NEGLECT AND ATTENTION NETWORKS

PubMed Central

Corbetta, Maurizio; Shulman, Gordon L.

2013-01-01

Unilateral spatial neglect is a common neurological syndrome following predominantly right hemisphere injuries to ventral fronto-parietal cortex. We propose that neglect reflects deficits in the coding of saliency, control of spatial attention, and representation within an egocentric frame of reference, in conjunction with non-spatial deficits of reorienting, target detection, and arousal/vigilance. In contrast to theories that link spatial neglect to structural damage of specific brain regions, we argue that neglect is better explained by the physiological dysfunction of distributed cortical networks. The ventral lesions in right parietal, temporal, and frontal cortex that cause neglect directly impair non-spatial functions and hypoactivate the right hemisphere, inducing abnormalities in task-evoked activity and functional connectivity of a dorsal frontal-parietal network that controls spatial attention. The anatomy and right hemisphere dominance of neglect follows from the anatomy and laterality of the ventral regions that interact with the dorsal attention network. PMID:21692662

Brain Entropy Mapping Using fMRI

PubMed Central

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

Unveiling the development of intracranial injury using dynamic brain EIT: an evaluation of current reconstruction algorithms.

PubMed

Li, Haoting; Chen, Rongqing; Xu, Canhua; Liu, Benyuan; Tang, Mengxing; Yang, Lin; Dong, Xiuzhen; Fu, Feng

2017-08-21

Dynamic brain electrical impedance tomography (EIT) is a promising technique for continuously monitoring the development of cerebral injury. While there are many reconstruction algorithms available for brain EIT, there is still a lack of study to compare their performance in the context of dynamic brain monitoring. To address this problem, we develop a framework for evaluating different current algorithms with their ability to correctly identify small intracranial conductivity changes. Firstly, a simulation 3D head phantom with realistic layered structure and impedance distribution is developed. Next several reconstructing algorithms, such as back projection (BP), damped least-square (DLS), Bayesian, split Bregman (SB) and GREIT are introduced. We investigate their temporal response, noise performance, location and shape error with respect to different noise levels on the simulation phantom. The results show that the SB algorithm demonstrates superior performance in reducing image error. To further improve the location accuracy, we optimize SB by incorporating the brain structure-based conductivity distribution priors, in which differences of the conductivities between different brain tissues and the inhomogeneous conductivity distribution of the skull are considered. We compare this novel algorithm (called SB-IBCD) with SB and DLS using anatomically correct head shaped phantoms with spatial varying skull conductivity. Main results and Significance: The results showed that SB-IBCD is the most effective in unveiling small intracranial conductivity changes, where it can reduce the image error by an average of 30.0% compared to DLS.

An anatomically comprehensive atlas of the adult human brain transcriptome

PubMed Central

Guillozet-Bongaarts, Angela L.; Shen, Elaine H.; Ng, Lydia; Miller, Jeremy A.; van de Lagemaat, Louie N.; Smith, Kimberly A.; Ebbert, Amanda; Riley, Zackery L.; Abajian, Chris; Beckmann, Christian F.; Bernard, Amy; Bertagnolli, Darren; Boe, Andrew F.; Cartagena, Preston M.; Chakravarty, M. Mallar; Chapin, Mike; Chong, Jimmy; Dalley, Rachel A.; David Daly, Barry; Dang, Chinh; Datta, Suvro; Dee, Nick; Dolbeare, Tim A.; Faber, Vance; Feng, David; Fowler, David R.; Goldy, Jeff; Gregor, Benjamin W.; Haradon, Zeb; Haynor, David R.; Hohmann, John G.; Horvath, Steve; Howard, Robert E.; Jeromin, Andreas; Jochim, Jayson M.; Kinnunen, Marty; Lau, Christopher; Lazarz, Evan T.; Lee, Changkyu; Lemon, Tracy A.; Li, Ling; Li, Yang; Morris, John A.; Overly, Caroline C.; Parker, Patrick D.; Parry, Sheana E.; Reding, Melissa; Royall, Joshua J.; Schulkin, Jay; Sequeira, Pedro Adolfo; Slaughterbeck, Clifford R.; Smith, Simon C.; Sodt, Andy J.; Sunkin, Susan M.; Swanson, Beryl E.; Vawter, Marquis P.; Williams, Derric; Wohnoutka, Paul; Zielke, H. Ronald; Geschwind, Daniel H.; Hof, Patrick R.; Smith, Stephen M.; Koch, Christof; Grant, Seth G. N.; Jones, Allan R.

2014-01-01

Neuroanatomically precise, genome-wide maps of transcript distributions are critical resources to complement genomic sequence data and to correlate functional and genetic brain architecture. Here we describe the generation and analysis of a transcriptional atlas of the adult human brain, comprising extensive histological analysis and comprehensive microarray profiling of ~900 neuroanatomically precise subdivisions in two individuals. Transcriptional regulation varies enormously by anatomical location, with different regions and their constituent cell types displaying robust molecular signatures that are highly conserved between individuals. Analysis of differential gene expression and gene co-expression relationships demonstrates that brain-wide variation strongly reflects the distributions of major cell classes such as neurons, oligodendrocytes, astrocytes and microglia. Local neighbourhood relationships between fine anatomical subdivisions are associated with discrete neuronal subtypes and genes involved with synaptic transmission. The neocortex displays a relatively homogeneous transcriptional pattern, but with distinct features associated selectively with primary sensorimotor cortices and with enriched frontal lobe expression. Notably, the spatial topography of the neocortex is strongly reflected in its molecular topography— the closer two cortical regions, the more similar their transcriptomes. This freely accessible online data resource forms a high-resolution transcriptional baseline for neurogenetic studies of normal and abnormal human brain function. PMID:22996553

Using Dual Regression to Investigate Network Shape and Amplitude in Functional Connectivity Analyses

PubMed Central

Nickerson, Lisa D.; Smith, Stephen M.; Öngür, Döst; Beckmann, Christian F.

2017-01-01

Independent Component Analysis (ICA) is one of the most popular techniques for the analysis of resting state FMRI data because it has several advantageous properties when compared with other techniques. Most notably, in contrast to a conventional seed-based correlation analysis, it is model-free and multivariate, thus switching the focus from evaluating the functional connectivity of single brain regions identified a priori to evaluating brain connectivity in terms of all brain resting state networks (RSNs) that simultaneously engage in oscillatory activity. Furthermore, typical seed-based analysis characterizes RSNs in terms of spatially distributed patterns of correlation (typically by means of simple Pearson's coefficients) and thereby confounds together amplitude information of oscillatory activity and noise. ICA and other regression techniques, on the other hand, retain magnitude information and therefore can be sensitive to both changes in the spatially distributed nature of correlations (differences in the spatial pattern or “shape”) as well as the amplitude of the network activity. Furthermore, motion can mimic amplitude effects so it is crucial to use a technique that retains such information to ensure that connectivity differences are accurately localized. In this work, we investigate the dual regression approach that is frequently applied with group ICA to assess group differences in resting state functional connectivity of brain networks. We show how ignoring amplitude effects and how excessive motion corrupts connectivity maps and results in spurious connectivity differences. We also show how to implement the dual regression to retain amplitude information and how to use dual regression outputs to identify potential motion effects. Two key findings are that using a technique that retains magnitude information, e.g., dual regression, and using strict motion criteria are crucial for controlling both network amplitude and motion-related amplitude effects, respectively, in resting state connectivity analyses. We illustrate these concepts using realistic simulated resting state FMRI data and in vivo data acquired in healthy subjects and patients with bipolar disorder and schizophrenia. PMID:28348512

Quantitative Susceptibility Mapping of Human Brain Reflects Spatial Variation in Tissue Composition

PubMed Central

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

Multivariate pattern analysis reveals subtle brain anomalies relevant to the cognitive phenotype in neurofibromatosis type 1.

PubMed

Duarte, João V; Ribeiro, Maria J; Violante, Inês R; Cunha, Gil; Silva, Eduardo; Castelo-Branco, Miguel

2014-01-01

Neurofibromatosis Type 1 (NF1) is a common genetic condition associated with cognitive dysfunction. However, the pathophysiology of the NF1 cognitive deficits is not well understood. Abnormal brain structure, including increased total brain volume, white matter (WM) and grey matter (GM) abnormalities have been reported in the NF1 brain. These previous studies employed univariate model-driven methods preventing detection of subtle and spatially distributed differences in brain anatomy. Multivariate pattern analysis allows the combination of information from multiple spatial locations yielding a discriminative power beyond that of single voxels. Here we investigated for the first time subtle anomalies in the NF1 brain, using a multivariate data-driven classification approach. We used support vector machines (SVM) to classify whole-brain GM and WM segments of structural T1 -weighted MRI scans from 39 participants with NF1 and 60 non-affected individuals, divided in children/adolescents and adults groups. We also employed voxel-based morphometry (VBM) as a univariate gold standard to study brain structural differences. SVM classifiers correctly classified 94% of cases (sensitivity 92%; specificity 96%) revealing the existence of brain structural anomalies that discriminate NF1 individuals from controls. Accordingly, VBM analysis revealed structural differences in agreement with the SVM weight maps representing the most relevant brain regions for group discrimination. These included the hippocampus, basal ganglia, thalamus, and visual cortex. This multivariate data-driven analysis thus identified subtle anomalies in brain structure in the absence of visible pathology. Our results provide further insight into the neuroanatomical correlates of known features of the cognitive phenotype of NF1. Copyright © 2012 Wiley Periodicals, Inc.

Decoding word and category-specific spatiotemporal representations from MEG and EEG

PubMed Central

Chan, Alexander M.; Halgren, Eric; Marinkovic, Ksenija; Cash, Sydney S.

2010-01-01

The organization and localization of lexico-semantic information in the brain has been debated for many years. Specifically, lesion and imaging studies have attempted to map the brain areas representing living versus non-living objects, however, results remain variable. This may be due, in part, to the fact that the univariate statistical mapping analyses used to detect these brain areas are typically insensitive to subtle, but widespread, effects. Decoding techniques, on the other hand, allow for a powerful multivariate analysis of multichannel neural data. In this study, we utilize machine-learning algorithms to first demonstrate that semantic category, as well as individual words, can be decoded from EEG and MEG recordings of subjects performing a language task. Mean accuracies of 76% (chance = 50%) and 83% (chance = 20%) were obtained for the decoding of living vs. non-living category or individual words respectively. Furthermore, we utilize this decoding analysis to demonstrate that the representations of words and semantic category are highly distributed both spatially and temporally. In particular, bilateral anterior temporal, bilateral inferior frontal, and left inferior temporal-occipital sensors are most important for discrimination. Successful intersubject and intermodality decoding shows that semantic representations between stimulus modalities and individuals are reasonably consistent. These results suggest that both word and category-specific information are present in extracranially recorded neural activity and that these representations may be more distributed, both spatially and temporally, than previous studies suggest. PMID:21040796

Automatic delineation of brain regions on MRI and PET images from the pig.

PubMed

Villadsen, Jonas; Hansen, Hanne D; Jørgensen, Louise M; Keller, Sune H; Andersen, Flemming L; Petersen, Ida N; Knudsen, Gitte M; Svarer, Claus

2018-01-15

The increasing use of the pig as a research model in neuroimaging requires standardized processing tools. For example, extraction of regional dynamic time series from brain PET images requires parcellation procedures that benefit from being automated. Manual inter-modality spatial normalization to a MRI atlas is operator-dependent, time-consuming, and can be inaccurate with lack of cortical radiotracer binding or skull uptake. A parcellated PET template that allows for automatic spatial normalization to PET images of any radiotracer. MRI and [ 11 C]Cimbi-36 PET scans obtained in sixteen pigs made the basis for the atlas. The high resolution MRI scans allowed for creation of an accurately averaged MRI template. By aligning the within-subject PET scans to their MRI counterparts, an averaged PET template was created in the same space. We developed an automatic procedure for spatial normalization of the averaged PET template to new PET images and hereby facilitated transfer of the atlas regional parcellation. Evaluation of the automatic spatial normalization procedure found the median voxel displacement to be 0.22±0.08mm using the MRI template with individual MRI images and 0.92±0.26mm using the PET template with individual [ 11 C]Cimbi-36 PET images. We tested the automatic procedure by assessing eleven PET radiotracers with different kinetics and spatial distributions by using perfusion-weighted images of early PET time frames. We here present an automatic procedure for accurate and reproducible spatial normalization and parcellation of pig PET images of any radiotracer with reasonable blood-brain barrier penetration. Copyright © 2017 Elsevier B.V. All rights reserved.

Interactive 3D visualization of structural changes in the brain of a person with corticobasal syndrome

PubMed Central

Hänel, Claudia; Pieperhoff, Peter; Hentschel, Bernd; Amunts, Katrin; Kuhlen, Torsten

2014-01-01

The visualization of the progression of brain tissue loss in neurodegenerative diseases like corticobasal syndrome (CBS) can provide not only information about the localization and distribution of the volume loss, but also helps to understand the course and the causes of this neurodegenerative disorder. The visualization of such medical imaging data is often based on 2D sections, because they show both internal and external structures in one image. Spatial information, however, is lost. 3D visualization of imaging data is capable to solve this problem, but it faces the difficulty that more internally located structures may be occluded by structures near the surface. Here, we present an application with two designs for the 3D visualization of the human brain to address these challenges. In the first design, brain anatomy is displayed semi-transparently; it is supplemented by an anatomical section and cortical areas for spatial orientation, and the volumetric data of volume loss. The second design is guided by the principle of importance-driven volume rendering: A direct line-of-sight to the relevant structures in the deeper parts of the brain is provided by cutting out a frustum-like piece of brain tissue. The application was developed to run in both, standard desktop environments and in immersive virtual reality environments with stereoscopic viewing for improving the depth perception. We conclude, that the presented application facilitates the perception of the extent of brain degeneration with respect to its localization and affected regions. PMID:24847243

The distribution of pain activity across the human neonatal brain is sex dependent.

PubMed

Verriotis, Madeleine; Jones, Laura; Whitehead, Kimberley; Laudiano-Dray, Maria; Panayotidis, Ismini; Patel, Hemani; Meek, Judith; Fabrizi, Lorenzo; Fitzgerald, Maria

2018-05-12

In adults, there are differences between male and female structural and functional brain connectivity, specifically for those regions involved in pain processing. This may partly explain the observed sex differences in pain sensitivity, tolerance, and inhibitory control, and in the development of chronic pain. However, it is not known if these differences exist from birth. Cortical activity in response to a painful stimulus can be observed in the human neonatal brain, but this nociceptive activity continues to develop in the postnatal period and is qualitatively different from that of adults, partly due to the considerable cortical maturation during this time. This research aimed to investigate the effects of sex and prematurity on the magnitude and spatial distribution pattern of the long-latency nociceptive event-related potential (nERP) using electroencephalography (EEG). We measured the cortical response time-locked to a clinically required heel lance in 81 neonates born between 29 and 42 weeks gestational age (median postnatal age 4 days). The results show that heel lance results in a spatially widespread nERP response in the majority of newborns. Importantly, a widespread pattern is significantly more likely to occur in females, irrespective of gestational age at birth. This effect is not observed for the short latency somatosensory waveform in the same infants, indicating that it is selective for the nociceptive component of the response. These results suggest the early onset of a greater anatomical and functional connectivity reported in the adult female brain, and indicate the presence of pain-related sex differences from birth. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Decoding complex flow-field patterns in visual working memory.

PubMed

Christophel, Thomas B; Haynes, John-Dylan

2014-05-01

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

Functionally independent components of the late positive event-related potential during visual spatial attention.

PubMed

Makeig, S; Westerfield, M; Jung, T P; Covington, J; Townsend, J; Sejnowski, T J; Courchesne, E

1999-04-01

Human event-related potentials (ERPs) were recorded from 10 subjects presented with visual target and nontarget stimuli at five screen locations and responding to targets presented at one of the locations. The late positive response complexes of 25-75 ERP average waveforms from the two task conditions were simultaneously analyzed with Independent Component Analysis, a new computational method for blindly separating linearly mixed signals. Three spatially fixed, temporally independent, behaviorally relevant, and physiologically plausible components were identified without reference to peaks in single-channel waveforms. A novel frontoparietal component (P3f) began at approximately 140 msec and peaked, in faster responders, at the onset of the motor command. The scalp distribution of P3f appeared consistent with brain regions activated during spatial orienting in functional imaging experiments. A longer-latency large component (P3b), positive over parietal cortex, was followed by a postmotor potential (Pmp) component that peaked 200 msec after the button press and reversed polarity near the central sulcus. A fourth component associated with a left frontocentral nontarget positivity (Pnt) was evoked primarily by target-like distractors presented in the attended location. When no distractors were presented, responses of five faster-responding subjects contained largest P3f and smallest Pmp components; when distractors were included, a Pmp component appeared only in responses of the five slower-responding subjects. Direct relationships between component amplitudes, latencies, and behavioral responses, plus similarities between component scalp distributions and regional activations reported in functional brain imaging experiments suggest that P3f, Pmp, and Pnt measure the time course and strength of functionally distinct brain processes.

From chemotaxis to the cognitive map: The function of olfaction

PubMed Central

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

Multiple foci of spatial attention in multimodal working memory.

PubMed

Katus, Tobias; Eimer, Martin

2016-11-15

The maintenance of sensory information in working memory (WM) is mediated by the attentional activation of stimulus representations that are stored in perceptual brain regions. Using event-related potentials (ERPs), we measured tactile and visual contralateral delay activity (tCDA/CDA components) in a bimodal WM task to concurrently track the attention-based maintenance of information stored in anatomically segregated (somatosensory and visual) brain areas. Participants received tactile and visual sample stimuli on both sides, and in different blocks, memorized these samples on the same side or on opposite sides. After a retention delay, memory was unpredictably tested for touch or vision. In the same side blocks, tCDA and CDA components simultaneously emerged over the same hemisphere, contralateral to the memorized tactile/visual sample set. In opposite side blocks, these two components emerged over different hemispheres, but had the same sizes and onset latencies as in the same side condition. Our results reveal distinct foci of tactile and visual spatial attention that were concurrently maintained on task-relevant stimulus representations in WM. The independence of spatially-specific biasing mechanisms for tactile and visual WM content suggests that multimodal information is stored in distributed perceptual brain areas that are activated through modality-specific processes that can operate simultaneously and largely independently of each other. Copyright © 2016 Elsevier Inc. All rights reserved.

Neural Correlates of Visual–Spatial Attention in Electrocorticographic Signals in Humans

PubMed Central

Gunduz, Aysegul; Brunner, Peter; Daitch, Amy; Leuthardt, Eric C.; Ritaccio, Anthony L.; Pesaran, Bijan; Schalk, Gerwin

2011-01-01

Attention is a cognitive selection mechanism that allocates the limited processing resources of the brain to the sensory streams most relevant to our immediate goals, thereby enhancing responsiveness and behavioral performance. The underlying neural mechanisms of orienting attention are distributed across a widespread cortical network. While aspects of this network have been extensively studied, details about the electrophysiological dynamics of this network are scarce. In this study, we investigated attentional networks using electrocorticographic (ECoG) recordings from the surface of the brain, which combine broad spatial coverage with high temporal resolution, in five human subjects. ECoG was recorded when subjects covertly attended to a spatial location and responded to contrast changes in the presence of distractors in a modified Posner cueing task. ECoG amplitudes in the alpha, beta, and gamma bands identified neural changes associated with covert attention and motor preparation/execution in the different stages of the task. The results show that attentional engagement was primarily associated with ECoG activity in the visual, prefrontal, premotor, and parietal cortices. Motor preparation/execution was associated with ECoG activity in premotor/sensorimotor cortices. In summary, our results illustrate rich and distributed cortical dynamics that are associated with orienting attention and the subsequent motor preparation and execution. These findings are largely consistent with and expand on primate studies using intracortical recordings and human functional neuroimaging studies. PMID:22046153

Human brain networks function in connectome-specific harmonic waves.

PubMed

Atasoy, Selen; Donnelly, Isaac; Pearson, Joel

2016-01-21

A key characteristic of human brain activity is coherent, spatially distributed oscillations forming behaviour-dependent brain networks. However, a fundamental principle underlying these networks remains unknown. Here we report that functional networks of the human brain are predicted by harmonic patterns, ubiquitous throughout nature, steered by the anatomy of the human cerebral cortex, the human connectome. We introduce a new technique extending the Fourier basis to the human connectome. In this new frequency-specific representation of cortical activity, that we call 'connectome harmonics', oscillatory networks of the human brain at rest match harmonic wave patterns of certain frequencies. We demonstrate a neural mechanism behind the self-organization of connectome harmonics with a continuous neural field model of excitatory-inhibitory interactions on the connectome. Remarkably, the critical relation between the neural field patterns and the delicate excitation-inhibition balance fits the neurophysiological changes observed during the loss and recovery of consciousness.

Atypical hemispheric dominance for attention: functional MRI topography.

PubMed

Flöel, Agnes; Jansen, Andreas; Deppe, Michael; Kanowski, Martin; Konrad, Carsten; Sommer, Jens; Knecht, Stefan

2005-09-01

The right hemisphere is predominantly involved in tasks associated with spatial attention. However, left hemispheric dominance for spatial attention can be found in healthy individuals, and both spatial attention and language can be lateralized to the same hemisphere. Little is known about the underlying regional distribution of neural activation in these 'atypical' individuals. Previously a large number of healthy subjects were screened for hemispheric dominance of visuospatial attention and language, using functional Doppler ultrasonography. From this group, subjects were chosen who were 'atypical' for hemispheric dominance of visuospatial attention and language, and their pattern of brain activation was studied with functional magnetic resonance imaging during a task probing spatial attention. Right-handed subjects with the 'typical' pattern of brain organization served as control subjects. It was found that subjects with an inverted lateralization of language and spatial attention (language right, attention left) recruited left-hemispheric areas in the attention task, homotopic to those recruited by control subjects in the right hemisphere. Subjects with lateralization of both language and attention to the right hemisphere activated an attentional network in the right hemisphere that was comparable to control subjects. The present findings suggest that not the hemispheric side, but the intrahemispheric pattern of activation is the distinct feature for the neural processes underlying language and attention.

Spatial analysis and high resolution mapping of the human whole-brain transcriptome for integrative analysis in neuroimaging.

PubMed

Gryglewski, Gregor; Seiger, René; James, Gregory Miles; Godbersen, Godber Mathis; Komorowski, Arkadiusz; Unterholzner, Jakob; Michenthaler, Paul; Hahn, Andreas; Wadsak, Wolfgang; Mitterhauser, Markus; Kasper, Siegfried; Lanzenberger, Rupert

2018-08-01

The quantification of big pools of diverse molecules provides important insights on brain function, but is often restricted to a limited number of observations, which impairs integration with other modalities. To resolve this issue, a method allowing for the prediction of mRNA expression in the entire brain based on microarray data provided in the Allen Human Brain Atlas was developed. Microarray data of 3702 samples from 6 brain donors was registered to MNI and cortical surface space using FreeSurfer. For each of 18,686 genes, spatial dependence of transcription was assessed using variogram modelling. Variogram models were employed in Gaussian process regression to calculate best linear unbiased predictions for gene expression at all locations represented in well-established imaging atlases for cortex, subcortical structures and cerebellum. For validation, predicted whole-brain transcription of the HTR1A gene was correlated with [carbonyl- 11 C]WAY-100635 positron emission tomography data collected from 30 healthy subjects. Prediction results showed minimal bias ranging within ±0.016 (cortical surface), ±0.12 (subcortical regions) and ±0.14 (cerebellum) in units of log2 expression intensity for all genes. Across genes, the correlation of predicted and observed mRNA expression in leave-one-out cross-validation correlated with the strength of spatial dependence (cortical surface: r = 0.91, subcortical regions: r = 0.85, cerebellum: r = 0.84). 816 out of 18,686 genes exhibited a high spatial dependence accounting for more than 50% of variance in the difference of gene expression on the cortical surface. In subcortical regions and cerebellum, different sets of genes were implicated by high spatially structured variability. For the serotonin 1A receptor, correlation between PET binding potentials and predicted comprehensive mRNA expression was markedly higher (Spearman ρ = 0.72 for cortical surface, ρ = 0.84 for subcortical regions) than correlation of PET and discrete samples only (ρ = 0.55 and ρ = 0.63, respectively). Prediction of mRNA expression in the entire human brain allows for intuitive visualization of gene transcription and seamless integration in multimodal analysis without bias arising from non-uniform distribution of available samples. Extension of this methodology promises to facilitate translation of omics research and enable investigation of human brain function at a systems level. Copyright © 2018 Elsevier Inc. All rights reserved.

Spatiotemporal analysis of single-trial EEG of emotional pictures based on independent component analysis and source location

NASA Astrophysics Data System (ADS)

Liu, Jiangang; Tian, Jie

2007-03-01

The present study combined the Independent Component Analysis (ICA) and low-resolution brain electromagnetic tomography (LORETA) algorithms to identify the spatial distribution and time course of single-trial EEG record differences between neural responses to emotional stimuli vs. the neutral. Single-trial multichannel (129-sensor) EEG records were collected from 21 healthy, right-handed subjects viewing the emotion emotional (pleasant/unpleasant) and neutral pictures selected from International Affective Picture System (IAPS). For each subject, the single-trial EEG records of each emotional pictures were concatenated with the neutral, and a three-step analysis was applied to each of them in the same way. First, the ICA was performed to decompose each concatenated single-trial EEG records into temporally independent and spatially fixed components, namely independent components (ICs). The IC associated with artifacts were isolated. Second, the clustering analysis classified, across subjects, the temporally and spatially similar ICs into the same clusters, in which nonparametric permutation test for Global Field Power (GFP) of IC projection scalp maps identified significantly different temporal segments of each emotional condition vs. neutral. Third, the brain regions accounted for those significant segments were localized spatially with LORETA analysis. In each cluster, a voxel-by-voxel randomization test identified significantly different brain regions between each emotional condition vs. the neutral. Compared to the neutral, both emotional pictures elicited activation in the visual, temporal, ventromedial and dorsomedial prefrontal cortex and anterior cingulated gyrus. In addition, the pleasant pictures activated the left middle prefrontal cortex and the posterior precuneus, while the unpleasant pictures activated the right orbitofrontal cortex, posterior cingulated gyrus and somatosensory region. Our results were well consistent with other functional imaging studies, while revealed temporal dynamics of emotional processing of specific brain structure with high temporal resolution.

Spatio-temporal models of mental processes from fMRI.

PubMed

Janoos, Firdaus; Machiraju, Raghu; Singh, Shantanu; Morocz, Istvan Ákos

2011-07-15

Understanding the highly complex, spatially distributed and temporally organized phenomena entailed by mental processes using functional MRI is an important research problem in cognitive and clinical neuroscience. Conventional analysis methods focus on the spatial dimension of the data discarding the information about brain function contained in the temporal dimension. This paper presents a fully spatio-temporal multivariate analysis method using a state-space model (SSM) for brain function that yields not only spatial maps of activity but also its temporal structure along with spatially varying estimates of the hemodynamic response. Efficient algorithms for estimating the parameters along with quantitative validations are given. A novel low-dimensional feature-space for representing the data, based on a formal definition of functional similarity, is derived. Quantitative validation of the model and the estimation algorithms is provided with a simulation study. Using a real fMRI study for mental arithmetic, the ability of this neurophysiologically inspired model to represent the spatio-temporal information corresponding to mental processes is demonstrated. Moreover, by comparing the models across multiple subjects, natural patterns in mental processes organized according to different mental abilities are revealed. Copyright © 2011 Elsevier Inc. All rights reserved.

Describing the brain in autism in five dimensions--magnetic resonance imaging-assisted diagnosis of autism spectrum disorder using a multiparameter classification approach.

PubMed

Ecker, Christine; Marquand, Andre; Mourão-Miranda, Janaina; Johnston, Patrick; Daly, Eileen M; Brammer, Michael J; Maltezos, Stefanos; Murphy, Clodagh M; Robertson, Dene; Williams, Steven C; Murphy, Declan G M

2010-08-11

Autism spectrum disorder (ASD) is a neurodevelopmental condition with multiple causes, comorbid conditions, and a wide range in the type and severity of symptoms expressed by different individuals. This makes the neuroanatomy of autism inherently difficult to describe. Here, we demonstrate how a multiparameter classification approach can be used to characterize the complex and subtle structural pattern of gray matter anatomy implicated in adults with ASD, and to reveal spatially distributed patterns of discriminating regions for a variety of parameters describing brain anatomy. A set of five morphological parameters including volumetric and geometric features at each spatial location on the cortical surface was used to discriminate between people with ASD and controls using a support vector machine (SVM) analytic approach, and to find a spatially distributed pattern of regions with maximal classification weights. On the basis of these patterns, SVM was able to identify individuals with ASD at a sensitivity and specificity of up to 90% and 80%, respectively. However, the ability of individual cortical features to discriminate between groups was highly variable, and the discriminating patterns of regions varied across parameters. The classification was specific to ASD rather than neurodevelopmental conditions in general (e.g., attention deficit hyperactivity disorder). Our results confirm the hypothesis that the neuroanatomy of autism is truly multidimensional, and affects multiple and most likely independent cortical features. The spatial patterns detected using SVM may help further exploration of the specific genetic and neuropathological underpinnings of ASD, and provide new insights into the most likely multifactorial etiology of the condition.

In vivo metabolic labeling of sialoglycans in the mouse brain by using a liposome-assisted bioorthogonal reporter strategy

PubMed Central

Xie, Ran; Dong, Lu; Du, Yifei; Zhu, Yuntao; Hua, Rui; Zhang, Chen; Chen, Xing

2016-01-01

Mammalian brains are highly enriched with sialoglycans, which have been implicated in brain development and disease progression. However, in vivo labeling and visualization of sialoglycans in the mouse brain remain a challenge because of the blood−brain barrier. Here we introduce a liposome-assisted bioorthogonal reporter (LABOR) strategy for shuttling 9-azido sialic acid (9AzSia), a sialic acid reporter, into the brain to metabolically label sialoglycoconjugates, including sialylated glycoproteins and glycolipids. Subsequent bioorthogonal conjugation of the incorporated 9AzSia with fluorescent probes via click chemistry enabled fluorescence imaging of brain sialoglycans in living animals and in brain sections. Newly synthesized sialoglycans were found to widely distribute on neuronal cell surfaces, in particular at synaptic sites. Furthermore, large-scale proteomic profiling identified 140 brain sialylated glycoproteins, including a wealth of synapse-associated proteins. Finally, by performing a pulse−chase experiment, we showed that dynamic sialylation is spatially regulated, and that turnover of sialoglycans in the hippocampus is significantly slower than that in other brain regions. The LABOR strategy provides a means to directly visualize and monitor the sialoglycan biosynthesis in the mouse brain and will facilitate elucidating the functional role of brain sialylation. PMID:27125855

In-vivo RGB marking and multicolour single-cell tracking in the adult brain

PubMed Central

Gomez-Nicola, Diego; Riecken, Kristoffer; Fehse, Boris; Perry, V. Hugh

2014-01-01

In neuroscience it is a technical challenge to identify and follow the temporal and spatial distribution of cells as they differentiate. We hypothesised that RGB marking, the tagging of individual cells with unique hues resulting from simultaneous expression of the three basic colours red, green and blue, provides a convenient toolbox for the study of the CNS anatomy at the single-cell level. Using γ-retroviral and lentiviral vector sets we describe for the first time the in-vivo multicolour RGB marking of neurons in the adult brain. RGB marking also enabled us to track the spatial and temporal fate of neural stem cells in the adult brain. The application of different viral envelopes and promoters provided a useful approach to track the generation of neurons vs. glial cells at the neurogenic niche, allowing the identification of the prominent generation of new astrocytes to the striatum. Multicolour RGB marking could serve as a universal and reproducible method to study and manipulate the CNS at the single-cell level, in both health and disease. PMID:25531807

Bayesian spatial transformation models with applications in neuroimaging data

PubMed Central

Miranda, Michelle F.; Zhu, Hongtu; Ibrahim, Joseph G.

2013-01-01

Summary The aim of this paper is to develop a class of spatial transformation models (STM) to spatially model the varying association between imaging measures in a three-dimensional (3D) volume (or 2D surface) and a set of covariates. Our STMs include a varying Box-Cox transformation model for dealing with the issue of non-Gaussian distributed imaging data and a Gaussian Markov Random Field model for incorporating spatial smoothness of the imaging data. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. Simulations and real data analysis demonstrate that the STM significantly outperforms the voxel-wise linear model with Gaussian noise in recovering meaningful geometric patterns. Our STM is able to reveal important brain regions with morphological changes in children with attention deficit hyperactivity disorder. PMID:24128143

TU-D-209-06: Head and Neck Tissue Dose From X-Ray Scatter to Physicians Performing Cardiovascular Procedures

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

Fetterly, K; Schueler, B; Grams, M

Purpose: The purpose of this work was to characterize the spatial distribution of scatter radiation to the head and neck of a physician performing an x-ray interventional procedure and assess brain, eye lens, and carotid artery dose. Methods: Radiographic x-ray beams were tuned to match the peak energy (56 to 106 keV) and HVL (3.5 to 6.5 mm Al) of x-ray scatter originating from a patient during a fluoroscopic procedure. The radiographic beam was directed upon a Rando phantom from an inferior-left location to mimic a typical patient-operator geometric relationship. A lead-equivalent protective garment was secured to the phantom. Directmore » exposure Gafchromic film (XRQA2) was placed between the transverse plane layers of the head and neck region of the phantom and exposed with 4 scatter-equivalent radiographic beams. A 3×3 cm{sup 2} film placed at the left collar of the phantom was used to monitor incident dose in the position of a radiation monitoring badge. The films were converted to 2D dose distribution maps using FilmQA Pro software and an Epson 11000-XL scanner. The 2D dose distributions maps were normalized by the left collar dose and the percent of left collar dose (%LCD) was calculated for select tissues. Results: The dose maps had high dynamic range (10{sub 4}) and spatial detail. Considering all transverse planes and 4 scatter beam qualities, the median %LCD values were: whole brain 8.5%, left brain 13%, right brain 5.4%, left eye lens 67%, right eye lens 25%, left carotid artery 72%, and right carotid artery 28%. Conclusion: Scatter radiation dose to an operator can be simulated using a tuned radiographic beam and used to expose a phantom and Gafchromic film, thereby creating detailed 2D dose distribution maps. This work facilitates individualized estimation of dose to select head and neck tissues based on an operator’s radiation monitoring badge value.« less

Cerebral White Matter Integrity and Cognitive Aging: Contributions from Diffusion Tensor Imaging

PubMed Central

Madden, David J.; Bennett, Ilana J.; Song, Allen W.

2009-01-01

The integrity of cerebral white matter is critical for efficient cognitive functioning, but little is known regarding the role of white matter integrity in age-related differences in cognition. Diffusion tensor imaging (DTI) measures the directional displacement of molecular water and as a result can characterize the properties of white matter that combine to restrict diffusivity in a spatially coherent manner. This review considers DTI studies of aging and their implications for understanding adult age differences in cognitive performance. Decline in white matter integrity contributes to a disconnection among distributed neural systems, with a consistent effect on perceptual speed and executive functioning. The relation between white matter integrity and cognition varies across brain regions, with some evidence suggesting that age-related effects exhibit an anterior-posterior gradient. With continued improvements in spatial resolution and integration with functional brain imaging, DTI holds considerable promise, both for theories of cognitive aging and for translational application. PMID:19705281

Using a Simple Neural Network to Delineate Some Principles of Distributed Economic Choice.

PubMed

Balasubramani, Pragathi P; Moreno-Bote, Rubén; Hayden, Benjamin Y

2018-01-01

The brain uses a mixture of distributed and modular organization to perform computations and generate appropriate actions. While the principles under which the brain might perform computations using modular systems have been more amenable to modeling, the principles by which the brain might make choices using distributed principles have not been explored. Our goal in this perspective is to delineate some of those distributed principles using a neural network method and use its results as a lens through which to reconsider some previously published neurophysiological data. To allow for direct comparison with our own data, we trained the neural network to perform binary risky choices. We find that value correlates are ubiquitous and are always accompanied by non-value information, including spatial information (i.e., no pure value signals). Evaluation, comparison, and selection were not distinct processes; indeed, value signals even in the earliest stages contributed directly, albeit weakly, to action selection. There was no place, other than at the level of action selection, at which dimensions were fully integrated. No units were specialized for specific offers; rather, all units encoded the values of both offers in an anti-correlated format, thus contributing to comparison. Individual network layers corresponded to stages in a continuous rotation from input to output space rather than to functionally distinct modules. While our network is likely to not be a direct reflection of brain processes, we propose that these principles should serve as hypotheses to be tested and evaluated for future studies.

Using a Simple Neural Network to Delineate Some Principles of Distributed Economic Choice

PubMed Central

Balasubramani, Pragathi P.; Moreno-Bote, Rubén; Hayden, Benjamin Y.

2018-01-01

The brain uses a mixture of distributed and modular organization to perform computations and generate appropriate actions. While the principles under which the brain might perform computations using modular systems have been more amenable to modeling, the principles by which the brain might make choices using distributed principles have not been explored. Our goal in this perspective is to delineate some of those distributed principles using a neural network method and use its results as a lens through which to reconsider some previously published neurophysiological data. To allow for direct comparison with our own data, we trained the neural network to perform binary risky choices. We find that value correlates are ubiquitous and are always accompanied by non-value information, including spatial information (i.e., no pure value signals). Evaluation, comparison, and selection were not distinct processes; indeed, value signals even in the earliest stages contributed directly, albeit weakly, to action selection. There was no place, other than at the level of action selection, at which dimensions were fully integrated. No units were specialized for specific offers; rather, all units encoded the values of both offers in an anti-correlated format, thus contributing to comparison. Individual network layers corresponded to stages in a continuous rotation from input to output space rather than to functionally distinct modules. While our network is likely to not be a direct reflection of brain processes, we propose that these principles should serve as hypotheses to be tested and evaluated for future studies. PMID:29643773

The Activity of Thalamic Nucleus Reuniens Is Critical for Memory Retrieval, but Not Essential for the Early Phase of "Off-Line" Consolidation

ERIC Educational Resources Information Center

Mei, Hao; Logothetis, Nikos K.; Eschenko, Oxana

2018-01-01

Spatial navigation depends on the hippocampal function, but also requires bidirectional interactions between the hippocampus (HPC) and the prefrontal cortex (PFC). The cross-regional communication is typically regulated by critical nodes of a distributed brain network. The thalamic nucleus reuniens (RE) is reciprocally connected to both HPC and…

Gray Matter Correlates of Fluid, Crystallized, and Spatial Intelligence: Testing the P-FIT Model

ERIC Educational Resources Information Center

Colom, Roberto; Haier, Richard J.; Head, Kevin; Alvarez-Linera, Juan; Quiroga, Maria Angeles; Shih, Pei Chun; Jung, Rex E.

2009-01-01

The parieto-frontal integration theory (P-FIT) nominates several areas distributed throughout the brain as relevant for intelligence. This theory was derived from previously published studies using a variety of both imaging methods and tests of cognitive ability. Here we test this theory in a new sample of young healthy adults (N = 100) using a…

"Who" is saying "what"? Brain-based decoding of human voice and speech.

PubMed

Formisano, Elia; De Martino, Federico; Bonte, Milene; Goebel, Rainer

2008-11-07

Can we decipher speech content ("what" is being said) and speaker identity ("who" is saying it) from observations of brain activity of a listener? Here, we combine functional magnetic resonance imaging with a data-mining algorithm and retrieve what and whom a person is listening to from the neural fingerprints that speech and voice signals elicit in the listener's auditory cortex. These cortical fingerprints are spatially distributed and insensitive to acoustic variations of the input so as to permit the brain-based recognition of learned speech from unknown speakers and of learned voices from previously unheard utterances. Our findings unravel the detailed cortical layout and computational properties of the neural populations at the basis of human speech recognition and speaker identification.

Brain responses to filled gaps.

PubMed

Hestvik, Arild; Maxfield, Nathan; Schwartz, Richard G; Shafer, Valerie

2007-03-01

An unresolved issue in the study of sentence comprehension is whether the process of gap-filling is mediated by the construction of empty categories (traces), or whether the parser relates fillers directly to the associated verb's argument structure. We conducted an event-related potentials (ERP) study that used the violation paradigm to examine the time course and spatial distribution of brain responses to ungrammatically filled gaps. The results indicate that the earliest brain response to the violation is an early left anterior negativity (eLAN). This ERP indexes an early phase of pure syntactic structure building, temporally preceding ERPs that reflect semantic integration and argument structure satisfaction. The finding is interpreted as evidence that gap-filling is mediated by structurally predicted empty categories, rather than directly by argument structure operations.

Environmental impoverishment and aging alter object recognition, spatial learning, and dentate gyrus astrocytes.

PubMed

Diniz, Daniel G; Foro, César A R; Rego, Carla M D; Gloria, David A; de Oliveira, Fabio R R; Paes, Juliana M P; de Sousa, Aline A; Tokuhashi, Tatyana P; Trindade, Lucas S; Turiel, Maíra C P; Vasconcelos, Erick G R; Torres, João B; Cunnigham, Colm; Perry, Victor H; Vasconcelos, Pedro F da Costa; Diniz, Cristovam W P

2010-08-01

Environmental and age-related effects on learning and memory were analysed and compared with changes observed in astrocyte laminar distribution in the dentate gyrus. Aged (20 months) and young (6 months) adult female albino Swiss mice were housed from weaning either in impoverished conditions or in enriched conditions, and tested for episodic-like and water maze spatial memories. After these behavioral tests, brain hippocampal sections were immunolabeled for glial fibrillary acid protein to identify astrocytes. The effects of environmental enrichment on episodic-like memory were not dependent on age, and may protect water maze spatial learning and memory from declines induced by aging or impoverished environment. In the dentate gyrus, the number of astrocytes increased with both aging and enriched environment in the molecular layer, increased only with aging in the polymorphic layer, and was unchanged in the granular layer. We suggest that long-term experience-induced glial plasticity by enriched environment may represent at least part of the circuitry groundwork for improvements in behavioral performance in the aged mice brain.

Visual spatial attention tracking using high-density SSVEP data for independent brain-computer communication.

PubMed

Kelly, Simon P; Lalor, Edmund C; Reilly, Richard B; Foxe, John J

2005-06-01

The steady-state visual evoked potential (SSVEP) has been employed successfully in brain-computer interface (BCI) research, but its use in a design entirely independent of eye movement has until recently not been reported. This paper presents strong evidence suggesting that the SSVEP can be used as an electrophysiological correlate of visual spatial attention that may be harnessed on its own or in conjunction with other correlates to achieve control in an independent BCI. In this study, 64-channel electroencephalography data were recorded from subjects who covertly attended to one of two bilateral flicker stimuli with superimposed letter sequences. Offline classification of left/right spatial attention was attempted by extracting SSVEPs at optimal channels selected for each subject on the basis of the scalp distribution of SSVEP magnitudes. This yielded an average accuracy of approximately 71% across ten subjects (highest 86%) comparable across two separate cases in which flicker frequencies were set within and outside the alpha range respectively. Further, combining SSVEP features with attention-dependent parieto-occipital alpha band modulations resulted in an average accuracy of 79% (highest 87%).

Scanpath memory binding: multiple read-out experiments

NASA Astrophysics Data System (ADS)

Stark, Lawrence W.; Privitera, Claudio M.; Yang, Huiyang; Azzariti, Michela; Ho, Yeuk F.; Chan, Angie; Krischer, Christof; Weinberger, Adam

1999-05-01

The scanpath theory proposed that an internal spatial- cognitive model controls perception and the active looking eye movements, EMs, of the scanpath sequence. Evidence for this came from new quantitative methods, experiments with ambiguous figures and visual imagery and from MRI studies, all on cooperating human subjects. Besides recording EMs, we introduce other experimental techniques wherein the subject must depend upon memory bindings as in visual imagery, but may call upon other motor behaviors than EMs to read-out the remembered patterns. How is the internal model distributed and operationally assembled. The concept of binding speaks to the assigning of values for the model and its execution in various parts of the brain. Current neurological information helps to localize different aspects of the spatial-cognitive model in the brain. We suppose that there are several levels of 'binding' -- semantic or symbolic binding, structural binding for the spatial locations of the regions-of-interest and sequential binding for the dynamic execution program that yields the sequence of EMs. Our aim is to dissect out respective contributions of these different forms of binding.

Accounting for Non-Gaussian Sources of Spatial Correlation in Parametric Functional Magnetic Resonance Imaging Paradigms II: A Method to Obtain First-Level Analysis Residuals with Uniform and Gaussian Spatial Autocorrelation Function and Independent and Identically Distributed Time-Series.

PubMed

Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Lacey, Simon; Sathian, K

2018-02-01

In a recent study Eklund et al. have shown that cluster-wise family-wise error (FWE) rate-corrected inferences made in parametric statistical method-based functional magnetic resonance imaging (fMRI) studies over the past couple of decades may have been invalid, particularly for cluster defining thresholds less stringent than p < 0.001; principally because the spatial autocorrelation functions (sACFs) of fMRI data had been modeled incorrectly to follow a Gaussian form, whereas empirical data suggest otherwise. Hence, the residuals from general linear model (GLM)-based fMRI activation estimates in these studies may not have possessed a homogenously Gaussian sACF. Here we propose a method based on the assumption that heterogeneity and non-Gaussianity of the sACF of the first-level GLM analysis residuals, as well as temporal autocorrelations in the first-level voxel residual time-series, are caused by unmodeled MRI signal from neuronal and physiological processes as well as motion and other artifacts, which can be approximated by appropriate decompositions of the first-level residuals with principal component analysis (PCA), and removed. We show that application of this method yields GLM residuals with significantly reduced spatial correlation, nearly Gaussian sACF and uniform spatial smoothness across the brain, thereby allowing valid cluster-based FWE-corrected inferences based on assumption of Gaussian spatial noise. We further show that application of this method renders the voxel time-series of first-level GLM residuals independent, and identically distributed across time (which is a necessary condition for appropriate voxel-level GLM inference), without having to fit ad hoc stochastic colored noise models. Furthermore, the detection power of individual subject brain activation analysis is enhanced. This method will be especially useful for case studies, which rely on first-level GLM analysis inferences.

A cytoarchitecture-driven myelin model reveals area-specific signatures in human primary and secondary areas using ultra-high resolution in-vivo brain MRI.

PubMed

Dinse, J; Härtwich, N; Waehnert, M D; Tardif, C L; Schäfer, A; Geyer, S; Preim, B; Turner, R; Bazin, P-L

2015-07-01

This work presents a novel approach for modelling laminar myelin patterns in the human cortex in brain MR images on the basis of known cytoarchitecture. For the first time, it is possible to estimate intracortical contrast visible in quantitative ultra-high resolution MR images in specific primary and secondary cytoarchitectonic areas. The presented technique reveals different area-specific signatures which may help to study the spatial distribution of cortical T1 values and the distribution of cortical myelin in general. It may lead to a new discussion on the concordance of cyto- and myeloarchitectonic boundaries, given the absence of such concordance atlases. The modelled myelin patterns are quantitatively compared with data from human ultra-high resolution in-vivo 7T brain MR images (9 subjects). In the validation, the results are compared to one post-mortem brain sample and its ex-vivo MRI and histological data. Details of the analysis pipeline are provided. In the context of the increasing interest in advanced methods in brain segmentation and cortical architectural studies, the presented model helps to bridge the gap between the microanatomy revealed by classical histology and the macroanatomy visible in MRI. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Defining ischemic burden after traumatic brain injury using 15O PET imaging of cerebral physiology.

PubMed

Coles, Jonathan P; Fryer, Tim D; Smielewski, Peter; Rice, Kenneth; Clark, John C; Pickard, John D; Menon, David K

2004-02-01

Whereas postmortem ischemic damage is common in head injury, antemortem demonstration of ischemia has proven to be elusive. Although 15O positron emission tomography may be useful in this area, the technique has traditionally analyzed data within regions of interest (ROIs) to improve statistical accuracy. In head injury, such techniques are limited because of the lack of a priori knowledge regarding the location of ischemia, coexistence of hyperaemia, and difficulty in defining ischemic cerebral blood flow (CBF) and cerebral oxygen metabolism (CMRO2) levels. We report a novel method for defining disease pathophysiology following head injury. Voxel-based approaches are used to define the distribution of oxygen extraction fraction (OEF) across the entire brain; the standard deviation of this distribution provides a measure of the variability of OEF. These data are also used to integrate voxels above a threshold OEF value to produce an ROI based upon coherent physiology rather than spatial contiguity (the ischemic brain volume; IBV). However, such approaches may suffer from poor statistical accuracy, particularly in regions with low blood flow. The magnitude of these errors has been assessed in modeling experiments using the Hoffman brain phantom and modified control datasets. We conclude that this technique is a valid and useful tool for quantifying ischemic burden after traumatic brain injury.

Random motor generation in a finger tapping task: influence of spatial contingency and of cortical and subcortical hemispheric brain lesions

PubMed Central

Annoni, J.; Pegna, A.

1997-01-01

OBJECTIVE—To test the hypothesis that, during random motor generation, the spatial contingencies inherent to the task would induce additional preferences in normal subjects, shifting their performances farther from randomness. By contrast, perceptual or executive dysfunction could alter these task related biases in patients with brain damage.
METHODS—Two groups of patients, with right and left focal brain lesions, as well as 25 right handed subjects matched for age and handedness were asked to execute a random choice motor task—namely, to generate a random series of 180 button presses from a set of 10 keys placed vertically in front of them.
RESULTS—In the control group, as in the left brain lesion group, motor generation was subject to deviations from theoretical expected randomness, similar to those when numbers are generated mentally, as immediate repetitions (successive presses on the same key) are avoided. However, the distribution of button presses was also contingent on the topographic disposition of the keys: the central keys were chosen more often than those placed at extreme positions. Small distances were favoured, particularly with the left hand. These patterns were influenced by implicit strategies and task related contingencies.
 By contrast, right brain lesion patients with frontal involvement tended to show a more square distribution of key presses—that is, the number of key presses tended to be more equally distributed. The strategies were also altered by brain lesions: the number of immediate repetitions was more frequent when the lesion involved the right frontal areas yielding a random generation nearer to expected theoretical randomness. The frequency of adjacent key presses was increased by right anterior and left posterior cortical as well as by right subcortical lesions, but decreased by left subcortical lesions.
CONCLUSIONS—Depending on the side of the lesion and the degree of cortical-subcortical involvement, the deficits take on a different aspect and direct repetions and adjacent key presses have different patterns of alterations. Motor random generation is therefore a complex task which seems to necessitate the participation of numerous cerebral structures, among which those situated in the right frontal, left posterior, and subcortical regions have a predominant role.

 PMID:9408109

Multi-modal imaging of long-term recovery post-stroke by positron emission tomography and matrix-assisted laser desorption/ionisation mass spectrometry.

PubMed

Henderson, Fiona; Hart, Philippa J; Pradillo, Jesus M; Kassiou, Michael; Christie, Lidan; Williams, Kaye J; Boutin, Herve; McMahon, Adam

2018-05-15

Stroke is a leading cause of disability worldwide. Understanding the recovery process post-stroke is essential; however, longer-term recovery studies are lacking. In vivo positron emission tomography (PET) can image biological recovery processes, but is limited by spatial resolution and its targeted nature. Untargeted mass spectrometry imaging offers high spatial resolution, providing an ideal ex vivo tool for brain recovery imaging. Magnetic resonance imaging (MRI) was used to image a rat brain 48 h after ischaemic stroke to locate the infarcted regions of the brain. PET was carried out 3 months post-stroke using the tracers [ 18 F]DPA-714 for TSPO and [ 18 F]IAM6067 for sigma-1 receptors to image neuroinflammation and neurodegeneration, respectively. The rat brain was flash-frozen immediately after PET scanning, and sectioned for matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-MS) imaging. Three months post-stroke, PET imaging shows minimal detection of neurodegeneration and neuroinflammation, indicating that the brain has stabilised. However, MALDI-MS images reveal distinct differences in lipid distributions (e.g. phosphatidylcholine and sphingomyelin) between the scar and the healthy brain, suggesting that recovery processes are still in play. It is currently not known if the altered lipids in the scar will change on a longer time scale, or if they are stabilised products of the brain post-stroke. The data demonstrates the ability to combine MALD-MS with in vivo PET to image different aspects of stroke recovery. Copyright © 2018 John Wiley & Sons, Ltd.

Brain temperature and its fundamental properties: a review for clinical neuroscientists

PubMed Central

Wang, Huan; Wang, Bonnie; Normoyle, Kieran P.; Jackson, Kevin; Spitler, Kevin; Sharrock, Matthew F.; Miller, Claire M.; Best, Catherine; Llano, Daniel; Du, Rose

2014-01-01

Brain temperature, as an independent therapeutic target variable, has received increasingly intense clinical attention. To date, brain hypothermia represents the most potent neuroprotectant in laboratory studies. Although the impact of brain temperature is prevalent in a number of common human diseases including: head trauma, stroke, multiple sclerosis, epilepsy, mood disorders, headaches, and neurodegenerative disorders, it is evident and well recognized that the therapeutic application of induced hypothermia is limited to a few highly selected clinical conditions such as cardiac arrest and hypoxic ischemic neonatal encephalopathy. Efforts to understand the fundamental aspects of brain temperature regulation are therefore critical for the development of safe, effective, and pragmatic clinical treatments for patients with brain injuries. Although centrally-mediated mechanisms to maintain a stable body temperature are relatively well established, very little is clinically known about brain temperature's spatial and temporal distribution, its physiological and pathological fluctuations, and the mechanism underlying brain thermal homeostasis. The human brain, a metabolically “expensive” organ with intense heat production, is sensitive to fluctuations in temperature with regards to its functional activity and energy efficiency. In this review, we discuss several critical aspects concerning the fundamental properties of brain temperature from a clinical perspective. PMID:25339859

The relationship between spatial configuration and functional connectivity of brain regions

PubMed Central

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

2018-01-01

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

Comparison of electric field strength and spatial distribution of electroconvulsive therapy and magnetic seizure therapy in a realistic human head model

PubMed Central

Lee, Won Hee; Lisanby, Sarah H.; Laine, Andrew F.; Peterchev, Angel V.

2017-01-01

Background This study examines the strength and spatial distribution of the electric field induced in the brain by electroconvulsive therapy (ECT) and magnetic seizure therapy (MST). Methods The electric field induced by standard (bilateral, right unilateral, and bifrontal) and experimental (focal electrically administered seizure therapy and frontomedial) ECT electrode configurations as well as a circular MST coil configuration was simulated in an anatomically realistic finite element model of the human head. Maps of the electric field strength relative to an estimated neural activation threshold were used to evaluate the stimulation strength and focality in specific brain regions of interest for these ECT and MST paradigms and various stimulus current amplitudes. Results The standard ECT configurations and current amplitude of 800–900 mA produced the strongest overall stimulation with median of 1.8–2.9 times neural activation threshold and more than 94% of the brain volume stimulated at suprathreshold level. All standard ECT electrode placements exposed the hippocampi to suprathreshold electric field, although there were differences across modalities with bilateral and right unilateral producing respectively the strongest and weakest hippocampal stimulation. MST stimulation is up to 9 times weaker compared to conventional ECT, resulting in direct activation of only 21% of the brain. Reducing the stimulus current amplitude can make ECT as focal as MST. Conclusions The relative differences in electric field strength may be a contributing factor for the cognitive sparing observed with right unilateral compared to bilateral ECT, and MST compared to right unilateral ECT. These simulations could help understand the mechanisms of seizure therapies and develop interventions with superior risk/benefit ratio. PMID:27318858

Textural content in 3T MR: an image-based marker for Alzheimer's disease

NASA Astrophysics Data System (ADS)

Bharath Kumar, S. V.; Mullick, Rakesh; Patil, Uday

2005-04-01

In this paper, we propose a study, which investigates the first-order and second-order distributions of T2 images from a magnetic resonance (MR) scan for an age-matched data set of 24 Alzheimer's disease and 17 normal patients. The study is motivated by the desire to analyze the brain iron uptake in the hippocampus of Alzheimer's patients, which is captured by low T2 values. Since, excess iron deposition occurs locally in certain regions of the brain, we are motivated to investigate the spatial distribution of T2, which is captured by higher-order statistics. Based on the first-order and second-order distributions (involving gray level co-occurrence matrix) of T2, we show that the second-order statistics provide features with sensitivity >90% (at 80% specificity), which in turn capture the textural content in T2 data. Hence, we argue that different texture characteristics of T2 in the hippocampus for Alzheimer's and normal patients could be used as an early indicator of Alzheimer's disease.

Bayesian spatial transformation models with applications in neuroimaging data.

PubMed

Miranda, Michelle F; Zhu, Hongtu; Ibrahim, Joseph G

2013-12-01

The aim of this article is to develop a class of spatial transformation models (STM) to spatially model the varying association between imaging measures in a three-dimensional (3D) volume (or 2D surface) and a set of covariates. The proposed STM include a varying Box-Cox transformation model for dealing with the issue of non-Gaussian distributed imaging data and a Gaussian Markov random field model for incorporating spatial smoothness of the imaging data. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. Simulations and real data analysis demonstrate that the STM significantly outperforms the voxel-wise linear model with Gaussian noise in recovering meaningful geometric patterns. Our STM is able to reveal important brain regions with morphological changes in children with attention deficit hyperactivity disorder. © 2013, The International Biometric Society.

From a meso- to micro-scale connectome: array tomography and mGRASP

PubMed Central

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

Characterization of multifocal T2*-weighted MRI hypointensities in the basal ganglia of elderly, community-dwelling subjects☆

PubMed Central

Glatz, Andreas; Valdés Hernández, Maria C.; Kiker, Alexander J.; Bastin, Mark E.; Deary, Ian J.; Wardlaw, Joanna M.

2013-01-01

Multifocal T2*-weighted (T2*w) hypointensities in the basal ganglia, which are believed to arise predominantly from mineralized small vessels and perivascular spaces, have been proposed as a biomarker for cerebral small vessel disease. This study provides baseline data on their appearance on conventional structural MRI for improving and automating current manual segmentation methods. Using a published thresholding method, multifocal T2*w hypointensities were manually segmented from whole brain T2*w volumes acquired from 98 community-dwelling subjects in their early 70s. Connected component analysis was used to derive the average T2*w hypointensity count and load per basal ganglia nucleus, as well as the morphology of their connected components, while nonlinear spatial probability mapping yielded their spatial distribution. T1-weighted (T1w), T2-weighted (T2w) and T2*w intensity distributions of basal ganglia T2*w hypointensities and their appearance on T1w and T2w MRI were investigated to gain further insights into the underlying tissue composition. In 75/98 subjects, on average, 3 T2*w hypointensities with a median total volume per intracranial volume of 50.3 ppm were located in and around the globus pallidus. Individual hypointensities appeared smooth and spherical with a median volume of 12 mm3 and median in-plane area of 4 mm2. Spatial probability maps suggested an association between T2*w hypointensities and the point of entry of lenticulostriate arterioles into the brain parenchyma. T1w and T2w and especially the T2*w intensity distributions of these hypointensities, which were negatively skewed, were generally not normally distributed indicating an underlying inhomogeneous tissue structure. Globus pallidus T2*w hypointensities tended to appear hypo- and isointense on T1w and T2w MRI, whereas those from other structures appeared iso- and hypointense. This pattern could be explained by an increased mineralization of the globus pallidus. In conclusion, the characteristic spatial distribution and appearance of multifocal basal ganglia T2*w hypointensities in our elderly cohort on structural MRI appear to support the suggested association with mineralized proximal lenticulostriate arterioles and perivascular spaces. PMID:23769704

Abnormal Intrinsic Functional Hubs in Severe Male Obstructive Sleep Apnea: Evidence from a Voxel-Wise Degree Centrality Analysis.

PubMed

Li, Haijun; Li, Lan; Shao, Yi; Gong, Honghan; Zhang, Wei; Zeng, Xianjun; Ye, Chenglong; Nie, Si; Chen, Liting; Peng, Dechang

2016-01-01

Obstructive sleep apnea (OSA) has been associated with changes in brain structure and regional function in certain brain areas. However, the functional features of network organization in the whole brain remain largely uncertain. The purpose of this study was to identify the OSA-related spatial centrality distribution of the whole brain functional network and to investigate the potential altered intrinsic functional hubs. Forty male patients with newly confirmed severe OSA on polysomnography, and well-matched good sleepers, participated in this study. All participants underwent a resting-state functional MRI scan and clinical and cognitive evaluation. Voxel-wise degree centrality (DC) was measured across the whole brain, and group difference in DC was compared. The relationship between the abnormal DC value and clinical variables was assessed using a linear correlation analysis. Remarkably similar spatial distributions of the functional hubs (high DC) were found in both groups. However, OSA patients exhibited a pattern of significantly reduced regional DC in the left middle occipital gyrus, posterior cingulate cortex, left superior frontal gyrus, and bilateral inferior parietal lobule, and DC was increased in the right orbital frontal cortex, bilateral cerebellum posterior lobes, and bilateral lentiform nucleus, including the putamen, extending to the hippocampus, and the inferior temporal gyrus, which overlapped with the functional hubs. Furthermore, a linear correlation analysis revealed that the DC value in the posterior cingulate cortex and left superior frontal gyrus were positively correlated with Montreal cognitive assessment scores, The DC value in the left middle occipital gyrus and bilateral inferior parietal lobule were negatively correlated with apnea-hypopnea index and arousal index in OSA patients. Our findings suggest that OSA patients exhibited specific abnormal intrinsic functional hubs including relatively reduced and increased DC. This expands our understanding of the functional characteristics of OSA, which may provide new insights into understanding the dysfunction and pathophysiology of OSA patients.

Spatial distribution of neurons innervated by chandelier cells.

PubMed

Blazquez-Llorca, Lidia; Woodruff, Alan; Inan, Melis; Anderson, Stewart A; Yuste, Rafael; DeFelipe, Javier; Merchan-Perez, Angel

2015-09-01

Chandelier (or axo-axonic) cells are a distinct group of GABAergic interneurons that innervate the axon initial segments of pyramidal cells and are thus thought to have an important role in controlling the activity of cortical circuits. To examine the circuit connectivity of chandelier cells (ChCs), we made use of a genetic targeting strategy to label neocortical ChCs in upper layers of juvenile mouse neocortex. We filled individual ChCs with biocytin in living brain slices and reconstructed their axonal arbors from serial semi-thin sections. We also reconstructed the cell somata of pyramidal neurons that were located inside the ChC axonal trees and determined the percentage of pyramidal neurons whose axon initial segments were innervated by ChC terminals. We found that the total percentage of pyramidal neurons that were innervated by a single labeled ChC was 18-22 %. Sholl analysis showed that this percentage peaked at 22-35 % for distances between 30 and 60 µm from the ChC soma, decreasing to lower percentages with increasing distances. We also studied the three-dimensional spatial distribution of the innervated neurons inside the ChC axonal arbor using spatial statistical analysis tools. We found that innervated pyramidal neurons are not distributed at random, but show a clustered distribution, with pockets where almost all cells are innervated and other regions within the ChC axonal tree that receive little or no innervation. Thus, individual ChCs may exert a strong, widespread influence on their local pyramidal neighbors in a spatially heterogeneous fashion.

Distributed Attention Is Implemented through Theta-Rhythmic Gamma Modulation.

PubMed

Landau, Ayelet Nina; Schreyer, Helene Marianne; van Pelt, Stan; Fries, Pascal

2015-08-31

When subjects monitor a single location, visual target detection depends on the pre-target phase of an ∼8 Hz brain rhythm. When multiple locations are monitored, performance decrements suggest a division of the 8 Hz rhythm over the number of locations, indicating that different locations are sequentially sampled. Indeed, when subjects monitor two locations, performance benefits alternate at a 4 Hz rhythm. These performance alternations were revealed after a reset of attention to one location. Although resets are common and important events for attention, it is unknown whether, in the absence of resets, ongoing attention samples stimuli in alternation. Here, we examined whether spatially specific attentional sampling can be revealed by ongoing pre-target brain rhythms. Visually induced gamma-band activity plays a role in spatial attention. Therefore, we hypothesized that performance on two simultaneously monitored stimuli can be predicted by a 4 Hz modulation of gamma-band activity. Brain rhythms were assessed with magnetoencephalography (MEG) while subjects monitored bilateral grating stimuli for a unilateral target event. The corresponding contralateral gamma-band responses were subtracted from each other to isolate spatially selective, target-related fluctuations. The resulting lateralized gamma-band activity (LGA) showed opposite pre-target 4 Hz phases for detected versus missed targets. The 4 Hz phase of pre-target LGA accounted for a 14.5% modulation in performance. These findings suggest that spatial attention is a theta-rhythmic sampling process that is continuously ongoing, with each sampling cycle being implemented through gamma-band synchrony. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

Determinants of the electric field during transcranial direct current stimulation.

PubMed

Opitz, Alexander; Paulus, Walter; Will, Susanne; Antunes, Andre; Thielscher, Axel

2015-04-01

Transcranial direct current stimulation (tDCS) causes a complex spatial distribution of the electric current flow in the head which hampers the accurate localization of the stimulated brain areas. In this study we show how various anatomical features systematically shape the electric field distribution in the brain during tDCS. We constructed anatomically realistic finite element (FEM) models of two individual heads including conductivity anisotropy and different skull layers. We simulated a widely employed electrode montage to induce motor cortex plasticity and moved the stimulating electrode over the motor cortex in small steps to examine the resulting changes of the electric field distribution in the underlying cortex. We examined the effect of skull thickness and composition on the passing currents showing that thinner skull regions lead to higher electric field strengths. This effect is counteracted by a larger proportion of higher conducting spongy bone in thicker regions leading to a more homogenous current over the skull. Using a multiple regression model we could identify key factors that determine the field distribution to a significant extent, namely the thicknesses of the cerebrospinal fluid and the skull, the gyral depth and the distance to the anode and cathode. These factors account for up to 50% of the spatial variation of the electric field strength. Further, we demonstrate that individual anatomical factors can lead to stimulation "hotspots" which are partly resistant to electrode positioning. Our results give valuable novel insights in the biophysical foundation of tDCS and highlight the importance to account for individual anatomical factors when choosing an electrode montage. Copyright © 2015 Elsevier Inc. All rights reserved.

Multimodal assessment of spatial distribution of drug-tracer uptake by brain tissue after intra-arterial injections

NASA Astrophysics Data System (ADS)

Singh-Moon, Rajinder; Chaudhuri, Durba; Wang, Mei; Straubinger, Robert; Bigio, Irving J.; Joshi, Shailendra

2014-02-01

It is challenging to track the rapid changes in drug concentrations after intra-arterial (IA) administration to elucidate the pharmacokinetics of this method of drug delivery. Traditional pharmacokinetic parameters (such as protein binding) that are highly relevant to intravenous (IV) administration do not seem to apply to IA injections. Regional drug delivery is affected by the biomechanics of drug injection, resting blood flow, and local tissue extraction. In-vivo and ex-vivo, optical methods for spatial mapping of drug deposition can assist in visualizing drug distributions and aid in the screening of potential drugs and carrier candidates. We present a multimodal approach for the assessment of drug distribution in postmortem tissue specimens using diffuse reflectance spectroscopy, multispectral imaging, and confocal microscopy and demonstrate feasibility of distinguishing route of administration advantages of liposome-dye conjugate delivery. The results of this study suggest that insight on drug dynamics gained by this aggregated approach can be used to help screen and/or optimize potential drug candidates and drug delivery protocols.

Individual differences in the dominance of interhemispheric connections predict cognitive ability beyond sex and brain size.

PubMed

Martínez, Kenia; Janssen, Joost; Pineda-Pardo, José Ángel; Carmona, Susanna; Román, Francisco Javier; Alemán-Gómez, Yasser; Garcia-Garcia, David; Escorial, Sergio; Quiroga, María Ángeles; Santarnecchi, Emiliano; Navas-Sánchez, Francisco Javier; Desco, Manuel; Arango, Celso; Colom, Roberto

2017-07-15

Global structural brain connectivity has been reported to be sex-dependent with women having increased interhemispheric connectivity (InterHc) and men having greater intrahemispheric connectivity (IntraHc). However, (a) smaller brains show greater InterHc, (b) larger brains show greater IntraHc, and (c) women have, on average, smaller brains than men. Therefore, sex differences in brain size may modulate sex differences in global brain connectivity. At the behavioural level, sex-dependent differences in connectivity are thought to contribute to men-women differences in spatial and verbal abilities. But this has never been tested at the individual level. The current study assessed whether individual differences in global structural connectome measures (InterHc, IntraHc and the ratio of InterHc relative to IntraHc) predict spatial and verbal ability while accounting for the effect of sex and brain size. The sample included forty men and forty women, who did neither differ in age nor in verbal and spatial latent components defined by a broad battery of tests and tasks. High-resolution T 1 -weighted and diffusion-weighted images were obtained for computing brain size and reconstructing the structural connectome. Results showed that men had higher IntraHc than women, while women had an increased ratio InterHc/IntraHc. However, these sex differences were modulated by brain size. Increased InterHc relative to IntraHc predicted higher spatial and verbal ability irrespective of sex and brain size. The positive correlations between the ratio InterHc/IntraHc and the spatial and verbal abilities were confirmed in 1000 random samples generated by bootstrapping. Therefore, sex differences in global structural connectome connectivity were modulated by brain size and did not underlie sex differences in verbal and spatial abilities. Rather, the level of dominance of InterHc over IntraHc may be associated with individual differences in verbal and spatial abilities in both men and women. Copyright © 2017 Elsevier Inc. All rights reserved.

The relationship between spatial configuration and functional connectivity of brain regions.

PubMed

Bijsterbosch, Janine Diane; Woolrich, Mark W; Glasser, Matthew F; Robinson, Emma C; Beckmann, Christian F; Van Essen, David C; Harrison, Samuel J; Smith, Stephen M

2018-02-16

Brain connectivity is often considered in terms of the communication between functionally distinct brain regions. Many studies have investigated the extent to which patterns of coupling strength between multiple neural populations relates to behaviour. For example, studies have used 'functional connectivity fingerprints' to characterise individuals' brain activity. Here, we investigate the extent to which the exact spatial arrangement of cortical regions interacts with measures of brain connectivity. We find that the shape and exact location of brain regions interact strongly with the modelling of brain connectivity, and present evidence that the spatial arrangement of functional regions is strongly predictive of non-imaging measures of behaviour and lifestyle. We believe that, in many cases, cross-subject variations in the spatial configuration of functional brain regions are being interpreted as changes in functional connectivity. Therefore, a better understanding of these effects is important when interpreting the relationship between functional imaging data and cognitive traits. © 2018, Bijsterbosch et al.

Three validation metrics for automated probabilistic image segmentation of brain tumours

PubMed Central

Zou, Kelly H.; Wells, William M.; Kikinis, Ron; Warfield, Simon K.

2005-01-01

SUMMARY The validity of brain tumour segmentation is an important issue in image processing because it has a direct impact on surgical planning. We examined the segmentation accuracy based on three two-sample validation metrics against the estimated composite latent gold standard, which was derived from several experts’ manual segmentations by an EM algorithm. The distribution functions of the tumour and control pixel data were parametrically assumed to be a mixture of two beta distributions with different shape parameters. We estimated the corresponding receiver operating characteristic curve, Dice similarity coefficient, and mutual information, over all possible decision thresholds. Based on each validation metric, an optimal threshold was then computed via maximization. We illustrated these methods on MR imaging data from nine brain tumour cases of three different tumour types, each consisting of a large number of pixels. The automated segmentation yielded satisfactory accuracy with varied optimal thresholds. The performances of these validation metrics were also investigated via Monte Carlo simulation. Extensions of incorporating spatial correlation structures using a Markov random field model were considered. PMID:15083482

Combined ICA-LORETA analysis of mismatch negativity.

PubMed

Marco-Pallarés, J; Grau, C; Ruffini, G

2005-04-01

A major challenge for neuroscience is to map accurately the spatiotemporal patterns of activity of the large neuronal populations that are believed to underlie computing in the human brain. To study a specific example, we selected the mismatch negativity (MMN) brain wave (an event-related potential, ERP) because it gives an electrophysiological index of a "primitive intelligence" capable of detecting changes, even abstract ones, in a regular auditory pattern. ERPs have a temporal resolution of milliseconds but appear to result from mixed neuronal contributions whose spatial location is not fully understood. Thus, it is important to separate these sources in space and time. To tackle this problem, a two-step approach was designed combining the independent component analysis (ICA) and low-resolution tomography (LORETA) algorithms. Here we implement this approach to analyze the subsecond spatiotemporal dynamics of MMN cerebral sources using trial-by-trial experimental data. We show evidence that a cerebral computation mechanism underlies MMN. This mechanism is mediated by the orchestrated activity of several spatially distributed brain sources located in the temporal, frontal, and parietal areas, which activate at distinct time intervals and are grouped in six main statistically independent components.

Transmissive liquid-crystal device for correcting primary coma aberration and astigmatism in biospecimen in two-photon excitation laser scanning microscopy

NASA Astrophysics Data System (ADS)

Tanabe, Ayano; Hibi, Terumasa; Ipponjima, Sari; Matsumoto, Kenji; Yokoyama, Masafumi; Kurihara, Makoto; Hashimoto, Nobuyuki; Nemoto, Tomomi

2016-12-01

All aberrations produced inside a biospecimen can degrade the quality of a three-dimensional image in two-photon excitation laser scanning microscopy. Previously, we developed a transmissive liquid-crystal device to correct spherical aberrations that improved the image quality of a fixed-mouse-brain slice treated with an optical clearing reagent. In this study, we developed a transmissive device that corrects primary coma aberration and astigmatism. The motivation for this study is that asymmetric aberration can be induced by the shape of a biospecimen and/or by a complicated refractive-index distribution in a sample; this can considerably degrade optical performance even near the sample surface. The device's performance was evaluated by observing fluorescence beads. The device was inserted between the objective lens and microscope revolver and succeeded in improving the spatial resolution and fluorescence signal of a bead image that was originally degraded by asymmetric aberration. Finally, we implemented the device for observing a fixed whole mouse brain with a sloping surface shape and complicated internal refractive-index distribution. The correction with the device improved the spatial resolution and increased the fluorescence signal by ˜2.4×. The device can provide a simple approach to acquiring higher-quality images of biospecimens.

Postnatal brain development of the pulse type, weakly electric gymnotid fish Gymnotus omarorum.

PubMed

Iribarne, Leticia; Castelló, María E

2014-01-01

Teleosts are a numerous and diverse group of fish showing great variation in body shape, ecological niches and behaviors, and a correspondent diversity in brain morphology, usually associated with their functional specialization. Weakly electric fish are a paradigmatic example of functional specialization, as these teleosts use self-generated electric fields to sense the nearby environment and communicate with conspecifics, enabling fish to better exploit particular ecological niches. We analyzed the development of the brain of the pulse type gymnotid Gymnotus omarorum, focusing on the brain regions involved directly or indirectly in electrosensory information processing. A morphometric analysis has been made of the whole brain and of brain regions of interest, based on volumetric data obtained from 3-D reconstructions to study the growth of the whole brain and the relative growth of brain regions, from late larvae to adulthood. In the smallest studied larvae some components of the electrosensory pathway appeared to be already organized and functional, as evidenced by tract-tracing and in vivo field potential recordings of electrosensory-evoked activity. From late larval to adult stages, rombencephalic brain regions (cerebellum and electrosensory lateral line lobe) showed a positive allometric growth, mesencephalic brain regions showed a negative allometric growth, and the telencephalon showed an isometric growth. In a first step towards elucidating the role of cell proliferation in the relative growth of the analyzed brain regions, we also studied the spatial distribution of proliferation zones by means of pulse type BrdU labeling revealed by immunohistochemistry. The brain of G. omarorum late larvae showed a widespread distribution of proliferating zones, most of which were located at the ventricular-cisternal lining. Interestingly, we also found extra ventricular-cisternal proliferation zones at in the rombencephalic cerebellum and electrosensory lateral line lobe. We discuss the role of extraventricular-cisternal proliferation in the relative growth of the latter brain regions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Reproducibility and reliability of short-TE whole-brain MR spectroscopic imaging of human brain at 3T.

PubMed

Ding, Xiao-Qi; Maudsley, Andrew A; Sabati, Mohammad; Sheriff, Sulaiman; Dellani, Paulo R; Lanfermann, Heinrich

2015-03-01

A feasibility study of an echo-planar spectroscopic imaging (EPSI) using a short echo time (TE) that trades off sensitivity, compared with other short-TE methods, to achieve whole brain coverage using inversion recovery and spatial oversampling to control lipid bleeding. Twenty subjects were scanned to examine intersubject variance. One subject was scanned five times to examine intrasubject reproducibility. Data were analyzed to determine coefficients of variance (COV) and intraclass correlation coefficient (ICC) for N-acetylaspartate (NAA), total creatine (tCr), total choline (tCho), glutamine/glutamate (Glx), and myo-inositol (mI). Regional metabolite concentrations were derived by using multi-voxel analysis based on lobar-level anatomic regions. For whole-brain mean values, the intrasubject COVs were 14%, 15%, and 20% for NAA, tCr, and tCho, respectively, and 31% for Glx and mI. The intersubject COVs were up to 6% higher. For regional distributions, the intrasubject COVs were ≤ 5% for NAA, tCr, and tCho; ≤ 9% for Glx; and ≤15% for mI, with about 6% higher intersubject COVs. The ICCs of 5 metabolites were ≥ 0.7, indicating the reliability of the measurements. The present EPSI method enables estimation of the whole-brain metabolite distributions, including Glx and mI with small voxel size, and a reasonable scan time and reproducibility. © 2014 Wiley Periodicals, Inc.

Histology and Gadolinium Distribution in the Rodent Brain After the Administration of Cumulative High Doses of Linear and Macrocyclic Gadolinium-Based Contrast Agents

PubMed Central

Lohrke, Jessica; Frisk, Anna-Lena; Frenzel, Thomas; Schöckel, Laura; Rosenbruch, Martin; Jost, Gregor; Lenhard, Diana Constanze; Sieber, Martin A.; Nischwitz, Volker; Küppers, Astrid; Pietsch, Hubertus

2017-01-01

Objectives Retrospective studies in patients with primary brain tumors or other central nervous system pathologies as well as postmortem studies have suggested that gadolinium (Gd) deposition occurs in the dentate nucleus (DN) and globus pallidus (GP) after multiple administrations of primarily linear Gd-based contrast agents (GBCAs). However, this deposition has not been associated with any adverse effects or histopathological alterations. The aim of this preclinical study was to systematically examine differences between linear and macrocyclic GBCAs in their potential to induce changes in brain and skin histology including Gd distribution in high spatial resolution. Materials and Methods Fifty male Wistar-Han rats were randomly allocated into control (saline, n = 10 rats) and 4 GBCA groups (linear GBCAs: gadodiamide and gadopentetate dimeglumine, macrocyclic GBCAs: gadobutrol and gadoteridol; n = 10 rats per group). The animals received 20 daily intravenous injections at a dose of 2.5 mmol Gd/kg body weight. Eight weeks after the last GBCA administration, the animals were killed, and the brain and skin samples were histopathologically assessed (hematoxylin and eosin; cresyl violet [Nissl]) and by immunohistochemistry. The Gd concentration in the skin, bone, brain, and skeletal muscle samples were analyzed using inductively coupled plasma mass spectroscopy (ICP-MS, n = 4). The spatial Gd distribution in the brain and skin samples was analyzed in cryosections using laser ablation coupled with ICP-MS (LA-ICP-MS, n = 3). For the ultra-high resolution of Gd distribution, brain sections of rats injected with gadodiamide or saline (n = 1) were assessed by scanning electron microscopy coupled to energy dispersive x-ray spectroscopy and transmission electron microscopy, respectively. Results No histological changes were observed in the brain. In contrast, 4 of 10 animals in the gadodiamide group but none of the animals in other groups showed macroscopic and histological nephrogenic systemic fibrosis–like skin lesions. The Gd concentrations observed in the skin/brain samples (in nanomole Gd per gram of tissue) for each agent were as follows: gadodiamide: 1472 ± 115/11.1 ± 5.1, gadopentetate dimeglumine: 80.8 ± 6.2/13.1 ± 7.3, gadobutrol: 1.1 ± 0.5/0.7 ± 0.4, and gadoteridol: 1.7 ± 0.8/0.5 ± 0.2. The average detected residual Gd concentration in the brain was approximately 15-fold higher for linear than for macrocyclic GBCAs. The highest amounts of Gd found in brain corresponded to less than 0.0002% of the injected dose per gram of tissue. Using LA-ICP-MS, high Gd concentrations in the deep cerebellar nuclei and in the granular layer of the cerebellar cortex were detected only for linear gadodiamide and gadopentetate dimeglumine but not for gadoteridol or gadobutrol. The energy dispersive x-ray spectroscopy analysis revealed Gd-containing spots in the skin of animals administered gadodiamide and gadopentetate dimeglumine. Transmission electron microscopy revealed several Gd-containing spots in the region of the dentate nuclei in the brain of 1 animal injected with gadodiamide. Conclusions After repeated high dosing, nephrogenic systemic fibrosis–like macroscopic and histopathological lesions of the skin were observed only in some of the gadodiamide-treated animals. No histopathological findings were detected in the rodent brain. The administration of linear GBCAs was associated with significantly higher Gd concentrations in the brain and skin compared with macrocyclic GBCA administration. The results of LA-ICP-MS demonstrated local accumulation of Gd within the deep cerebellar nuclei and the granular layer only after the administration of linear agents. In summary, the detected low Gd concentrations in the skin and brain were well correlated with the higher kinetic stability of macrocyclic GBCA. PMID:28323657

Histology and Gadolinium Distribution in the Rodent Brain After the Administration of Cumulative High Doses of Linear and Macrocyclic Gadolinium-Based Contrast Agents.

PubMed

Lohrke, Jessica; Frisk, Anna-Lena; Frenzel, Thomas; Schöckel, Laura; Rosenbruch, Martin; Jost, Gregor; Lenhard, Diana Constanze; Sieber, Martin A; Nischwitz, Volker; Küppers, Astrid; Pietsch, Hubertus

2017-06-01

Retrospective studies in patients with primary brain tumors or other central nervous system pathologies as well as postmortem studies have suggested that gadolinium (Gd) deposition occurs in the dentate nucleus (DN) and globus pallidus (GP) after multiple administrations of primarily linear Gd-based contrast agents (GBCAs). However, this deposition has not been associated with any adverse effects or histopathological alterations. The aim of this preclinical study was to systematically examine differences between linear and macrocyclic GBCAs in their potential to induce changes in brain and skin histology including Gd distribution in high spatial resolution. Fifty male Wistar-Han rats were randomly allocated into control (saline, n = 10 rats) and 4 GBCA groups (linear GBCAs: gadodiamide and gadopentetate dimeglumine, macrocyclic GBCAs: gadobutrol and gadoteridol; n = 10 rats per group). The animals received 20 daily intravenous injections at a dose of 2.5 mmol Gd/kg body weight. Eight weeks after the last GBCA administration, the animals were killed, and the brain and skin samples were histopathologically assessed (hematoxylin and eosin; cresyl violet [Nissl]) and by immunohistochemistry. The Gd concentration in the skin, bone, brain, and skeletal muscle samples were analyzed using inductively coupled plasma mass spectroscopy (ICP-MS, n = 4). The spatial Gd distribution in the brain and skin samples was analyzed in cryosections using laser ablation coupled with ICP-MS (LA-ICP-MS, n = 3). For the ultra-high resolution of Gd distribution, brain sections of rats injected with gadodiamide or saline (n = 1) were assessed by scanning electron microscopy coupled to energy dispersive x-ray spectroscopy and transmission electron microscopy, respectively. No histological changes were observed in the brain. In contrast, 4 of 10 animals in the gadodiamide group but none of the animals in other groups showed macroscopic and histological nephrogenic systemic fibrosis-like skin lesions. The Gd concentrations observed in the skin/brain samples (in nanomole Gd per gram of tissue) for each agent were as follows: gadodiamide: 1472 ± 115/11.1 ± 5.1, gadopentetate dimeglumine: 80.8 ± 6.2/13.1 ± 7.3, gadobutrol: 1.1 ± 0.5/0.7 ± 0.4, and gadoteridol: 1.7 ± 0.8/0.5 ± 0.2. The average detected residual Gd concentration in the brain was approximately 15-fold higher for linear than for macrocyclic GBCAs. The highest amounts of Gd found in brain corresponded to less than 0.0002% of the injected dose per gram of tissue. Using LA-ICP-MS, high Gd concentrations in the deep cerebellar nuclei and in the granular layer of the cerebellar cortex were detected only for linear gadodiamide and gadopentetate dimeglumine but not for gadoteridol or gadobutrol. The energy dispersive x-ray spectroscopy analysis revealed Gd-containing spots in the skin of animals administered gadodiamide and gadopentetate dimeglumine. Transmission electron microscopy revealed several Gd-containing spots in the region of the dentate nuclei in the brain of 1 animal injected with gadodiamide. After repeated high dosing, nephrogenic systemic fibrosis-like macroscopic and histopathological lesions of the skin were observed only in some of the gadodiamide-treated animals. No histopathological findings were detected in the rodent brain. The administration of linear GBCAs was associated with significantly higher Gd concentrations in the brain and skin compared with macrocyclic GBCA administration. The results of LA-ICP-MS demonstrated local accumulation of Gd within the deep cerebellar nuclei and the granular layer only after the administration of linear agents. In summary, the detected low Gd concentrations in the skin and brain were well correlated with the higher kinetic stability of macrocyclic GBCA.

Artifact suppression and analysis of brain activities with electroencephalography signals.

PubMed

Rashed-Al-Mahfuz, Md; Islam, Md Rabiul; Hirose, Keikichi; Molla, Md Khademul Islam

2013-06-05

Brain-computer interface is a communication system that connects the brain with computer (or other devices) but is not dependent on the normal output of the brain (i.e., peripheral nerve and muscle). Electro-oculogram is a dominant artifact which has a significant negative influence on further analysis of real electroencephalography data. This paper presented a data adaptive technique for artifact suppression and brain wave extraction from electroencephalography signals to detect regional brain activities. Empirical mode decomposition based adaptive thresholding approach was employed here to suppress the electro-oculogram artifact. Fractional Gaussian noise was used to determine the threshold level derived from the analysis data without any training. The purified electroencephalography signal was composed of the brain waves also called rhythmic components which represent the brain activities. The rhythmic components were extracted from each electroencephalography channel using adaptive wiener filter with the original scale. The regional brain activities were mapped on the basis of the spatial distribution of rhythmic components, and the results showed that different regions of the brain are activated in response to different stimuli. This research analyzed the activities of a single rhythmic component, alpha with respect to different motor imaginations. The experimental results showed that the proposed method is very efficient in artifact suppression and identifying individual motor imagery based on the activities of alpha component.

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

PubMed

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

2018-01-01

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

Discriminative analysis of non-linear brain connectivity for leukoaraiosis with resting-state fMRI

NASA Astrophysics Data System (ADS)

Lai, Youzhi; Xu, Lele; Yao, Li; Wu, Xia

2015-03-01

Leukoaraiosis (LA) describes diffuse white matter abnormalities on CT or MR brain scans, often seen in the normal elderly and in association with vascular risk factors such as hypertension, or in the context of cognitive impairment. The mechanism of cognitive dysfunction is still unclear. The recent clinical studies have revealed that the severity of LA was not corresponding to the cognitive level, and functional connectivity analysis is an appropriate method to detect the relation between LA and cognitive decline. However, existing functional connectivity analyses of LA have been mostly limited to linear associations. In this investigation, a novel measure utilizing the extended maximal information coefficient (eMIC) was applied to construct non-linear functional connectivity in 44 LA subjects (9 dementia, 25 mild cognitive impairment (MCI) and 10 cognitively normal (CN)). The strength of non-linear functional connections for the first 1% of discriminative power increased in MCI compared with CN and dementia, which was opposed to its linear counterpart. Further functional network analysis revealed that the changes of the non-linear and linear connectivity have similar but not completely the same spatial distribution in human brain. In the multivariate pattern analysis with multiple classifiers, the non-linear functional connectivity mostly identified dementia, MCI and CN from LA with a relatively higher accuracy rate than the linear measure. Our findings revealed the non-linear functional connectivity provided useful discriminative power in classification of LA, and the spatial distributed changes between the non-linear and linear measure may indicate the underlying mechanism of cognitive dysfunction in LA.

Frequency-dependent tACS modulation of BOLD signal during rhythmic visual stimulation.

PubMed

Chai, Yuhui; Sheng, Jingwei; Bandettini, Peter A; Gao, Jia-Hong

2018-05-01

Transcranial alternating current stimulation (tACS) has emerged as a promising tool for modulating cortical oscillations. In previous electroencephalogram (EEG) studies, tACS has been found to modulate brain oscillatory activity in a frequency-specific manner. However, the spatial distribution and hemodynamic response for this modulation remains poorly understood. Functional magnetic resonance imaging (fMRI) has the advantage of measuring neuronal activity in regions not only below the tACS electrodes but also across the whole brain with high spatial resolution. Here, we measured fMRI signal while applying tACS to modulate rhythmic visual activity. During fMRI acquisition, tACS at different frequencies (4, 8, 16, and 32 Hz) was applied along with visual flicker stimulation at 8 and 16 Hz. We analyzed the blood-oxygen-level-dependent (BOLD) signal difference between tACS-ON vs tACS-OFF, and different frequency combinations (e.g., 4 Hz tACS, 8 Hz flicker vs 8 Hz tACS, 8 Hz flicker). We observed significant tACS modulation effects on BOLD responses when the tACS frequency matched the visual flicker frequency or the second harmonic frequency. The main effects were predominantly seen in regions that were activated by the visual task and targeted by the tACS current distribution. These findings bridge different scientific domains of tACS research and demonstrate that fMRI could localize the tACS effect on stimulus-induced brain rhythms, which could lead to a new approach for understanding the high-level cognitive process shaped by the ongoing oscillatory signal. © 2018 Wiley Periodicals, Inc.

Progressive Disintegration of Brain Networking from Normal Aging to Alzheimer Disease: Analysis of Independent Components of 18F-FDG PET Data.

PubMed

Pagani, Marco; Giuliani, Alessandro; Öberg, Johanna; De Carli, Fabrizio; Morbelli, Silvia; Girtler, Nicola; Arnaldi, Dario; Accardo, Jennifer; Bauckneht, Matteo; Bongioanni, Francesca; Chincarini, Andrea; Sambuceti, Gianmario; Jonsson, Cathrine; Nobili, Flavio

2017-07-01

Brain connectivity has been assessed in several neurodegenerative disorders investigating the mutual correlations between predetermined regions or nodes. Selective breakdown of brain networks during progression from normal aging to Alzheimer disease dementia (AD) has also been observed. Methods: We implemented independent-component analysis of 18 F-FDG PET data in 5 groups of subjects with cognitive states ranging from normal aging to AD-including mild cognitive impairment (MCI) not converting or converting to AD-to disclose the spatial distribution of the independent components in each cognitive state and their accuracy in discriminating the groups. Results: We could identify spatially distinct independent components in each group, with generation of local circuits increasing proportionally to the severity of the disease. AD-specific independent components first appeared in the late-MCI stage and could discriminate converting MCI and AD from nonconverting MCI with an accuracy of 83.5%. Progressive disintegration of the intrinsic networks from normal aging to MCI to AD was inversely proportional to the conversion time. Conclusion: Independent-component analysis of 18 F-FDG PET data showed a gradual disruption of functional brain connectivity with progression of cognitive decline in AD. This information might be useful as a prognostic aid for individual patients and as a surrogate biomarker in intervention trials. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Quantitative dual-probe microdialysis: mathematical model and analysis.

PubMed

Chen, Kevin C; Höistad, Malin; Kehr, Jan; Fuxe, Kjell; Nicholson, Charles

2002-04-01

Steady-state microdialysis is a widely used technique to monitor the concentration changes and distributions of substances in tissues. To obtain more information about brain tissue properties from microdialysis, a dual-probe approach was applied to infuse and sample the radiotracer, [3H]mannitol, simultaneously both in agar gel and in the rat striatum. Because the molecules released by one probe and collected by the other must diffuse through the interstitial space, the concentration profile exhibits dynamic behavior that permits the assessment of the diffusion characteristics in the brain extracellular space and the clearance characteristics. In this paper a mathematical model for dual-probe microdialysis was developed to study brain interstitial diffusion and clearance processes. Theoretical expressions for the spatial distribution of the infused tracer in the brain extracellular space and the temporal concentration at the probe outlet were derived. A fitting program was developed using the simplex algorithm, which finds local minima of the standard deviations between experiments and theory by adjusting the relevant parameters. The theoretical curves accurately fitted the experimental data and generated realistic diffusion parameters, implying that the mathematical model is capable of predicting the interstitial diffusion behavior of [3H]mannitol and that it will be a valuable quantitative tool in dual-probe microdialysis.

Bayesian analysis of multimodal data and brain imaging

NASA Astrophysics Data System (ADS)

Assadi, Amir H.; Eghbalnia, Hamid; Backonja, Miroslav; Wakai, Ronald T.; Rutecki, Paul; Haughton, Victor

2000-06-01

It is often the case that information about a process can be obtained using a variety of methods. Each method is employed because of specific advantages over the competing alternatives. An example in medical neuro-imaging is the choice between fMRI and MEG modes where fMRI can provide high spatial resolution in comparison to the superior temporal resolution of MEG. The combination of data from varying modes provides the opportunity to infer results that may not be possible by means of any one mode alone. We discuss a Bayesian and learning theoretic framework for enhanced feature extraction that is particularly suited to multi-modal investigations of massive data sets from multiple experiments. In the following Bayesian approach, acquired knowledge (information) regarding various aspects of the process are all directly incorporated into the formulation. This information can come from a variety of sources. In our case, it represents statistical information obtained from other modes of data collection. The information is used to train a learning machine to estimate a probability distribution, which is used in turn by a second machine as a prior, in order to produce a more refined estimation of the distribution of events. The computational demand of the algorithm is handled by proposing a distributed parallel implementation on a cluster of workstations that can be scaled to address real-time needs if required. We provide a simulation of these methods on a set of synthetically generated MEG and EEG data. We show how spatial and temporal resolutions improve by using prior distributions. The method on fMRI signals permits one to construct the probability distribution of the non-linear hemodynamics of the human brain (real data). These computational results are in agreement with biologically based measurements of other labs, as reported to us by researchers from UK. We also provide preliminary analysis involving multi-electrode cortical recording that accompanies behavioral data in pain experiments on freely moving mice subjected to moderate heat delivered by an electric bulb. Summary of new or breakthrough ideas: (1) A new method to estimate probability distribution for measurement of nonlinear hemodynamics of brain from a multi- modal neuronal data. This is the first time that such an idea is tried, to our knowledge. (2) Breakthrough in improvement of time resolution of fMRI signals using (1) above.

Current density distributions, field distributions and impedance analysis of segmented deep brain stimulation electrodes

NASA Astrophysics Data System (ADS)

Wei, Xuefeng F.; Grill, Warren M.

2005-12-01

Deep brain stimulation (DBS) electrodes are designed to stimulate specific areas of the brain. The most widely used DBS electrode has a linear array of 4 cylindrical contacts that can be selectively turned on depending on the placement of the electrode and the specific area of the brain to be stimulated. The efficacy of DBS therapy can be improved by localizing the current delivery into specific populations of neurons and by increasing the power efficiency through a suitable choice of electrode geometrical characteristics. We investigated segmented electrode designs created by sectioning each cylindrical contact into multiple rings. Prototypes of these designs, made with different materials and larger dimensions than those of clinical DBS electrodes, were evaluated in vitro and in simulation. A finite element model was developed to study the effects of varying the electrode characteristics on the current density and field distributions in an idealized electrolytic medium and in vitro experiments were conducted to measure the electrode impedance. The current density over the electrode surface increased towards the edges of the electrode, and multiple edges increased the non-uniformity of the current density profile. The edge effects were more pronounced over the end segments than over the central segments. Segmented electrodes generated larger magnitudes of the second spatial difference of the extracellular potentials, and thus required lower stimulation intensities to achieve the same level of neuronal activation as solid electrodes. For a fixed electrode conductive area, increasing the number of segments (edges) decreased the impedance compared to a single solid electrode, because the average current density over the segments increased. Edge effects played a critical role in determining the current density distributions, neuronal excitation patterns, and impedance of cylindrical electrodes, and segmented electrodes provide a means to increase the efficiency of DBS.

Primary Blast Injury Criteria for Animal/Human TBI Models using Field Validated Shock Tubes

DTIC Science & Technology

2017-09-01

differential pathological response, which depends on the local tissue composition, and the response is to insult depends upon the cell type. regions...Neuroinflammation A single blast induces cell-type dependent increase in NADPH oxidase isoforms We have performed characterization of the spatial variations and...uniformly distribute and affect the whole brain. However, pathophysiological outcomes (e.g., NOX changes) in response to bTBI depend on the differential

Lateralization of Egocentric and Allocentric Spatial Processing after Parietal Brain Lesions

ERIC Educational Resources Information Center

Iachini, Tina; Ruggiero, Gennaro; Conson, Massimiliano; Trojano, Luigi

2009-01-01

The purpose of this paper was to verify whether left and right parietal brain lesions may selectively impair egocentric and allocentric processing of spatial information in near/far spaces. Two Right-Brain-Damaged (RBD), 2 Left-Brain-Damaged (LBD) patients (not affected by neglect or language disturbances) and eight normal controls were submitted…

TBI-Induced Formation of Toxic Tau and Its Biochemical Similarities to Tau in AD Brains

DTIC Science & Technology

2016-10-01

onto wild-type mice markedly reduces 1) memory including contextual fear memory and spatial memory, and 2) long-term potentiation, a type of...TERMS Tau, contextual fear memory, spatial memory, synaptic plasticity, traumatic brain injury, Alzheimer’s disease 16. SECURITY CLASSIFICATION OF: 17...mechanism leading to TBI and AD. 2 KEYWORDS Tau, contextual fear memory, spatial memory, synaptic plasticity, traumatic brain injury, Alzheimer’s

Spatial Hyperschematia without Spatial Neglect after Insulo-Thalamic Disconnection

PubMed Central

Saj, Arnaud; Wilcke, Juliane C.; Gschwind, Markus; Emond, Héloïse; Assal, Frédéric

2013-01-01

Different spatial representations are not stored as a single multipurpose map in the brain. Right brain-damaged patients can show a distortion, a compression of peripersonal and extrapersonal space. Here we report the case of a patient with a right insulo-thalamic disconnection without spatial neglect. The patient, compared with 10 healthy control subjects, showed a constant and reliable increase of her peripersonal and extrapersonal egocentric space representations - that we named spatial hyperschematia - yet left her allocentric space representations intact. This striking dissociation shows that our interactions with the surrounding world are represented and processed modularly in the human brain, depending on their frame of reference. PMID:24302992

Structural white-matter connections mediating distinct behavioral components of spatial neglect in right brain-damaged patients.

PubMed

Vaessen, Maarten J; Saj, Arnaud; Lovblad, Karl-Olof; Gschwind, Markus; Vuilleumier, Patrik

2016-04-01

Spatial neglect is a neuropsychological syndrome in which patients fail to perceive and orient to stimuli located in the space contralateral to the lesioned hemisphere. It is characterized by a wide heterogeneity in clinical symptoms which can be grouped into distinct behavioral components correlating with different lesion sites. Moreover, damage to white-matter (WM) fiber tracts has been suggested to disconnect brain networks that mediate different functions associated with spatial cognition and attention. However, it remains unclear what WM pathways are associated with functionally dissociable neglect components. In this study we examined nine patients with a focal right hemisphere stroke using a series of neuropsychological tests and diffusion tensor imaging (DTI) in order to disentangle the role of specific WM pathways in neglect symptoms. First, following previous work, the behavioral test scores of patients were factorized into three independent components reflecting perceptual, exploratory, and object-centered deficits in spatial awareness. We then examined the structural neural substrates of these components by correlating indices of WM integrity (fractional anisotropy) with the severity of deficits along each profile. Several locations in the right parietal and frontal WM correlated with neuropsychological scores. Fiber tracts projecting from these locations indicated that posterior parts of the superior longitudinal fasciculus (SLF), as well as nearby callosal fibers connecting ipsilateral and contralateral parietal areas, were associated with perceptual spatial deficits, whereas more anterior parts of SLF and inferior fronto-occipital fasciculus (IFOF) were predominantly associated with object-centered deficits. In addition, connections between frontal areas and superior colliculus were found to be associated with the exploratory deficits. Our results provide novel support to the view that neglect may result from disconnection lesions in distributed brain networks, but also extend these notions by highlighting the role of dissociable circuits in different functional components of the neglect syndrome. However these preliminary findings require replication with larger samples of patients. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatial working memory in heavy cannabis users: a functional magnetic resonance imaging study.

PubMed

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.

Tracking ongoing cognition in individuals using brief, whole-brain functional connectivity patterns

PubMed Central

Gonzalez-Castillo, Javier; Hoy, Colin W.; Handwerker, Daniel A.; Robinson, Meghan E.; Buchanan, Laura C.; Saad, Ziad S.; Bandettini, Peter A.

2015-01-01

Functional connectivity (FC) patterns in functional MRI exhibit dynamic behavior on the scale of seconds, with rich spatiotemporal structure and limited sets of whole-brain, quasi-stable FC configurations (FC states) recurring across time and subjects. Based on previous evidence linking various aspects of cognition to group-level, minute-to-minute FC changes in localized connections, we hypothesized that whole-brain FC states may reflect the global, orchestrated dynamics of cognitive processing on the scale of seconds. To test this hypothesis, subjects were continuously scanned as they engaged in and transitioned between mental states dictated by tasks. FC states computed within windows as short as 22.5 s permitted robust tracking of cognition in single subjects with near perfect accuracy. Accuracy dropped markedly for subjects with the lowest task performance. Spatially restricting FC information decreased accuracy at short time scales, emphasizing the distributed nature of whole-brain FC dynamics, beyond univariate magnitude changes, as valuable markers of cognition. PMID:26124112

Towards deep brain monitoring with superficial EEG sensors plus neuromodulatory focused ultrasound

PubMed Central

Darvas, F; Mehić, E; Caler, CJ; Ojemann, JG; Mourad, PD

2017-01-01

Noninvasive recordings of electrophysiological activity have limited anatomical specificity and depth. We hypothesized that spatially tagging a small volume of brain with a unique electroencephalogram (EEG) signal induced by pulsed focused ultrasound (pFU) could overcome those limitations. As a first step towards testing this hypothesis, we applied transcranial ultrasound (2 MHz, 200 microsecond-long pulses applied at 1050 Hz for one second at a spatial peak temporal average intensity of 1.4 W/cm2) to the brains of anesthetized rats while simultaneously recording EEG signals. We observed a significant 1050 Hz electrophysiological signal only when ultrasound was applied to living brain. Moreover, amplitude demodulation of the EEG signal at 1050 Hz yielded measurement of gamma band (>30 Hz) brain activity consistent with direct measurements of that activity. These results represent preliminary support for use of pFU as a spatial tagging mechanism for non-invasive EEG-based mapping of deep brain activity with high spatial resolution. PMID:27181686

Investigation of blast-induced traumatic brain injury.

PubMed

Taylor, Paul A; Ludwigsen, John S; Ford, Corey C

2014-01-01

Many troops deployed in Iraq and Afghanistan have sustained blast-related, closed-head injuries from being within non-lethal distance of detonated explosive devices. Little is known, however, about the mechanisms associated with blast exposure that give rise to traumatic brain injury (TBI). This study attempts to identify the precise conditions of focused stress wave energy within the brain, resulting from blast exposure, which will correlate with a threshold for persistent brain injury. This study developed and validated a set of modelling tools to simulate blast loading to the human head. Using these tools, the blast-induced, early-time intracranial wave motions that lead to focal brain damage were simulated. The simulations predict the deposition of three distinct wave energy components, two of which can be related to injury-inducing mechanisms, namely cavitation and shear. Furthermore, the results suggest that the spatial distributions of these damaging energy components are independent of blast direction. The predictions reported herein will simplify efforts to correlate simulation predictions with clinical measures of TBI and aid in the development of protective headwear.

Investigation of blast-induced traumatic brain injury

PubMed Central

Ludwigsen, John S.; Ford, Corey C.

2014-01-01

Objective Many troops deployed in Iraq and Afghanistan have sustained blast-related, closed-head injuries from being within non-lethal distance of detonated explosive devices. Little is known, however, about the mechanisms associated with blast exposure that give rise to traumatic brain injury (TBI). This study attempts to identify the precise conditions of focused stress wave energy within the brain, resulting from blast exposure, which will correlate with a threshold for persistent brain injury. Methods This study developed and validated a set of modelling tools to simulate blast loading to the human head. Using these tools, the blast-induced, early-time intracranial wave motions that lead to focal brain damage were simulated. Results The simulations predict the deposition of three distinct wave energy components, two of which can be related to injury-inducing mechanisms, namely cavitation and shear. Furthermore, the results suggest that the spatial distributions of these damaging energy components are independent of blast direction. Conclusions The predictions reported herein will simplify efforts to correlate simulation predictions with clinical measures of TBI and aid in the development of protective headwear. PMID:24766453

Active immunization against vasoactive intestinal polypeptide decreases neuronal recruitment and inhibits reproduction in zebra finches.

PubMed

Vistoropsky, Yulia; Heiblum, Rachel; Smorodinsky, Nechama-Ina; Barnea, Anat

2016-08-15

Neurogenesis and neuronal recruitment occur in adult brains of many vertebrates, and the hypothesis is that these phenomena contribute to the brain plasticity that enables organisms to adjust to environmental changes. In mammals, vasoactive intestinal polypeptide (VIP) is known to have many neuroprotective properties, but in the avian brain, although widely distributed, its role in neuronal recruitment is not yet understood. In the present study we actively immunized adult zebra finches against VIP conjugated to KLH and compared neuronal recruitment in their brains, with brains of control birds, which were immunized against KLH. We looked at two forebrain regions: the nidopallium caudale (NC), which plays a role in vocal communication, and the hippocampus (HC), which is involved in the processing of spatial information. Our data demonstrate that active immunization against VIP reduces neuronal recruitment, inhibits reproduction, and induces molting, with no change in plasma prolactin levels. Thus, our observations suggest that VIP has a direct positive role in neuronal recruitment and reproduction in birds. J. Comp. Neurol. 524:2516-2528, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Plasticity and stability of visual field maps in adult primary visual cortex

PubMed Central

Wandell, Brian A.; Smirnakis, Stelios M.

2010-01-01

Preface It is important to understand the balance between cortical plasticity and stability in various systems and spatial scales in the adult brain. We review measurements of adult plasticity in primary visual cortex (V1), a structure that has a key role in distributing visual information. There are claims of plasticity at multiple spatial scales in adult V1, but many inconsistencies in the data raise questions about the extent and nature of such plasticity. Understanding is further limited by a lack of quantitative models to guide the interpretation of the data. These problems limit efforts to translate research findings about adult cortical plasticity into significant clinical, educational and policy applications. PMID:19904279

The circuit architecture of whole brains at the mesoscopic scale.

PubMed

Mitra, Partha P

2014-09-17

Vertebrate brains of even moderate size are composed of astronomically large numbers of neurons and show a great degree of individual variability at the microscopic scale. This variation is presumably the result of phenotypic plasticity and individual experience. At a larger scale, however, relatively stable species-typical spatial patterns are observed in neuronal architecture, e.g., the spatial distributions of somata and axonal projection patterns, probably the result of a genetically encoded developmental program. The mesoscopic scale of analysis of brain architecture is the transitional point between a microscopic scale where individual variation is prominent and the macroscopic level where a stable, species-typical neural architecture is observed. The empirical existence of this scale, implicit in neuroanatomical atlases, combined with advances in computational resources, makes studying the circuit architecture of entire brains a practical task. A methodology has previously been proposed that employs a shotgun-like grid-based approach to systematically cover entire brain volumes with injections of neuronal tracers. This methodology is being employed to obtain mesoscale circuit maps in mouse and should be applicable to other vertebrate taxa. The resulting large data sets raise issues of data representation, analysis, and interpretation, which must be resolved. Even for data representation the challenges are nontrivial: the conventional approach using regional connectivity matrices fails to capture the collateral branching patterns of projection neurons. Future success of this promising research enterprise depends on the integration of previous neuroanatomical knowledge, partly through the development of suitable computational tools that encapsulate such expertise. Copyright © 2014 Elsevier Inc. All rights reserved.

Whole-brain diffusion tensor imaging in correlation to visual-evoked potentials in multiple sclerosis: a tract-based spatial statistics analysis.

PubMed

Lobsien, D; Ettrich, B; Sotiriou, K; Classen, J; Then Bergh, F; Hoffmann, K-T

2014-01-01

Functional correlates of microstructural damage of the brain affected by MS are incompletely understood. The purpose of this study was to evaluate correlations of visual-evoked potentials with microstructural brain changes as determined by DTI in patients with demyelinating central nervous disease. Sixty-one patients with clinically isolated syndrome or MS were prospectively recruited. The mean P100 visual-evoked potential latencies of the right and left eyes of each patient were calculated and used for the analysis. For DTI acquisition, a single-shot echo-planar imaging pulse sequence with 80 diffusion directions was performed at 3T. Fractional anisotropy, radial diffusivity, and axial diffusivity were calculated and correlated with mean P100 visual-evoked potentials by tract-based spatial statistics. Significant negative correlations between mean P100 visual-evoked potentials and fractional anisotropy and significant positive correlations between mean P100 visual-evoked potentials and radial diffusivity were found widespread over the whole brain. The highest significance was found in the optic radiation, frontoparietal white matter, and corpus callosum. Significant positive correlations between mean P100 visual-evoked potentials and axial diffusivity were less widespread, notably sparing the optic radiation. Microstructural changes of the whole brain correlated significantly with mean P100 visual-evoked potentials. The distribution of the correlations showed clear differences among axial diffusivity, fractional anisotropy, and radial diffusivity, notably in the optic radiation. This finding suggests a stronger correlation of mean P100 visual-evoked potentials to demyelination than to axonal damage. © 2014 by American Journal of Neuroradiology.

Neglect severity after left and right brain damage.

PubMed

Suchan, Julia; Rorden, Chris; Karnath, Hans-Otto

2012-05-01

While unilateral spatial neglect after left brain damage is undoubtedly less common than spatial neglect after a right hemisphere lesion, it is also assumed to be less severe. Here we directly test this latter hypothesis using a continuous measure of neglect severity: the so-called Center of Cancellation (CoC). Rorden and Karnath (2010) recently validated this index for right brain damaged neglect patients. A first aim of the present study was to evaluate this new measure for spatial neglect after left brain damage. In a group of 48 left-sided stroke patients with and without neglect, a score greater than -0.086 on the Bells Test and greater than -0.024 on the Letter Cancellation Task turned out to indicate neglect behavior for acute left brain damaged patients. A second aim was to directly compare the severity of spatial neglect after left versus right brain injury by using the new CoC measure. While neglect is less frequent following left than right hemisphere injury, we found that when this symptom occurs it is of similar severity in acute left brain injury as in patients after acute right brain injury. Copyright © 2012 Elsevier Ltd. All rights reserved.

[In search for neurophysiological criteria of altered consciousness].

PubMed

Sviderskaia, N E

2002-01-01

Neurophysiological approaches to brain mechanisms of consciousness are discussed. The concept of spatial synchronization of nervous processes developed by M.N. Livanov is applied to neurophysiological analysis of higher brain functions. However, the spatial synchronization of brain potentials is only a condition for information processing and does not represent it as such. This imposes restrictions on conclusions about the neural mechanisms of consciousness. It is more adequate to use the concept of spatial synchronization in views of consciousness as a psychophysiological level along with sub- and superconsciousness in three-level structure of mind according to P.V. Simonov. Forms of consciousness interaction with other levels concern the problem of altered consciousness and may be reflected in various patterns of spatial organization of brain potentials.

Multiple imputation of missing fMRI data in whole brain analysis

PubMed Central

Vaden, Kenneth I.; Gebregziabher, Mulugeta; Kuchinsky, Stefanie E.; Eckert, Mark A.

2012-01-01

Whole brain fMRI analyses rarely include the entire brain because of missing data that result from data acquisition limits and susceptibility artifact, in particular. This missing data problem is typically addressed by omitting voxels from analysis, which may exclude brain regions that are of theoretical interest and increase the potential for Type II error at cortical boundaries or Type I error when spatial thresholds are used to establish significance. Imputation could significantly expand statistical map coverage, increase power, and enhance interpretations of fMRI results. We examined multiple imputation for group level analyses of missing fMRI data using methods that leverage the spatial information in fMRI datasets for both real and simulated data. Available case analysis, neighbor replacement, and regression based imputation approaches were compared in a general linear model framework to determine the extent to which these methods quantitatively (effect size) and qualitatively (spatial coverage) increased the sensitivity of group analyses. In both real and simulated data analysis, multiple imputation provided 1) variance that was most similar to estimates for voxels with no missing data, 2) fewer false positive errors in comparison to mean replacement, and 3) fewer false negative errors in comparison to available case analysis. Compared to the standard analysis approach of omitting voxels with missing data, imputation methods increased brain coverage in this study by 35% (from 33,323 to 45,071 voxels). In addition, multiple imputation increased the size of significant clusters by 58% and number of significant clusters across statistical thresholds, compared to the standard voxel omission approach. While neighbor replacement produced similar results, we recommend multiple imputation because it uses an informed sampling distribution to deal with missing data across subjects that can include neighbor values and other predictors. Multiple imputation is anticipated to be particularly useful for 1) large fMRI data sets with inconsistent missing voxels across subjects and 2) addressing the problem of increased artifact at ultra-high field, which significantly limit the extent of whole brain coverage and interpretations of results. PMID:22500925

Highlighting the Structure-Function Relationship of the Brain with the Ising Model and Graph Theory

PubMed Central

Das, T. K.; Abeyasinghe, P. M.; Crone, J. S.; Sosnowski, A.; Laureys, S.; Owen, A. M.; Soddu, A.

2014-01-01

With the advent of neuroimaging techniques, it becomes feasible to explore the structure-function relationships in the brain. When the brain is not involved in any cognitive task or stimulated by any external output, it preserves important activities which follow well-defined spatial distribution patterns. Understanding the self-organization of the brain from its anatomical structure, it has been recently suggested to model the observed functional pattern from the structure of white matter fiber bundles. Different models which study synchronization (e.g., the Kuramoto model) or global dynamics (e.g., the Ising model) have shown success in capturing fundamental properties of the brain. In particular, these models can explain the competition between modularity and specialization and the need for integration in the brain. Graphing the functional and structural brain organization supports the model and can also highlight the strategy used to process and organize large amount of information traveling between the different modules. How the flow of information can be prevented or partially destroyed in pathological states, like in severe brain injured patients with disorders of consciousness or by pharmacological induction like in anaesthesia, will also help us to better understand how global or integrated behavior can emerge from local and modular interactions. PMID:25276772

A comprehensive high-resolution mass spectrometry approach for characterization of metabolites by combination of ambient ionization, chromatography and imaging methods.

PubMed

Berisha, Arton; Dold, Sebastian; Guenther, Sabine; Desbenoit, Nicolas; Takats, Zoltan; Spengler, Bernhard; Römpp, Andreas

2014-08-30

An ideal method for bioanalytical applications would deliver spatially resolved quantitative information in real time and without sample preparation. In reality these requirements can typically not be met by a single analytical technique. Therefore, we combine different mass spectrometry approaches: chromatographic separation, ambient ionization and imaging techniques, in order to obtain comprehensive information about metabolites in complex biological samples. Samples were analyzed by laser desorption followed by electrospray ionization (LD-ESI) as an ambient ionization technique, by matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging for spatial distribution analysis and by high-performance liquid chromatography/electrospray ionization mass spectrometry (HPLC/ESI-MS) for quantitation and validation of compound identification. All MS data were acquired with high mass resolution and accurate mass (using orbital trapping and ion cyclotron resonance mass spectrometers). Grape berries were analyzed and evaluated in detail, whereas wheat seeds and mouse brain tissue were analyzed in proof-of-concept experiments. In situ measurements by LD-ESI without any sample preparation allowed for fast screening of plant metabolites on the grape surface. MALDI imaging of grape cross sections at 20 µm pixel size revealed the detailed distribution of metabolites which were in accordance with their biological function. HPLC/ESI-MS was used to quantify 13 anthocyanin species as well as to separate and identify isomeric compounds. A total of 41 metabolites (amino acids, carbohydrates, anthocyanins) were identified with all three approaches. Mass accuracy for all MS measurements was better than 2 ppm (root mean square error). The combined approach provides fast screening capabilities, spatial distribution information and the possibility to quantify metabolites. Accurate mass measurements proved to be critical in order to reliably combine data from different MS techniques. Initial results on the mycotoxin deoxynivalenol (DON) in wheat seed and phospholipids in mouse brain as a model for mammalian tissue indicate a broad applicability of the presented workflow. Copyright © 2014 John Wiley & Sons, Ltd.

Brain temperature in volunteers subjected to intranasal cooling.

PubMed

Covaciu, L; Weis, J; Bengtsson, C; Allers, M; Lunderquist, A; Ahlström, H; Rubertsson, S

2011-08-01

Intranasal cooling can be used to initiate therapeutic hypothermia. However, direct measurement of brain temperature is difficult and the intra-cerebral distribution of temperature changes with cooling is unknown. The purpose of this study was to measure the brain temperature of human volunteers subjected to intranasal cooling using non-invasive magnetic resonance (MR) methods. Intranasal balloons catheters circulated with saline at 20°C were applied for 60 min in ten awake volunteers. No sedation was used. Brain temperature changes were measured and mapped using MR spectroscopic imaging (MRSI) and phase-mapping techniques. Heart rate and blood pressure were monitored throughout the experiment. Rectal temperature was measured before and after the cooling. Mini Mental State Examination (MMSE) test and nasal inspection were done before and after the cooling. Questionnaires about the subjects' personal experience were completed after the experiment. Brain temperature decrease measured by MRSI was -1.7 ± 0.8°C and by phase-mapping -1.8 ± 0.9°C (n = 9) at the end of cooling. Spatial distribution of temperature changes was relatively uniform. Rectal temperature decreased by -0.5 ± 0.3°C (n = 5). The physiological parameters were stable and no shivering was reported. The volunteers remained alert during cooling and no cognitive dysfunctions were apparent in the MMSE test. Postcooling nasal examination detected increased nasal secretion in nine of the ten volunteers. Volunteers' acceptance of the method was good. Both MR techniques revealed brain temperature reductions after 60 min of intranasal cooling with balloons circulated with saline at 20°C in awake, unsedated volunteers.

Effects of different correlation metrics and preprocessing factors on small-world brain functional networks: a resting-state functional MRI study.

PubMed

Liang, Xia; Wang, Jinhui; Yan, Chaogan; Shu, Ni; Xu, Ke; Gong, Gaolang; He, Yong

2012-01-01

Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01-0.027 Hz) versus slow-4 (0.027-0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the "best" network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027-0.073 Hz band exhibited greater reliability than those in the 0.01-0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics and specific preprocessing choices on both the global and nodal topological properties of functional brain networks. This study also has important implications for how to choose reliable analytical schemes in brain network studies.

Virtual Reality Tumor Resection: The Force Pyramid Approach.

PubMed

Sawaya, Robin; Bugdadi, Abdulgadir; Azarnoush, Hamed; Winkler-Schwartz, Alexander; Alotaibi, Fahad E; Bajunaid, Khalid; AlZhrani, Gmaan A; Alsideiri, Ghusn; Sabbagh, Abdulrahman J; Del Maestro, Rolando F

2018-06-01

The force pyramid is a novel visual representation allowing spatial delineation of instrument force application during surgical procedures. In this study, the force pyramid concept is employed to create and quantify dominant hand, nondominant hand, and bimanual force pyramids during resection of virtual reality brain tumors. To address 4 questions: Do ergonomics and handedness influence force pyramid structure? What are the differences between dominant and nondominant force pyramids? What is the spatial distribution of forces applied in specific tumor quadrants? What differentiates "expert" and "novice" groups regarding their force pyramids? Using a simulated aspirator in the dominant hand and a simulated sucker in the nondominant hand, 6 neurosurgeons and 14 residents resected 8 different tumors using the CAE NeuroVR virtual reality neurosurgical simulation platform (CAE Healthcare, Montréal, Québec and the National Research Council Canada, Boucherville, Québec). Position and force data were used to create force pyramids and quantify tumor quadrant force distribution. Force distribution quantification demonstrates the critical role that handedness and ergonomics play on psychomotor performance during simulated brain tumor resections. Neurosurgeons concentrate their dominant hand forces in a defined crescent in the lower right tumor quadrant. Nondominant force pyramids showed a central peak force application in all groups. Bimanual force pyramids outlined the combined impact of each hand. Distinct force pyramid patterns were seen when tumor stiffness, border complexity, and color were altered. Force pyramids allow delineation of specific tumor regions requiring greater psychomotor ability to resect. This information can focus and improve resident technical skills training.

Spatial embedding of structural similarity in the cerebral cortex

PubMed Central

Song, H. Francis; Kennedy, Henry; Wang, Xiao-Jing

2014-01-01

Recent anatomical tracing studies have yielded substantial amounts of data on the areal connectivity underlying distributed processing in cortex, yet the fundamental principles that govern the large-scale organization of cortex remain unknown. Here we show that functional similarity between areas as defined by the pattern of shared inputs or outputs is a key to understanding the areal network of cortex. In particular, we report a systematic relation in the monkey, human, and mouse cortex between the occurrence of connections from one area to another and their similarity distance. This characteristic relation is rooted in the wiring distance dependence of connections in the brain. We introduce a weighted, spatially embedded random network model that robustly gives rise to this structure, as well as many other spatial and topological properties observed in cortex. These include features that were not accounted for in any previous model, such as the wide range of interareal connection weights. Connections in the model emerge from an underlying distribution of spatially embedded axons, thereby integrating the two scales of cortical connectivity—individual axons and interareal pathways—into a common geometric framework. These results provide insights into the origin of large-scale connectivity in cortex and have important implications for theories of cortical organization. PMID:25368200

A preliminary study of sex differences in brain activation during a spatial navigation task in healthy adults.

PubMed

Sneider, Jennifer Tropp; Sava, Simona; Rogowska, Jadwiga; Yurgelun-Todd, Deborah A

2011-10-01

The hippocampus plays a significant role in spatial memory processing, with sex differences being prominent on various spatial tasks. This study examined sex differences in healthy adults, using functional magnetic resonance imaging (fMRI) in areas implicated in spatial processing during navigation of a virtual analogue of the Morris water-maze. There were three conditions: learning, hidden, and visible control. There were no significant differences in performance measures. However, sex differences were found in regional brain activation during learning in the right hippocampus, right parahippocampal gyrus, and the cingulate cortex. During the hidden condition, the hippocampus, parahippocampal gyrus, and cingulate cortex were activated in both men and women. Additional brain areas involved in spatial processing may be recruited in women when learning information about the environment, by utilizing external cues (landmarks) more than do men, contributing to the observed sex differences in brain activation.

Seeing the whole picture: A comprehensive imaging approach to functional mapping of circuits in behaving zebrafish.

PubMed

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.

Brain electric microstates and momentary conscious mind states as building blocks of spontaneous thinking: I. Visual imagery and abstract thoughts.

PubMed

Lehmann, D; Strik, W K; Henggeler, B; Koenig, T; Koukkou, M

1998-06-01

Prompted reports of recall of spontaneous, conscious experiences were collected in a no-input, no-task, no-response paradigm (30 random prompts to each of 13 healthy volunteers). The mentation reports were classified into visual imagery and abstract thought. Spontaneous 19-channel brain electric activity (EEG) was continuously recorded, viewed as series of momentary spatial distributions (maps) of the brain electric field and segmented into microstates, i.e. into time segments characterized by quasi-stable landscapes of potential distribution maps which showed varying durations in the sub-second range. Microstate segmentation used a data-driven strategy. Different microstates, i.e. different brain electric landscapes must have been generated by activity of different neural assemblies and therefore are hypothesized to constitute different functions. The two types of reported experiences were associated with significantly different microstates (mean duration 121 ms) immediately preceding the prompts; these microstates showed, across subjects, for abstract thought (compared to visual imagery) a shift of the electric gravity center to the left and a clockwise rotation of the field axis. Contrariwise, the microstates 2 s before the prompt did not differ between the two types of experiences. The results support the hypothesis that different microstates of the brain as recognized in its electric field implement different conscious, reportable mind states, i.e. different classes (types) of thoughts (mentations); thus, the microstates might be candidates for the 'atoms of thought'.

Clinical MRS studies of the brain

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

Hubesch, B.; Marinier, D.S.; Hetherington, H.P.

1989-12-01

Image-guided {sup 31}P and 1H magnetic resonance localized spectroscopy was performed on patients with brain tumors, temporal lobe epilepsy, chronic brain stroke, and deep white matter lesions. Absolute molar concentrations of metabolites, peak area ratios, and pH were obtained. The important findings were that {sup 31}P metabolite concentrations were significantly reduced in tumors, infarcts, and deep white matter lesions. Similarly, {sup 1}H metabolite intensities were reduced in chronic stroke. In the seizure foci of epilepsy patients, in tumors, and in chronic stroke, the pH was more alkaline than the normal pH. Peak area ratios were altered in tumors (reduction ofmore » phosphocreatine/inorganic phosphate) and in chronic stroke (large increases in Cr/NAA and Cho/NAA). Finally, the spectroscopic imaging technique offers a versatile alternative to the single point techniques, producing spectra or images of the spatial distribution of individual {sup 31}P metabolites.« less

Bio-heat transfer model of deep brain stimulation-induced temperature changes

NASA Astrophysics Data System (ADS)

Elwassif, Maged M.; Kong, Qingjun; Vazquez, Maribel; Bikson, Marom

2006-12-01

There is a growing interest in the use of chronic deep brain stimulation (DBS) for the treatment of medically refractory movement disorders and other neurological and psychiatric conditions. Fundamental questions remain about the physiologic effects of DBS. Previous basic research studies have focused on the direct polarization of neuronal membranes by electrical stimulation. The goal of this paper is to provide information on the thermal effects of DBS using finite element models to investigate the magnitude and spatial distribution of DBS-induced temperature changes. The parameters investigated include stimulation waveform, lead selection, brain tissue electrical and thermal conductivities, blood perfusion, metabolic heat generation during the stimulation and lead thermal conductivity/heat dissipation through the electrode. Our results show that clinical DBS protocols will increase the temperature of surrounding tissue by up to 0.8 °C depending on stimulation/tissue parameters.

A mesoscale connectome of the mouse brain

PubMed Central

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

2016-01-01

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

Effects of Inter-Alpha Inhibitor Proteins on Neonatal Brain Injury: Age, Task and Treatment Dependent Neurobehavioral Outcomes

PubMed Central

Threlkeld, Steven W.; Gaudet, Cynthia M.; La Rue, Molly E.; Dugas, Ethan; Hill, Courtney A.; Lim, Yow-Pin; Stonestreet, Barbara S.

2014-01-01

Hypoxic-ischemic (HI) brain injury is frequently associated with premature and/or full term birth related complications. HI injury often results in learning and processing deficits that reflect widespread damage to an extensive range of cortical and sub-cortical brain structures. Further, inflammation has been implicated in the long-term progression and severity of HI injury. Recently, Inter-alpha Inhibitor Proteins (IAIPs) have been shown to attenuate inflammation in models of systemic infection. Importantly, preclinical studies of neonatal HI injury and neuroprotection often focus on single time windows of assessment or single behavioral domains. This approach limits translational validity, given evidence for a diverse spectrum of neurobehavioral deficits that may change across developmental windows following neonatal brain injury. Therefore, the aims of this research were to assess the effects of human IAIPs on early neocortical cell death (72 hours post insult), adult regional brain volume measurements (cerebral cortex, hippocampus, striatum, corpus callosum) and long-term behavioral outcomes in juvenile (P38-50) and adult (P80+) periods across two independent learning domains (spatial and non-spatial learning), after postnatal day 7 HI injury in rats. Here, for the first time, we show that IAIPs reduce acute neocortical neuronal cell death and improve brain weight outcome 72 hours following HI injury in the neonatal rat. Further, these longitudinal studies are the first to show age, task and treatment dependent improvements in behavioral outcome for both spatial and non-spatial learning following systemic administration of IAIPs in neonatal HI injured rats. Finally, results also show sparing of brain regions critical for spatial and non-spatial learning in adult animals treated with IAIPs at the time of injury onset. These data support the proposal that Inter-alpha Inhibitor Proteins may serve as novel therapeutics for brain injury associated with premature birth and/or neonatal brain injury and highlight the importance of assessing multiple ages, brain regions and behavioral domains when investigating experimental treatment efficacy. PMID:25084519

Mueller-matrix mapping of optically anisotropic fluorophores of molecular biological tissues in the diagnosis of death causes

NASA Astrophysics Data System (ADS)

Ushenko, A. G.; Dubolazov, A. V.; Ushenko, V. A.; Ushenko, Yu. A.; Pidkamin, L. Y.; Soltys, I. V.; Zhytaryuk, V. G.; Pavlyukovich, N.

2016-09-01

A model of generalized optical anisotropy of polycrystalline networks of albumin and globulin of human brain liquor has been suggested. The polarization-phase method of spatial and frequency differentiation of linear and circular birefringence coordinate distributions have been analytically substantiated. A set of criteria of the dynamics of necrotic changes of polarization-phase images of liquor polycrystalline films for determination of death coming prescription has been detected and substantiated.

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

Schweizer, M.

This report summarizes progress during the past year on maturing Boron-11 magnetic resonance imaging (MRI) methodology for noninvasive determination of BNCT agents (BSH) spatially in time. Three major areas are excerpted: (1) Boron-11 MRI of BSH distributions in a canine intracranial tumor model and the first human glioblastoma patient, (2) whole body Boron-11 MRI of BSH pharmacokinetics in a rat flank tumor model, and (3) penetration of gadolinium salts through the BBB as a function of tumor growth in the canine brain.

Task Dependence, Tissue Specificity, and Spatial Distribution of Widespread Activations in Large Single-Subject Functional MRI Datasets at 7T

PubMed Central

Gonzalez-Castillo, Javier; Hoy, Colin W.; Handwerker, Daniel A.; Roopchansingh, Vinai; Inati, Souheil J.; Saad, Ziad S.; Cox, Robert W.; Bandettini, Peter A.

2015-01-01

It was recently shown that when large amounts of task-based blood oxygen level–dependent (BOLD) data are combined to increase contrast- and temporal signal-to-noise ratios, the majority of the brain shows significant hemodynamic responses time-locked with the experimental paradigm. Here, we investigate the biological significance of such widespread activations. First, the relationship between activation extent and task demands was investigated by varying cognitive load across participants. Second, the tissue specificity of responses was probed using the better BOLD signal localization capabilities of a 7T scanner. Finally, the spatial distribution of 3 primary response types—namely positively sustained (pSUS), negatively sustained (nSUS), and transient—was evaluated using a newly defined voxel-wise waveshape index that permits separation of responses based on their temporal signature. About 86% of gray matter (GM) became significantly active when all data entered the analysis for the most complex task. Activation extent scaled with task load and largely followed the GM contour. The most common response type was nSUS BOLD, irrespective of the task. Our results suggest that widespread activations associated with extremely large single-subject functional magnetic resonance imaging datasets can provide valuable information about the functional organization of the brain that goes undetected in smaller sample sizes. PMID:25405938

Cortex-based inter-subject analysis of iEEG and fMRI data sets: application to sustained task-related BOLD and gamma responses.

PubMed

Esposito, Fabrizio; Singer, Neomi; Podlipsky, Ilana; Fried, Itzhak; Hendler, Talma; Goebel, Rainer

2013-02-01

Linking regional metabolic changes with fluctuations in the local electromagnetic fields directly on the surface of the human cerebral cortex is of tremendous importance for a better understanding of detailed brain processes. Functional magnetic resonance imaging (fMRI) and intra-cranial electro-encephalography (iEEG) measure two technically unrelated but spatially and temporally complementary sets of functional descriptions of human brain activity. In order to allow fine-grained spatio-temporal human brain mapping at the population-level, an effective comparative framework for the cortex-based inter-subject analysis of iEEG and fMRI data sets is needed. We combined fMRI and iEEG recordings of the same patients with epilepsy during alternated intervals of passive movie viewing and music listening to explore the degree of local spatial correspondence and temporal coupling between blood oxygen level dependent (BOLD) fMRI changes and iEEG spectral power modulations across the cortical surface after cortex-based inter-subject alignment. To this purpose, we applied a simple model of the iEEG activity spread around each electrode location and the cortex-based inter-subject alignment procedure to transform discrete iEEG measurements into cortically distributed group patterns by establishing a fine anatomic correspondence of many iEEG cortical sites across multiple subjects. Our results demonstrate the feasibility of a multi-modal inter-subject cortex-based distributed analysis for combining iEEG and fMRI data sets acquired from multiple subjects with the same experimental paradigm but with different iEEG electrode coverage. The proposed iEEG-fMRI framework allows for improved group statistics in a common anatomical space and preserves the dynamic link between the temporal features of the two modalities. Copyright © 2012 Elsevier Inc. All rights reserved.

Optimal design of a bank of spatio-temporal filters for EEG signal classification.

PubMed

Higashi, Hiroshi; Tanaka, Toshihisa

2011-01-01

The spatial weights for electrodes called common spatial pattern (CSP) are known to be effective in EEG signal classification for motor imagery based brain computer interfaces (MI-BCI). To achieve accurate classification in CSP, the frequency filter should be properly designed. To this end, several methods for designing the filter have been proposed. However, the existing methods cannot consider plural brain activities described with different frequency bands and different spatial patterns such as activities of mu and beta rhythms. In order to efficiently extract these brain activities, we propose a method to design plural filters and spatial weights which extract desired brain activity. The proposed method designs finite impulse response (FIR) filters and the associated spatial weights by optimization of an objective function which is a natural extension of CSP. Moreover, we show by a classification experiment that the bank of FIR filters which are designed by introducing an orthogonality into the objective function can extract good discriminative features. Moreover, the experiment result suggests that the proposed method can automatically detect and extract brain activities related to motor imagery.

High and ultra-high resolution metabolite mapping of the human brain using 1H FID MRSI at 9.4T.

PubMed

Nassirpour, Sahar; Chang, Paul; Henning, Anke

2018-03-01

Magnetic resonance spectroscopic imaging (MRSI) is a promising technique for mapping the spatial distribution of multiple metabolites in the human brain. These metabolite maps can be used as a diagnostic tool to gain insight into several biochemical processes and diseases in the brain. In comparison to lower field strengths, MRSI at ultra-high field strengths benefits from a higher signal to noise ratio (SNR) as well as higher chemical shift dispersion, and hence spectral resolution. This study combines the benefits of an ultra-high field magnet with the advantages of an ultra-short TE and TR single-slice FID-MRSI sequence (such as negligible J-evolution and loss of SNR due to T 2 relaxation effects) and presents the first metabolite maps acquired at 9.4T in the healthy human brain at both high (voxel size of 97.6µL) and ultra-high (voxel size of 24.4µL) spatial resolutions in a scan time of 11 and 46min respectively. In comparison to lower field strengths, more anatomically-detailed maps with higher SNR from a larger number of metabolites are shown. A total of 12 metabolites including glutamate (Glu), glutamine (Gln), N-acetyl-aspartyl-glutamate (NAAG), Gamma-aminobutyric acid (GABA) and glutathione (GSH) are reliably mapped. Comprehensive description of the methodology behind these maps is provided. Copyright © 2016 Elsevier Inc. All rights reserved.

Spatially aggregated multiclass pattern classification in functional MRI using optimally selected functional brain areas.

PubMed

Zheng, Weili; Ackley, Elena S; Martínez-Ramón, Manel; Posse, Stefan

2013-02-01

In previous works, boosting aggregation of classifier outputs from discrete brain areas has been demonstrated to reduce dimensionality and improve the robustness and accuracy of functional magnetic resonance imaging (fMRI) classification. However, dimensionality reduction and classification of mixed activation patterns of multiple classes remain challenging. In the present study, the goals were (a) to reduce dimensionality by combining feature reduction at the voxel level and backward elimination of optimally aggregated classifiers at the region level, (b) to compare region selection for spatially aggregated classification using boosting and partial least squares regression methods and (c) to resolve mixed activation patterns using probabilistic prediction of individual tasks. Brain activation maps from interleaved visual, motor, auditory and cognitive tasks were segmented into 144 functional regions. Feature selection reduced the number of feature voxels by more than 50%, leaving 95 regions. The two aggregation approaches further reduced the number of regions to 30, resulting in more than 75% reduction of classification time and misclassification rates of less than 3%. Boosting and partial least squares (PLS) were compared to select the most discriminative and the most task correlated regions, respectively. Successful task prediction in mixed activation patterns was feasible within the first block of task activation in real-time fMRI experiments. This methodology is suitable for sparsifying activation patterns in real-time fMRI and for neurofeedback from distributed networks of brain activation. Copyright © 2013 Elsevier Inc. All rights reserved.

Experimental assessment of thermal effects of high power density light stimulation for optogenetics control of deep brain structures (Conference Presentation)

NASA Astrophysics Data System (ADS)

Senova, Suhan; Scisniak, Ilona; Chiang, Chih Chieh; Doignon, Isabelle; Martin, Claire; Palfi, Stephane; Chaillet, Antoine; Pain, Frederic

2016-03-01

2D surface maps of light distribution and temperature increase were recorded in wild type anesthetized rats brains during 90s light stimulation at 478nm (blue) and 638nm (red) with continuous or pulsed optical stimulations with corresponding power ranging from 100 up to 1200 mW/mm² at the output of an optical fiber. Post mortem maps were recorded in the same animals to assess the cooling effect of blood flow. Post mortem histological analysis were carried out to assess whether high power light stimulations had phototoxic effects or could trigger non physiological functional activation. Temperature increase remains below physiological changes (0,5 -1°) for stimulations up to 400mW/mm² at 40Hz. . Histology did not show significant irreversible modifications or damage to the tissues. The spatial profile of light distribution and heat were correlated and demonstrate as expected a rapid attenuation with diatnce to the fiber.

Statistical analysis of dendritic spine distributions in rat hippocampal cultures

PubMed Central

2013-01-01

Background Dendritic spines serve as key computational structures in brain plasticity. Much remains to be learned about their spatial and temporal distribution among neurons. Our aim in this study was to perform exploratory analyses based on the population distributions of dendritic spines with regard to their morphological characteristics and period of growth in dissociated hippocampal neurons. We fit a log-linear model to the contingency table of spine features such as spine type and distance from the soma to first determine which features were important in modeling the spines, as well as the relationships between such features. A multinomial logistic regression was then used to predict the spine types using the features suggested by the log-linear model, along with neighboring spine information. Finally, an important variant of Ripley’s K-function applicable to linear networks was used to study the spatial distribution of spines along dendrites. Results Our study indicated that in the culture system, (i) dendritic spine densities were "completely spatially random", (ii) spine type and distance from the soma were independent quantities, and most importantly, (iii) spines had a tendency to cluster with other spines of the same type. Conclusions Although these results may vary with other systems, our primary contribution is the set of statistical tools for morphological modeling of spines which can be used to assess neuronal cultures following gene manipulation such as RNAi, and to study induced pluripotent stem cells differentiated to neurons. PMID:24088199

Allometric Analysis Detects Brain Size-Independent Effects of Sex and Sex Chromosome Complement on Human Cerebellar Organization

PubMed Central

Mankiw, Catherine; Park, Min Tae M.; Reardon, P.K.; Fish, Ari M.; Clasen, Liv S.; Greenstein, Deanna; Blumenthal, Jonathan D.; Lerch, Jason P.; Chakravarty, M. Mallar

2017-01-01

The cerebellum is a large hindbrain structure that is increasingly recognized for its contribution to diverse domains of cognitive and affective processing in human health and disease. Although several of these domains are sex biased, our fundamental understanding of cerebellar sex differences—including their spatial distribution, potential biological determinants, and independence from brain volume variation—lags far behind that for the cerebrum. Here, we harness automated neuroimaging methods for cerebellar morphometrics in 417 individuals to (1) localize normative male–female differences in raw cerebellar volume, (2) compare these to sex chromosome effects estimated across five rare sex (X/Y) chromosome aneuploidy (SCA) syndromes, and (3) clarify brain size-independent effects of sex and SCA on cerebellar anatomy using a generalizable allometric approach that considers scaling relationships between regional cerebellar volume and brain volume in health. The integration of these approaches shows that (1) sex and SCA effects on raw cerebellar volume are large and distributed, but regionally heterogeneous, (2) human cerebellar volume scales with brain volume in a highly nonlinear and regionally heterogeneous fashion that departs from documented patterns of cerebellar scaling in phylogeny, and (3) cerebellar organization is modified in a brain size-independent manner by sex (relative expansion of total cerebellum, flocculus, and Crus II-lobule VIIIB volumes in males) and SCA (contraction of total cerebellar, lobule IV, and Crus I volumes with additional X- or Y-chromosomes; X-specific contraction of Crus II-lobule VIIIB). Our methods and results clarify the shifts in human cerebellar organization that accompany interwoven variations in sex, sex chromosome complement, and brain size. SIGNIFICANCE STATEMENT Cerebellar systems are implicated in diverse domains of sex-biased behavior and pathology, but we lack a basic understanding of how sex differences in the human cerebellum are distributed and determined. We leverage a rare neuroimaging dataset to deconvolve the interwoven effects of sex, sex chromosome complement, and brain size on human cerebellar organization. We reveal topographically variegated scaling relationships between regional cerebellar volume and brain size in humans, which (1) are distinct from those observed in phylogeny, (2) invalidate a traditional neuroimaging method for brain volume correction, and (3) allow more valid and accurate resolution of which cerebellar subcomponents are sensitive to sex and sex chromosome complement. These findings advance understanding of cerebellar organization in health and sex chromosome aneuploidy. PMID:28314818

Spatial gradient for unique-feature detection in patients with unilateral neglect: evidence from auditory and visual search.

PubMed

Eramudugolla, Ranmalee; Mattingley, Jason B

2008-01-01

Patients with unilateral spatial neglect following right hemisphere damage are impaired in detecting contralesional targets in both visual and haptic search tasks, and often show a graded improvement in detection performance for more ipsilesional spatial locations. In audition, multiple simultaneous sounds are most effectively perceived if they are distributed along the frequency dimension. Thus, attention to spectro-temporal features alone can allow detection of a target sound amongst multiple simultaneous distracter sounds, regardless of whether these sounds are spatially separated. Spatial bias in attention associated with neglect should not affect auditory search based on spectro-temporal features of a sound target. We report that a right brain damaged patient with neglect demonstrated a significant gradient favouring the ipsilesional side on a visual search task as well as an auditory search task in which the target was a frequency modulated tone amongst steady distractor tones. No such asymmetry was apparent in the auditory search performance of a control patient with a right hemisphere lesion but no neglect. The results suggest that the spatial bias in attention exhibited by neglect patients affects stimulus processing even when spatial information is irrelevant to the task.

Abnormal interactions of verbal- and spatial-memory networks in young people at familial high-risk for schizophrenia.

PubMed

Li, Xiaobo; Thermenos, Heidi W; Wu, Ziyan; Momura, Yoko; Wu, Kai; Keshavan, Matcheri; Seidman, Lawrence; DeLisi, Lynn E

2016-10-01

Working memory impairment (especially in verbal and spatial domains) is the core neurocognitive impairment in schizophrenia and the familial high-risk (FHR) population. Inconsistent results have been reported in clinical and neuroimaging studies examining the verbal- and spatial-memory deficits in the FHR subjects, due to sample differences and lack of understanding on interactions of the brain regions for processing verbal- and spatial-working memory. Functional MRI data acquired during a verbal- vs. spatial-memory task were included from 51 young adults [26 FHR and 25 controls]. Group comparisons were conducted in brain activation patterns responding to 1) verbal-memory condition (A), 2) spatial-memory condition (B), 3) verbal higher than spatial (A-B), 4) spatial higher than verbal (B-A), 5) conjunction of brain regions that were activated during both A and B (A∧B). Group difference of the laterality index (LI) in inferior frontal lobe for condition A was also assessed. Compared to controls, the FHR group exhibited significantly decreased brain activity in left inferior frontal during A, and significantly stronger involvement of ACC, PCC, paracentral gyrus for the contrast of A-B. The LI showed a trend of reduced left-higher-than-right pattern for verbal-memory processing in the HR group. Our findings suggest that in the entire functional brain network for working-memory processing, verbal information processing associated brain pathways are significantly altered in people at familial high risk for developing schizophrenia. Future studies will need to examine whether these alterations may indicate vulnerability for predicting the onset of Schizophrenia. Copyright © 2016 Elsevier B.V. All rights reserved.

Scale invariant rearrangement of resting state networks in the human brain under sustained stimulation.

PubMed

Tommasin, Silvia; Mascali, Daniele; Moraschi, Marta; Gili, Tommaso; Assan, Ibrahim Eid; Fratini, Michela; DiNuzzo, Mauro; Wise, Richard G; Mangia, Silvia; Macaluso, Emiliano; Giove, Federico

2018-06-14

Brain activity at rest is characterized by widely distributed and spatially specific patterns of synchronized low-frequency blood-oxygenation level-dependent (BOLD) fluctuations, which correspond to physiologically relevant brain networks. This network behaviour is known to persist also during task execution, yet the details underlying task-associated modulations of within- and between-network connectivity are largely unknown. In this study we exploited a multi-parametric and multi-scale approach to investigate how low-frequency fluctuations adapt to a sustained n-back working memory task. We found that the transition from the resting state to the task state involves a behaviourally relevant and scale-invariant modulation of synchronization patterns within both task-positive and default mode networks. Specifically, decreases of connectivity within networks are accompanied by increases of connectivity between networks. In spite of large and widespread changes of connectivity strength, the overall topology of brain networks is remarkably preserved. We show that these findings are strongly influenced by connectivity at rest, suggesting that the absolute change of connectivity (i.e., disregarding the baseline) may be not the most suitable metric to study dynamic modulations of functional connectivity. Our results indicate that a task can evoke scale-invariant, distributed changes of BOLD fluctuations, further confirming that low frequency BOLD oscillations show a specialized response and are tightly bound to task-evoked activation. Copyright © 2018. Published by Elsevier Inc.

Multimodal detection of GM2 and GM3 lipid species in the brain of mucopolysaccharidosis type II mouse by serial imaging mass spectrometry and immunohistochemistry.

PubMed

Dufresne, Martin; Guneysu, Daniel; Patterson, Nathan Heath; Marcinkiewicz, Mieczyslaw Martin; Regina, Anthony; Demeule, Michel; Chaurand, Pierre

2017-02-01

Mucopolysaccharidosis type II (Hunter's disease) mouse model (IdS-KO) was investigated by both imaging mass spectrometry (IMS) and immunohistochemistry (IHC) performed on the same tissue sections. For this purpose, IdS-KO mice brain sections were coated with sublimated 1,5-diaminonaphtalene and analyzed by high spatial resolution IMS (5 μm) and anti-GM3 IHC on the same tissue sections to characterize the ganglioside monosialated ganglioside (GM) deposits found in Hunter's disease. IMS analysis have found that two species of GM3 and GM2 that are only different due to the length of their fatty acid residue (stearic or arachidic residue) were overexpressed in the IdS-KO mice compared to a control mouse. GM3 and GM2 were characterized by on-tissue exact mass and MS/MS compared to a GM3 standard. Realignment of both IMS and IHC data sets further confirmed the observed regioselective signal previously detected by providing direct correlation of the IMS image for the two GM3 overly expressed MS signals with the anti-GM3 IHC image. Furthermore, these regioselective GM MS signals were also found to have highly heterogeneous distributions within the GM3-IHC staining. Some deposits showed high content in GM3 and GM2 stearic species (r = 0.74) and others had more abundant GM3 and GM2 arachidic species (r = 0.76). Same-section analysis of Hunter's disease mouse model by both high spatial resolution IMS and IHC provides a more in-depth analysis of the composition of the GM aggregates while providing spatial distribution of the observed molecular species. Graphical Abstract Ganglioside imaging mass spectrometry followed by immunohistochemistry performed on the same tissue section.

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

PubMed

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

2018-05-01

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

Spatial distribution of intermingling pools of projection neurons with distinct targets: A 3D analysis of the commissural ganglia in Cancer borealis.

PubMed

Follmann, Rosangela; Goldsmith, Christopher John; Stein, Wolfgang

2017-06-01

Projection neurons play a key role in carrying long-distance information between spatially distant areas of the nervous system and in controlling motor circuits. Little is known about how projection neurons with distinct anatomical targets are organized, and few studies have addressed their spatial organization at the level of individual cells. In the paired commissural ganglia (CoGs) of the stomatogastric nervous system of the crab Cancer borealis, projection neurons convey sensory, motor, and modulatory information to several distinct anatomical regions. While the functions of descending projection neurons (dPNs) which control downstream motor circuits in the stomatogastric ganglion are well characterized, their anatomical distribution as well as that of neurons projecting to the labrum, brain, and thoracic ganglion have received less attention. Using cell membrane staining, we investigated the spatial distribution of CoG projection neurons in relation to all CoG neurons. Retrograde tracing revealed that somata associated with different axonal projection pathways were not completely spatially segregated, but had distinct preferences within the ganglion. Identified dPNs had diameters larger than 70% of CoG somata and were restricted to the most medial and anterior 25% of the ganglion. They were contained within a cluster of motor neurons projecting through the same nerve to innervate the labrum, indicating that soma position was independent of function and target area. Rather, our findings suggest that CoG neurons projecting to a variety of locations follow a generalized rule: for all nerve pathway origins, the soma cluster centroids in closest proximity are those whose axons project down that pathway. © 2017 Wiley Periodicals, Inc.

Behavioral and Brain Measures of Phasic Alerting Effects on Visual Attention.

PubMed

Wiegand, Iris; Petersen, Anders; Finke, Kathrin; Bundesen, Claus; Lansner, Jon; Habekost, Thomas

2017-01-01

In the present study, we investigated effects of phasic alerting on visual attention in a partial report task, in which half of the displays were preceded by an auditory warning cue. Based on the computational Theory of Visual Attention (TVA), we estimated parameters of spatial and non-spatial aspects of visual attention and measured event-related lateralizations (ERLs) over visual processing areas. We found that the TVA parameter sensory effectiveness a , which is thought to reflect visual processing capacity, significantly increased with phasic alerting. By contrast, the distribution of visual processing resources according to task relevance and spatial position, as quantified in parameters top-down control α and spatial bias w index , was not modulated by phasic alerting. On the electrophysiological level, the latencies of ERLs in response to the task displays were reduced following the warning cue. These results suggest that phasic alerting facilitates visual processing in a general, unselective manner and that this effect originates in early stages of visual information processing.

Chronnectome fingerprinting: Identifying individuals and predicting higher cognitive functions using dynamic brain connectivity patterns.

PubMed

Liu, Jin; Liao, Xuhong; Xia, Mingrui; He, Yong

2018-02-01

The human brain is a large, interacting dynamic network, and its architecture of coupling among brain regions varies across time (termed the "chronnectome"). However, very little is known about whether and how the dynamic properties of the chronnectome can characterize individual uniqueness, such as identifying individuals as a "fingerprint" of the brain. Here, we employed multiband resting-state functional magnetic resonance imaging data from the Human Connectome Project (N = 105) and a sliding time-window dynamic network analysis approach to systematically examine individual time-varying properties of the chronnectome. We revealed stable and remarkable individual variability in three dynamic characteristics of brain connectivity (i.e., strength, stability, and variability), which was mainly distributed in three higher order cognitive systems (i.e., default mode, dorsal attention, and fronto-parietal) and in two primary systems (i.e., visual and sensorimotor). Intriguingly, the spatial patterns of these dynamic characteristics of brain connectivity could successfully identify individuals with high accuracy and could further significantly predict individual higher cognitive performance (e.g., fluid intelligence and executive function), which was primarily contributed by the higher order cognitive systems. Together, our findings highlight that the chronnectome captures inherent functional dynamics of individual brain networks and provides implications for individualized characterization of health and disease. © 2017 Wiley Periodicals, Inc.

Spatial Rotation and Recognizing Emotions: Gender Related Differences in Brain Activity

ERIC Educational Resources Information Center

Jausovec, Norbert; Jausovec, Ksenija

2008-01-01

In three experiments, gender and ability (performance and emotional intelligence) related differences in brain activity--assessed with EEG methodology--while respondents were solving a spatial rotation tasks and identifying emotions in faces were investigated. The most robust gender related difference in brain activity was observed in the lower-2…

Neural network for processing both spatial and temporal data with time based back-propagation

NASA Technical Reports Server (NTRS)

Villarreal, James A. (Inventor); Shelton, Robert O. (Inventor)

1993-01-01

Neural networks are computing systems modeled after the paradigm of the biological brain. For years, researchers using various forms of neural networks have attempted to model the brain's information processing and decision-making capabilities. Neural network algorithms have impressively demonstrated the capability of modeling spatial information. On the other hand, the application of parallel distributed models to the processing of temporal data has been severely restricted. The invention introduces a novel technique which adds the dimension of time to the well known back-propagation neural network algorithm. In the space-time neural network disclosed herein, the synaptic weights between two artificial neurons (processing elements) are replaced with an adaptable-adjustable filter. Instead of a single synaptic weight, the invention provides a plurality of weights representing not only association, but also temporal dependencies. In this case, the synaptic weights are the coefficients to the adaptable digital filters. Novelty is believed to lie in the disclosure of a processing element and a network of the processing elements which are capable of processing temporal as well as spacial data.

Repeated mild traumatic brain injury produces neuroinflammation, anxiety-like behaviour and impaired spatial memory in mice.

PubMed

Broussard, John I; Acion, Laura; De Jesús-Cortés, Héctor; Yin, Terry; Britt, Jeremiah K; Salas, Ramiro; Costa-Mattioli, Mauro; Robertson, Claudia; Pieper, Andrew A; Arciniegas, David B; Jorge, Ricardo

2018-01-01

Repeated traumatic brain injuries (rmTBI) are frequently associated with debilitating neuropsychiatric conditions such as cognitive impairment, mood disorders, and post-traumatic stress disorder. We tested the hypothesis that repeated mild traumatic brain injury impairs spatial memory and enhances anxiety-like behaviour. We used a between groups design using single (smTBI) or repeated (rmTBI) controlled cranial closed skull impacts to mice, compared to a control group. We assessed the effects of smTBI and rmTBI using measures of motor performance (Rotarod Test [RT]), anxiety-like behaviour (Elevated Plus Maze [EPM] and Open Field [OF] tests), and spatial memory (Morris Water Maze [MWM]) within 12 days of the final injury. In separate groups of mice, astrocytosis and microglial activation were assessed 24 hours after the final injury using GFAP and IBA-1 immunohistochemistry. RmTBI impaired spatial memory in the MWM and increased anxiety-like behaviour in the EPM and OFT. In addition, rmTBI elevated GFAP and IBA-1 immunohistochemistry throughout the mouse brain. RmTBI produced astrocytosis and microglial activation, and elicited impaired spatial memory and anxiety-like behaviour. rmTBI produces acute cognitive and anxiety-like disturbances associated with inflammatory changes in brain regions involved in spatial memory and anxiety.

Predictability of depression severity based on posterior alpha oscillations.

PubMed

Jiang, H; Popov, T; Jylänki, P; Bi, K; Yao, Z; Lu, Q; Jensen, O; van Gerven, M A J

2016-04-01

We aimed to integrate neural data and an advanced machine learning technique to predict individual major depressive disorder (MDD) patient severity. MEG data was acquired from 22 MDD patients and 22 healthy controls (HC) resting awake with eyes closed. Individual power spectra were calculated by a Fourier transform. Sources were reconstructed via beamforming technique. Bayesian linear regression was applied to predict depression severity based on the spatial distribution of oscillatory power. In MDD patients, decreased theta (4-8 Hz) and alpha (8-14 Hz) power was observed in fronto-central and posterior areas respectively, whereas increased beta (14-30 Hz) power was observed in fronto-central regions. In particular, posterior alpha power was negatively related to depression severity. The Bayesian linear regression model showed significant depression severity prediction performance based on the spatial distribution of both alpha (r=0.68, p=0.0005) and beta power (r=0.56, p=0.007) respectively. Our findings point to a specific alteration of oscillatory brain activity in MDD patients during rest as characterized from MEG data in terms of spectral and spatial distribution. The proposed model yielded a quantitative and objective estimation for the depression severity, which in turn has a potential for diagnosis and monitoring of the recovery process. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

A hierarchical model for probabilistic independent component analysis of multi-subject fMRI studies

PubMed Central

Tang, Li

2014-01-01

Summary An important goal in fMRI studies is to decompose the observed series of brain images to identify and characterize underlying brain functional networks. Independent component analysis (ICA) has been shown to be a powerful computational tool for this purpose. Classic ICA has been successfully applied to single-subject fMRI data. The extension of ICA to group inferences in neuroimaging studies, however, is challenging due to the unavailability of a pre-specified group design matrix. Existing group ICA methods generally concatenate observed fMRI data across subjects on the temporal domain and then decompose multi-subject data in a similar manner to single-subject ICA. The major limitation of existing methods is that they ignore between-subject variability in spatial distributions of brain functional networks in group ICA. In this paper, we propose a new hierarchical probabilistic group ICA method to formally model subject-specific effects in both temporal and spatial domains when decomposing multi-subject fMRI data. The proposed method provides model-based estimation of brain functional networks at both the population and subject level. An important advantage of the hierarchical model is that it provides a formal statistical framework to investigate similarities and differences in brain functional networks across subjects, e.g., subjects with mental disorders or neurodegenerative diseases such as Parkinson’s as compared to normal subjects. We develop an EM algorithm for model estimation where both the E-step and M-step have explicit forms. We compare the performance of the proposed hierarchical model with that of two popular group ICA methods via simulation studies. We illustrate our method with application to an fMRI study of Zen meditation. PMID:24033125

Neurocognitive and electrophysiological evidence of altered face processing in parents of children with autism: implications for a model of abnormal development of social brain circuitry in autism.

PubMed

Dawson, Geraldine; Webb, Sara Jane; Wijsman, Ellen; Schellenberg, Gerard; Estes, Annette; Munson, Jeffrey; Faja, Susan

2005-01-01

Neuroimaging and behavioral studies have shown that children and adults with autism have impaired face recognition. Individuals with autism also exhibit atypical event-related brain potentials to faces, characterized by a failure to show a negative component (N170) latency advantage to face compared to nonface stimuli and a bilateral, rather than right lateralized, pattern of N170 distribution. In this report, performance by 143 parents of children with autism on standardized verbal, visual-spatial, and face recognition tasks was examined. It was found that parents of children with autism exhibited a significant decrement in face recognition ability relative to their verbal and visual spatial abilities. Event-related brain potentials to face and nonface stimuli were examined in 21 parents of children with autism and 21 control adults. Parents of children with autism showed an atypical event-related potential response to faces, which mirrored the pattern shown by children and adults with autism. These results raise the possibility that face processing might be a functional trait marker of genetic susceptibility to autism. Discussion focuses on hypotheses regarding the neurodevelopmental and genetic basis of altered face processing in autism. A general model of the normal emergence of social brain circuitry in the first year of life is proposed, followed by a discussion of how the trajectory of normal development of social brain circuitry, including cortical specialization for face processing, is altered in individuals with autism. The hypothesis that genetic-mediated dysfunction of the dopamine reward system, especially its functioning in social contexts, might account for altered face processing in individuals with autism and their relatives is discussed.

Imaging Taurine in the Central Nervous System Using Chemically Specific X-ray Fluorescence Imaging at the Sulfur K-Edge

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

Hackett, Mark J.; Paterson, Phyllis G.; Pickering, Ingrid J.

A method to image taurine distributions within the central nervous system and other organs has long been sought. Since taurine is small and mobile, it cannot be chemically “tagged” and imaged using conventional immuno-histochemistry methods. Combining numerous indirect measurements, taurine is known to play critical roles in brain function during health and disease and is proposed to act as a neuro-osmolyte, neuro-modulator, and possibly a neuro-transmitter. Elucidation of taurine’s neurochemical roles and importance would be substantially enhanced by a direct method to visualize alterations, due to physiological and pathological events in the brain, in the local concentration of taurine atmore » or near cellular spatial resolution in vivo or in situ in tissue sections. We thus have developed chemically specific X-ray fluorescence imaging (XFI) at the sulfur K-edge to image the sulfonate group in taurine in situ in ex vivo tissue sections. To our knowledge, this represents the first undistorted imaging of taurine distribution in brain at 20 μm resolution. We report quantitative technique validation by imaging taurine in the cerebellum and hippocampus regions of the rat brain. Further, we apply the technique to image taurine loss from the vulnerable CA1 (cornus ammonis 1) sector of the rat hippocampus following global brain ischemia. The location-specific loss of taurine from CA1 but not CA3 neurons following ischemia reveals osmotic stress may be a key factor in delayed neurodegeneration after a cerebral ischemic insult and highlights the significant potential of chemically specific XFI to study the role of taurine in brain disease.« less

Quantification of brain macrostates using dynamical nonstationarity of physiological time series.

PubMed

Latchoumane, Charles-Francois Vincent; Jeong, Jaeseung

2011-04-01

The brain shows complex, nonstationarity temporal dynamics, with abrupt micro- and macrostate transitions during its information processing. Detecting and characterizing these transitions in dynamical states of the brain is a critical issue in the field of neuroscience and psychiatry. In the current study, a novel method is proposed to quantify brain macrostates (e.g., sleep stages or cognitive states) from shifts of dynamical microstates or dynamical nonstationarity. A ``dynamical microstate'' is a temporal unit of the information processing in the brain with fixed dynamical parameters and specific spatial distribution. In this proposed approach, a phase-space-based dynamical dissimilarity map (DDM) is used to detect transitions between dynamically stationary microstates in the time series, and Tsallis time-dependent entropy is applied to quantify dynamical patterns of transitions in the DDM. We demonstrate that the DDM successfully detects transitions between microstates of different temporal dynamics in the simulated physiological time series against high levels of noise. Based on the assumption of nonlinear, deterministic brain dynamics, we also demonstrate that dynamical nonstationarity analysis is useful to quantify brain macrostates (sleep stages I, II, III, IV, and rapid eye movement (REM) sleep) from sleep EEGs with an overall accuracy of 77%. We suggest that dynamical nonstationarity is a useful tool to quantify macroscopic mental states (statistical integration) of the brain using dynamical transitions at the microscopic scale in physiological data.

Multi-Compartment T2 Relaxometry Using a Spatially Constrained Multi-Gaussian Model

PubMed Central

Raj, Ashish; Pandya, Sneha; Shen, Xiaobo; LoCastro, Eve; Nguyen, Thanh D.; Gauthier, Susan A.

2014-01-01

The brain’s myelin content can be mapped by T2-relaxometry, which resolves multiple differentially relaxing T2 pools from multi-echo MRI. Unfortunately, the conventional fitting procedure is a hard and numerically ill-posed problem. Consequently, the T2 distributions and myelin maps become very sensitive to noise and are frequently difficult to interpret diagnostically. Although regularization can improve stability, it is generally not adequate, particularly at relatively low signal to noise ratio (SNR) of around 100–200. The purpose of this study was to obtain a fitting algorithm which is able to overcome these difficulties and generate usable myelin maps from noisy acquisitions in a realistic scan time. To this end, we restrict the T2 distribution to only 3 distinct resolvable tissue compartments, modeled as Gaussians: myelin water, intra/extra-cellular water and a slow relaxing cerebrospinal fluid compartment. We also impose spatial smoothness expectation that volume fractions and T2 relaxation times of tissue compartments change smoothly within coherent brain regions. The method greatly improves robustness to noise, reduces spatial variations, improves definition of white matter fibers, and enhances detection of demyelinating lesions. Due to efficient design, the additional spatial aspect does not cause an increase in processing time. The proposed method was applied to fast spiral acquisitions on which conventional fitting gives uninterpretable results. While these fast acquisitions suffer from noise and inhomogeneity artifacts, our preliminary results indicate the potential of spatially constrained 3-pool T2 relaxometry. PMID:24896833

Brain activity during driving with distraction: an immersive fMRI study

PubMed Central

Schweizer, Tom A.; Kan, Karen; Hung, Yuwen; Tam, Fred; Naglie, Gary; Graham, Simon J.

2013-01-01

Introduction: Non-invasive measurements of brain activity have an important role to play in understanding driving ability. The current study aimed to identify the neural underpinnings of human driving behavior by visualizing the areas of the brain involved in driving under different levels of demand, such as driving while distracted or making left turns at busy intersections. Materials and Methods: To capture brain activity during driving, we placed a driving simulator with a fully functional steering wheel and pedals in a 3.0 Tesla functional magnetic resonance imaging (fMRI) system. To identify the brain areas involved while performing different real-world driving maneuvers, participants completed tasks ranging from simple (right turns) to more complex (left turns at busy intersections). To assess the effects of driving while distracted, participants were asked to perform an auditory task while driving analogous to speaking on a hands-free device and driving. Results: A widely distributed brain network was identified, especially when making left turns at busy intersections compared to more simple driving tasks. During distracted driving, brain activation shifted dramatically from the posterior, visual and spatial areas to the prefrontal cortex. Conclusions: Our findings suggest that the distracted brain sacrificed areas in the posterior brain important for visual attention and alertness to recruit enough brain resources to perform a secondary, cognitive task. The present findings offer important new insights into the scientific understanding of the neuro-cognitive mechanisms of driving behavior and lay down an important foundation for future clinical research. PMID:23450757

A Lateralization of Function Approach to Sex Differences in Spatial Ability: A Reexamination

ERIC Educational Resources Information Center

Rilea, Stacy L.

2008-01-01

The current study assessed the lateralization of function hypothesis (Rilea, S. L., Roskos-Ewoldsen, B., & Boles, D. (2004). "Sex differences in spatial ability: A lateralization of function approach." "Brain and Cognition," 56, 332-343) which suggested that it was the interaction of brain organization and the type of spatial task that led to sex…

Strategic Resource Allocation in the Human Brain Supports Cognitive Coordination of Object and Spatial Working Memory

PubMed Central

Jackson, Margaret C; Morgan, Helen M; Shapiro, Kimron L; Mohr, Harald; Linden, David EJ

2011-01-01

The ability to integrate different types of information (e.g., object identity and spatial orientation) and maintain or manipulate them concurrently in working memory (WM) facilitates the flow of ongoing tasks and is essential for normal human cognition. Research shows that object and spatial information is maintained and manipulated in WM via separate pathways in the brain (object/ventral versus spatial/dorsal). How does the human brain coordinate the activity of different specialized systems to conjoin different types of information? Here we used functional magnetic resonance imaging to investigate conjunction- versus single-task manipulation of object (compute average color blend) and spatial (compute intermediate angle) information in WM. Object WM was associated with ventral (inferior frontal gyrus, occipital cortex), and spatial WM with dorsal (parietal cortex, superior frontal, and temporal sulci) regions. Conjoined object/spatial WM resulted in intermediate activity in these specialized areas, but greater activity in different prefrontal and parietal areas. Unique to our study, we found lower temporo-occipital activity and greater deactivation in temporal and medial prefrontal cortices for conjunction- versus single-tasks. Using structural equation modeling, we derived a conjunction-task connectivity model that comprises a frontoparietal network with a bidirectional DLPFC-VLPFC connection, and a direct parietal-extrastriate pathway. We suggest that these activation/deactivation patterns reflect efficient resource allocation throughout the brain and propose a new extended version of the biased competition model of WM. Hum Brain Mapp, 2011. © 2010 Wiley-Liss, Inc. PMID:20715083

High-resolution whole-brain DCE-MRI using constrained reconstruction: Prospective clinical evaluation in brain tumor patients.

PubMed

Guo, Yi; Lebel, R Marc; Zhu, Yinghua; Lingala, Sajan Goud; Shiroishi, Mark S; Law, Meng; Nayak, Krishna

2016-05-01

To clinically evaluate a highly accelerated T1-weighted dynamic contrast-enhanced (DCE) MRI technique that provides high spatial resolution and whole-brain coverage via undersampling and constrained reconstruction with multiple sparsity constraints. Conventional (rate-2 SENSE) and experimental DCE-MRI (rate-30) scans were performed 20 minutes apart in 15 brain tumor patients. The conventional clinical DCE-MRI had voxel dimensions 0.9 × 1.3 × 7.0 mm(3), FOV 22 × 22 × 4.2 cm(3), and the experimental DCE-MRI had voxel dimensions 0.9 × 0.9 × 1.9 mm(3), and broader coverage 22 × 22 × 19 cm(3). Temporal resolution was 5 s for both protocols. Time-resolved images and blood-brain barrier permeability maps were qualitatively evaluated by two radiologists. The experimental DCE-MRI scans showed no loss of qualitative information in any of the cases, while achieving substantially higher spatial resolution and whole-brain spatial coverage. Average qualitative scores (from 0 to 3) were 2.1 for the experimental scans and 1.1 for the conventional clinical scans. The proposed DCE-MRI approach provides clinically superior image quality with higher spatial resolution and coverage than currently available approaches. These advantages may allow comprehensive permeability mapping in the brain, which is especially valuable in the setting of large lesions or multiple lesions spread throughout the brain.

Viral neurotropism, peripheral neuropathy and other morphological abnormalities in bovine ephemeral fever virus-infected downer cattle.

PubMed

Barigye, R; Davis, S; Hunt, R; Hunt, N; Walsh, S; Elliott, N; Burnup, C; Aumann, S; Day, C; Dyrting, K; Weir, R; Melville, L F

2016-10-01

This study assessed the neurotropism of bovine ephemeral fever (BEF) virus (BEFV) and described histomorphological abnormalities of the brain, spinal cord and peripheral nerves that may causally contribute to paresis or paralysis in BEF. Four paralysed and six asymptomatic but virus-infected cattle were monitored, and blood and serum samples screened by qRT-PCR, virus isolation and neutralisation tests. Fresh brain, spinal cord, peripheral nerve and other tissues were qRT-PCR-tested for viral RNA, while formalin-fixed specimens were processed routinely and immunohistochemically evaluated for histomorphological abnormalities and viral antigen distribution, respectively. The neurotropism of BEFV was immunohistochemically confirmed in the brain and peripheral nerves and peripheral neuropathy was demonstrated in three paralysed but not the six aneurological but virus-infected animals. Wallerian degeneration (WD) was present in the ventral funicular white matter of the lumbar spinal cord of a paralysed steer and in cervical and thoracic spinal cord segments of three paralysed animals. Although no spinal cord lesions were seen in the steer euthanased within 7 days of illness, peripheral neuropathy was present and more severe in nerves of the brachial plexuses than in the gluteal or fibular nerves. The only steer with WD in the lumbar spinal cord also showed intrahistiocytic cell viral antigen that was spatially distributed within areas of moderate brain stem encephalitis. The data confirmed neurotropism of BEFV in cattle and documented histomorphological abnormalities in peripheral nerves and brain which, together with spinal cord lesions, may contribute to chronic paralysis in BEFV-infected downer cattle. © 2016 Australian Veterinary Association.

Large-Scale Brain Networks Supporting Divided Attention across Spatial Locations and Sensory Modalities

PubMed Central

Santangelo, Valerio

2018-01-01

Higher-order cognitive processes were shown to rely on the interplay between large-scale neural networks. However, brain networks involved with the capability to split attentional resource over multiple spatial locations and multiple stimuli or sensory modalities have been largely unexplored to date. Here I re-analyzed data from Santangelo et al. (2010) to explore the causal interactions between large-scale brain networks during divided attention. During fMRI scanning, participants monitored streams of visual and/or auditory stimuli in one or two spatial locations for detection of occasional targets. This design allowed comparing a condition in which participants monitored one stimulus/modality (either visual or auditory) in two spatial locations vs. a condition in which participants monitored two stimuli/modalities (both visual and auditory) in one spatial location. The analysis of the independent components (ICs) revealed that dividing attentional resources across two spatial locations necessitated a brain network involving the left ventro- and dorso-lateral prefrontal cortex plus the posterior parietal cortex, including the intraparietal sulcus (IPS) and the angular gyrus, bilaterally. The analysis of Granger causality highlighted that the activity of lateral prefrontal regions were predictive of the activity of all of the posteriors parietal nodes. By contrast, dividing attention across two sensory modalities necessitated a brain network including nodes belonging to the dorsal frontoparietal network, i.e., the bilateral frontal eye-fields (FEF) and IPS, plus nodes belonging to the salience network, i.e., the anterior cingulated cortex and the left and right anterior insular cortex (aIC). The analysis of Granger causality highlights a tight interdependence between the dorsal frontoparietal and salience nodes in trials requiring divided attention between different sensory modalities. The current findings therefore highlighted a dissociation among brain networks implicated during divided attention across spatial locations and sensory modalities, pointing out the importance of investigating effective connectivity of large-scale brain networks supporting complex behavior. PMID:29535614

Large-Scale Brain Networks Supporting Divided Attention across Spatial Locations and Sensory Modalities.

PubMed

Santangelo, Valerio

2018-01-01

Higher-order cognitive processes were shown to rely on the interplay between large-scale neural networks. However, brain networks involved with the capability to split attentional resource over multiple spatial locations and multiple stimuli or sensory modalities have been largely unexplored to date. Here I re-analyzed data from Santangelo et al. (2010) to explore the causal interactions between large-scale brain networks during divided attention. During fMRI scanning, participants monitored streams of visual and/or auditory stimuli in one or two spatial locations for detection of occasional targets. This design allowed comparing a condition in which participants monitored one stimulus/modality (either visual or auditory) in two spatial locations vs. a condition in which participants monitored two stimuli/modalities (both visual and auditory) in one spatial location. The analysis of the independent components (ICs) revealed that dividing attentional resources across two spatial locations necessitated a brain network involving the left ventro- and dorso-lateral prefrontal cortex plus the posterior parietal cortex, including the intraparietal sulcus (IPS) and the angular gyrus, bilaterally. The analysis of Granger causality highlighted that the activity of lateral prefrontal regions were predictive of the activity of all of the posteriors parietal nodes. By contrast, dividing attention across two sensory modalities necessitated a brain network including nodes belonging to the dorsal frontoparietal network, i.e., the bilateral frontal eye-fields (FEF) and IPS, plus nodes belonging to the salience network, i.e., the anterior cingulated cortex and the left and right anterior insular cortex (aIC). The analysis of Granger causality highlights a tight interdependence between the dorsal frontoparietal and salience nodes in trials requiring divided attention between different sensory modalities. The current findings therefore highlighted a dissociation among brain networks implicated during divided attention across spatial locations and sensory modalities, pointing out the importance of investigating effective connectivity of large-scale brain networks supporting complex behavior.

Spatial distribution of resting-state BOLD regional homogeneity as a predictor of brain glucose uptake: A study in healthy aging.

PubMed

Bernier, Michaël; Croteau, Etienne; Castellano, Christian-Alexandre; Cunnane, Stephen C; Whittingstall, Kevin

2017-04-15

Positron emission tomography using [18F]-fluorodeoxyglucose (PET-FDG) is the primary imaging modality used to measure glucose metabolism in the brain (CMRGlu). CMRGlu has been used as a biomarker of brain aging and neurodegenerative diseases, but the complexity and invasive nature of PET often limits its use in research. There is therefore great interest in developing non-invasive metrics for estimating brain CMRGlu. We therefore investigated resting state fMRI metrics such as regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF) and regional global connectivity (Closeness) with multiple analytical approaches to determine their relationship to CMRGlu. We investigated this relation in two distinct cognitively healthy populations separated by age (27 young adults and 35 older adults). Overall, we found that both regionally and across participants, ReHo strongly correlated with CMRGlu in healthy young and older adults. Moreover, ReHo demonstrated the same age-related differences as CMRGlu throughout all cortical regions, particularly in the default network and frontal areas. Copyright © 2017 Elsevier Inc. All rights reserved.

Clarifying the Ghrelin System's Ability to Regulate Feeding Behaviours Despite Enigmatic Spatial Separation of the GHSR and Its Endogenous Ligand.

PubMed

Edwards, Alexander; Abizaid, Alfonso

2017-04-19

Ghrelin is a hormone predominantly produced in and secreted from the stomach. Ghrelin is involved in many physiological processes including feeding, the stress response, and in modulating learning, memory and motivational processes. Ghrelin does this by binding to its receptor, the growth hormone secretagogue receptor (GHSR), a receptor found in relatively high concentrations in hypothalamic and mesolimbic brain regions. While the feeding and metabolic effects of ghrelin can be explained by the effects of this hormone on regions of the brain that have a more permeable blood brain barrier (BBB), ghrelin produced within the periphery demonstrates a limited ability to reach extrahypothalamic regions where GHSRs are expressed. Therefore, one of the most pressing unanswered questions plaguing ghrelin research is how GHSRs, distributed in brain regions protected by the BBB, are activated despite ghrelin's predominant peripheral production and poor ability to transverse the BBB. This manuscript will describe how peripheral ghrelin activates central GHSRs to encourage feeding, and how central ghrelin synthesis and ghrelin independent activation of GHSRs may also contribute to the modulation of feeding behaviours.

Measurements and models of electric fields in the in vivo human brain during transcranial electric stimulation

PubMed Central

Huang, Yu; Liu, Anli A; Lafon, Belen; Friedman, Daniel; Dayan, Michael; Wang, Xiuyuan; Bikson, Marom; Doyle, Werner K; Devinsky, Orrin; Parra, Lucas C

2017-01-01

Transcranial electric stimulation aims to stimulate the brain by applying weak electrical currents at the scalp. However, the magnitude and spatial distribution of electric fields in the human brain are unknown. We measured electric potentials intracranially in ten epilepsy patients and estimated electric fields across the entire brain by leveraging calibrated current-flow models. When stimulating at 2 mA, cortical electric fields reach 0.8 V/m, the lower limit of effectiveness in animal studies. When individual whole-head anatomy is considered, the predicted electric field magnitudes correlate with the recorded values in cortical (r = 0.86) and depth (r = 0.88) electrodes. Accurate models require adjustment of tissue conductivity values reported in the literature, but accuracy is not improved when incorporating white matter anisotropy or different skull compartments. This is the first study to validate and calibrate current-flow models with in vivo intracranial recordings in humans, providing a solid foundation to target stimulation and interpret clinical trials. DOI: http://dx.doi.org/10.7554/eLife.18834.001 PMID:28169833

Modelling dynamic fronto-parietal behaviour during minimally invasive surgery--a Markovian trip distribution approach.

PubMed

Leff, Daniel Richard; Orihuela-Espina, Felipe; Leong, Julian; Darzi, Ara; Yang, Guang-Zhong

2008-01-01

Learning to perform Minimally Invasive Surgery (MIS) requires considerable attention, concentration and spatial ability. Theoretically, this leads to activation in executive control (prefrontal) and visuospatial (parietal) centres of the brain. A novel approach is presented in this paper for analysing the flow of fronto-parietal haemodynamic behaviour and the associated variability between subjects. Serially acquired functional Near Infrared Spectroscopy (fNIRS) data from fourteen laparoscopic novices at different stages of learning is projected into a low-dimensional 'geospace', where sequentially acquired data is mapped to different locations. A trip distribution matrix based on consecutive directed trips between locations in the geospace reveals confluent fronto-parietal haemodynamic changes and a gravity model is applied to populate this matrix. To model global convergence in haemodynamic behaviour, a Markov chain is constructed and by comparing sequential haemodynamic distributions to the Markov's stationary distribution, inter-subject variability in learning an MIS task can be identified.

Three urocortins in medaka: identification and spatial expression in the central nervous system.

PubMed

Hosono, K; Yamashita, J; Kikuchi, Y; Hiraki-Kajiyama, T; Okubo, K

2017-05-01

The urocortin (UCN) group of neuropeptides includes urocortin 1/sauvagine/urotensin 1 (UTS1), urocortin 2 (UCN2) and urocortin 3 (UCN3). In recent years, evidence has accumulated showing that UCNs play pivotal roles in mediating stress response and anxiety in mammals. Evidence has also emerged regarding the evolutionary conservation of UCNs in vertebrates, but very little information is available about UCNs in non-mammalian vertebrates. Indeed, at present, there are no reports of the empirical identification of ucn2 in non-mammalian vertebrates or of the distribution of ucn2 and ucn3 expression in the adult central nervous system (CNS) of these animals. To gain insight into the evolutionary nature of UCNs in vertebrates, we cloned uts1, ucn2 and ucn3 in a teleost fish, medaka and examined the spatial expression of these genes in the adult brain and spinal cord. Although all known UCN2 genes except those in rodents have been reported to likely lack the necessary structural features to produce a functional pre-pro-protein, all three UCN genes in medaka, including ucn2, displayed all of these features, suggesting their functionality. The three UCN genes exhibited distinct spatial expression patterns in the medaka brain: uts1 was primarily expressed in broad regions of the dorsal telencephalon, ucn2 was expressed in restricted regions of the thalamus and brainstem and ucn3 was expressed in discrete nuclei throughout many regions of the brain. We also found that these genes were all expressed throughout the medaka spinal cord, each with a distinct spatial pattern. Given that many of these regions have been implicated in stress responses and anxiety, the three UCNs may serve distinct physiological roles in the medaka CNS, including those involved in stress and anxiety, as shown in the mammalian CNS. © 2017 British Society for Neuroendocrinology.

Features of spatial and functional segregation and integration of the primate connectome revealed by trade-off between wiring cost and efficiency

PubMed Central

Chen, Yuhan; Wang, Shengjun

2017-01-01

The primate connectome, possessing a characteristic global topology and specific regional connectivity profiles, is well organized to support both segregated and integrated brain function. However, the organization mechanisms shaping the characteristic connectivity and its relationship to functional requirements remain unclear. The primate brain connectome is shaped by metabolic economy as well as functional values. Here, we explored the influence of two competing factors and additional advanced functional requirements on the primate connectome employing an optimal trade-off model between neural wiring cost and the representative functional requirement of processing efficiency. Moreover, we compared this model with a generative model combining spatial distance and topological similarity, with the objective of statistically reproducing multiple topological features of the network. The primate connectome indeed displays a cost-efficiency trade-off and that up to 67% of the connections were recovered by optimal combination of the two basic factors of wiring economy and processing efficiency, clearly higher than the proportion of connections (56%) explained by the generative model. While not explicitly aimed for, the trade-off model captured several key topological features of the real connectome as the generative model, yet better explained the connectivity of most regions. The majority of the remaining 33% of connections unexplained by the best trade-off model were long-distance links, which are concentrated on few cortical areas, termed long-distance connectors (LDCs). The LDCs are mainly non-hubs, but form a densely connected group overlapping on spatially segregated functional modalities. LDCs are crucial for both functional segregation and integration across different scales. These organization features revealed by the optimization analysis provide evidence that the demands of advanced functional segregation and integration among spatially distributed regions may play a significant role in shaping the cortical connectome, in addition to the basic cost-efficiency trade-off. These findings also shed light on inherent vulnerabilities of brain networks in diseases. PMID:28961235

Features of spatial and functional segregation and integration of the primate connectome revealed by trade-off between wiring cost and efficiency.

PubMed

Chen, Yuhan; Wang, Shengjun; Hilgetag, Claus C; Zhou, Changsong

2017-09-01

The primate connectome, possessing a characteristic global topology and specific regional connectivity profiles, is well organized to support both segregated and integrated brain function. However, the organization mechanisms shaping the characteristic connectivity and its relationship to functional requirements remain unclear. The primate brain connectome is shaped by metabolic economy as well as functional values. Here, we explored the influence of two competing factors and additional advanced functional requirements on the primate connectome employing an optimal trade-off model between neural wiring cost and the representative functional requirement of processing efficiency. Moreover, we compared this model with a generative model combining spatial distance and topological similarity, with the objective of statistically reproducing multiple topological features of the network. The primate connectome indeed displays a cost-efficiency trade-off and that up to 67% of the connections were recovered by optimal combination of the two basic factors of wiring economy and processing efficiency, clearly higher than the proportion of connections (56%) explained by the generative model. While not explicitly aimed for, the trade-off model captured several key topological features of the real connectome as the generative model, yet better explained the connectivity of most regions. The majority of the remaining 33% of connections unexplained by the best trade-off model were long-distance links, which are concentrated on few cortical areas, termed long-distance connectors (LDCs). The LDCs are mainly non-hubs, but form a densely connected group overlapping on spatially segregated functional modalities. LDCs are crucial for both functional segregation and integration across different scales. These organization features revealed by the optimization analysis provide evidence that the demands of advanced functional segregation and integration among spatially distributed regions may play a significant role in shaping the cortical connectome, in addition to the basic cost-efficiency trade-off. These findings also shed light on inherent vulnerabilities of brain networks in diseases.

Approaches to Capture Variance Differences in Rest fMRI Networks in the Spatial Geometric Features: Application to Schizophrenia.

PubMed

Gopal, Shruti; Miller, Robyn L; Baum, Stefi A; Calhoun, Vince D

2016-01-01

Identification of functionally connected regions while at rest has been at the forefront of research focusing on understanding interactions between different brain regions. Studies have utilized a variety of approaches including seed based as well as data-driven approaches to identifying such networks. Most such techniques involve differentiating groups based on group mean measures. There has been little work focused on differences in spatial characteristics of resting fMRI data. We present a method to identify between group differences in the variability in the cluster characteristics of network regions within components estimated via independent vector analysis (IVA). IVA is a blind source separation approach shown to perform well in capturing individual subject variability within a group model. We evaluate performance of the approach using simulations and then apply to a relatively large schizophrenia data set (82 schizophrenia patients and 89 healthy controls). We postulate, that group differences in the intra-network distributional characteristics of resting state network voxel intensities might indirectly capture important distinctions between the brain function of healthy and clinical populations. Results demonstrate that specific areas of the brain, superior, and middle temporal gyrus that are involved in language and recognition of emotions, show greater component level variance in amplitude weights for schizophrenia patients than healthy controls. Statistically significant correlation between component level spatial variance and component volume was observed in 19 of the 27 non-artifactual components implying an evident relationship between the two parameters. Additionally, the greater spread in the distance of the cluster peak of a component from the centroid in schizophrenia patients compared to healthy controls was observed for seven components. These results indicate that there is hidden potential in exploring variance and possibly higher-order measures in resting state networks to better understand diseases such as schizophrenia. It furthers comprehension of how spatial characteristics can highlight previously unexplored differences between populations such as schizophrenia patients and healthy controls.

Spatial Neglect Hinders Success of Inpatient Rehabilitation in Individuals With Traumatic Brain Injury: A Retrospective Study.

PubMed

Chen, Peii; Ward, Irene; Khan, Ummais; Liu, Yan; Hreha, Kimberly

2016-06-01

Background Current knowledge about spatial neglect and its impact on rehabilitation mostly originates from stroke studies. Objective To examine the impact of spatial neglect on rehabilitation outcome in individuals with traumatic brain injury (TBI). Methods The retrospective study included 156 consecutive patients with TBI (73 women; median age = 69.5 years; interquartile range = 50-81 years) at an inpatient rehabilitation facility (IRF). We examined whether the presence of spatial neglect affected the Functional Independence Measure (FIM) scores, length of stay, or discharge disposition. Based on the available medical records, we also explored whether spatial neglect was associated with tactile sensation or muscle strength asymmetry in the extremities and whether specific brain injuries or lesions predicted spatial neglect. Results In all, 30.1% (47 of 156) of the sample had spatial neglect. Sex, age, severity of TBI, or time postinjury did not differ between patients with and without spatial neglect. In comparison to patients without spatial neglect, patients with the disorder stayed in IRF 5 days longer, had lower FIM scores at discharge, improved slower in both Cognitive and Motor FIM scores, and might have less likelihood of return home. In addition, left-sided neglect was associated with asymmetric strength in the lower extremities, specifically left weaker than the right. Finally, brain injury-induced mass effect predicted left-sided neglect. Conclusions Spatial neglect is common following TBI, impedes rehabilitation progress in both motor and cognitive domains, and prolongs length of stay. Future research is needed for linking specific traumatic injuries and lesioned networks to spatial neglect and related impairment. © The Author(s) 2015.

Right-hemispheric dominance of spatial memory in split-brain mice.

PubMed

Shinohara, Yoshiaki; Hosoya, Aki; Yamasaki, Nobuyuki; Ahmed, Hassan; Hattori, Satoko; Eguchi, Megumi; Yamaguchi, Shun; Miyakawa, Tsuyoshi; Hirase, Hajime; Shigemoto, Ryuichi

2012-02-01

Left-right asymmetry of human brain function has been known for a century, although much of molecular and cellular basis of brain laterality remains to be elusive. Recent studies suggest that hippocampal CA3-CA1 excitatory synapses are asymmetrically arranged, however, the functional implication of the asymmetrical circuitry has not been studied at the behavioral level. In order to address the left-right asymmetry of hippocampal function in behaving mice, we analyzed the performance of "split-brain" mice in the Barnes maze. The "split-brain" mice received ventral hippocampal commissure and corpus callosum transection in addition to deprivation of visual input from one eye. In such mice, the hippocampus in the side of visual deprivation receives sensory-driven input. Better spatial task performance was achieved by the mice which were forced to use the right hippocampus than those which were forced to use the left hippocampus. In two-choice spatial maze, forced usage of left hippocampus resulted in a comparable performance to the right counterpart, suggesting that both hippocampal hemispheres are capable of conducting spatial learning. Therefore, the results obtained from the Barnes maze suggest that the usage of the right hippocampus improves the accuracy of spatial memory. Performance of non-spatial yet hippocampus-dependent tasks (e.g. fear conditioning) was not influenced by the laterality of the hippocampus. Copyright © 2010 Wiley Periodicals, Inc.

View-invariant object category learning, recognition, and search: how spatial and object attention are coordinated using surface-based attentional shrouds.

PubMed

Fazl, Arash; Grossberg, Stephen; Mingolla, Ennio

2009-02-01

How does the brain learn to recognize an object from multiple viewpoints while scanning a scene with eye movements? How does the brain avoid the problem of erroneously classifying parts of different objects together? How are attention and eye movements intelligently coordinated to facilitate object learning? A neural model provides a unified mechanistic explanation of how spatial and object attention work together to search a scene and learn what is in it. The ARTSCAN model predicts how an object's surface representation generates a form-fitting distribution of spatial attention, or "attentional shroud". All surface representations dynamically compete for spatial attention to form a shroud. The winning shroud persists during active scanning of the object. The shroud maintains sustained activity of an emerging view-invariant category representation while multiple view-specific category representations are learned and are linked through associative learning to the view-invariant object category. The shroud also helps to restrict scanning eye movements to salient features on the attended object. Object attention plays a role in controlling and stabilizing the learning of view-specific object categories. Spatial attention hereby coordinates the deployment of object attention during object category learning. Shroud collapse releases a reset signal that inhibits the active view-invariant category in the What cortical processing stream. Then a new shroud, corresponding to a different object, forms in the Where cortical processing stream, and search using attention shifts and eye movements continues to learn new objects throughout a scene. The model mechanistically clarifies basic properties of attention shifts (engage, move, disengage) and inhibition of return. It simulates human reaction time data about object-based spatial attention shifts, and learns with 98.1% accuracy and a compression of 430 on a letter database whose letters vary in size, position, and orientation. The model provides a powerful framework for unifying many data about spatial and object attention, and their interactions during perception, cognition, and action.

Effect of head motion on MRI B0 field distribution.

PubMed

Liu, Jiaen; de Zwart, Jacco A; van Gelderen, Peter; Murphy-Boesch, Joseph; Duyn, Jeff H

2018-05-16

To identify and characterize the sources of B 0 field changes due to head motion, to reduce motion sensitivity in human brain MRI. B 0 fields were measured in 5 healthy human volunteers at various head poses. After measurement of the total field, the field originating from the subject was calculated by subtracting the external field generated by the magnet and shims. A subject-specific susceptibility model was created to quantify the contribution of the head and torso. The spatial complexity of the field changes was analyzed using spherical harmonic expansion. Minor head pose changes can cause substantial and spatially complex field changes in the brain. For rotations and translations of approximately 5 º and 5 mm, respectively, at 7 T, the field change that is associated with the subject's magnetization generates a standard deviation (SD) of about 10 Hz over the brain. The stationary torso contributes to this subject-associated field change significantly with a SD of about 5 Hz. The subject-associated change leads to image-corrupting phase errors in multi-shot T2*-weighted acquisitions. The B 0 field changes arising from head motion are problematic for multishot T2*-weighted imaging. Characterization of the underlying sources provides new insights into mitigation strategies, which may benefit from individualized predictive field models in addition to real-time field monitoring and correction strategies. © 2018 International Society for Magnetic Resonance in Medicine.

Function Lateralization via Measuring Coherence Laterality

PubMed Central

Wang, Ze; Mechanic-Hamilton, Dawn; Pluta, John; Glynn, Simon; Detre, John A.

2009-01-01

A data-driven approach for lateralization of brain function based on the spatial coherence difference of functional MRI (fMRI) data in homologous regions-of-interest (ROI) in each hemisphere is proposed. The utility of using coherence laterality (CL) to determine function laterality was assessed first by examining motor laterality using normal subjects’ data acquired both at rest and with a simple unilateral motor task and subsequently by examining mesial temporal lobe memory laterality in normal subjects and patients with temporal lobe epilepsy. The motor task was used to demonstrate that CL within motor ROI correctly lateralized functional stimulation. In patients with unilateral epilepsy studied during a scene-encoding task, CL in a hippocampus-parahippocampus-fusiform (HPF) ROI was concordant with lateralization based on task activation, and the CL index (CLI) significantly differentiated the right side group to the left side group. By contrast, normal controls showed a symmetric HPF CLI distribution. Additionally, similar memory laterality prediction results were still observed using CL in epilepsy patients with unilateral seizures after the memory encoding effect was removed from the data, suggesting the potential for lateralization of pathological brain function based on resting fMRI data. A better lateralization was further achieved via a combination of the proposed approach and the standard activation based approach, demonstrating that assessment of spatial coherence changes provides a complementary approach to quantifying task-correlated activity for lateralizing brain function. PMID:19345736

Probabilistic atlases for face and biological motion perception: an analysis of their reliability and overlap.

PubMed

Engell, Andrew D; McCarthy, Gregory

2013-07-01

Neuroimaging research has identified several category-selective regions in visual cortex that respond most strongly when viewing an exemplar image from a preferred category, such as faces. Recent studies, however, have suggested a more complex pattern of activation that has been heretofore unrecognized, e.g., the presence of additional patches of activation to faces beyond the well-studied fusiform face area, and the activation of ostensible face selective regions by animate motion of non-biological forms. Here, we characterize the spatial pattern of brain activity evoked by viewing faces or biological motion in large fMRI samples (N>120). We create probabilistic atlases for both face and biological motion activation, and directly compare their spatial patterns of activation. Our findings support the suggestion that the fusiform face area is composed of at least two separable foci of activation. The face-evoked response in the fusiform and nearby ventral temporal cortex has good reliability across runs; however, we found surprisingly high variability in lateral brain regions by faces, and for all brain regions by biological motion, which had an overall much lower effect size. We found that faces and biological motion evoke substantially overlapping activation distributions in both ventral and lateral occipitotemporal cortices. The peaks of activation for these different categories within these overlapping regions were close but distinct. Copyright © 2013 Elsevier Inc. All rights reserved.

Time-reversal Techniques in Ultrasound-assisted Convection-enhanced Drug Delivery to the Brain: Technology Development and In Vivo Evaluation

PubMed Central

Lewis, George K.; Guarino, Sabrina; Gandhi, Gaurav; Filinger, Laurent; Lewis, George K.; Olbricht, Willam L.; Sarvazyan, Armen

2011-01-01

We describe a drug delivery method that combines Time-Reversal Acoustics (TRA) with Convection-Enhanced Delivery (CED) to improve the delivery of therapeutics to the interstitium of the brain. The Ultrasound-assisted CED approach (UCED) circumvents the blood-brain barrier by infusing compounds through a cannula that is inserted into the brain while simultaneously delivering ultrasound to improve the penetration of pharmaceuticals. CED without ultrasound-assistance has been used to treat a variety of neural disorders, including glioblastoma multiforme, a malignancy that presents a very poor prognosis for patients. We describe a novel system that is used to infuse fluids into the brain parenchyma while simultaneously exposing the tissue to safe levels of 1-MHz, low intensity, ultrasound energy. The system includes a combined infusion needle-hydrophone, a 10-channel ultralow-output impedance amplifier, a broad-band ultrasound resonator, and MatLab®-based TRA control and user-interface. TRA allows easy coupling of ultrasound therapy through the skull without complex phase-correction and array design. The smart targeting UCED system has been tested in vivo and results show it provides 1.5-mm spatial resolution for UCED and improves tracer distribution in the brain over CED alone. PMID:21881622

Deep Independence Network Analysis of Structural Brain Imaging: Application to Schizophrenia

PubMed Central

Castro, Eduardo; Hjelm, R. Devon; Plis, Sergey M.; Dinh, Laurent; Turner, Jessica A.; Calhoun, Vince D.

2016-01-01

Linear independent component analysis (ICA) is a standard signal processing technique that has been extensively used on neuroimaging data to detect brain networks with coherent brain activity (functional MRI) or covarying structural patterns (structural MRI). However, its formulation assumes that the measured brain signals are generated by a linear mixture of the underlying brain networks and this assumption limits its ability to detect the inherent nonlinear nature of brain interactions. In this paper, we introduce nonlinear independent component estimation (NICE) to structural MRI data to detect abnormal patterns of gray matter concentration in schizophrenia patients. For this biomedical application, we further addressed the issue of model regularization of nonlinear ICA by performing dimensionality reduction prior to NICE, together with an appropriate control of the complexity of the model and the usage of a proper approximation of the probability distribution functions of the estimated components. We show that our results are consistent with previous findings in the literature, but we also demonstrate that the incorporation of nonlinear associations in the data enables the detection of spatial patterns that are not identified by linear ICA. Specifically, we show networks including basal ganglia, cerebellum and thalamus that show significant differences in patients versus controls, some of which show distinct nonlinear patterns. PMID:26891483

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

PubMed Central

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

2015-01-01

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

Measurement of Local Partial Pressure of Oxygen in the Brain Tissue under Normoxia and Epilepsy with Phosphorescence Lifetime Microscopy.

PubMed

Zhang, Cong; Bélanger, Samuel; Pouliot, Philippe; Lesage, Frédéric

2015-01-01

In this work a method for measuring brain oxygen partial pressure with confocal phosphorescence lifetime microscopy system is reported. When used in conjunction with a dendritic phosphorescent probe, Oxyphor G4, this system enabled minimally invasive measurements of oxygen partial pressure (pO2) in cerebral tissue with high spatial and temporal resolution during 4-AP induced epileptic seizures. Investigating epileptic events, we characterized the spatio-temporal distribution of the "initial dip" in pO2 near the probe injection site and along nearby arterioles. Our results reveal a correlation between the percent change in the pO2 signal during the "initial dip" and the duration of seizure-like activity, which can help localize the epileptic focus and predict the length of seizure.

Individual differences in brain activity during visuo-spatial processing assessed by slow cortical potentials and LORETA.

PubMed

Lamm, Claus; Fischmeister, Florian Ph S; Bauer, Herbert

2005-12-01

Using slow-cortical potentials (SCPs), Vitouch et al. demonstrated that subjects with low ability to solve a complex visuo-spatial imagery task show higher activity in occipital, parietal and frontal cortex during task processing than subjects with high ability. This finding has been interpreted in the sense of the so-called "neural efficiency" hypothesis, which assumes that the central nervous system of individuals with higher intellectual abilities is functioning in a more efficient way than the one of individuals with lower abilities. Using a higher spatial resolution of SCP recordings, and by employing the source localization method of LORETA (low-resolution electromagnetic tomography), we investigated this hypothesis by performing an extended replication of Vitouch et al.'s study. SCPs during processing of a visuo-spatial imagery task were recorded in pre-selected subjects with either high or low abilities in solving the imagery task. Topographic and LORETA analyses of SCPs revealed that a distributed network of extrastriate occipital, superior parietal, temporal, medial frontal and prefrontal areas was active during task solving. This network is well in line with former studies of the functional neuroanatomy of visuo-spatial imagery. Contrary to our expectations, however, the results of Vitouch et al. as well as of other studies supporting the neural efficiency hypothesis could not be confirmed since no difference in brain activity between groups was observed. This inconsistency between studies might be due to differing task processing strategies. While subjects with high abilities in the Vitouch et al. study seemed to use a visuo-perceptual task solving approach, all other subjects relied upon a visuo-motor task processing strategy.

High density event-related potential data acquisition in cognitive neuroscience.

PubMed

Slotnick, Scott D

2010-04-16

Functional magnetic resonance imaging (fMRI) is currently the standard method of evaluating brain function in the field of Cognitive Neuroscience, in part because fMRI data acquisition and analysis techniques are readily available. Because fMRI has excellent spatial resolution but poor temporal resolution, this method can only be used to identify the spatial location of brain activity associated with a given cognitive process (and reveals virtually nothing about the time course of brain activity). By contrast, event-related potential (ERP) recording, a method that is used much less frequently than fMRI, has excellent temporal resolution and thus can track rapid temporal modulations in neural activity. Unfortunately, ERPs are under utilized in Cognitive Neuroscience because data acquisition techniques are not readily available and low density ERP recording has poor spatial resolution. In an effort to foster the increased use of ERPs in Cognitive Neuroscience, the present article details key techniques involved in high density ERP data acquisition. Critically, high density ERPs offer the promise of excellent temporal resolution and good spatial resolution (or excellent spatial resolution if coupled with fMRI), which is necessary to capture the spatial-temporal dynamics of human brain function.

Metabolic enzymes in glial cells of the honeybee brain and their associations with aging, starvation and food response.

PubMed

Shah, Ashish K; Kreibich, Claus D; Amdam, Gro V; Münch, Daniel

2018-01-01

The honey bee has been extensively studied as a model for neuronal circuit and memory function and more recently has emerged as an unconventional model in biogerontology. Yet, the detailed knowledge of neuronal processing in the honey bee brain contrasts with the very sparse information available on glial cells. In other systems glial cells are involved in nutritional homeostasis, detoxification, and aging. These glial functions have been linked to metabolic enzymes, such as glutamine synthetase and glycogen phosphorylase. As a step in identifying functional roles and potential differences among honey bee glial types, we examined the spatial distribution of these enzymes and asked if enzyme abundance is associated with aging and other processes essential for survival. Using immunohistochemistry and confocal laser microscopy we demonstrate that glutamine synthetase and glycogen phosphorylase are abundant in glia but appear to co-localize with different glial sub-types. The overall spatial distribution of both enzymes was not homogenous and differed markedly between different neuropiles and also within each neuropil. Using semi-quantitative Western blotting we found that rapid aging, typically observed in shortest-lived worker bees (foragers), was associated with declining enzyme levels. Further, we found enzyme abundance changes after severe starvation stress, and that glutamine synthetase is associated with food response. Together, our data indicate that aging and nutritional physiology in bees are linked to glial specific metabolic enzymes. Enzyme specific localization patterns suggest a functional differentiation among identified glial types.

Feasibility of approaches combining sensor and source features in brain-computer interface.

PubMed

Ahn, Minkyu; Hong, Jun Hee; Jun, Sung Chan

2012-02-15

Brain-computer interface (BCI) provides a new channel for communication between brain and computers through brain signals. Cost-effective EEG provides good temporal resolution, but its spatial resolution is poor and sensor information is blurred by inherent noise. To overcome these issues, spatial filtering and feature extraction techniques have been developed. Source imaging, transformation of sensor signals into the source space through source localizer, has gained attention as a new approach for BCI. It has been reported that the source imaging yields some improvement of BCI performance. However, there exists no thorough investigation on how source imaging information overlaps with, and is complementary to, sensor information. Information (visible information) from the source space may overlap as well as be exclusive to information from the sensor space is hypothesized. Therefore, we can extract more information from the sensor and source spaces if our hypothesis is true, thereby contributing to more accurate BCI systems. In this work, features from each space (sensor or source), and two strategies combining sensor and source features are assessed. The information distribution among the sensor, source, and combined spaces is discussed through a Venn diagram for 18 motor imagery datasets. Additional 5 motor imagery datasets from the BCI Competition III site were examined. The results showed that the addition of source information yielded about 3.8% classification improvement for 18 motor imagery datasets and showed an average accuracy of 75.56% for BCI Competition data. Our proposed approach is promising, and improved performance may be possible with better head model. Copyright © 2011 Elsevier B.V. All rights reserved.

Spatial heterogeneity of the relation between resting-state connectivity and blood flow: an important consideration for pharmacological studies.

PubMed

Khalili-Mahani, Najmeh; van Osch, Matthias J; de Rooij, Mark; Beckmann, Christian F; van Buchem, Mark A; Dahan, Albert; van Gerven, Johannes M; Rombouts, Serge A R B

2014-03-01

Resting state fMRI (RSfMRI) and arterial spin labeling (ASL) provide the field of pharmacological Neuroimaging tool for investigating states of brain activity in terms of functional connectivity or cerebral blood flow (CBF). Functional connectivity reflects the degree of synchrony or correlation of spontaneous fluctuations--mostly in the blood oxygen level dependent (BOLD) signal--across brain networks; but CBF reflects mean delivery of arterial blood to the brain tissue over time. The BOLD and CBF signals are linked to common neurovascular and hemodynamic mechanisms that necessitate increased oxygen transportation to the site of neuronal activation; however, the scale and the sources of variation in static CBF and spatiotemporal BOLD correlations are likely different. We tested this hypothesis by examining the relation between CBF and resting-state-network consistency (RSNC)--representing average intranetwork connectivity, determined from dual regression analysis with eight standard networks of interest (NOIs)--in a crossover placebo-controlled study of morphine and alcohol. Overall, we observed spatially heterogeneous relations between RSNC and CBF, and between the experimental factors (drug-by-time, time, drug and physiological rates) and each of these metrics. The drug-by-time effects on CBF were significant in all networks, but significant RSNC changes were limited to the sensorimotor, the executive/salience and the working memory networks. The post-hoc voxel-wise statistics revealed similar dissociations, perhaps suggesting differential sensitivity of RSNC and CBF to neuronal and vascular endpoints of drug actions. The spatial heterogeneity of RSNC/CBF relations encourages further investigation into the role of neuroreceptor distribution and cerebrovascular anatomy in predicting spontaneous fluctuations under drugs. Copyright © 2012 Wiley Periodicals, Inc.

Effects of a cognitive training on spatial learning and associated functional brain activations

PubMed Central

2013-01-01

Background Both cognitive and physical exercise have been discussed as promising interventions for healthy cognitive aging. The present study assessed the effects of cognitive training (spatial vs. perceptual training) and physical training (endurance training vs. non-endurance training) on spatial learning and associated brain activation in 33 adults (40–55 years). Spatial learning was assessed with a virtual maze task, and at the same time neural correlates were measured with functional magnetic resonance imaging (fMRI). Results Only the spatial training improved performance in the maze task. These behavioral gains were accompanied by a decrease in frontal and temporal lobe activity. At posttest, participants of the spatial training group showed lower activity than participants of the perceptual training group in a network of brain regions associated with spatial learning, including the hippocampus and parahippocampal gyrus. No significant differences were observed between the two physical intervention groups. Conclusions Functional changes in neural systems associated with spatial navigation can be induced by cognitive interventions and seem to be stronger than effects of physical exercise in middle-aged adults. PMID:23870447

Effects of Different Correlation Metrics and Preprocessing Factors on Small-World Brain Functional Networks: A Resting-State Functional MRI Study

PubMed Central

Liang, Xia; Wang, Jinhui; Yan, Chaogan; Shu, Ni; Xu, Ke; Gong, Gaolang; He, Yong

2012-01-01

Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01–0.027 Hz) versus slow-4 (0.027–0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the “best” network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027–0.073 Hz band exhibited greater reliability than those in the 0.01–0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics and specific preprocessing choices on both the global and nodal topological properties of functional brain networks. This study also has important implications for how to choose reliable analytical schemes in brain network studies. PMID:22412922

Development of Spatial and Verbal Working Memory Capacity in the Human Brain

ERIC Educational Resources Information Center

Thomason, Moriah E.; Race, Elizabeth; Burrows, Brittany; Whitfield-Gabrieli, Susan; Glover, Gary H.; Gabrieli, John D. E.

2009-01-01

A core aspect of working memory (WM) is the capacity to maintain goal-relevant information in mind, but little is known about how this capacity develops in the human brain. We compared brain activation, via fMRI, between children (ages 7-12 years) and adults (ages 20-29 years) performing tests of verbal and spatial WM with varying amounts (loads)…

Rostrocaudal gradients of dopamine D2/3 receptor binding in striatal subregions measured with [(11)C]raclopride and high-resolution positron emission tomography.

PubMed

Alakurtti, Kati; Johansson, Jarkko J; Tuokkola, Terhi; Någren, Kjell; Rinne, Juha O

2013-11-15

The human striatum has structural and functional subdivisions, both dorsoventrally and rostrocaudally. To date, the gradients of dopamine D2/3 receptor binding in the human striatum have not been measured with positron emission tomography (PET). Seven healthy male subjects aged 24.5 ± 3.5 years were scanned with brain-dedicated high-resolution research tomography (HRRT, Siemens Medical Solutions, Knoxville, TN, USA) and [(11)C]raclopride. Coronally defined regions of interest (ROIs) of the caudate nucleus, putamen and ventral striatum (VST) were sampled plane-by-plane, 1.5mm apart, on spatially normalized binding potential (BPND) images. Regional [(11)C]raclopride BPND values were calculated using the simplified reference tissue model (SRTM) from a total of 25 coronal planes. An increasing rostrocaudal gradient of the D2/3 receptor binding was detected in the putamen, which is consistent with the known distribution of D2/3 dopamine receptors. In the caudate nucleus, there was an initial increase in the BPND values in the most anterior planes, suggesting that the highest D2/3 receptor binding occurred in the head; however, there was an overall descending gradient. A declining trend was also observed in the VST. The novelty of this study lies in the presentation, for the first time, of the D2/3 receptor binding gradients in each striatal subregion in the brains of living healthy humans. The high spatial resolution provided by HRRT enables frequent sampling of BPND along the longitudinal extent of striatum; this method is superior to the sectioning used in previous post mortem studies. Regarding the functional organization of the striatum, our findings can inform future investigations of normal neurophysiology as well as efforts to differentiate neuropsychiatric disorders affecting the brain dopamine (DA) system. Furthermore, the average distribution of D2/3 receptor binding revealed in this study could serve as a basis for a database that includes distributions of various DA markers as a function of healthy aging. Copyright © 2013 Elsevier Inc. All rights reserved.

Brain shaving: adaptive detection for brain PET data

NASA Astrophysics Data System (ADS)

Grecchi, Elisabetta; Doyle, Orla M.; Bertoldo, Alessandra; Pavese, Nicola; Turkheimer, Federico E.

2014-05-01

The intricacy of brain biology is such that the variation of imaging end-points in health and disease exhibits an unpredictable range of spatial distributions from the extremely localized to the very diffuse. This represents a challenge for the two standard approaches to analysis, the mass univariate and the multivariate that exhibit either strong specificity but not as good sensitivity (the former) or poor specificity and comparatively better sensitivity (the latter). In this work, we develop an analytical methodology for positron emission tomography that operates an extraction (‘shaving’) of coherent patterns of signal variation while maintaining control of the type I error. The methodology operates two rotations on the image data, one local using the wavelet transform and one global using the singular value decomposition. The control of specificity is obtained by using the gap statistic that selects, within each eigenvector, a subset of significantly coherent elements. Face-validity of the algorithm is demonstrated using a paradigmatic data-set with two radiotracers, [11C]-raclopride and [11C]-(R)-PK11195, measured on the same Huntington's disease patients, a disorder with a genetic based diagnosis. The algorithm is able to detect the two well-known separate but connected processes of dopamine neuronal loss (localized in the basal ganglia) and neuroinflammation (diffusive around the whole brain). These processes are at the two extremes of the distributional envelope, one being very sparse and the latter being perfectly Gaussian and they are not adequately detected by the univariate and the multivariate approaches.

Spatial and temporal distribution of rabies in northern Tanzania in the period of 1993-2002.

PubMed

Swai, E S; Moshy, W E; Kaaya, J E; Mtui, P F

2010-01-01

A retrospective study was carried out to investigate the occurrence and distribution patterns of rabies cases in northern Tanzania. Data on laboratory confirmed brain samples and associated case reports submitted to the Arusha Veterinary Investigation Centre, for a period of ten years (1993-2002) was retrieved and reviewed. A total of 98 suspected rabies brain specimens from different animal species and geographical areas were submitted and processed during the period under review. Rabies was confirmed using Fluorescent Antibody Technique test. Of the 98 brain specimens processed, 65 (66.3%) were confirmed to be rabies cases. Canine rabies accounted for 73.8% of the cases and was diagnosed in dogs (43), jackals (4) and hyenas (1). Rabies in wildlife accounted for 5 out of 48 canine confirmed cases. Most of the cases were from Arusha Municipality (20) followed by Arumeru (19), Ngorongoro (9) and Moshi (8) districts. Rabies positive cases in other animal species were in the following order of frequencies: bovine (9 out of 11); feline (5 out of 10); equine (1 out of 2); caprine (2 out of 2). One porcine brain specimen was rabies negative. The high proportion of rabies positive cases confirmed suggests the level of their endemicity in the northern regions of Tanzania. Moreover, the findings highlights the need for sustained surveillance and institution of control measures among dog population and awareness creation particularly among general public and children whom are at high risk of contracting rabies because of their close contact with dogs.

Brain signature and functional impact of centralized pain: a multidisciplinary approach to the study of chronic pelvic pain (MAPP) network study.

PubMed

Kutch, Jason J; Ichesco, Eric; Hampson, Johnson P; Labus, Jennifer S; Farmer, Melissa A; Martucci, Katherine T; Ness, Timothy J; Deutsch, Georg; Apkarian, A Vania; Mackey, Sean C; Klumpp, David J; Schaeffer, Anthony J; Rodriguez, Larissa V; Kreder, Karl J; Buchwald, Dedra; Andriole, Gerald L; Lai, H Henry; Mullins, Chris; Kusek, John W; Landis, J Richard; Mayer, Emeran A; Clemens, J Quentin; Clauw, Daniel J; Harris, Richard E

2017-10-01

Chronic pain is often measured with a severity score that overlooks its spatial distribution across the body. This widespread pain is believed to be a marker of centralization, a central nervous system process that decouples pain perception from nociceptive input. Here, we investigated whether centralization is manifested at the level of the brain using data from 1079 participants in the Multidisciplinary Approach to the Study of Chronic Pelvic Pain Research Network (MAPP) study. Participants with a clinical diagnosis of urological chronic pelvic pain syndrome (UCPPS) were compared to pain-free controls and patients with fibromyalgia, the prototypical centralized pain disorder. Participants completed questionnaires capturing pain severity, function, and a body map of pain. A subset (UCPPS N = 110; fibromyalgia N = 23; healthy control N = 49) underwent functional and structural magnetic resonance imaging. Patients with UCPPS reported pain ranging from localized (pelvic) to widespread (throughout the body). Patients with widespread UCPPS displayed increased brain gray matter volume and functional connectivity involving sensorimotor and insular cortices (P < 0.05 corrected). These changes translated across disease diagnoses as identical outcomes were present in patients with fibromyalgia but not pain-free controls. Widespread pain was also associated with reduced physical and mental function independent of pain severity. Brain pathology in patients with centralized pain is related to pain distribution throughout the body. These patients may benefit from interventions targeting the central nervous system.

Language-specific dysgraphia in Korean patients with right brain stroke: influence of unilateral spatial neglect.

PubMed

Jang, Dae-Hyun; Kim, Min-Wook; Park, Kyoung Ha; Lee, Jae Woo

2015-03-01

The purpose of the present study was to investigate the relationship between Korean language-specific dysgraphia and unilateral spatial neglect in 31 right brain stroke patients. All patients were tested for writing errors in spontaneous writing, dictation, and copying tests. The dysgraphia was classified into visuospatial omission, visuospatial destruction, syllabic tilting, stroke omission, stroke addition, and stroke tilting. Twenty-three (77.4%) of the 31 patients made dysgraphia and 18 (58.1%) demonstrated unilateral spatial neglect. The visuospatial omission was the most common dysgraphia followed by stroke addition and omission errors. The highest number of errors was made in the copying and the least was in the spontaneous writing test. Patients with unilateral spatial neglect made a significantly higher number of dysgraphia in the copying test than those without. We identified specific dysgraphia features such as a right side space omission and a vertical stroke addition in Korean right brain stroke patients. In conclusion, unilateral spatial neglect influences copy writing system of Korean language in patients with right brain stroke.

Tracking brain arousal fluctuations with fMRI

PubMed Central

Chang, Catie; Leopold, David A.; Schölvinck, Marieke Louise; Mandelkow, Hendrik; Picchioni, Dante; Liu, Xiao; Ye, Frank Q.; Turchi, Janita N.; Duyn, Jeff H.

2016-01-01

Changes in brain activity accompanying shifts in vigilance and arousal can interfere with the study of other intrinsic and task-evoked characteristics of brain function. However, the difficulty of tracking and modeling the arousal state during functional MRI (fMRI) typically precludes the assessment of arousal-dependent influences on fMRI signals. Here we combine fMRI, electrophysiology, and the monitoring of eyelid behavior to demonstrate an approach for tracking continuous variations in arousal level from fMRI data. We first characterize the spatial distribution of fMRI signal fluctuations that track a measure of behavioral arousal; taking this pattern as a template, and using the local field potential as a simultaneous and independent measure of cortical activity, we observe that the time-varying expression level of this template in fMRI data provides a close approximation of electrophysiological arousal. We discuss the potential benefit of these findings for increasing the sensitivity of fMRI as a cognitive and clinical biomarker. PMID:27051064

Gold-nanorod contrast-enhanced photoacoustic micro-imaging of focused-ultrasound induced blood-brain-barrier opening in a rat model

NASA Astrophysics Data System (ADS)

Wang, Po-Hsun; Liu, Hao-Li; Hsu, Po-Hung; Lin, Chia-Yu; Chris Wang, Churng-Ren; Chen, Pin-Yuan; Wei, Kuo-Chen; Yen, Tzu-Chen; Li, Meng-Lin

2012-06-01

In this study, we develop a novel photoacoustic imaging technique based on gold nanorods (AuNRs) for quantitatively monitoring focused-ultrasound (FUS) induced blood-brain barrier (BBB) opening in a rat model in vivo. This study takes advantage of the strong near-infrared absorption (peak at ~800 nm) of AuNRs and the extravasation tendency from BBB opening foci due to their nano-scale size to passively label the BBB disruption area. Experimental results show that AuNR contrast-enhanced photoacoustic microscopy (PAM) successfully reveals the spatial distribution and temporal response of BBB disruption area in the rat brains. The quantitative measurement of contrast enhancement has potential to estimate the local concentration of AuNRs and even the dosage of therapeutic molecules when AuNRs are further used as nano-carrier for drug delivery or photothermal therapy. The photoacoustic results also provide complementary information to MRI, being helpful to discover more details about FUS induced BBB opening in small animal models.

Network structure of brain atrophy in de novo Parkinson's disease

PubMed Central

Zeighami, Yashar; Ulla, Miguel; Iturria-Medina, Yasser; Dadar, Mahsa; Zhang, Yu; Larcher, Kevin Michel-Herve; Fonov, Vladimir; Evans, Alan C; Collins, D Louis; Dagher, Alain

2015-01-01

We mapped the distribution of atrophy in Parkinson's disease (PD) using magnetic resonance imaging (MRI) and clinical data from 232 PD patients and 117 controls from the Parkinson's Progression Markers Initiative. Deformation-based morphometry and independent component analysis identified PD-specific atrophy in the midbrain, basal ganglia, basal forebrain, medial temporal lobe, and discrete cortical regions. The degree of atrophy reflected clinical measures of disease severity. The spatial pattern of atrophy demonstrated overlap with intrinsic networks present in healthy brain, as derived from functional MRI. Moreover, the degree of atrophy in each brain region reflected its functional and anatomical proximity to a presumed disease epicenter in the substantia nigra, compatible with a trans-neuronal spread of the disease. These results support a network-spread mechanism in PD. Finally, the atrophy pattern in PD was also seen in healthy aging, where it also correlated with the loss of striatal dopaminergic innervation. DOI: http://dx.doi.org/10.7554/eLife.08440.001 PMID:26344547

Neural correlate of spatial presence in an arousing and noninteractive virtual reality: an EEG and psychophysiology study.

PubMed

Baumgartner, Thomas; Valko, Lilian; Esslen, Michaela; Jäncke, Lutz

2006-02-01

Using electroencephalography (EEG), psychophysiology, and psychometric measures, this is the first study which investigated the neurophysiological underpinnings of spatial presence. Spatial presence is considered a sense of being physically situated within a spatial environment portrayed by a medium (e.g., television, virtual reality). Twelve healthy children and 11 healthy adolescents were watching different virtual roller coaster scenarios. During a control session, the roller coaster cab drove through a horizontal roundabout track. The following realistic roller coaster rides consisted of spectacular ups, downs, and loops. Low-resolution brain electromagnetic tomography (LORETA) and event-related desynchronization (ERD) were used to analyze the EEG data. As expected, we found that, compared to the control condition, experiencing a virtual roller coaster ride evoked in both groups strong SP experiences, increased electrodermal reactions, and activations in parietal brain areas known to be involved in spatial navigation. In addition, brain areas that receive homeostatic afferents from somatic and visceral sensations of the body were strongly activated. Most interesting, children (as compared to adolescents) reported higher spatial presence experiences and demonstrated a different frontal activation pattern. While adolescents showed increased activation in prefrontal areas known to be involved in the control of executive functions, children demonstrated a decreased activity in these brain regions. Interestingly, recent neuroanatomical and neurophysiological studies have shown that the frontal brain continues to develop to adult status well into adolescence. Thus, the result of our study implies that the increased spatial presence experience in children may result from the not fully developed control functions of the frontal cortex.

Allometric Analysis Detects Brain Size-Independent Effects of Sex and Sex Chromosome Complement on Human Cerebellar Organization.

PubMed

Mankiw, Catherine; Park, Min Tae M; Reardon, P K; Fish, Ari M; Clasen, Liv S; Greenstein, Deanna; Giedd, Jay N; Blumenthal, Jonathan D; Lerch, Jason P; Chakravarty, M Mallar; Raznahan, Armin

2017-05-24

The cerebellum is a large hindbrain structure that is increasingly recognized for its contribution to diverse domains of cognitive and affective processing in human health and disease. Although several of these domains are sex biased, our fundamental understanding of cerebellar sex differences-including their spatial distribution, potential biological determinants, and independence from brain volume variation-lags far behind that for the cerebrum. Here, we harness automated neuroimaging methods for cerebellar morphometrics in 417 individuals to (1) localize normative male-female differences in raw cerebellar volume, (2) compare these to sex chromosome effects estimated across five rare sex (X/Y) chromosome aneuploidy (SCA) syndromes, and (3) clarify brain size-independent effects of sex and SCA on cerebellar anatomy using a generalizable allometric approach that considers scaling relationships between regional cerebellar volume and brain volume in health. The integration of these approaches shows that (1) sex and SCA effects on raw cerebellar volume are large and distributed, but regionally heterogeneous, (2) human cerebellar volume scales with brain volume in a highly nonlinear and regionally heterogeneous fashion that departs from documented patterns of cerebellar scaling in phylogeny, and (3) cerebellar organization is modified in a brain size-independent manner by sex (relative expansion of total cerebellum, flocculus, and Crus II-lobule VIIIB volumes in males) and SCA (contraction of total cerebellar, lobule IV, and Crus I volumes with additional X- or Y-chromosomes; X-specific contraction of Crus II-lobule VIIIB). Our methods and results clarify the shifts in human cerebellar organization that accompany interwoven variations in sex, sex chromosome complement, and brain size. SIGNIFICANCE STATEMENT Cerebellar systems are implicated in diverse domains of sex-biased behavior and pathology, but we lack a basic understanding of how sex differences in the human cerebellum are distributed and determined. We leverage a rare neuroimaging dataset to deconvolve the interwoven effects of sex, sex chromosome complement, and brain size on human cerebellar organization. We reveal topographically variegated scaling relationships between regional cerebellar volume and brain size in humans, which (1) are distinct from those observed in phylogeny, (2) invalidate a traditional neuroimaging method for brain volume correction, and (3) allow more valid and accurate resolution of which cerebellar subcomponents are sensitive to sex and sex chromosome complement. These findings advance understanding of cerebellar organization in health and sex chromosome aneuploidy. Copyright © 2017 the authors 0270-6474/17/375222-11$15.00/0.

High-resolution whole-brain DCE-MRI using constrained reconstruction: Prospective clinical evaluation in brain tumor patients

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

Guo, Yi, E-mail: yiguo@usc.edu; Zhu, Yinghua; Lingala, Sajan Goud

Purpose: To clinically evaluate a highly accelerated T1-weighted dynamic contrast-enhanced (DCE) MRI technique that provides high spatial resolution and whole-brain coverage via undersampling and constrained reconstruction with multiple sparsity constraints. Methods: Conventional (rate-2 SENSE) and experimental DCE-MRI (rate-30) scans were performed 20 minutes apart in 15 brain tumor patients. The conventional clinical DCE-MRI had voxel dimensions 0.9 × 1.3 × 7.0 mm{sup 3}, FOV 22 × 22 × 4.2 cm{sup 3}, and the experimental DCE-MRI had voxel dimensions 0.9 × 0.9 × 1.9 mm{sup 3}, and broader coverage 22 × 22 × 19 cm{sup 3}. Temporal resolution was 5 smore » for both protocols. Time-resolved images and blood–brain barrier permeability maps were qualitatively evaluated by two radiologists. Results: The experimental DCE-MRI scans showed no loss of qualitative information in any of the cases, while achieving substantially higher spatial resolution and whole-brain spatial coverage. Average qualitative scores (from 0 to 3) were 2.1 for the experimental scans and 1.1 for the conventional clinical scans. Conclusions: The proposed DCE-MRI approach provides clinically superior image quality with higher spatial resolution and coverage than currently available approaches. These advantages may allow comprehensive permeability mapping in the brain, which is especially valuable in the setting of large lesions or multiple lesions spread throughout the brain.« less

Cerebral asymmetry for mental rotation: effects of response hand, handedness and gender.

PubMed

Johnson, Blake W; McKenzie, Kirsten J; Hamm, Jeff P

2002-10-28

We assessed lateralization of brain function during mental rotation, measuring the scalp distribution of a 400-600 ms latency event-related potential (ERP) with 128 recording electrodes. Twenty-four subjects, consisting of equal numbers of dextral and sinistral males and females, performed a mental rotation task under two response conditions (dominant non-dominant hand). For males, ERPs showed a right parietal bias regardless of response hand. For females, the parietal ERPs were slightly left-lateralized when making dominant hand responses, but strongly right-lateralized when making non-dominant hand responses. These results support the notion that visuo-spatial processing is more bilaterally organized in females. However, left hemisphere resources may be allocated to response preparation when using the non-dominant hand, forcing visuo-spatial processing to the right hemisphere.

Mitochondrial impairments contribute to spatial learning and memory dysfunction induced by chronic tramadol administration in rat: Protective effect of physical exercise.

PubMed

Mehdizadeh, Hajar; Pourahmad, Jalal; Taghizadeh, Ghorban; Vousooghi, Nasim; Yoonessi, Ali; Naserzadeh, Parvaneh; Behzadfar, Ladan; Rouini, Mohammad Reza; Sharifzadeh, Mohammad

2017-10-03

Despite the worldwide use of tramadol, few studies have been conducted about its effects on memory and mitochondrial function, and controversial results have been reported. Recently, there has been an increasing interest in physical exercise as a protective approach to neuronal and cognitive impairments. Therefore, the aim of this study was to investigate the effects of physical exercise on spatial learning and memory and brain mitochondrial function in tramadol-treated rats. After completion of 2-week (short-term) and 4-week (long-term) treadmill exercise regimens, male Wistar rats received tramadol (20, 40, 80mg/kg/day) intraperitoneally for 30days. Then spatial learning and memory was assessed by Morris water maze test (MWM). Moreover, brain mitochondrial function was evaluated by determination of mitochondrial reactive oxygen species (ROS) level, mitochondrial membrane potential (MMP), mitochondrial swelling and cytochrome c release from mitochondria. Chronic administration of tramadol impaired spatial learning and memory as well as brain mitochondrial function as indicated by increased ROS level, MMP collapse, increased mitochondrial swelling and cytochrome c release from mitochondria. Conversely, treadmill exercise significantly attenuated the impairments of spatial learning and memory and brain mitochondrial dysfunction induced by tramadol. The results revealed that chronic tramadol treatment caused memory impairments through induction of brain mitochondrial dysfunction. Furthermore, pre-exposure to physical exercise markedly mitigated these impairments through its positive effects on brain mitochondrial function. Copyright © 2017. Published by Elsevier Inc.

Gene expression based mouse brain parcellation using Markov random field regularized non-negative matrix factorization

NASA Astrophysics Data System (ADS)

Pathak, Sayan D.; Haynor, David R.; Thompson, Carol L.; Lein, Ed; Hawrylycz, Michael

2009-02-01

Understanding the geography of genetic expression in the mouse brain has opened previously unexplored avenues in neuroinformatics. The Allen Brain Atlas (www.brain-map.org) (ABA) provides genome-wide colorimetric in situ hybridization (ISH) gene expression images at high spatial resolution, all mapped to a common three-dimensional 200μm3 spatial framework defined by the Allen Reference Atlas (ARA) and is a unique data set for studying expression based structural and functional organization of the brain. The goal of this study was to facilitate an unbiased data-driven structural partitioning of the major structures in the mouse brain. We have developed an algorithm that uses nonnegative matrix factorization (NMF) to perform parts based analysis of ISH gene expression images. The standard NMF approach and its variants are limited in their ability to flexibly integrate prior knowledge, in the context of spatial data. In this paper, we introduce spatial connectivity as an additional regularization in NMF decomposition via the use of Markov Random Fields (mNMF). The mNMF algorithm alternates neighborhood updates with iterations of the standard NMF algorithm to exploit spatial correlations in the data. We present the algorithm and show the sub-divisions of hippocampus and somatosensory-cortex obtained via this approach. The results are compared with established neuroanatomic knowledge. We also highlight novel gene expression based sub divisions of the hippocampus identified by using the mNMF algorithm.

The Ontogeny and Brain Distribution Dynamics of the Appetite Regulators NPY, CART and pOX in Larval Atlantic Cod (Gadus morhua L.)

PubMed Central

Le, Hoang T. M. D.; Angotzi, Anna Rita; Ebbesson, Lars O. E.; Karlsen, Ørjan

2016-01-01

Similar to many marine teleost species, Atlantic cod undergo remarkable physiological changes during the early life stages with concurrent and profound changes in feeding biology and ecology. In contrast to the digestive system, very little is known about the ontogeny and the localization of the centers that control appetite and feed ingestion in the developing brain of fish. We examined the expression patterns of three appetite regulating factors (orexigenic: neuropeptide Y, NPY; prepro-orexin, pOX and anorexigenic: cocaine- and amphetamine-regulated transcript, CART) in discrete brain regions of developing Atlantic cod using chromogenic and double fluorescent in situ hybridization. Differential temporal and spatial expression patterns for each appetite regulator were found from first feeding (4 days post hatch; dph) to juvenile stage (76 dph). Neurons expressing NPY mRNA were detected in the telencephalon (highest expression), diencephalon, and optic tectum from 4 dph onward. CART mRNA expression had a wider distribution along the anterior-posterior brain axis, including both telencephalon and diencephalon from 4 dph. From 46 dph, CART transcripts were also detected in the olfactory bulb, region of the nucleus of medial longitudinal fascicle, optic tectum and midbrain tegmentum. At 4 and 20 dph, pOX mRNA expression was exclusively found in the preoptic region, but extended to the hypothalamus at 46 and 76 dph. Co-expression of both CART and pOX genes were also observed in several hypothalamic neurons throughout larval development. Our results show that both orexigenic and anorexigenic factors are present in the telencephalon, diencephalon and mesencephalon in cod larvae. The telencephalon mostly contains key factors of hunger control (NPY), while the diencephalon, and particularly the hypothalamus may have a more complex role in modulating the multifunctional control of appetite in this species. As the larvae develop, the overall progression in temporal and spatial complexity of NPY, CART and pOX mRNAs expression might be correlated to the maturation of appetite control regulation. These observations suggest that teleost larvae continue to develop the regulatory networks underlying appetite control after onset of exogenous feeding. PMID:27100086

The Ontogeny and Brain Distribution Dynamics of the Appetite Regulators NPY, CART and pOX in Larval Atlantic Cod (Gadus morhua L.).

PubMed

Le, Hoang T M D; Angotzi, Anna Rita; Ebbesson, Lars O E; Karlsen, Ørjan; Rønnestad, Ivar

2016-01-01

Similar to many marine teleost species, Atlantic cod undergo remarkable physiological changes during the early life stages with concurrent and profound changes in feeding biology and ecology. In contrast to the digestive system, very little is known about the ontogeny and the localization of the centers that control appetite and feed ingestion in the developing brain of fish. We examined the expression patterns of three appetite regulating factors (orexigenic: neuropeptide Y, NPY; prepro-orexin, pOX and anorexigenic: cocaine- and amphetamine-regulated transcript, CART) in discrete brain regions of developing Atlantic cod using chromogenic and double fluorescent in situ hybridization. Differential temporal and spatial expression patterns for each appetite regulator were found from first feeding (4 days post hatch; dph) to juvenile stage (76 dph). Neurons expressing NPY mRNA were detected in the telencephalon (highest expression), diencephalon, and optic tectum from 4 dph onward. CART mRNA expression had a wider distribution along the anterior-posterior brain axis, including both telencephalon and diencephalon from 4 dph. From 46 dph, CART transcripts were also detected in the olfactory bulb, region of the nucleus of medial longitudinal fascicle, optic tectum and midbrain tegmentum. At 4 and 20 dph, pOX mRNA expression was exclusively found in the preoptic region, but extended to the hypothalamus at 46 and 76 dph. Co-expression of both CART and pOX genes were also observed in several hypothalamic neurons throughout larval development. Our results show that both orexigenic and anorexigenic factors are present in the telencephalon, diencephalon and mesencephalon in cod larvae. The telencephalon mostly contains key factors of hunger control (NPY), while the diencephalon, and particularly the hypothalamus may have a more complex role in modulating the multifunctional control of appetite in this species. As the larvae develop, the overall progression in temporal and spatial complexity of NPY, CART and pOX mRNAs expression might be correlated to the maturation of appetite control regulation. These observations suggest that teleost larvae continue to develop the regulatory networks underlying appetite control after onset of exogenous feeding.

Triple-aspect monism: physiological, mental unconscious and conscious aspects of brain activity.

PubMed

Pereira, Alfredo

2014-06-01

Brain activity contains three fundamental aspects: (a) The physiological aspect, covering all kinds of processes that involve matter and/or energy; (b) the mental unconscious aspect, consisting of dynamical patterns (i.e., frequency, amplitude and phase-modulated waves) embodied in neural activity. These patterns are variously operated (transmitted, stored, combined, matched, amplified, erased, etc), forming cognitive and emotional unconscious processes and (c) the mental conscious aspect, consisting of feelings experienced in the first-person perspective and cognitive functions grounded in feelings, as memory formation, selection of the focus of attention, voluntary behavior, aesthetical appraisal and ethical judgment. Triple-aspect monism (TAM) is a philosophical theory that provides a model of the relation of the three aspects. Spatially distributed neuronal dendritic potentials generate amplitude-modulated waveforms transmitted to the extracellular medium and adjacent astrocytes, prompting the formation of large waves in the astrocyte network, which are claimed to both integrate distributed information and instantiate feelings. According to the valence of the feeling, the large wave feeds back on neuronal synapses, modulating (reinforcing or depressing) cognitive and behavioral functions.

Amyloid-β Plaques in Clinical Alzheimer’s Disease Brain Incorporate Stable Isotope Tracer In Vivo and Exhibit Nanoscale Heterogeneity

PubMed Central

Wildburger, Norelle C.; Gyngard, Frank; Guillermier, Christelle; Patterson, Bruce W.; Elbert, Donald; Mawuenyega, Kwasi G.; Schneider, Theresa; Green, Karen; Roth, Robyn; Schmidt, Robert E.; Cairns, Nigel J.; Benzinger, Tammie L. S.; Steinhauser, Matthew L.; Bateman, Randall J.

2018-01-01

Alzheimer’s disease (AD) is a neurodegenerative disorder with clinical manifestations of progressive memory decline and loss of executive function and language. AD affects an estimated 5.3 million Americans alone and is the most common form of age-related dementia with a rapidly growing prevalence among the aging population—those 65 years of age or older. AD is characterized by accumulation of aggregated amyloid-beta (Aβ) in the brain, which leads to one of the pathological hallmarks of AD—Aβ plaques. As a result, Aβ plaques have been extensively studied after being first described over a century ago. Advances in brain imaging and quantitative measures of Aβ in biological fluids have yielded insight into the time course of plaque development decades before and after AD symptom onset. However, despite the fundamental role of Aβ plaques in AD, in vivo measures of individual plaque growth, growth distribution, and dynamics are still lacking. To address this question, we combined stable isotope labeling kinetics (SILK) and nanoscale secondary ion mass spectrometry (NanoSIMS) imaging in an approach termed SILK–SIMS to resolve plaque dynamics in three human AD brains. In human AD brain, plaques exhibit incorporation of a stable isotope tracer. Tracer enrichment was highly variable between plaques and the spatial distribution asymmetric with both quiescent and active nanometer sub-regions of tracer incorporation. These data reveal that Aβ plaques are dynamic structures with deposition rates over days indicating a highly active process. Here, we report the first, direct quantitative measures of in vivo deposition into plaques in human AD brain. Our SILK–SIMS studies will provide invaluable information on plaque dynamics in the normal and diseased brain and offer many new avenues for investigation into pathological mechanisms of the disease, with implications for therapeutic development. PMID:29623063

Amyloid-β Plaques in Clinical Alzheimer's Disease Brain Incorporate Stable Isotope Tracer In Vivo and Exhibit Nanoscale Heterogeneity.

PubMed

Wildburger, Norelle C; Gyngard, Frank; Guillermier, Christelle; Patterson, Bruce W; Elbert, Donald; Mawuenyega, Kwasi G; Schneider, Theresa; Green, Karen; Roth, Robyn; Schmidt, Robert E; Cairns, Nigel J; Benzinger, Tammie L S; Steinhauser, Matthew L; Bateman, Randall J

2018-01-01

Alzheimer's disease (AD) is a neurodegenerative disorder with clinical manifestations of progressive memory decline and loss of executive function and language. AD affects an estimated 5.3 million Americans alone and is the most common form of age-related dementia with a rapidly growing prevalence among the aging population-those 65 years of age or older. AD is characterized by accumulation of aggregated amyloid-beta (Aβ) in the brain, which leads to one of the pathological hallmarks of AD-Aβ plaques. As a result, Aβ plaques have been extensively studied after being first described over a century ago. Advances in brain imaging and quantitative measures of Aβ in biological fluids have yielded insight into the time course of plaque development decades before and after AD symptom onset. However, despite the fundamental role of Aβ plaques in AD, in vivo measures of individual plaque growth, growth distribution, and dynamics are still lacking. To address this question, we combined stable isotope labeling kinetics (SILK) and nanoscale secondary ion mass spectrometry (NanoSIMS) imaging in an approach termed SILK-SIMS to resolve plaque dynamics in three human AD brains. In human AD brain, plaques exhibit incorporation of a stable isotope tracer. Tracer enrichment was highly variable between plaques and the spatial distribution asymmetric with both quiescent and active nanometer sub-regions of tracer incorporation. These data reveal that Aβ plaques are dynamic structures with deposition rates over days indicating a highly active process. Here, we report the first, direct quantitative measures of in vivo deposition into plaques in human AD brain. Our SILK-SIMS studies will provide invaluable information on plaque dynamics in the normal and diseased brain and offer many new avenues for investigation into pathological mechanisms of the disease, with implications for therapeutic development.

Dissecting hemisphere-specific contributions to visual spatial imagery using parametric brain mapping.

PubMed

Bien, Nina; Sack, Alexander T

2014-07-01

In the current study we aimed to empirically test previously proposed accounts of a division of labour between the left and right posterior parietal cortices during visuospatial mental imagery. The representation of mental images in the brain has been a topic of debate for several decades. Although the posterior parietal cortex is involved bilaterally, previous studies have postulated that hemispheric specialisation might result in a division of labour between the left and right parietal cortices. In the current fMRI study, we used an elaborated version of a behaviourally-controlled spatial imagery paradigm, the mental clock task, which involves mental image generation and a subsequent spatial comparison between two angles. By systematically varying the difference between the two angles that are mentally compared, we induced a symbolic distance effect: smaller differences between the two angles result in higher task difficulty. We employed parametrically weighed brain imaging to reveal brain areas showing a graded activation pattern in accordance with the induced distance effect. The parametric difficulty manipulation influenced behavioural data and brain activation patterns in a similar matter. Moreover, since this difficulty manipulation only starts to play a role from the angle comparison phase onwards, it allows for a top-down dissociation between the initial mental image formation, and the subsequent angle comparison phase of the spatial imagery task. Employing parametrically weighed fMRI analysis enabled us to top-down disentangle brain activation related to mental image formation, and activation reflecting spatial angle comparison. The results provide first empirical evidence for the repeatedly proposed division of labour between the left and right posterior parietal cortices during spatial imagery. Copyright © 2014 Elsevier Inc. All rights reserved.

An algorithm for localization of optical disturbances in turbid media using time-resolved diffuse optical tomography

NASA Astrophysics Data System (ADS)

Potlov, A. Yu.; Frolov, S. V.; Proskurin, S. G.

2018-04-01

Optical structure disturbances localization algorithm for time-resolved diffuse optical tomography of biological objects is described. The key features of the presented algorithm are: the initial approximation for the spatial distribution of the optical characteristics based on the Homogeneity Index and the assumption that all the absorbing and scattering inhomogeneities in an investigated object are spherical and have the same absorption and scattering coefficients. The described algorithm can be used in the brain structures diagnosis, in traumatology and optical mammography.

Compensatory Motor Network Connectivity is Associated with Motor Sequence Learning after Subcortical Stroke

PubMed Central

Wadden, Katie P.; Woodward, Todd S.; Metzak, Paul D.; Lavigne, Katie M.; Lakhani, Bimal; Auriat, Angela M.; Boyd, Lara A.

2015-01-01

Following stroke, functional networks reorganize and the brain demonstrates widespread alterations in cortical activity. Implicit motor learning is preserved after stroke. However the manner in which brain reorganization occurs, and how it supports behaviour within the damaged brain remains unclear. In this functional magnetic resonance imaging (fMRI) study, we evaluated whole brain patterns of functional connectivity during the performance of an implicit tracking task at baseline and retention, following 5 days of practice. Following motor practice, a significant difference in connectivity within a motor network, consisting of bihemispheric activation of the sensory and motor cortices, parietal lobules, cerebellar and occipital lobules, was observed at retention. Healthy subjects demonstrated greater activity within this motor network during sequence learning compared to random practice. The stroke group did not show the same level of functional network integration, presumably due to the heterogeneity of functional reorganization following stroke. In a secondary analysis, a binary mask of the functional network activated from the aforementioned whole brain analyses was created to assess within-network connectivity, decreasing the spatial distribution and large variability of activation that exists within the lesioned brain. The stroke group demonstrated reduced clusters of connectivity within the masked brain regions as compared to the whole brain approach. Connectivity within this smaller motor network correlated with repeated sequence performance on the retention test. Increased functional integration within the motor network may be an important neurophysiological predictor of motor learning-related change in individuals with stroke. PMID:25757996

Influence of Wiring Cost on the Large-Scale Architecture of Human Cortical Connectivity

PubMed Central

Samu, David; Seth, Anil K.; Nowotny, Thomas

2014-01-01

In the past two decades some fundamental properties of cortical connectivity have been discovered: small-world structure, pronounced hierarchical and modular organisation, and strong core and rich-club structures. A common assumption when interpreting results of this kind is that the observed structural properties are present to enable the brain's function. However, the brain is also embedded into the limited space of the skull and its wiring has associated developmental and metabolic costs. These basic physical and economic aspects place separate, often conflicting, constraints on the brain's connectivity, which must be characterized in order to understand the true relationship between brain structure and function. To address this challenge, here we ask which, and to what extent, aspects of the structural organisation of the brain are conserved if we preserve specific spatial and topological properties of the brain but otherwise randomise its connectivity. We perform a comparative analysis of a connectivity map of the cortical connectome both on high- and low-resolutions utilising three different types of surrogate networks: spatially unconstrained (‘random’), connection length preserving (‘spatial’), and connection length optimised (‘reduced’) surrogates. We find that unconstrained randomisation markedly diminishes all investigated architectural properties of cortical connectivity. By contrast, spatial and reduced surrogates largely preserve most properties and, interestingly, often more so in the reduced surrogates. Specifically, our results suggest that the cortical network is less tightly integrated than its spatial constraints would allow, but more strongly segregated than its spatial constraints would necessitate. We additionally find that hierarchical organisation and rich-club structure of the cortical connectivity are largely preserved in spatial and reduced surrogates and hence may be partially attributable to cortical wiring constraints. In contrast, the high modularity and strong s-core of the high-resolution cortical network are significantly stronger than in the surrogates, underlining their potential functional relevance in the brain. PMID:24699277

The development and modeling of devices and paradigms for transcranial magnetic stimulation

PubMed Central

Goetz, Stefan M.; Deng, Zhi-De

2017-01-01

Magnetic stimulation is a noninvasive neurostimulation technique that can evoke action potentials and modulate neural circuits through induced electric fields. Biophysical models of magnetic stimulation have become a major driver for technological developments and the understanding of the mechanisms of magnetic neurostimulation and neuromodulation. Major technological developments involve stimulation coils with different spatial characteristics and pulse sources to control the pulse waveform. While early technological developments were the result of manual design and invention processes, there is a trend in both stimulation coil and pulse source design to mathematically optimize parameters with the help of computational models. To date, macroscopically highly realistic spatial models of the brain as well as peripheral targets, and user-friendly software packages enable researchers and practitioners to simulate the treatment-specific and induced electric field distribution in the brains of individual subjects and patients. Neuron models further introduce the microscopic level of neural activation to understand the influence of activation dynamics in response to different pulse shapes. A number of models that were designed for online calibration to extract otherwise covert information and biomarkers from the neural system recently form a third branch of modeling. PMID:28443696

Horizontal visual search in a large field by patients with unilateral spatial neglect.

PubMed

Nakatani, Ken; Notoya, Masako; Sunahara, Nobuyuki; Takahashi, Shusuke; Inoue, Katsumi

2013-06-01

In this study, we investigated the horizontal visual search ability and pattern of horizontal visual search in a large space performed by patients with unilateral spatial neglect (USN). Subjects included nine patients with right hemisphere damage caused by cerebrovascular disease showing left USN, nine patients with right hemisphere damage but no USN, and six healthy individuals with no history of brain damage who were age-matched to the groups with brain right hemisphere damage. The number of visual search tasks accomplished was recorded in the first experiment. Neck rotation angle was continuously measured during the task and quantitative data of the measurements were collected. There was a strong correlation between the number of visual search tasks accomplished and the total Behavioral Inattention Test Conventional Subtest (BITC) score in subjects with right hemisphere damage. In both USN and control groups, the head position during the visual search task showed a balanced bell-shaped distribution from the central point on the field to the left and right sides. Our results indicate that compensatory strategies, including cervical rotation, may improve visual search capability and achieve balance on the neglected side. Copyright © 2012 Elsevier Ltd. All rights reserved.

The development and modelling of devices and paradigms for transcranial magnetic stimulation.

PubMed

Goetz, Stefan M; Deng, Zhi-De

2017-04-01

Magnetic stimulation is a non-invasive neurostimulation technique that can evoke action potentials and modulate neural circuits through induced electric fields. Biophysical models of magnetic stimulation have become a major driver for technological developments and the understanding of the mechanisms of magnetic neurostimulation and neuromodulation. Major technological developments involve stimulation coils with different spatial characteristics and pulse sources to control the pulse waveform. While early technological developments were the result of manual design and invention processes, there is a trend in both stimulation coil and pulse source design to mathematically optimize parameters with the help of computational models. To date, macroscopically highly realistic spatial models of the brain, as well as peripheral targets, and user-friendly software packages enable researchers and practitioners to simulate the treatment-specific and induced electric field distribution in the brains of individual subjects and patients. Neuron models further introduce the microscopic level of neural activation to understand the influence of activation dynamics in response to different pulse shapes. A number of models that were designed for online calibration to extract otherwise covert information and biomarkers from the neural system recently form a third branch of modelling.

Electrocortical amplification for emotionally arousing natural scenes: The contribution of luminance and chromatic visual channels

PubMed Central

Miskovic, Vladimir; Martinovic, Jasna; Wieser, Matthias M.; Petro, Nathan M.; Bradley, Margaret M.; Keil, Andreas

2015-01-01

Emotionally arousing scenes readily capture visual attention, prompting amplified neural activity in sensory regions of the brain. The physical stimulus features and related information channels in the human visual system that contribute to this modulation, however, are not known. Here, we manipulated low-level physical parameters of complex scenes varying in hedonic valence and emotional arousal in order to target the relative contributions of luminance based versus chromatic visual channels to emotional perception. Stimulus-evoked brain electrical activity was measured during picture viewing and used to quantify neural responses sensitive to lower-tier visual cortical involvement (steady-state visual evoked potentials) as well as the late positive potential, reflecting a more distributed cortical event. Results showed that the enhancement for emotional content was stimulus-selective when examining the steady-state segments of the evoked visual potentials. Response amplification was present only for low spatial frequency, grayscale stimuli, and not for high spatial frequency, red/green stimuli. In contrast, the late positive potential was modulated by emotion regardless of the scene’s physical properties. Our findings are discussed in relation to neurophysiologically plausible constraints operating at distinct stages of the cortical processing stream. PMID:25640949

Electrocortical amplification for emotionally arousing natural scenes: the contribution of luminance and chromatic visual channels.

PubMed

Miskovic, Vladimir; Martinovic, Jasna; Wieser, Matthias J; Petro, Nathan M; Bradley, Margaret M; Keil, Andreas

2015-03-01

Emotionally arousing scenes readily capture visual attention, prompting amplified neural activity in sensory regions of the brain. The physical stimulus features and related information channels in the human visual system that contribute to this modulation, however, are not known. Here, we manipulated low-level physical parameters of complex scenes varying in hedonic valence and emotional arousal in order to target the relative contributions of luminance based versus chromatic visual channels to emotional perception. Stimulus-evoked brain electrical activity was measured during picture viewing and used to quantify neural responses sensitive to lower-tier visual cortical involvement (steady-state visual evoked potentials) as well as the late positive potential, reflecting a more distributed cortical event. Results showed that the enhancement for emotional content was stimulus-selective when examining the steady-state segments of the evoked visual potentials. Response amplification was present only for low spatial frequency, grayscale stimuli, and not for high spatial frequency, red/green stimuli. In contrast, the late positive potential was modulated by emotion regardless of the scene's physical properties. Our findings are discussed in relation to neurophysiologically plausible constraints operating at distinct stages of the cortical processing stream. Copyright © 2015 Elsevier B.V. All rights reserved.

Topology of genetic associations between regional gray matter volume and intellectual ability: Evidence for a high capacity network.

PubMed

Bohlken, Marc M; Brouwer, Rachel M; Mandl, René C W; Hedman, Anna M; van den Heuvel, Martijn P; van Haren, Neeltje E M; Kahn, René S; Hulshoff Pol, Hilleke E

2016-01-01

Intelligence is associated with a network of distributed gray matter areas including the frontal and parietal higher association cortices and primary processing areas of the temporal and occipital lobes. Efficient information transfer between gray matter regions implicated in intelligence is thought to be critical for this trait to emerge. Genetic factors implicated in intelligence and gray matter may promote a high capacity for information transfer. Whether these genetic factors act globally or on local gray matter areas separately is not known. Brain maps of phenotypic and genetic associations between gray matter volume and intelligence were made using structural equation modeling of 3T MRI T1-weighted scans acquired in 167 adult twins of the newly acquired U-TWIN cohort. Subsequently, structural connectivity analyses (DTI) were performed to test the hypothesis that gray matter regions associated with intellectual ability form a densely connected core. Gray matter regions associated with intellectual ability were situated in the right prefrontal, bilateral temporal, bilateral parietal, right occipital and subcortical regions. Regions implicated in intelligence had high structural connectivity density compared to 10,000 reference networks (p=0.031). The genetic association with intelligence was for 39% explained by a genetic source unique to these regions (independent of total brain volume), this source specifically implicated the right supramarginal gyrus. Using a twin design, we show that intelligence is genetically represented in a spatially distributed and densely connected network of gray matter regions providing a high capacity infrastructure. Although genes for intelligence have overlap with those for total brain volume, we present evidence that there are genes for intelligence that act specifically on the subset of brain areas that form an efficient brain network. Copyright © 2015 Elsevier Inc. All rights reserved.

A finite element analysis of the effect of electrode area and inter-electrode distance on the spatial distribution of the current density in tDCS

NASA Astrophysics Data System (ADS)

Faria, Paula; Hallett, Mark; Cavaleiro Miranda, Pedro

2011-12-01

We investigated the effect of electrode area and inter-electrode distance on the spatial distribution of the current density in transcranial direct current stimulation (tDCS). For this purpose, we used the finite element method to compute the distribution of the current density in a four-layered spherical head model using various electrode montages, corresponding to a range of electrode sizes and inter-electrode distances. We found that smaller electrodes required slightly less current to achieve a constant value of the current density at a reference point on the brain surface located directly under the electrode center. Under these conditions, smaller electrodes also produced a more focal current density distribution in the brain, i.e. the magnitude of the current density fell more rapidly with distance from the reference point. The combination of two electrodes with different areas produced an asymmetric current distribution that could lead to more effective and localized neural modulation under the smaller electrode than under the larger one. Focality improved rapidly with decreasing electrode size when the larger electrode sizes were considered but the improvement was less marked for the smaller electrode sizes. Also, focality was not affected significantly by inter-electrode distance unless two large electrodes were placed close together. Increasing the inter-electrode distance resulted in decreased shunting of the current through the scalp and the cerebrospinal fluid, and decreasing electrode area resulted in increased current density on the scalp under the edges of the electrode. Our calculations suggest that when working with conventional electrodes (25-35 cm2), one of the electrodes should be placed just 'behind' the target relative to the other electrode, for maximum current density on the target. Also electrodes with areas in the range 3.5-12 cm2 may provide a better compromise between focality and current density in the scalp than the traditional electrodes. Finally, the use of multiple small return electrodes may be more efficient than the use of a single large return electrode.

EXIMS: an improved data analysis pipeline based on a new peak picking method for EXploring Imaging Mass Spectrometry data.

PubMed

Wijetunge, Chalini D; Saeed, Isaam; Boughton, Berin A; Spraggins, Jeffrey M; Caprioli, Richard M; Bacic, Antony; Roessner, Ute; Halgamuge, Saman K

2015-10-01

Matrix Assisted Laser Desorption Ionization-Imaging Mass Spectrometry (MALDI-IMS) in 'omics' data acquisition generates detailed information about the spatial distribution of molecules in a given biological sample. Various data processing methods have been developed for exploring the resultant high volume data. However, most of these methods process data in the spectral domain and do not make the most of the important spatial information available through this technology. Therefore, we propose a novel streamlined data analysis pipeline specifically developed for MALDI-IMS data utilizing significant spatial information for identifying hidden significant molecular distribution patterns in these complex datasets. The proposed unsupervised algorithm uses Sliding Window Normalization (SWN) and a new spatial distribution based peak picking method developed based on Gray level Co-Occurrence (GCO) matrices followed by clustering of biomolecules. We also use gist descriptors and an improved version of GCO matrices to extract features from molecular images and minimum medoid distance to automatically estimate the number of possible groups. We evaluated our algorithm using a new MALDI-IMS metabolomics dataset of a plant (Eucalypt) leaf. The algorithm revealed hidden significant molecular distribution patterns in the dataset, which the current Component Analysis and Segmentation Map based approaches failed to extract. We further demonstrate the performance of our peak picking method over other traditional approaches by using a publicly available MALDI-IMS proteomics dataset of a rat brain. Although SWN did not show any significant improvement as compared with using no normalization, the visual assessment showed an improvement as compared to using the median normalization. The source code and sample data are freely available at http://exims.sourceforge.net/. awgcdw@student.unimelb.edu.au or chalini_w@live.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Label-free, multi-scale imaging of ex-vivo mouse brain using spatial light interference microscopy

NASA Astrophysics Data System (ADS)

Min, Eunjung; Kandel, Mikhail E.; Ko, Chemyong J.; Popescu, Gabriel; Jung, Woonggyu; Best-Popescu, Catherine

2016-12-01

Brain connectivity spans over broad spatial scales, from nanometers to centimeters. In order to understand the brain at multi-scale, the neural network in wide-field has been visualized in detail by taking advantage of light microscopy. However, the process of staining or addition of fluorescent tags is commonly required, and the image contrast is insufficient for delineation of cytoarchitecture. To overcome this barrier, we use spatial light interference microscopy to investigate brain structure with high-resolution, sub-nanometer pathlength sensitivity without the use of exogenous contrast agents. Combining wide-field imaging and a mosaic algorithm developed in-house, we show the detailed architecture of cells and myelin, within coronal olfactory bulb and cortical sections, and from sagittal sections of the hippocampus and cerebellum. Our technique is well suited to identify laminar characteristics of fiber tract orientation within white matter, e.g. the corpus callosum. To further improve the macro-scale contrast of anatomical structures, and to better differentiate axons and dendrites from cell bodies, we mapped the tissue in terms of its scattering property. Based on our results, we anticipate that spatial light interference microscopy can potentially provide multiscale and multicontrast perspectives of gross and microscopic brain anatomy.

The Brain and Learning: Examining the Connection between Brain Activity, Spatial Intelligence, and Learning Outcomes in Online Visual Instruction

ERIC Educational Resources Information Center

Lee, Hyangsook

2013-01-01

The purpose of the study was to compare 2D and 3D visual presentation styles, both still frame and animation, on subjects' brain activity measured by the amplitude of EEG alpha wave and on their recall to see if alpha power and recall differ significantly by depth and movement of visual presentation style and by spatial intelligence. In addition,…

Spatial Brain Control Interface using Optical and Electrophysiological Measures

DTIC Science & Technology

2013-08-27

appropriate for implementing a reliable brain-computer interface ( BCI ). The LSVM method 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 27-08-2013 13...Machine (LSVM) was the most appropriate for implementing a reliable brain-computer interface ( BCI ). The LSVM method was applied to the imaging data...local field potentials proved to be fast and strongly tuned for the spatial parameters of the task. Thus, a reliable BCI that can predict upcoming

The downfall of TBA-354 - a possible explanation for its neurotoxicity via mass spectrometric imaging.

PubMed

Ntshangase, Sphamandla; Shobo, Adeola; Kruger, Hendrik G; Asperger, Arndt; Niemeyer, Dagmar; Arvidsson, Per I; Govender, Thavendran; Baijnath, Sooraj

2017-10-13

1. TBA-354 was a promising antitubercular compound with activity against both replicating and static Mycobacterium tuberculosis (M.tb), making it the focal point of many clinical trials conducted by the TB Alliance. However, findings from these trials have shown that TBA-354 results in mild signs of reversible neurotoxicity; this left the TB Alliance with no other choice but to stop the research. 2. In this study, mass spectrometric methods were used to evaluate the pharmacokinetics and spatial distribution of TBA-354 in the brain using a validated liquid chromatography tandem-mass spectrometry (LCMS/MS) and mass spectrometric imaging (MSI), respectively. Healthy female Sprague-Dawley rats received intraperitoneal (i.p.) doses of TBA-354 (20 mg/kg bw). 3. The concentrationtime profiles showed a gradual absorption and tissue penetration of TBA-354 reaching the C max at 6 h post dose, followed by a rapid elimination. MSI analysis showed a time-dependent drug distribution, with highest drug concentration mainly in the neocortical regions of the brain. 4. The distribution of TBA-354 provides a possible explanation for the motor dysfunction observed in clinical trials. These results prove the importance of MSI as a potential tool in preclinical evaluations of suspected neurotoxic compounds.

Measurement of Local Partial Pressure of Oxygen in the Brain Tissue under Normoxia and Epilepsy with Phosphorescence Lifetime Microscopy

PubMed Central

Zhang, Cong; Bélanger, Samuel; Pouliot, Philippe; Lesage, Frédéric

2015-01-01

In this work a method for measuring brain oxygen partial pressure with confocal phosphorescence lifetime microscopy system is reported. When used in conjunction with a dendritic phosphorescent probe, Oxyphor G4, this system enabled minimally invasive measurements of oxygen partial pressure (pO2) in cerebral tissue with high spatial and temporal resolution during 4-AP induced epileptic seizures. Investigating epileptic events, we characterized the spatio-temporal distribution of the "initial dip" in pO2 near the probe injection site and along nearby arterioles. Our results reveal a correlation between the percent change in the pO2 signal during the "initial dip" and the duration of seizure-like activity, which can help localize the epileptic focus and predict the length of seizure. PMID:26305777

Prediction of brain maturity based on cortical thickness at different spatial resolutions.

PubMed

Khundrakpam, Budhachandra S; Tohka, Jussi; Evans, Alan C

2015-05-01

Several studies using magnetic resonance imaging (MRI) scans have shown developmental trajectories of cortical thickness. Cognitive milestones happen concurrently with these structural changes, and a delay in such changes has been implicated in developmental disorders such as attention-deficit/hyperactivity disorder (ADHD). Accurate estimation of individuals' brain maturity, therefore, is critical in establishing a baseline for normal brain development against which neurodevelopmental disorders can be assessed. In this study, cortical thickness derived from structural magnetic resonance imaging (MRI) scans of a large longitudinal dataset of normally growing children and adolescents (n=308), were used to build a highly accurate predictive model for estimating chronological age (cross-validated correlation up to R=0.84). Unlike previous studies which used kernelized approach in building prediction models, we used an elastic net penalized linear regression model capable of producing a spatially sparse, yet accurate predictive model of chronological age. Upon investigating different scales of cortical parcellation from 78 to 10,240 brain parcels, we observed that the accuracy in estimated age improved with increased spatial scale of brain parcellation, with the best estimations obtained for spatial resolutions consisting of 2560 and 10,240 brain parcels. The top predictors of brain maturity were found in highly localized sensorimotor and association areas. The results of our study demonstrate that cortical thickness can be used to estimate individuals' brain maturity with high accuracy, and the estimated ages relate to functional and behavioural measures, underscoring the relevance and scope of the study in the understanding of biological maturity. Copyright © 2015 Elsevier Inc. All rights reserved.

CARS microscopy of Alzheimer's diseased brain tissue

NASA Astrophysics Data System (ADS)

Enejder, Annika; Kiskis, Juris; Fink, Helen; Nyberg, Lena; Thyr, Jakob; Li, Jia-Yi

2014-02-01

Alzheimer's disease (AD) is a progressive neurodegenerative disorder currently without cure, characterized by the presence of extracellular plaques surrounded by dystrophic neurites. In an effort to understand the underlying mechanisms, biochemical analysis (protein immunoblot) of plaque extracts reveals that they consist of amyloid-beta (Aβ) peptides assembled as oligomers, protofibrils and aggregates. Their spatial distribution has been confirmed by Thioflavin-S or immuno-staining with fluorescence microscopy. However, it is increasingly understood that the protein aggregation is only one of several mechanism that causes neuronal dysfunction and death. This raises the need for a more complete biochemical analysis. In this study, we have complemented 2-photon fluorescence microscopy of Thioflavin-S and Aβ immuno-stained human AD plaques with CARS microscopy. We show that the chemical build-up of AD plaques is more complex and that Aβ staining does not provide the complete picture of the spatial distribution or the molecular composition of AD plaques. CARS images provide important complementary information to that obtained by fluorescence microscopy, motivating a broader introduction of CARS microscopy in the AD research field.

Spatial mapping of dynamic cerebral autoregulation by multichannel near-infrared spectroscopy in high-grade carotid artery disease

NASA Astrophysics Data System (ADS)

Reinhard, Matthias; Schumacher, F. Konrad; Rutsch, Sebastian; Oeinck, Maximilian; Timmer, Jens; Mader, Irina; Schelter, Björn; Weiller, Cornelius; Kaller, Christoph P.

2014-09-01

The exact spatial distribution of impaired cerebral autoregulation in carotid artery disease is unknown. In this pilot study, we present a new approach of multichannel near-infrared spectroscopy (mcNIRS) for noninvasive spatial mapping of dynamic autoregulation in carotid artery disease. In 15 patients with unilateral severe carotid artery stenosis or occlusion, cortical hemodynamics in the bilateral frontal cortex were assessed from changes in oxyhemoglobin concentration using 52-channel NIRS (spatial resolution ˜2 cm). Dynamic autoregulation was graded by the phase shift between respiratory-induced 0.1 Hz oscillations of blood pressure and oxyhemoglobin. Ten of 15 patients showed regular phase values in the expected (patho) physiological range. Five patients had clearly outlying irregular phase values mostly due to artifacts. In patients with a regular phase pattern, a significant side-to-side difference of dynamic autoregulation was observed for the cortical border zone area between the middle and anterior cerebral artery (p<0.05). In conclusion, dynamic cerebral autoregulation can be spatially assessed from slow hemodynamic oscillations with mcNIRS. In high-grade carotid artery disease, cortical dynamic autoregulation is affected mostly in the vascular border zone. Spatial mapping of dynamic autoregulation may serve as a powerful tool for identifying brain regions at specific risks for hemodynamic infarction.

The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience

PubMed Central

Burns, Randal; Roncal, William Gray; Kleissas, Dean; Lillaney, Kunal; Manavalan, Priya; Perlman, Eric; Berger, Daniel R.; Bock, Davi D.; Chung, Kwanghun; Grosenick, Logan; Kasthuri, Narayanan; Weiler, Nicholas C.; Deisseroth, Karl; Kazhdan, Michael; Lichtman, Jeff; Reid, R. Clay; Smith, Stephen J.; Szalay, Alexander S.; Vogelstein, Joshua T.; Vogelstein, R. Jacob

2013-01-01

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes— neural connectivity maps of the brain—using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems—reads to parallel disk arrays and writes to solid-state storage—to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization. PMID:24401992

Application of spatially modulated near-infrared structured light to study changes in optical properties of mouse brain tissue during heatstress.

PubMed

Shaul, Oren; Fanrazi-Kahana, Michal; Meitav, Omri; Pinhasi, Gad A; Abookasis, David

2017-11-10

Heat stress (HS) is a medical emergency defined by abnormally elevated body temperature that causes biochemical, physiological, and hematological changes. The goal of the present research was to detect variations in optical properties (absorption, reduced scattering, and refractive index coefficients) of mouse brain tissue during HS by using near-infrared (NIR) spatial light modulation. NIR spatial patterns with different spatial phases were used to differentiate the effects of tissue scattering from those of absorption. Decoupling optical scattering from absorption enabled the quantification of a tissue's chemical constituents (related to light absorption) and structural properties (related to light scattering). Technically, structured light patterns at low and high spatial frequencies of six wavelengths ranging between 690 and 970 nm were projected onto the mouse scalp surface while diffuse reflected light was recorded by a CCD camera positioned perpendicular to the mouse scalp. Concurrently to pattern projection, brain temperature was measured with a thermal camera positioned slightly off angle from the mouse head while core body temperature was monitored by thermocouple probe. Data analysis demonstrated variations from baseline measurements in a battery of intrinsic brain properties following HS.

Choline distribution and metabolism in pregnant rats and fetuses are influenced by the choline content of the maternal diet.

PubMed

Garner, S C; Mar, M H; Zeisel, S H

1995-11-01

Choline supplementation of pregnant rats between d 12 and 17 of pregnancy permanently enhances the spatial memory of offspring; however, the mechanism is unknown. We examined the effect of choline supplementation on metabolism of orally ingested choline by nonmated rats and pregnant rats and their fetuses. We studied the metabolism of an acute oral dose of 14C-choline chloride in pregnant and nonmated rats with and without choline supplementation (25 mmol/L choline chloride in water) on d 12-17 of pregnancy. During the first 2 h after oral dosing, plasma radiolabeled choline was detectable, whereas plasma choline metabolites contributed little to total radioactivity at any time. The pattern of accumulation of label in placentas was similar in all groups. Fetal tissues (i.e., brain, liver and carcass remnant) contained primarily 14C-phosphatidylcholine and 14C-phosphorylcholine. Also, we examined the fetal tissue distribution of isotopically labeled (deuterated) choline derived from the diet and from the dietary choline supplement. The distribution patterns for radiolabeled choline metabolites in fetuses of supplemented dams accumulated significantly (P < 0.01) more of their total choline and its metabolites than fetuses of control dams during d 12-17 of gestation (50 vs. 20%). In fetuses from supplemented dams, betaine concentrations were greater than in fetuses from control dams in all organs assayed (by 36-57%). Phosphorylcholine concentrations in brain of fetuses from supplemented dams were also greater. These experiments identify potential metabolites of choline that might mediate the observed effects on brain development in the rats.

Functional Geometry Alignment and Localization of Brain Areas.

PubMed

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.

Extracting alpha band modulation during visual spatial attention without flickering stimuli using common spatial pattern.

PubMed

Fujisawa, Junya; Touyama, Hideaki; Hirose, Michitaka

2008-01-01

In this paper, alpha band modulation during visual spatial attention without visual stimuli was focused. Visual spatial attention has been expected to provide a new channel of non-invasive independent brain computer interface (BCI), but little work has been done on the new interfacing method. The flickering stimuli used in previous work cause a decline of independency and have difficulties in a practical use. Therefore we investigated whether visual spatial attention could be detected without such stimuli. Further, the common spatial patterns (CSP) were for the first time applied to the brain states during visual spatial attention. The performance evaluation was based on three brain states of left, right and center direction attention. The 30-channel scalp electroencephalographic (EEG) signals over occipital cortex were recorded for five subjects. Without CSP, the analyses made 66.44 (range 55.42 to 72.27) % of average classification performance in discriminating left and right attention classes. With CSP, the averaged classification accuracy was 75.39 (range 63.75 to 86.13) %. It is suggested that CSP is useful in the context of visual spatial attention, and the alpha band modulation during visual spatial attention without flickering stimuli has the possibility of a new channel for independent BCI as well as motor imagery.

Radiofrequency field inhomogeneity compensation in high spatial resolution magnetic resonance spectroscopic imaging

NASA Astrophysics Data System (ADS)

Passeri, Alessandro; Mazzuca, Stefano; Del Bene, Veronica

2014-06-01

Clinical magnetic resonance spectroscopy imaging (MRSI) is a non-invasive functional technique, whose mathematical framework falls into the category of linear inverse problems. However, its use in medical diagnostics is hampered by two main problems, both linked to the Fourier-based technique usually implemented for spectra reconstruction: poor spatial resolution and severe blurring in the spatial localization of the reconstructed spectra. Moreover, the intrinsic ill-posedness of the MRSI problem might be worsened by (i) spatially dependent distortions of the static magnetic field (B0) distribution, as well as by (ii) inhomogeneity in the power deposition distribution of the radiofrequency magnetic field (B1). Among several alternative methods, slim (Spectral Localization by IMaging) and bslim (B0 compensated slim) are reconstruction algorithms in which a priori information concerning the spectroscopic target is introduced into the reconstruction kernel. Nonetheless, the influence of the B1 field, particularly when its operating wavelength is close to the size of the human organs being studied, continues to be disregarded. starslim (STAtic and Radiofrequency-compensated slim), an evolution of the slim and bslim methods, is therefore proposed, in which the transformation kernel also includes the B1 field inhomogeneity map, thus allowing almost complete 3D modelling of the MRSI problem. Moreover, an original method for the experimental determination of the B1 field inhomogeneity map specific to the target under evaluation is also included. The compensation capabilities of the proposed method have been tested and illustrated using synthetic raw data reproducing the human brain.

Effect of bulk modulus on deformation of the brain under rotational accelerations

NASA Astrophysics Data System (ADS)

Ganpule, S.; Daphalapurkar, N. P.; Cetingul, M. P.; Ramesh, K. T.

2018-01-01

Traumatic brain injury such as that developed as a consequence of blast is a complex injury with a broad range of symptoms and disabilities. Computational models of brain biomechanics hold promise for illuminating the mechanics of traumatic brain injury and for developing preventive devices. However, reliable material parameters are needed for models to be predictive. Unfortunately, the properties of human brain tissue are difficult to measure, and the bulk modulus of brain tissue in particular is not well characterized. Thus, a wide range of bulk modulus values are used in computational models of brain biomechanics, spanning up to three orders of magnitude in the differences between values. However, the sensitivity of these variations on computational predictions is not known. In this work, we study the sensitivity of a 3D computational human head model to various bulk modulus values. A subject-specific human head model was constructed from T1-weighted MRI images at 2-mm3 voxel resolution. Diffusion tensor imaging provided data on spatial distribution and orientation of axonal fiber bundles for modeling white matter anisotropy. Non-injurious, full-field brain deformations in a human volunteer were used to assess the simulated predictions. The comparison suggests that a bulk modulus value on the order of GPa gives the best agreement with experimentally measured in vivo deformations in the human brain. Further, simulations of injurious loading suggest that bulk modulus values on the order of GPa provide the closest match with the clinical findings in terms of predicated injured regions and extent of injury.

Repair of astrocytes, blood vessels, and myelin in the injured brain: possible roles of blood monocytes

PubMed Central

2013-01-01

Inflammation in injured tissue has both repair functions and cytotoxic consequences. However, the issue of whether brain inflammation has a repair function has received little attention. Previously, we demonstrated monocyte infiltration and death of neurons and resident microglia in LPS-injected brains (Glia. 2007. 55:1577; Glia. 2008. 56:1039). Here, we found that astrocytes, oligodendrocytes, myelin, and endothelial cells disappeared in the damage core within 1–3 d and then re-appeared at 7–14 d, providing evidence of repair of the brain microenvironment. Since round Iba-1+/CD45+ monocytes infiltrated before the repair, we examined whether these cells were involved in the repair process. Analysis of mRNA expression profiles showed significant upregulation of repair/resolution-related genes, whereas proinflammatory-related genes were barely detectable at 3 d, a time when monocytes filled injury sites. Moreover, Iba-1+/CD45+ cells highly expressed phagocytic activity markers (e.g., the mannose receptors, CD68 and LAMP2), but not proinflammatory mediators (e.g., iNOS and IL1β). In addition, the distribution of round Iba-1+/CD45+ cells was spatially and temporally correlated with astrocyte recovery. We further found that monocytes in culture attracted astrocytes by releasing soluble factor(s). Together, these results suggest that brain inflammation mediated by monocytes functions to repair the microenvironment of the injured brain. PMID:23758980

A time-course analysis of changes in cerebral metal levels following a controlled cortical impact.

PubMed

Portbury, Stuart D; Hare, Dominic J; Sgambelloni, Charlotte; Finkelstein, David I; Adlard, Paul A

2016-02-01

Traumatic brain injury (TBI) is complicated by a sudden and dramatic change in brain metal levels, including iron (Fe), copper (Cu) and zinc (Zn). Specific 'metallo-pathological' features of TBI include increased non-heme bound Fe and the liberation of free Zn ions, both of which may contribute to the pathogenesis of TBI. To further characterise the metal dyshomeostasis that occurs following brain trauma, we performed a quantitative time-course survey of spatial Fe, Cu and Zn distribution in mice receiving a controlled cortical impact TBI. Images of brain metal levels produced using laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) in the upper quadrant of the ipsilateral hemisphere were compared to the corresponding contralateral hemisphere, together with regional areas radiating toward the center of the brain from the site of lesion. Significant regional and time point specific elevations in Fe, Zn and Cu were detected immediately and up to 28 days after TBI. The magnitude and timeframe of many of these changes suggest that TBI results in a pronounced and sustained alteration in normal metal levels within the brain. Such alterations are likely to play a role in both the short- and long-term consequences of head trauma and suggest that pharmacological modulation to normalize these metal levels may be efficacious in improving functional outcome.

Binocular fusion and invariant category learning due to predictive remapping during scanning of a depthful scene with eye movements

PubMed Central

Grossberg, Stephen; Srinivasan, Karthik; Yazdanbakhsh, Arash

2015-01-01

How does the brain maintain stable fusion of 3D scenes when the eyes move? Every eye movement causes each retinal position to process a different set of scenic features, and thus the brain needs to binocularly fuse new combinations of features at each position after an eye movement. Despite these breaks in retinotopic fusion due to each movement, previously fused representations of a scene in depth often appear stable. The 3D ARTSCAN neural model proposes how the brain does this by unifying concepts about how multiple cortical areas in the What and Where cortical streams interact to coordinate processes of 3D boundary and surface perception, spatial attention, invariant object category learning, predictive remapping, eye movement control, and learned coordinate transformations. The model explains data from single neuron and psychophysical studies of covert visual attention shifts prior to eye movements. The model further clarifies how perceptual, attentional, and cognitive interactions among multiple brain regions (LGN, V1, V2, V3A, V4, MT, MST, PPC, LIP, ITp, ITa, SC) may accomplish predictive remapping as part of the process whereby view-invariant object categories are learned. These results build upon earlier neural models of 3D vision and figure-ground separation and the learning of invariant object categories as the eyes freely scan a scene. A key process concerns how an object's surface representation generates a form-fitting distribution of spatial attention, or attentional shroud, in parietal cortex that helps maintain the stability of multiple perceptual and cognitive processes. Predictive eye movement signals maintain the stability of the shroud, as well as of binocularly fused perceptual boundaries and surface representations. PMID:25642198

A novel three-dimensional tool for teaching human neuroanatomy.

PubMed

Estevez, Maureen E; Lindgren, Kristen A; Bergethon, Peter R

2010-01-01

Three-dimensional (3D) visualization of neuroanatomy can be challenging for medical students. This knowledge is essential in order for students to correlate cross-sectional neuroanatomy and whole brain specimens within neuroscience curricula and to interpret clinical and radiological information as clinicians or researchers. This study implemented and evaluated a new tool for teaching 3D neuroanatomy to first-year medical students at Boston University School of Medicine. Students were randomized into experimental and control classrooms. All students were taught neuroanatomy according to traditional 2D methods. Then, during laboratory review, the experimental group constructed 3D color-coded physical models of the periventricular structures, while the control group re-examined 2D brain cross-sections. At the end of the course, 2D and 3D spatial relationships of the brain and preferred learning styles were assessed in both groups. The overall quiz scores for the experimental group were significantly higher than the control group (t(85) = 2.02, P < 0.05). However, when the questions were divided into those requiring either 2D or 3D visualization, only the scores for the 3D questions were significantly higher in the experimental group (F₁(,)₈₅ = 5.48, P = 0.02). When surveyed, 84% of students recommended repeating the 3D activity for future laboratories, and this preference was equally distributed across preferred learning styles (χ² = 0.14, n.s.). Our results suggest that our 3D physical modeling activity is an effective method for teaching spatial relationships of brain anatomy and will better prepare students for visualization of 3D neuroanatomy, a skill essential for higher education in neuroscience, neurology, and neurosurgery. Copyright © 2010 American Association of Anatomists.

A Novel Three-Dimensional Tool for Teaching Human Neuroanatomy

PubMed Central

Estevez, Maureen E.; Lindgren, Kristen A.; Bergethon, Peter R.

2011-01-01

Three-dimensional (3-D) visualization of neuroanatomy can be challenging for medical students. This knowledge is essential in order for students to correlate cross-sectional neuroanatomy and whole brain specimens within neuroscience curricula and to interpret clinical and radiological information as clinicians or researchers. This study implemented and evaluated a new tool for teaching 3-D neuroanatomy to first-year medical students at Boston University School of Medicine. Students were randomized into experimental and control classrooms. All students were taught neuroanatomy according to traditional 2-D methods. Then, during laboratory review, the experimental group constructed 3-D color-coded physical models of the periventricular structures, while the control group re-examined 2-D brain cross-sections. At the end of the course, 2-D and 3-D spatial relationships of the brain and preferred learning styles were assessed in both groups. The overall quiz scores for the experimental group were significantly higher than the control group (t(85) = 2.02, P < 0.05). However, when the questions were divided into those requiring either 2-D or 3-D visualization, only the scores for the 3-D questions were significantly higher in the experimental group (F1,85 = 5.48, P = 0.02). When surveyed, 84% of students recommended repeating the 3-D activity for future laboratories, and this preference was equally distributed across preferred learning styles (χ2 = 0.14, n.s.). Our results suggest that our 3-D physical modeling activity is an effective method for teaching spatial relationships of brain anatomy and will better prepare students for visualization of 3-D neuroanatomy, a skill essential for higher education in neuroscience, neurology, and neurosurgery. PMID:20939033

Binocular fusion and invariant category learning due to predictive remapping during scanning of a depthful scene with eye movements.

PubMed

Grossberg, Stephen; Srinivasan, Karthik; Yazdanbakhsh, Arash

2014-01-01

How does the brain maintain stable fusion of 3D scenes when the eyes move? Every eye movement causes each retinal position to process a different set of scenic features, and thus the brain needs to binocularly fuse new combinations of features at each position after an eye movement. Despite these breaks in retinotopic fusion due to each movement, previously fused representations of a scene in depth often appear stable. The 3D ARTSCAN neural model proposes how the brain does this by unifying concepts about how multiple cortical areas in the What and Where cortical streams interact to coordinate processes of 3D boundary and surface perception, spatial attention, invariant object category learning, predictive remapping, eye movement control, and learned coordinate transformations. The model explains data from single neuron and psychophysical studies of covert visual attention shifts prior to eye movements. The model further clarifies how perceptual, attentional, and cognitive interactions among multiple brain regions (LGN, V1, V2, V3A, V4, MT, MST, PPC, LIP, ITp, ITa, SC) may accomplish predictive remapping as part of the process whereby view-invariant object categories are learned. These results build upon earlier neural models of 3D vision and figure-ground separation and the learning of invariant object categories as the eyes freely scan a scene. A key process concerns how an object's surface representation generates a form-fitting distribution of spatial attention, or attentional shroud, in parietal cortex that helps maintain the stability of multiple perceptual and cognitive processes. Predictive eye movement signals maintain the stability of the shroud, as well as of binocularly fused perceptual boundaries and surface representations.

Diffeomorphic functional brain surface alignment: Functional demons.

PubMed

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.

Specialized Cortex Glial Cells Accumulate Lipid Droplets in Drosophila melanogaster.

PubMed

Kis, Viktor; Barti, Benjámin; Lippai, Mónika; Sass, Miklós

2015-01-01

Lipid droplets (LDs) are common organelles of the majority of eukaryotic cell types. Their biological significance has been extensively studied in mammalian liver cells and white adipose tissue. Although the central nervous system contains the highest relative amount and the largest number of different lipid species, neither the spatial nor the temporal distribution of LDs has been described. In this study, we used the brain of the fruitfly, Drosophila melanogaster, to investigate the neuroanatomy of LDs. We demonstrated that LDs are exclusively localised in glial cells but not in neurons in the larval nervous system. We showed that the brain's LD pool, rather than being constant, changes dynamically during development and reaches its highest value at the beginning of metamorphosis. LDs are particularly enriched in cortex glial cells located close to the brain surface. These specialized superficial cortex glial cells contain the highest amount of LDs among glial cell types and encapsulate neuroblasts and their daughter cells. Superficial cortex glial cells, combined with subperineurial glial cells, express the Drosophila fatty acid binding protein (Dfabp), as we have demonstrated through light- and electron microscopic immunocytochemistry. To the best of our best knowledge this is the first study that describes LD neuroanatomy in the Drosophila larval brain.

Clarifying the Ghrelin System’s Ability to Regulate Feeding Behaviours Despite Enigmatic Spatial Separation of the GHSR and Its Endogenous Ligand

PubMed Central

Edwards, Alexander; Abizaid, Alfonso

2017-01-01

Ghrelin is a hormone predominantly produced in and secreted from the stomach. Ghrelin is involved in many physiological processes including feeding, the stress response, and in modulating learning, memory and motivational processes. Ghrelin does this by binding to its receptor, the growth hormone secretagogue receptor (GHSR), a receptor found in relatively high concentrations in hypothalamic and mesolimbic brain regions. While the feeding and metabolic effects of ghrelin can be explained by the effects of this hormone on regions of the brain that have a more permeable blood brain barrier (BBB), ghrelin produced within the periphery demonstrates a limited ability to reach extrahypothalamic regions where GHSRs are expressed. Therefore, one of the most pressing unanswered questions plaguing ghrelin research is how GHSRs, distributed in brain regions protected by the BBB, are activated despite ghrelin’s predominant peripheral production and poor ability to transverse the BBB. This manuscript will describe how peripheral ghrelin activates central GHSRs to encourage feeding, and how central ghrelin synthesis and ghrelin independent activation of GHSRs may also contribute to the modulation of feeding behaviours. PMID:28422060

SISSY: An efficient and automatic algorithm for the analysis of EEG sources based on structured sparsity.

PubMed

Becker, H; Albera, L; Comon, P; Nunes, J-C; Gribonval, R; Fleureau, J; Guillotel, P; Merlet, I

2017-08-15

Over the past decades, a multitude of different brain source imaging algorithms have been developed to identify the neural generators underlying the surface electroencephalography measurements. While most of these techniques focus on determining the source positions, only a small number of recently developed algorithms provides an indication of the spatial extent of the distributed sources. In a recent comparison of brain source imaging approaches, the VB-SCCD algorithm has been shown to be one of the most promising algorithms among these methods. However, this technique suffers from several problems: it leads to amplitude-biased source estimates, it has difficulties in separating close sources, and it has a high computational complexity due to its implementation using second order cone programming. To overcome these problems, we propose to include an additional regularization term that imposes sparsity in the original source domain and to solve the resulting optimization problem using the alternating direction method of multipliers. Furthermore, we show that the algorithm yields more robust solutions by taking into account the temporal structure of the data. We also propose a new method to automatically threshold the estimated source distribution, which permits to delineate the active brain regions. The new algorithm, called Source Imaging based on Structured Sparsity (SISSY), is analyzed by means of realistic computer simulations and is validated on the clinical data of four patients. Copyright © 2017 Elsevier Inc. All rights reserved.

Influence of anisotropic conductivity in the skull and white matter on transcranial direct current stimulation via an anatomically realistic finite element head model

NASA Astrophysics Data System (ADS)

Suh, Hyun Sang; Lee, Won Hee; Kim, Tae-Seong

2012-11-01

To establish safe and efficient transcranial direct current stimulation (tDCS), it is of particular importance to understand the electrical effects of tDCS in the brain. Since the current density (CD) and electric field (EF) in the brain generated by tDCS depend on various factors including complex head geometries and electrical tissue properties, in this work, we investigated the influence of anisotropic conductivity in the skull and white matter (WM) on tDCS via a 3D anatomically realistic finite element head model. We systematically incorporated various anisotropic conductivity ratios into the skull and WM. The effects of anisotropic tissue conductivity on the CD and EF were subsequently assessed through comparisons to the conventional isotropic solutions. Our results show that the anisotropic skull conductivity significantly affects the CD and EF distribution: there is a significant reduction in the ratio of the target versus non-target total CD and EF on the order of 12-14%. In contrast, the WM anisotropy does not significantly influence the CD and EF on the targeted cortical surface, only on the order of 1-3%. However, the WM anisotropy highly alters the spatial distribution of both the CD and EF inside the brain. This study shows that it is critical to incorporate anisotropic conductivities in planning of tDCS for improved efficacy and safety.

Hubs defined with participation coefficient metric altered following acute mTBI

NASA Astrophysics Data System (ADS)

Wang, Xiaocui; Sun, Chuanzhu; Wang, Shan; Cao, Jieli; Xu, Hui; Gan, Shuoqiu; Chen, Zhen; Yin, Bo; Bai, Guanghui; Shao, Meihua; Gu, Chenghui; Hu, Liuxun; Ye, Limei; Li, Dandong; Yan, Zhihan; Bai, Lijun

2018-03-01

Patients with mild traumatic brain injury (mTBI) may suffer from a widespread spectrum of symptoms that arise from the damage of long-distance white matter connections in distributed brain networks. In brain networks, an increasing attention has been devoted to assessing the functional roles of regions by estimating the spatial layout of their connections among different modules, using the participation coefficient. In the present study, we aimed to investigate the role of hubs in inter-subnetwork information coordination and integration by using participation coefficients after mTBI. 74 patients after mTBI within 7 days post-injury and 51 matched healthy controls enrolled in this study. Our results presented that hubs for mTBI patients distributed in more extensive networks such as the default mode network (DMN), ventral attention network (VAN) and frontoparietal network (FPN), somatomotor network (SMN) and visual network (VN), compared with healthy controls limited to the first three. Participation coefficients for mTBI presented significantly decreased in the DMN (P=0.015) and FPN (P=0.02), while increased in the VN (P=0.035). SVM trained with participation coefficient metrics were able to identify mTBI patients from controls with 78% accuracy, providing for its diagnose potential in clinical settings. From our point of view, difference between two groups could be related with functional network reorganization in mTBI groups.

The effects of laboratory housing and spatial enrichment on brain size and metabolic rate in the eastern mosquitofish, Gambusia holbrooki

PubMed Central

Turschwell, Mischa P.; White, Craig R.

2016-01-01

ABSTRACT It has long been hypothesised that there is a functional correlation between brain size and metabolic rate in vertebrates. The present study tested this hypothesis in wild-caught adult mosquitofish Gambusia holbrooki by testing for an intra-specific association between resting metabolic rate (RMR) and brain size while controlling for variation in body size, and through the examination of the effects of spatial enrichment and laboratory housing on body mass-independent measures of brain size and RMR. Controlling for body mass, there was no relationship between brain size and RMR in wild-caught fish. Contrary to predictions, spatial enrichment caused a decrease in mass-independent brain size, highlighting phenotypic plasticity in the adult brain. As expected, after controlling for differences in body size, wild-caught fish had relatively larger brains than fish that had been maintained in the laboratory for a minimum of six weeks, but wild-caught fish also had significantly lower mass-independent RMR. This study demonstrates that an organisms' housing environment can cause significant plastic changes to fitness related traits including brain size and RMR. We therefore conclude that current standard laboratory housing conditions may cause captive animals to be non-representative of their wild counterparts, potentially undermining the transferability of previous laboratory-based studies of aquatic ectothermic vertebrates to wild populations. PMID:26794608

Automatic determination of white matter hyperintensity properties in relation to the development of Alzheimer's disease

NASA Astrophysics Data System (ADS)

van der Velden, Sandra; Moenninghoff, Christoph; Wanke, Isabel; Jokisch, Martha; Weimar, Christian; Lopes Simoes, Rita; van Cappellen van Walsum, Anne-Marie; Slump, Cornelis

2016-03-01

Alzheimer's disease (AD) is the most common form of dementia seen in the elderly. No curing medicine for AD exists at this moment. In the search for an effective medicine, research is directed towards the prediction of conversion of mild cognitive impairment (MCI) to AD. White matter hyperintensities (WMHs) have been shown to contain information regarding the development of AD, although non-conclusive results are found in literature. These studies often use qualitative measures to describe WMHs, which is time consuming and prone to variability. To investigate the relation between WMHs and the development of AD, algorithms to automatically determine quantitative properties in terms of volume and spatial distribution of WMHs are developed and compared between normal controls and MCI subjects. MCI subjects have a significantly higher total volume of WMHs than normal controls. This difference persists when lesions are classified according to their distance to the ventricular wall. Spatial distribution is also described by defining different brain regions based on a common coordinate system. This reveals that MCI subjects have a larger WMH volume in the upper part of the brain compared to normal controls. In four subjects, the change of WMH properties over time is studied in detail. Although such a small dataset cannot be used to give definitive conclusions, the data suggests that progression of WMHs in subjects with a low lesion load is caused by an increase in the number of lesions and by the progression of juxtacortical lesions. In subjects with a larger lesion load, progression is caused by expansion of pre-existing lesions.

Oscillatory activity in neocortical networks during tactile discrimination near the limit of spatial acuity.

PubMed

Adhikari, Bhim M; Sathian, K; Epstein, Charles M; Lamichhane, Bidhan; Dhamala, Mukesh

2014-05-01

Oscillatory interactions within functionally specialized but distributed brain regions are believed to be central to perceptual and cognitive functions. Here, using human scalp electroencephalography (EEG) recordings combined with source reconstruction techniques, we study how oscillatory activity functionally organizes different neocortical regions during a tactile discrimination task near the limit of spatial acuity. While undergoing EEG recordings, blindfolded participants felt a linear three-dot array presented electromechanically, under computer control, and reported whether the central dot was offset to the left or right. The average brain response differed significantly for trials with correct and incorrect perceptual responses in the timeframe approximately between 130 and 175ms. During trials with correct responses, source-level peak activity appeared in the left primary somatosensory cortex (SI) at around 45ms, in the right lateral occipital complex (LOC) at 130ms, in the right posterior intraparietal sulcus (pIPS) at 160ms, and finally in the left dorsolateral prefrontal cortex (dlPFC) at 175ms. Spectral interdependency analysis of activity in these nodes showed two distinct distributed networks, a dominantly feedforward network in the beta band (12-30Hz) that included all four nodes and a recurrent network in the gamma band (30-100Hz) that linked SI, pIPS and dlPFC. Measures of network activity in both bands were correlated with the accuracy of task performance. These findings suggest that beta and gamma band oscillatory networks coordinate activity between neocortical regions mediating sensory and cognitive processing to arrive at tactile perceptual decisions. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Trypsin and MALDI matrix pre-coated targets simplify sample preparation for mapping proteomic distributions within biological tissues by imaging mass spectrometry

PubMed Central

Zubair, Faizan; Laibinis, Paul E.; Swisher, William G.; Yang, Junhai; Spraggins, Jeffrey M.; Norris, Jeremy L.; Caprioli, Richard M.

2017-01-01

Prefabricated surfaces containing α-cyano-4-hydroxycinnamic acid and trypsin have been developed to facilitate enzymatic digestion of endogenous tissue proteins prior to matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS). Tissue sections are placed onto slides that were previously coated with α-cyano-4-hydroxycinnamic acid and trypsin. After incubation to promote enzymatic digestion, the tissue is analyzed by MALDI IMS to determine the spatial distribution of the tryptic fragments. The peptides detected in the MALDI IMS dataset were identified by Liquid chromatography-tandem mass spectrometry/mass spectrometry. Protein identification was further confirmed by correlating the localization of unique tryptic fragments originating from common parent proteins. Using this procedure, proteins with molecular weights as large as 300 kDa were identified and their distributions were imaged in sections of rat brain. In particular, large proteins such as myristoylated alanine-rich C-kinase substrate (29.8 kDa) and spectrin alpha chain, non-erythrocytic 1 (284 kDa) were detected that are not observed without trypsin. The pre-coated targets simplify workflow and increase sample throughput by decreasing the sample preparation time. Further, the approach allows imaging at higher spatial resolution compared with robotic spotters that apply one drop at a time. PMID:27676701

Spatial distribution and cellular composition of adult brain proliferative zones in the teleost, Gymnotus omarorum

PubMed Central

Olivera-Pasilio, Valentina; Peterson, Daniel A.; Castelló, María E.

2014-01-01

Proliferation of stem/progenitor cells during development provides for the generation of mature cell types in the CNS. While adult brain proliferation is highly restricted in the mammals, it is widespread in teleosts. The extent of adult neural proliferation in the weakly electric fish, Gymnotus omarorum has not yet been described. To address this, we used double thymidine analog pulse-chase labeling of proliferating cells to identify brain proliferation zones, characterize their cellular composition, and analyze the fate of newborn cells in adult G. omarorum. Short thymidine analog chase periods revealed the ubiquitous distribution of adult brain proliferation, similar to other teleosts, particularly Apteronotus leptorhynchus. Proliferating cells were abundant at the ventricular-subventricular lining of the ventricular-cisternal system, adjacent to the telencephalic subpallium, the diencephalic preoptic region and hypothalamus, and the mesencephalic tectum opticum and torus semicircularis. Extraventricular proliferation zones, located distant from the ventricular-cisternal system surface, were found in all divisions of the rombencephalic cerebellum. We also report a new adult proliferation zone at the caudal-lateral border of the electrosensory lateral line lobe. All proliferation zones showed a heterogeneous cellular composition. The use of short (24 h) and long (30 day) chase periods revealed abundant fast cycling cells (potentially intermediate amplifiers), sparse slow cycling (potentially stem) cells, cells that appear to have entered a quiescent state, and cells that might correspond to migrating newborn neural cells. Their abundance and migration distance differed among proliferation zones: greater numbers and longer range and/or pace of migrating cells were associated with subpallial and cerebellar proliferation zones. PMID:25249943

An experimental study and finite element modeling of head and neck cooling for brain hypothermia.

PubMed

Li, Hui; Chen, Roland K; Tang, Yong; Meurer, William; Shih, Albert J

2018-01-01

Reducing brain temperature by head and neck cooling is likely to be the protective treatment for humans when subjects to sudden cardiac arrest. This study develops the experimental validation model and finite element modeling (FEM) to study the head and neck cooling separately, which can induce therapeutic hypothermia focused on the brain. Anatomically accurate geometries based on CT images of the skull and carotid artery are utilized to find the 3D geometry for FEM to analyze the temperature distributions and 3D-printing to build the physical model for experiment. The results show that FEM predicted and experimentally measured temperatures have good agreement, which can be used to predict the temporal and spatial temperature distributions of the tissue and blood during the head and neck cooling process. Effects of boundary condition, perfusion, blood flow rate, and size of cooling area are studied. For head cooling, the cooling penetration depth is greatly depending on the blood perfusion in the brain. In the normal blood flow condition, the neck internal carotid artery temperature is decreased only by about 0.13°C after 60min of hypothermia. In an ischemic (low blood flow rate) condition, such temperature can be decreased by about 1.0°C. In conclusion, decreasing the blood perfusion and metabolic reduction factor could be more beneficial to cool the core zone. The results also suggest that more SBC researches should be explored, such as the optimization of simulation and experimental models, and to perform the experiment on human subjects. Copyright © 2017 Elsevier Ltd. All rights reserved.

Neural correlates of spatial and nonspatial attention determined using intracranial electroencephalographic signals in humans

PubMed Central

Park, Ga Young; Kim, Taekyung; Park, Jinsick; Lee, Eun Mi; Ryu, Han Uk; Kim, Sun I.; Kim, In Young; Husain, Masud

2016-01-01

Abstract Few studies have directly compared the neural correlates of spatial attention (i.e., attention to a particular location) and nonspatial attention (i.e., attention to a feature in the visual scene) using well‐controlled tasks. Here, we investigated the neural correlates of spatial and nonspatial attention in humans using intracranial electroencephalography. The topography and number of electrodes showing significant event‐related desynchronization (ERD) or event‐related synchronization (ERS) in different frequency bands were studied in 13 epileptic patients. Performance was not significantly different between the two conditions. In both conditions, ERD in the low‐frequency bands and ERS in the high‐frequency bands were present bilaterally in the parietal cortex (prominently on the right hemisphere) and frontal regions. In addition to these common changes, spatial attention involved right‐lateralized activity that was maximal in the right superior parietal lobule (SPL), whereas nonspatial attention involved wider brain networks including the bilateral parietal, frontal, and temporal regions, but still had maximal activity in the right parietal lobe. Within the parietal lobe, spatial attention involved ERD or ERS in the right SPL, whereas nonspatial attention involved ERD or ERS in the right inferior parietal lobule. These findings reveal that common as well as different brain networks are engaged in spatial and nonspatial attention. Hum Brain Mapp 37:3041–3054, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. PMID:27125904

Back-Projection Cortical Potential Imaging: Theory and Results.

PubMed

Haor, Dror; Shavit, Reuven; Shapiro, Moshe; Geva, Amir B

2017-07-01

Electroencephalography (EEG) is the single brain monitoring technique that is non-invasive, portable, passive, exhibits high-temporal resolution, and gives a directmeasurement of the scalp electrical potential. Amajor disadvantage of the EEG is its low-spatial resolution, which is the result of the low-conductive skull that "smears" the currents coming from within the brain. Recording brain activity with both high temporal and spatial resolution is crucial for the localization of confined brain activations and the study of brainmechanismfunctionality, whichis then followed by diagnosis of brain-related diseases. In this paper, a new cortical potential imaging (CPI) method is presented. The new method gives an estimation of the electrical activity on the cortex surface and thus removes the "smearing effect" caused by the skull. The scalp potentials are back-projected CPI (BP-CPI) onto the cortex surface by building a well-posed problem to the Laplace equation that is solved by means of the finite elements method on a realistic head model. A unique solution to the CPI problem is obtained by introducing a cortical normal current estimation technique. The technique is based on the same mechanism used in the well-known surface Laplacian calculation, followed by a scalp-cortex back-projection routine. The BP-CPI passed four stages of validation, including validation on spherical and realistic head models, probabilistic analysis (Monte Carlo simulation), and noise sensitivity tests. In addition, the BP-CPI was compared with the minimum norm estimate CPI approach and found superior for multi-source cortical potential distributions with very good estimation results (CC >0.97) on a realistic head model in the regions of interest, for two representative cases. The BP-CPI can be easily incorporated in different monitoring tools and help researchers by maintaining an accurate estimation for the cortical potential of ongoing or event-related potentials in order to have better neurological inferences from the EEG.

A Linear Temporal Increase in Thrombin Activity and Loss of Its Receptor in Mouse Brain following Ischemic Stroke.

PubMed

Bushi, Doron; Stein, Efrat Shavit; Golderman, Valery; Feingold, Ekaterina; Gera, Orna; Chapman, Joab; Tanne, David

2017-01-01

Brain thrombin activity is increased following acute ischemic stroke and may play a pathogenic role through the protease-activated receptor 1 (PAR1). In order to better assess these factors, we obtained a novel detailed temporal and spatial profile of thrombin activity in a mouse model of permanent middle cerebral artery occlusion (pMCAo). Thrombin activity was measured by fluorescence spectroscopy on coronal slices taken from the ipsilateral and contralateral hemispheres 2, 5, and 24 h following pMCAo ( n  = 5, 6, 5 mice, respectively). Its spatial distribution was determined by punch samples taken from the ischemic core and penumbra and further confirmed using an enzyme histochemistry technique ( n  = 4). Levels of PAR1 were determined using western blot. Two hours following pMCAo, thrombin activity in the stroke core was already significantly higher than the contralateral area (11 ± 5 vs. 2 ± 1 mU/ml). At 5 and 24 h, thrombin activity continued to rise linearly ( r  = 0.998, p  = 0.001) and to expand in the ischemic hemisphere beyond the ischemic core reaching deleterious levels of 271 ± 117 and 123 ± 14 mU/ml (mean ± SEM) in the basal ganglia and ischemic cortex, respectively. The peak elevation of thrombin activity in the ischemic core that was confirmed by fluorescence histochemistry was in good correlation with the infarcts areas. PAR1 levels in the ischemic core decreased as stroke progressed and thrombin activity increased. In conclusion, there is a time- and space-related increase in brain thrombin activity in acute ischemic stroke that is closely related to the progression of brain damage. These results may be useful in the development of therapeutic strategies for ischemic stroke that involve the thrombin-PAR1 pathway in order to prevent secondary thrombin related brain damage.

Questions of Brain Hemispheric Specialization and Gender Difference in Spatial Tests.

ERIC Educational Resources Information Center

McWhinnie, Harold J.

This paper presents a review of selected literature relevant to a general question of hemispheric specialization (right or left brain) and questions of gender differences in spatial abilities among a group of art students. Three basic questions for discussion are proposed: (1) is there a relationship between hemispheric dominance and spatial…

Brain Oscillatory Activity during Spatial Navigation: Theta and Gamma Activity Link Medial Temporal and Parietal Regions

ERIC Educational Resources Information Center

White, David J.; Congedo, Marco; Ciorciari, Joseph; Silberstein, Richard B.

2012-01-01

Brain oscillatory correlates of spatial navigation were investigated using blind source separation (BSS) and standardized low resolution electromagnetic tomography (sLORETA) analyses of 62-channel EEG recordings. Twenty-five participants were instructed to navigate to distinct landmark buildings in a previously learned virtual reality town…

Hemispheric Visual Attentional Imbalance in Patients with Traumatic Brain Injury

ERIC Educational Resources Information Center

Pavlovskaya, Marina; Groswasser, Zeev; Keren, Ofer; Mordvinov, Eugene; Hochstein, Shaul

2007-01-01

We find a spatially asymmetric allocation of attention in patients with traumatic brain injury (TBI) despite the lack of obvious asymmetry in neurological indicators. Identification performance was measured for simple spatial patterns presented briefly to a locus 5 degrees into the left or right hemifield, after precuing attention to the same…

A Subspace Pursuit–based Iterative Greedy Hierarchical Solution to the Neuromagnetic Inverse Problem

PubMed Central

Babadi, Behtash; Obregon-Henao, Gabriel; Lamus, Camilo; Hämäläinen, Matti S.; Brown, Emery N.; Purdon, Patrick L.

2013-01-01

Magnetoencephalography (MEG) is an important non-invasive method for studying activity within the human brain. Source localization methods can be used to estimate spatiotemporal activity from MEG measurements with high temporal resolution, but the spatial resolution of these estimates is poor due to the ill-posed nature of the MEG inverse problem. Recent developments in source localization methodology have emphasized temporal as well as spatial constraints to improve source localization accuracy, but these methods can be computationally intense. Solutions emphasizing spatial sparsity hold tremendous promise, since the underlying neurophysiological processes generating MEG signals are often sparse in nature, whether in the form of focal sources, or distributed sources representing large-scale functional networks. Recent developments in the theory of compressed sensing (CS) provide a rigorous framework to estimate signals with sparse structure. In particular, a class of CS algorithms referred to as greedy pursuit algorithms can provide both high recovery accuracy and low computational complexity. Greedy pursuit algorithms are difficult to apply directly to the MEG inverse problem because of the high-dimensional structure of the MEG source space and the high spatial correlation in MEG measurements. In this paper, we develop a novel greedy pursuit algorithm for sparse MEG source localization that overcomes these fundamental problems. This algorithm, which we refer to as the Subspace Pursuit-based Iterative Greedy Hierarchical (SPIGH) inverse solution, exhibits very low computational complexity while achieving very high localization accuracy. We evaluate the performance of the proposed algorithm using comprehensive simulations, as well as the analysis of human MEG data during spontaneous brain activity and somatosensory stimuli. These studies reveal substantial performance gains provided by the SPIGH algorithm in terms of computational complexity, localization accuracy, and robustness. PMID:24055554

High-field fMRI unveils orientation columns in humans.

PubMed

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.

Temporal Dynamics Assessment of Spatial Overlap Pattern of Functional Brain Networks Reveals Novel Functional Architecture of Cerebral Cortex.

PubMed

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.

A high-performance spatial database based approach for pathology imaging algorithm evaluation

PubMed Central

Wang, Fusheng; Kong, Jun; Gao, Jingjing; Cooper, Lee A.D.; Kurc, Tahsin; Zhou, Zhengwen; Adler, David; Vergara-Niedermayr, Cristobal; Katigbak, Bryan; Brat, Daniel J.; Saltz, Joel H.

2013-01-01

Background: Algorithm evaluation provides a means to characterize variability across image analysis algorithms, validate algorithms by comparison with human annotations, combine results from multiple algorithms for performance improvement, and facilitate algorithm sensitivity studies. The sizes of images and image analysis results in pathology image analysis pose significant challenges in algorithm evaluation. We present an efficient parallel spatial database approach to model, normalize, manage, and query large volumes of analytical image result data. This provides an efficient platform for algorithm evaluation. Our experiments with a set of brain tumor images demonstrate the application, scalability, and effectiveness of the platform. Context: The paper describes an approach and platform for evaluation of pathology image analysis algorithms. The platform facilitates algorithm evaluation through a high-performance database built on the Pathology Analytic Imaging Standards (PAIS) data model. Aims: (1) Develop a framework to support algorithm evaluation by modeling and managing analytical results and human annotations from pathology images; (2) Create a robust data normalization tool for converting, validating, and fixing spatial data from algorithm or human annotations; (3) Develop a set of queries to support data sampling and result comparisons; (4) Achieve high performance computation capacity via a parallel data management infrastructure, parallel data loading and spatial indexing optimizations in this infrastructure. Materials and Methods: We have considered two scenarios for algorithm evaluation: (1) algorithm comparison where multiple result sets from different methods are compared and consolidated; and (2) algorithm validation where algorithm results are compared with human annotations. We have developed a spatial normalization toolkit to validate and normalize spatial boundaries produced by image analysis algorithms or human annotations. The validated data were formatted based on the PAIS data model and loaded into a spatial database. To support efficient data loading, we have implemented a parallel data loading tool that takes advantage of multi-core CPUs to accelerate data injection. The spatial database manages both geometric shapes and image features or classifications, and enables spatial sampling, result comparison, and result aggregation through expressive structured query language (SQL) queries with spatial extensions. To provide scalable and efficient query support, we have employed a shared nothing parallel database architecture, which distributes data homogenously across multiple database partitions to take advantage of parallel computation power and implements spatial indexing to achieve high I/O throughput. Results: Our work proposes a high performance, parallel spatial database platform for algorithm validation and comparison. This platform was evaluated by storing, managing, and comparing analysis results from a set of brain tumor whole slide images. The tools we develop are open source and available to download. Conclusions: Pathology image algorithm validation and comparison are essential to iterative algorithm development and refinement. One critical component is the support for queries involving spatial predicates and comparisons. In our work, we develop an efficient data model and parallel database approach to model, normalize, manage and query large volumes of analytical image result data. Our experiments demonstrate that the data partitioning strategy and the grid-based indexing result in good data distribution across database nodes and reduce I/O overhead in spatial join queries through parallel retrieval of relevant data and quick subsetting of datasets. The set of tools in the framework provide a full pipeline to normalize, load, manage and query analytical results for algorithm evaluation. PMID:23599905

Cognitive memory and mapping in a brain-like system for robotic navigation.

PubMed

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.

Differential attentional responding in caesarean versus vaginally delivered infants.

PubMed

Adler, Scott A; Wong-Kee-You, Audrey M B

2015-11-01

Little is known about the role that the birth experience plays in brain and cognitive development. Recent research has suggested that birth experience influences the development of the somatosensory cortex, an area involved in spatial attention to sensory information. In this study, we explored whether differences in spatial attention would occur in infants who had different birth experiences, as occurs for caesarean versus vaginal delivery. Three-month-old infants performed either a spatial cueing task or a visual expectation task. We showed that caesarean-delivered infants' stimulus-driven, reflexive attention was slowed relative to vaginally delivered infants', whereas their cognitively driven, voluntary attention was unaffected. Thus, types of birth experience influence at least one form of infants' attention, and possibly any cognitive process that relies on spatial attention. This study also suggests that birth experience influences the initial state of brain functioning and, consequently, should be considered in our understanding of brain development.

Discrete capacity limits and neuroanatomical correlates of visual short-term memory for objects and spatial locations.

PubMed

Konstantinou, Nikos; Constantinidou, Fofi; Kanai, Ryota

2017-02-01

Working memory is responsible for keeping information in mind when it is no longer in view, linking perception with higher cognitive functions. Despite such crucial role, short-term maintenance of visual information is severely limited. Research suggests that capacity limits in visual short-term memory (VSTM) are correlated with sustained activity in distinct brain areas. Here, we investigated whether variability in the structure of the brain is reflected in individual differences of behavioral capacity estimates for spatial and object VSTM. Behavioral capacity estimates were calculated separately for spatial and object information using a novel adaptive staircase procedure and were found to be unrelated, supporting domain-specific VSTM capacity limits. Voxel-based morphometry (VBM) analyses revealed dissociable neuroanatomical correlates of spatial versus object VSTM. Interindividual variability in spatial VSTM was reflected in the gray matter density of the inferior parietal lobule. In contrast, object VSTM was reflected in the gray matter density of the left insula. These dissociable findings highlight the importance of considering domain-specific estimates of VSTM capacity and point to the crucial brain regions that limit VSTM capacity for different types of visual information. Hum Brain Mapp 38:767-778, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Magnetic Resonance Elastography of the Brain using Multi-Shot Spiral Readouts with Self-Navigated Motion Correction

PubMed Central

Johnson, Curtis L.; McGarry, Matthew D. J.; Van Houten, Elijah E. W.; Weaver, John B.; Paulsen, Keith D.; Sutton, Bradley P.; Georgiadis, John G.

2012-01-01

MRE has been introduced in clinical practice as a possible surrogate for mechanical palpation, but its application to study the human brain in vivo has been limited by low spatial resolution and the complexity of the inverse problem associated with biomechanical property estimation. Here, we report significant improvements in brain MRE data acquisition by reporting images with high spatial resolution and signal-to-noise ratio as quantified by octahedral shear strain metrics. Specifically, we have developed a sequence for brain MRE based on multi-shot, variable-density spiral imaging and three-dimensional displacement acquisition, and implemented a correction scheme for any resulting phase errors. A Rayleigh damped model of brain tissue mechanics was adopted to represent the parenchyma, and was integrated via a finite element-based iterative inversion algorithm. A multi-resolution phantom study demonstrates the need for obtaining high-resolution MRE data when estimating focal mechanical properties. Measurements on three healthy volunteers demonstrate satisfactory resolution of grey and white matter, and mechanical heterogeneities correspond well with white matter histoarchitecture. Together, these advances enable MRE scans that result in high-fidelity, spatially-resolved estimates of in vivo brain tissue mechanical properties, improving upon lower resolution MRE brain studies which only report volume averaged stiffness values. PMID:23001771

Evaluation of biomolecular distributions in rat brain tissues by means of ToF-SIMS using a continuous beam of Ar clusters.

PubMed

Nakano, Shusuke; Yokoyama, Yuta; Aoyagi, Satoka; Himi, Naoyuki; Fletcher, John S; Lockyer, Nicholas P; Henderson, Alex; Vickerman, John C

2016-06-08

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) provides detailed chemical structure information and high spatial resolution images. Therefore, ToF-SIMS is useful for studying biological phenomena such as ischemia. In this study, in order to evaluate cerebral microinfarction, the distribution of biomolecules generated by ischemia was measured with ToF-SIMS. ToF-SIMS data sets were analyzed by means of multivariate analysis for interpreting complex samples containing unknown information and to obtain biomolecular mapping indicated by fragment ions from the target biomolecules. Using conventional ToF-SIMS (primary ion source: Bi cluster ion), it is difficult to detect secondary ions beyond approximately 1000 u. Moreover, the intensity of secondary ions related to biomolecules is not always high enough for imaging because of low concentration even if the masses are lower than 1000 u. However, for the observation of biomolecular distributions in tissues, it is important to detect low amounts of biological molecules from a particular area of tissue. Rat brain tissue samples were measured with ToF-SIMS (J105, Ionoptika, Ltd., Chandlers Ford, UK), using a continuous beam of Ar clusters as a primary ion source. ToF-SIMS with Ar clusters efficiently detects secondary ions related to biomolecules and larger molecules. Molecules detected by ToF-SIMS were examined by analyzing ToF-SIMS data using multivariate analysis. Microspheres (45 μm diameter) were injected into the rat unilateral internal carotid artery (MS rat) to cause cerebral microinfarction. The rat brain was sliced and then measured with ToF-SIMS. The brain samples of a normal rat and the MS rat were examined to find specific secondary ions related to important biomolecules, and then the difference between them was investigated. Finally, specific secondary ions were found around vessels incorporating microspheres in the MS rat. The results suggest that important biomolecules related to cerebral microinfarction can be detected by ToF-SIMS.

Comparison of different spatial transformations applied to EEG data: A case study of error processing.

PubMed

Cohen, Michael X

2015-09-01

The purpose of this paper is to compare the effects of different spatial transformations applied to the same scalp-recorded EEG data. The spatial transformations applied are two referencing schemes (average and linked earlobes), the surface Laplacian, and beamforming (a distributed source localization procedure). EEG data were collected during a speeded reaction time task that provided a comparison of activity between error vs. correct responses. Analyses focused on time-frequency power, frequency band-specific inter-electrode connectivity, and within-subject cross-trial correlations between EEG activity and reaction time. Time-frequency power analyses showed similar patterns of midfrontal delta-theta power for errors compared to correct responses across all spatial transformations. Beamforming additionally revealed error-related anterior and lateral prefrontal beta-band activity. Within-subject brain-behavior correlations showed similar patterns of results across the spatial transformations, with the correlations being the weakest after beamforming. The most striking difference among the spatial transformations was seen in connectivity analyses: linked earlobe reference produced weak inter-site connectivity that was attributable to volume conduction (zero phase lag), while the average reference and Laplacian produced more interpretable connectivity results. Beamforming did not reveal any significant condition modulations of connectivity. Overall, these analyses show that some findings are robust to spatial transformations, while other findings, particularly those involving cross-trial analyses or connectivity, are more sensitive and may depend on the use of appropriate spatial transformations. Copyright © 2014 Elsevier B.V. All rights reserved.

Role of Network Science in the Study of Anesthetic State Transitions.

PubMed

Lee, UnCheol; Mashour, George A

2018-04-23

The heterogeneity of molecular mechanisms, target neural circuits, and neurophysiologic effects of general anesthetics makes it difficult to develop a reliable and drug-invariant index of general anesthesia. No single brain region or mechanism has been identified as the neural correlate of consciousness, suggesting that consciousness might emerge through complex interactions of spatially and temporally distributed brain functions. The goal of this review article is to introduce the basic concepts of networks and explain why the application of network science to general anesthesia could be a pathway to discover a fundamental mechanism of anesthetic-induced unconsciousness. This article reviews data suggesting that reduced network efficiency, constrained network repertoires, and changes in cortical dynamics create inhospitable conditions for information processing and transfer, which lead to unconsciousness. This review proposes that network science is not just a useful tool but a necessary theoretical framework and method to uncover common principles of anesthetic-induced unconsciousness.

Discover mouse gene coexpression landscapes using dictionary learning and sparse coding.

PubMed

Li, Yujie; Chen, Hanbo; Jiang, Xi; Li, Xiang; Lv, Jinglei; Peng, Hanchuan; Tsien, Joe Z; Liu, Tianming

2017-12-01

Gene coexpression patterns carry rich information regarding enormously complex brain structures and functions. Characterization of these patterns in an unbiased, integrated, and anatomically comprehensive manner will illuminate the higher-order transcriptome organization and offer genetic foundations of functional circuitry. Here using dictionary learning and sparse coding, we derived coexpression networks from the space-resolved anatomical comprehensive in situ hybridization data from Allen Mouse Brain Atlas dataset. The key idea is that if two genes use the same dictionary to represent their original signals, then their gene expressions must share similar patterns, thereby considering them as "coexpressed." For each network, we have simultaneous knowledge of spatial distributions, the genes in the network and the extent a particular gene conforms to the coexpression pattern. Gene ontologies and the comparisons with published gene lists reveal biologically identified coexpression networks, some of which correspond to major cell types, biological pathways, and/or anatomical regions.

Gene expression links functional networks across cortex and striatum.

PubMed

Anderson, Kevin M; Krienen, Fenna M; Choi, Eun Young; Reinen, Jenna M; Yeo, B T Thomas; Holmes, Avram J

2018-04-12

The human brain is comprised of a complex web of functional networks that link anatomically distinct regions. However, the biological mechanisms supporting network organization remain elusive, particularly across cortical and subcortical territories with vastly divergent cellular and molecular properties. Here, using human and primate brain transcriptional atlases, we demonstrate that spatial patterns of gene expression show strong correspondence with limbic and somato/motor cortico-striatal functional networks. Network-associated expression is consistent across independent human datasets and evolutionarily conserved in non-human primates. Genes preferentially expressed within the limbic network (encompassing nucleus accumbens, orbital/ventromedial prefrontal cortex, and temporal pole) relate to risk for psychiatric illness, chloride channel complexes, and markers of somatostatin neurons. Somato/motor associated genes are enriched for oligodendrocytes and markers of parvalbumin neurons. These analyses indicate that parallel cortico-striatal processing channels possess dissociable genetic signatures that recapitulate distributed functional networks, and nominate molecular mechanisms supporting cortico-striatal circuitry in health and disease.

Numerical modeling and characterization of blast waves for application in blast-induced mild traumatic brain injury research

NASA Astrophysics Data System (ADS)

Phillips, Michael G.

Human exposure to blast waves, including blast-induced traumatic brain injury, is a developing field in medical research. Experiments with explosives have many disadvantages including safety, cost, and required area for trials. Shock tubes provide an alternative method to produce free field blast wave profiles. A compressed nitrogen shock tube experiment instrumented with static and reflective pressure taps is modeled using a numerical simulation. The geometry of the numerical model is simplified and blast wave characteristics are derived based upon static and pressure profiles. The pressure profiles are analyzed along the shock tube centerline and radially away from the tube axis. The blast wave parameters found from the pressure profiles provide guidelines for spatial location of a specimen. The location could be based on multiple parameters and provides a distribution of anticipated pressure profiles experience by the specimen.

Transcranial cavitation-mediated ultrasound therapy at sub-MHz frequency via temporal interference modulation

NASA Astrophysics Data System (ADS)

Sun, Tao; Sutton, Jonathan T.; Power, Chanikarn; Zhang, Yongzhi; Miller, Eric L.; McDannold, Nathan J.

2017-10-01

Sub-megahertz transmission is not usually adopted in pre-clinical small animal experiments for focused ultrasound (FUS) brain therapy due to the large focal size. However, low frequency FUS is vital for preclinical evaluations due to the frequency-dependence of cavitation behavior. To maximize clinical relevance, a dual-aperture FUS system was designed for low-frequency (274.3 kHz) cavitation-mediated FUS therapy. Combining two spherically curved transducers provides significantly improved focusing in the axial direction while yielding an interference pattern with strong side lobes, leading to inhomogeneously distributed cavitation activities. By operating the two transducers at slightly offset frequencies to modulate this interference pattern over the period of sonication, the acoustic energy was redistributed and resulted in a spatially homogenous treatment profile. Simulation and pressure field measurements in water were performed to assess the beam profiles. In addition, the system performance was demonstrated in vivo in rats via drug delivery through microbubble-mediated blood-brain barrier disruption. This design resulted in a homogenous treatment profile that was fully contained within the rat brain at a clinically relevant acoustic frequency.

Cortico-muscular coherence on artifact corrected EEG-EMG data recorded with a MRI scanner.

PubMed

Muthuraman, M; Galka, A; Hong, V N; Heute, U; Deuschl, G; Raethjen, J

2013-01-01

Simultaneous recording of electroencephalogram (EEG) and electromyogram (EMG) with magnetic resonance imaging (MRI) provides great potential for studying human brain activity with high temporal and spatial resolution. But, due to the MRI, the recorded signals are contaminated with artifacts. The correction of these artifacts is important to use these signals for further spectral analysis. The coherence can reveal the cortical representation of peripheral muscle signal in particular motor tasks, e.g. finger movements. The artifact correction of these signals was done by two different algorithms the Brain vision analyzer (BVA) and the Matlab FMRIB plug-in for EEGLAB. The Welch periodogram method was used for estimating the cortico-muscular coherence. Our analysis revealed coherence with a frequency of 5Hz in the contralateral side of the brain. The entropy is estimated for the calculated coherence to get the distribution of coherence in the scalp. The significance of the paper is to identify the optimal algorithm to rectify the MR artifacts and as a first step to use both these signals EEG and EMG in conjunction with MRI for further studies.

Influence of White and Gray Matter Connections on Endogenous Human Cortical Oscillations

PubMed Central

Hawasli, Ammar H.; Kim, DoHyun; Ledbetter, Noah M.; Dahiya, Sonika; Barbour, Dennis L.; Leuthardt, Eric C.

2016-01-01

Brain oscillations reflect changes in electrical potentials summated across neuronal populations. Low- and high-frequency rhythms have different modulation patterns. Slower rhythms are spatially broad, while faster rhythms are more local. From this observation, we hypothesized that low- and high-frequency oscillations reflect white- and gray-matter communications, respectively, and synchronization between low-frequency phase with high-frequency amplitude represents a mechanism enabling distributed brain-networks to coordinate local processing. Testing this common understanding, we selectively disrupted white or gray matter connections to human cortex while recording surface field potentials. Counter to our original hypotheses, we found that cortex consists of independent oscillatory-units (IOUs) that maintain their own complex endogenous rhythm structure. IOUs are differentially modulated by white and gray matter connections. White-matter connections maintain topographical anatomic heterogeneity (i.e., separable processing in cortical space) and gray-matter connections segregate cortical synchronization patterns (i.e., separable temporal processing through phase-power coupling). Modulation of distinct oscillatory modules enables the functional diversity necessary for complex processing in the human brain. PMID:27445767

sLORETA current source density analysis of evoked potentials for spatial updating in a virtual navigation task

PubMed Central

Nguyen, Hai M.; Matsumoto, Jumpei; Tran, Anh H.; Ono, Taketoshi; Nishijo, Hisao

2014-01-01

Previous studies have reported that multiple brain regions are activated during spatial navigation. However, it is unclear whether these activated brain regions are specifically associated with spatial updating or whether some regions are recruited for parallel cognitive processes. The present study aimed to localize current sources of event related potentials (ERPs) associated with spatial updating specifically. In the control phase of the experiment, electroencephalograms (EEGs) were recorded while subjects sequentially traced 10 blue checkpoints on the streets of a virtual town, which were sequentially connected by a green line, by manipulating a joystick. In the test phase of the experiment, the checkpoints and green line were not indicated. Instead, a tone was presented when the subjects entered the reference points where they were then required to trace the 10 invisible spatial reference points corresponding to the checkpoints. The vertex-positive ERPs with latencies of approximately 340 ms from the moment when the subjects entered the unmarked reference points were significantly larger in the test than in the control phases. Current source density analysis of the ERPs by standardized low-resolution brain electromagnetic tomography (sLORETA) indicated activation of brain regions in the test phase that are associated with place and landmark recognition (entorhinal cortex/hippocampus, parahippocampal and retrosplenial cortices, fusiform, and lingual gyri), detecting self-motion (posterior cingulate and posterior insular cortices), motor planning (superior frontal gyrus, including the medial frontal cortex), and regions that process spatial attention (inferior parietal lobule). The present results provide the first identification of the current sources of ERPs associated with spatial updating, and suggest that multiple systems are active in parallel during spatial updating. PMID:24624067

The need for theory to guide concussion research.

PubMed

Molfese, Dennis L

2015-01-01

Although research into concussion has greatly expanded over the past decade, progress in identifying the mechanisms and consequences of head injury and recovery are largely absent. Instead, data are accumulated without the guidance of a systematic theory to direct research questions or generate testable hypotheses. As part of this special issue on sports concussion, I advance a theory that emphasizes changes in spatial and temporal distributions of the brain's neural networks during normal learning and the disruptions of these networks following injury. Specific predictions are made regarding both the development of the network as well as its breakdown following injury.

High Resolution MALDI Imaging Mass Spectrometry of Retinal Tissue Lipids

NASA Astrophysics Data System (ADS)

Anderson, David M. G.; Ablonczy, Zsolt; Koutalos, Yiannis; Spraggins, Jeffrey; Crouch, Rosalie K.; Caprioli, Richard M.; Schey, Kevin L.

2014-08-01

Matrix assisted laser desorption ionization imaging mass spectrometry (MALDI IMS) has the ability to provide an enormous amount of information on the abundances and spatial distributions of molecules within biological tissues. The rapid progress in the development of this technology significantly improves our ability to analyze smaller and smaller areas and features within tissues. The mammalian eye has evolved over millions of years to become an essential asset for survival, providing important sensory input of an organism's surroundings. The highly complex sensory retina of the eye is comprised of numerous cell types organized into specific layers with varying dimensions, the thinnest of which is the 10 μm retinal pigment epithelium (RPE). This single cell layer and the photoreceptor layer contain the complex biochemical machinery required to convert photons of light into electrical signals that are transported to the brain by axons of retinal ganglion cells. Diseases of the retina, including age-related macular degeneration (AMD), retinitis pigmentosa, and diabetic retinopathy, occur when the functions of these cells are interrupted by molecular processes that are not fully understood. In this report, we demonstrate the use of high spatial resolution MALDI IMS and FT-ICR tandem mass spectrometry in the Abca4 -/- knockout mouse model of Stargardt disease, a juvenile onset form of macular degeneration. The spatial distributions and identity of lipid and retinoid metabolites are shown to be unique to specific retinal cell layers.

Evaluation of Denoising Strategies to Address Motion-Correlated Artifacts in Resting-State Functional Magnetic Resonance Imaging Data from the Human Connectome Project

PubMed Central

Kandala, Sridhar; Nolan, Dan; Laumann, Timothy O.; Power, Jonathan D.; Adeyemo, Babatunde; Harms, Michael P.; Petersen, Steven E.; Barch, Deanna M.

2016-01-01

Abstract Like all resting-state functional connectivity data, the data from the Human Connectome Project (HCP) are adversely affected by structured noise artifacts arising from head motion and physiological processes. Functional connectivity estimates (Pearson's correlation coefficients) were inflated for high-motion time points and for high-motion participants. This inflation occurred across the brain, suggesting the presence of globally distributed artifacts. The degree of inflation was further increased for connections between nearby regions compared with distant regions, suggesting the presence of distance-dependent spatially specific artifacts. We evaluated several denoising methods: censoring high-motion time points, motion regression, the FMRIB independent component analysis-based X-noiseifier (FIX), and mean grayordinate time series regression (MGTR; as a proxy for global signal regression). The results suggest that FIX denoising reduced both types of artifacts, but left substantial global artifacts behind. MGTR significantly reduced global artifacts, but left substantial spatially specific artifacts behind. Censoring high-motion time points resulted in a small reduction of distance-dependent and global artifacts, eliminating neither type. All denoising strategies left differences between high- and low-motion participants, but only MGTR substantially reduced those differences. Ultimately, functional connectivity estimates from HCP data showed spatially specific and globally distributed artifacts, and the most effective approach to address both types of motion-correlated artifacts was a combination of FIX and MGTR. PMID:27571276

[Application of spatial working memory task fMRI in evaluation of primary insomnia patient's cognitive dysfunction].

PubMed

Dou, Shewei; Wang, Enfeng; Zhang, Hongju; Tong, Li; Zhang, Xiaoqi; Shi, Dapeng; Cheng, Jingliang; Li, Yongli

2015-06-02

To explore abnormal brain activation of spatial working memory in primary insomnia and its potential neuromechanism. we recruited 30 cases primary insomnia (PI) patients and 30 cases age, gender matched healthy control (HC) subjects from July 2013 to December 2013, the diagnosis of primary insomnia matched the diagnosis criterion of DSM-IV and Classification and diagnostic criteria of mental disorders in China third edition (CCMD-3). All the subjects attended the tests of PSQI, HAMA, HAMD and index of spatial working memory. And then, we collected the data of routine MRI and spatial working memory task fMRI on 3.0 T MRI scanner. After that, we used SPM8 and REST1.8 to analyze the fMRI data, compared difference of PSQI, HAMA, HAMD, index of spatial working memory and brain activation of spatial working memory between PI group and HC group. There were significant difference between PI group and HC group in PSQI, HAMA, HAMD and index of spatial working memory (P < 0.05). In the spatial working memory related activate brain region, compared with HC group, left temporal lobe, occipital lobe and right frontal lobe activation increased and bilateral parahippocampalis, temporal cortex, frontal cortex and superior parietal lobule activation reduced in PI group. Spatial working memory task fMRI revealed the pathological mechanisms of cognitive dysfunction of clinical spatial working memory and emotional disorder in primary insomnia patients.

Spatial Attention, Motor Intention, and Bayesian Cue Predictability in the Human Brain.

PubMed

Kuhns, Anna B; Dombert, Pascasie L; Mengotti, Paola; Fink, Gereon R; Vossel, Simone

2017-05-24

Predictions about upcoming events influence how we perceive and respond to our environment. There is increasing evidence that predictions may be generated based upon previous observations following Bayesian principles, but little is known about the underlying cortical mechanisms and their specificity for different cognitive subsystems. The present study aimed at identifying common and distinct neural signatures of predictive processing in the spatial attentional and motor intentional system. Twenty-three female and male healthy human volunteers performed two probabilistic cueing tasks with either spatial or motor cues while lying in the fMRI scanner. In these tasks, the percentage of cue validity changed unpredictably over time. Trialwise estimates of cue predictability were derived from a Bayesian observer model of behavioral responses. These estimates were included as parametric regressors for analyzing the BOLD time series. Parametric effects of cue predictability in valid and invalid trials were considered to reflect belief updating by precision-weighted prediction errors. The brain areas exhibiting predictability-dependent effects dissociated between the spatial attention and motor intention task, with the right temporoparietal cortex being involved during spatial attention and the left angular gyrus and anterior cingulate cortex during motor intention. Connectivity analyses revealed that all three areas showed predictability-dependent coupling with the right hippocampus. These results suggest that precision-weighted prediction errors of stimulus locations and motor responses are encoded in distinct brain regions, but that crosstalk with the hippocampus may be necessary to integrate new trialwise outcomes in both cognitive systems. SIGNIFICANCE STATEMENT The brain is able to infer the environments' statistical structure and responds strongly to expectancy violations. In the spatial attentional domain, it has been shown that parts of the attentional networks are sensitive to the predictability of stimuli. It remains unknown, however, whether these effects are ubiquitous or if they are specific for different cognitive systems. The present study compared the influence of model-derived cue predictability on brain activity in the spatial attentional and motor intentional system. We identified areas with distinct predictability-dependent activation for spatial attention and motor intention, but also common connectivity changes of these regions with the hippocampus. These findings provide novel insights into the generality and specificity of predictive processing signatures in the human brain. Copyright © 2017 the authors 0270-6474/17/375334-11$15.00/0.

Application of a data-mining method based on Bayesian networks to lesion-deficit analysis

NASA Technical Reports Server (NTRS)

Herskovits, Edward H.; Gerring, Joan P.

2003-01-01

Although lesion-deficit analysis (LDA) has provided extensive information about structure-function associations in the human brain, LDA has suffered from the difficulties inherent to the analysis of spatial data, i.e., there are many more variables than subjects, and data may be difficult to model using standard distributions, such as the normal distribution. We herein describe a Bayesian method for LDA; this method is based on data-mining techniques that employ Bayesian networks to represent structure-function associations. These methods are computationally tractable, and can represent complex, nonlinear structure-function associations. When applied to the evaluation of data obtained from a study of the psychiatric sequelae of traumatic brain injury in children, this method generates a Bayesian network that demonstrates complex, nonlinear associations among lesions in the left caudate, right globus pallidus, right side of the corpus callosum, right caudate, and left thalamus, and subsequent development of attention-deficit hyperactivity disorder, confirming and extending our previous statistical analysis of these data. Furthermore, analysis of simulated data indicates that methods based on Bayesian networks may be more sensitive and specific for detecting associations among categorical variables than methods based on chi-square and Fisher exact statistics.

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

PubMed

Shehzad, Zarrar; McCarthy, Gregory

2018-06-01

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

The Focus of Spatial Attention Determines the Number and Precision of Face Representations in Working Memory.

PubMed

Towler, John; Kelly, Maria; Eimer, Martin

2016-06-01

The capacity of visual working memory for faces is extremely limited, but the reasons for these limitations remain unknown. We employed event-related brain potential measures to demonstrate that individual faces have to be focally attended in order to be maintained in working memory, and that attention is allocated to only a single face at a time. When 2 faces have to be memorized simultaneously in a face identity-matching task, the focus of spatial attention during encoding predicts which of these faces can be successfully maintained in working memory and matched to a subsequent test face. We also show that memory representations of attended faces are maintained in a position-dependent fashion. These findings demonstrate that the limited capacity of face memory is directly linked to capacity limits of spatial attention during the encoding and maintenance of individual face representations. We suggest that the capacity and distribution of selective spatial attention is a dynamic resource that constrains the capacity and fidelity of working memory for faces. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Vesicular glutamate transporter VGLUT1 has a role in hippocampal long-term potentiation and spatial reversal learning.

PubMed

Balschun, Detlef; Moechars, Diederik; Callaerts-Vegh, Zsuzsanna; Vermaercke, Ben; Van Acker, Nathalie; Andries, Luc; D'Hooge, Rudi

2010-03-01

Vesicular glutamate transporters 1 and 2 (VGLUT1, VGLUT2) show largely complementary distribution in the mature rodent brain and tend to segregate to synapses with different physiological properties. In the hippocampus, VGLUT1 is the dominate subtype in adult animals, whereas VGLUT2 is transiently expressed during early postnatal development. We generated and characterized VGLUT1 knockout mice in order to examine the functional contribution of this transporter to hippocampal synaptic plasticity and hippocampus-dependent spatial learning. Because complete deletion of VGLUT1 resulted in postnatal lethality, we used heterozygous animals for analysis. Here, we report that deletion of VGLUT1 resulted in impaired hippocampal long-term potentiation (LTP) in the CA1 region in vitro. In contrast, heterozygous VGLUT2 mice that were investigated for comparison did not show any changes in LTP. The reduced ability of VGLUT1-deficient mice to express LTP was accompanied by a specific deficit in spatial reversal learning in the water maze. Our data suggest a functional role of VGLUT1 in forms of hippocampal synaptic plasticity that are required to adapt and modify acquired spatial maps to external stimuli and changes.

Human-specific features of spatial gene expression and regulation in eight brain regions.

PubMed

Xu, Chuan; Li, Qian; Efimova, Olga; He, Liu; Tatsumoto, Shoji; Stepanova, Vita; Oishi, Takao; Udono, Toshifumi; Yamaguchi, Katsushi; Shigenobu, Shuji; Kakita, Akiyoshi; Nawa, Hiroyuki; Khaitovich, Philipp; Go, Yasuhiro

2018-06-13

Molecular maps of the human brain alone do not inform us of the features unique to humans. Yet, the identification of these features is important for understanding both the evolution and nature of human cognition. Here, we approached this question by analyzing gene expression and H3K27ac chromatin modification data collected in eight brain regions of humans, chimpanzees, gorillas, a gibbon and macaques. An analysis of spatial transcriptome trajectories across eight brain regions in four primate species revealed 1,851 genes showing human-specific transcriptome differences in one or multiple brain regions, in contrast to 240 chimpanzee-specific ones. More than half of these human-specific differences represented elevated expression of genes enriched in neuronal and astrocytic markers in the human hippocampus, while the rest were enriched in microglial markers and displayed human-specific expression in several frontal cortical regions and the cerebellum. An analysis of the predicted regulatory interactions driving these differences revealed the role of transcription factors in species-specific transcriptome changes, while epigenetic modifications were linked to spatial expression differences conserved across species. Published by Cold Spring Harbor Laboratory Press.

On Expression Patterns and Developmental Origin of Human Brain Regions.

PubMed

Kirsch, Lior; Chechik, Gal

2016-08-01

Anatomical substructures of the human brain have characteristic cell-types, connectivity and local circuitry, which are reflected in area-specific transcriptome signatures, but the principles governing area-specific transcription and their relation to brain development are still being studied. In adult rodents, areal transcriptome patterns agree with the embryonic origin of brain regions, but the processes and genes that preserve an embryonic signature in regional expression profiles were not quantified. Furthermore, it is not clear how embryonic-origin signatures of adult-brain expression interplay with changes in expression patterns during development. Here we first quantify which genes have regional expression-patterns related to the developmental origin of brain regions, using genome-wide mRNA expression from post-mortem adult human brains. We find that almost all human genes (92%) exhibit an expression pattern that agrees with developmental brain-region ontology, but that this agreement changes at multiple phases during development. Agreement is particularly strong in neuron-specific genes, but also in genes that are not spatially correlated with neuron-specific or glia-specific markers. Surprisingly, agreement is also stronger in early-evolved genes. We further find that pairs of similar genes having high agreement to developmental region ontology tend to be more strongly correlated or anti-correlated, and that the strength of spatial correlation changes more strongly in gene pairs with stronger embryonic signatures. These results suggest that transcription regulation of most genes in the adult human brain is spatially tuned in a way that changes through life, but in agreement with development-determined brain regions.

On Expression Patterns and Developmental Origin of Human Brain Regions

PubMed Central

Kirsch, Lior; Chechik, Gal

2016-01-01

Anatomical substructures of the human brain have characteristic cell-types, connectivity and local circuitry, which are reflected in area-specific transcriptome signatures, but the principles governing area-specific transcription and their relation to brain development are still being studied. In adult rodents, areal transcriptome patterns agree with the embryonic origin of brain regions, but the processes and genes that preserve an embryonic signature in regional expression profiles were not quantified. Furthermore, it is not clear how embryonic-origin signatures of adult-brain expression interplay with changes in expression patterns during development. Here we first quantify which genes have regional expression-patterns related to the developmental origin of brain regions, using genome-wide mRNA expression from post-mortem adult human brains. We find that almost all human genes (92%) exhibit an expression pattern that agrees with developmental brain-region ontology, but that this agreement changes at multiple phases during development. Agreement is particularly strong in neuron-specific genes, but also in genes that are not spatially correlated with neuron-specific or glia-specific markers. Surprisingly, agreement is also stronger in early-evolved genes. We further find that pairs of similar genes having high agreement to developmental region ontology tend to be more strongly correlated or anti-correlated, and that the strength of spatial correlation changes more strongly in gene pairs with stronger embryonic signatures. These results suggest that transcription regulation of most genes in the adult human brain is spatially tuned in a way that changes through life, but in agreement with development-determined brain regions. PMID:27564987

Mephedrone (4-Methylmethcathinone): Acute Behavioral Effects, Hyperthermic, and Pharmacokinetic Profile in Rats

PubMed Central

Šíchová, Klára; Pinterová, Nikola; Židková, Monika; Horsley, Rachel R.; Lhotková, Eva; Štefková, Kristýna; Vejmola, Čestmír; Uttl, Libor; Balíková, Marie; Kuchař, Martin; Páleníček, Tomáš

2018-01-01

Mephedrone (MEPH) is a synthetic cathinone derivative with effects that mimic MDMA and/or cocaine. Our study in male Wistar rats provides detailed investigations of MEPH’s and its primary metabolite nor-mephedrone’s (nor-MEPH) pharmacokinetics and bio-distribution to four different substrates (serum, brain, lungs, and liver), as well as comparative analysis of their effects on locomotion [open field test (OFT)] and sensorimotor gating [prepulse inhibition of acoustic startle reaction (PPI ASR)]. Furthermore, in order to mimic the crowded condition where MEPH is typically taken (e.g., clubs), the acute effect of MEPH on thermoregulation in singly- and group-housed rats was evaluated. Pharmacokinetics of MEPH and nor-MEPH after MEPH (5 mg/kg, sc.) were analyzed over 8 h using liquid chromatography with mass spectrometry. MEPH (2.5, 5, or 20 mg/kg, sc.) and nor-MEPH (5 mg/kg, sc.) were administered 5 or 40 min before the behavioral testing in the OFT and PPI ASR; locomotion and its spatial distribution, ASR, habituation and PPI itself were quantified. The effect of MEPH on rectal temperature was measured after 5 and 20 mg/kg, sc. Both MEPH and nor-MEPH were detected in all substrates, with the highest levels detected in lungs. Mean brain: serum ratios were 1:1.19 (MEPH) and 1:1.91 (nor-MEPH), maximum concentrations were observed at 30 min; at 2 and 4 h after administration, nor-MEPH concentrations were higher compared to the parent drug. While neither of the drugs disrupted PPI, both increased locomotion and affected its spatial distribution. The effects of MEPH were dose dependent, rapid, and short-lasting, and the intensity of locomotor stimulant effects was comparable between MEPH and nor-MEPH. Despite the disappearance of behavioral effects within 40 min after administration, MEPH induced rectal temperature elevations that persisted for 3 h even in singly housed rats. To conclude, we observed a robust, short-lasting, and most likely synergistic stimulatory effect of both drugs which corresponded to brain pharmacokinetics. The dissociation between the duration of behavioral and hyperthermic effects is indicative of the possible contribution of nor-MEPH or other biologically active metabolites. This temporal dissociation may be related to the risk of prolonged somatic toxicity when stimulatory effects are no longer present. PMID:29375408

Comprehensive Survey on Improved Focality and Penetration Depth of Transcranial Magnetic Stimulation Employing Multi-Coil Arrays.

PubMed

Wei, Xile; Li, Yao; Lu, Meili; Wang, Jiang; Yi, Guosheng

2017-11-14

Multi-coil arrays applied in transcranial magnetic stimulation (TMS) are proposed to accurately stimulate brain tissues and modulate neural activities by an induced electric field (EF). Composed of numerous independently driven coils, a multi-coil array has alternative energizing strategies to evoke EFs targeting at different cerebral regions. To improve the locating resolution and the stimulating focality, we need to fully understand the variation properties of induced EFs and the quantitative control method of the spatial arrangement of activating coils, both of which unfortunately are still unclear. In this paper, a comprehensive analysis of EF properties was performed based on multi-coil arrays. Four types of planar multi-coil arrays were used to study the relationship between the spatial distribution of EFs and the structure of stimuli coils. By changing coil-driven strategies in a basic 16-coil array, we find that an EF induced by compactly distributed coils decays faster than that induced by dispersedly distributed coils, but the former has an advantage over the latter in terms of the activated brain volume. Simulation results also indicate that the attenuation rate of an EF induced by the 36-coil dense array is 3 times and 1.5 times greater than those induced by the 9-coil array and the 16-coil array, respectively. The EF evoked by the 36-coil dispense array has the slowest decay rate. This result demonstrates that larger multi-coil arrays, compared to smaller ones, activate deeper brain tissues at the expense of decreased focality. A further study on activating a specific field of a prescribed shape and size was conducted based on EF variation. Accurate target location was achieved with a 64-coil array 18 mm in diameter. A comparison between the figure-8 coil, the planar array, and the cap-formed array was made and demonstrates an improvement of multi-coil configurations in the penetration depth and the focality. These findings suggest that there is a tradeoff between attenuation rate and focality in the application of multi-coil arrays. Coil-energizing strategies and array dimensions should be based on an adequate evaluation of these two important demands and the topological structure of target tissues.

Brain functional network changes following Prelimbic area inactivation in a spatial memory extinction task.

PubMed

Méndez-Couz, Marta; Conejo, Nélida M; Vallejo, Guillermo; Arias, Jorge L

2015-01-01

Several studies suggest a prefrontal cortex involvement during the acquisition and consolidation of spatial memory, suggesting an active modulating role at late stages of acquisition processes. Recently, we have reported that the prelimbic and infralimbic areas of the prefrontal cortex, among other structures, are also specifically involved in the late phases of spatial memory extinction. This study aimed to evaluate whether the inactivation of the prelimbic area of the prefrontal cortex impaired spatial memory extinction. For this purpose, male Wistar rats were implanted bilaterally with cannulae into the prelimbic region of the prefrontal cortex. Animals were trained during 5 consecutive days in a hidden platform task and tested for reference spatial memory immediately after the last training session. One day after completing the training task, bilateral infusion of the GABAA receptor agonist Muscimol was performed before the extinction protocol was carried out. Additionally, cytochrome c oxidase histochemistry was applied to map the metabolic brain activity related to the spatial memory extinction under prelimbic cortex inactivation. Results show that animals acquired the reference memory task in the water maze, and the extinction task was successfully completed without significant impairment. However, analysis of the functional brain networks involved by cytochrome oxidase activity interregional correlations showed changes in brain networks between the group treated with Muscimol as compared to the saline-treated group, supporting the involvement of the mammillary bodies at a the late stage in the memory extinction process. Copyright © 2015 Elsevier B.V. All rights reserved.

Transfer Kernel Common Spatial Patterns for Motor Imagery Brain-Computer Interface Classification.

PubMed

Dai, Mengxi; Zheng, Dezhi; Liu, Shucong; Zhang, Pengju

2018-01-01

Motor-imagery-based brain-computer interfaces (BCIs) commonly use the common spatial pattern (CSP) as preprocessing step before classification. The CSP method is a supervised algorithm. Therefore a lot of time-consuming training data is needed to build the model. To address this issue, one promising approach is transfer learning, which generalizes a learning model can extract discriminative information from other subjects for target classification task. To this end, we propose a transfer kernel CSP (TKCSP) approach to learn a domain-invariant kernel by directly matching distributions of source subjects and target subjects. The dataset IVa of BCI Competition III is used to demonstrate the validity by our proposed methods. In the experiment, we compare the classification performance of the TKCSP against CSP, CSP for subject-to-subject transfer (CSP SJ-to-SJ), regularizing CSP (RCSP), stationary subspace CSP (ssCSP), multitask CSP (mtCSP), and the combined mtCSP and ssCSP (ss + mtCSP) method. The results indicate that the superior mean classification performance of TKCSP can achieve 81.14%, especially in case of source subjects with fewer number of training samples. Comprehensive experimental evidence on the dataset verifies the effectiveness and efficiency of the proposed TKCSP approach over several state-of-the-art methods.

Gradient-based reliability maps for ACM-based segmentation of hippocampus.

PubMed

Zarpalas, Dimitrios; Gkontra, Polyxeni; Daras, Petros; Maglaveras, Nicos

2014-04-01

Automatic segmentation of deep brain structures, such as the hippocampus (HC), in MR images has attracted considerable scientific attention due to the widespread use of MRI and to the principal role of some structures in various mental disorders. In this literature, there exists a substantial amount of work relying on deformable models incorporating prior knowledge about structures' anatomy and shape information. However, shape priors capture global shape characteristics and thus fail to model boundaries of varying properties; HC boundaries present rich, poor, and missing gradient regions. On top of that, shape prior knowledge is blended with image information in the evolution process, through global weighting of the two terms, again neglecting the spatially varying boundary properties, causing segmentation faults. An innovative method is hereby presented that aims to achieve highly accurate HC segmentation in MR images, based on the modeling of boundary properties at each anatomical location and the inclusion of appropriate image information for each of those, within an active contour model framework. Hence, blending of image information and prior knowledge is based on a local weighting map, which mixes gradient information, regional and whole brain statistical information with a multi-atlas-based spatial distribution map of the structure's labels. Experimental results on three different datasets demonstrate the efficacy and accuracy of the proposed method.

Transfer Kernel Common Spatial Patterns for Motor Imagery Brain-Computer Interface Classification

PubMed Central

Dai, Mengxi; Liu, Shucong; Zhang, Pengju

2018-01-01

Motor-imagery-based brain-computer interfaces (BCIs) commonly use the common spatial pattern (CSP) as preprocessing step before classification. The CSP method is a supervised algorithm. Therefore a lot of time-consuming training data is needed to build the model. To address this issue, one promising approach is transfer learning, which generalizes a learning model can extract discriminative information from other subjects for target classification task. To this end, we propose a transfer kernel CSP (TKCSP) approach to learn a domain-invariant kernel by directly matching distributions of source subjects and target subjects. The dataset IVa of BCI Competition III is used to demonstrate the validity by our proposed methods. In the experiment, we compare the classification performance of the TKCSP against CSP, CSP for subject-to-subject transfer (CSP SJ-to-SJ), regularizing CSP (RCSP), stationary subspace CSP (ssCSP), multitask CSP (mtCSP), and the combined mtCSP and ssCSP (ss + mtCSP) method. The results indicate that the superior mean classification performance of TKCSP can achieve 81.14%, especially in case of source subjects with fewer number of training samples. Comprehensive experimental evidence on the dataset verifies the effectiveness and efficiency of the proposed TKCSP approach over several state-of-the-art methods. PMID:29743934

On ultrasound-induced microbubble oscillation in a capillary blood vessel and its implications for the blood-brain barrier

NASA Astrophysics Data System (ADS)

Wiedemair, W.; Tuković, Ž.; Jasak, H.; Poulikakos, D.; Kurtcuoglu, V.

2012-02-01

The complex interaction between an ultrasound-driven microbubble and an enclosing capillary microvessel is investigated by means of a coupled, multi-domain numerical model using the finite volume formulation. This system is of interest in the study of transient blood-brain barrier disruption (BBBD) for drug delivery applications. The compliant vessel structure is incorporated explicitly as a distinct domain described by a dedicated physical model. Red blood cells (RBCs) are taken into account as elastic solids in the blood plasma. We report the temporal and spatial development of transmural pressure (Ptm) and wall shear stress (WSS) at the luminal endothelial interface, both of which are candidates for the yet unknown mediator of BBBD. The explicit introduction of RBCs shapes the Ptm and WSS distributions and their derivatives markedly. While the peak values of these mechanical wall parameters are not affected considerably by the presence of RBCs, a pronounced increase in their spatial gradients is observed compared to a configuration with blood plasma alone. The novelty of our work lies in the explicit treatment of the vessel wall, and in the modelling of blood as a composite fluid, which we show to be relevant for the mechanical processes at the endothelium.

A computed tomography-based spatial normalization for the analysis of [18F] fluorodeoxyglucose positron emission tomography of the brain.

PubMed

Cho, Hanna; Kim, Jin Su; Choi, Jae Yong; Ryu, Young Hoon; Lyoo, Chul Hyoung

2014-01-01

We developed a new computed tomography (CT)-based spatial normalization method and CT template to demonstrate its usefulness in spatial normalization of positron emission tomography (PET) images with [(18)F] fluorodeoxyglucose (FDG) PET studies in healthy controls. Seventy healthy controls underwent brain CT scan (120 KeV, 180 mAs, and 3 mm of thickness) and [(18)F] FDG PET scans using a PET/CT scanner. T1-weighted magnetic resonance (MR) images were acquired for all subjects. By averaging skull-stripped and spatially-normalized MR and CT images, we created skull-stripped MR and CT templates for spatial normalization. The skull-stripped MR and CT images were spatially normalized to each structural template. PET images were spatially normalized by applying spatial transformation parameters to normalize skull-stripped MR and CT images. A conventional perfusion PET template was used for PET-based spatial normalization. Regional standardized uptake values (SUV) measured by overlaying the template volume of interest (VOI) were compared to those measured with FreeSurfer-generated VOI (FSVOI). All three spatial normalization methods underestimated regional SUV values by 0.3-20% compared to those measured with FSVOI. The CT-based method showed slightly greater underestimation bias. Regional SUV values derived from all three spatial normalization methods were correlated significantly (p < 0.0001) with those measured with FSVOI. CT-based spatial normalization may be an alternative method for structure-based spatial normalization of [(18)F] FDG PET when MR imaging is unavailable. Therefore, it is useful for PET/CT studies with various radiotracers whose uptake is expected to be limited to specific brain regions or highly variable within study population.

Spatial information is processed even when it is task-irrelevant: implications for neuroimaging task design.

PubMed

Meegan, Daniel V; Honsberger, Michael J M

2005-05-01

Many neuroimaging studies have been designed to differentiate domain-specific processes in the brain. A common design constraint is to use identical stimuli for different domain-specific tasks. For example, an experiment investigating spatial versus identity processing would present compound spatial-identity stimuli in both spatial and identity tasks, and participants would be instructed to attend to, encode, maintain, or retrieve spatial information in the spatial task, and identity information in the identity task. An assumption in such studies is that spatial information will not be processed in the identity task, as it is irrelevant for that task. We report three experiments demonstrating violations of this assumption. Our results suggest that comparisons of spatial and identity tasks in existing neuroimaging studies have underestimated the amount of brain activation that is spatial-specific. For future neuroimaging studies, we recommend unique stimulus displays for each domain-specific task, and event-related measurement of post-stimulus processing.

Intraoperative virtual brain counseling

NASA Astrophysics Data System (ADS)

Jiang, Zhaowei; Grosky, William I.; Zamorano, Lucia J.; Muzik, Otto; Diaz, Fernando

1997-06-01

Our objective is to offer online real-tim e intelligent guidance to the neurosurgeon. Different from traditional image-guidance technologies that offer intra-operative visualization of medical images or atlas images, virtual brain counseling goes one step further. It can distinguish related brain structures and provide information about them intra-operatively. Virtual brain counseling is the foundation for surgical planing optimization and on-line surgical reference. It can provide a warning system that alerts the neurosurgeon if the chosen trajectory will pass through eloquent brain areas. In order to fulfill this objective, tracking techniques are involved for intra- operativity. Most importantly, a 3D virtual brian environment, different from traditional 3D digitized atlases, is an object-oriented model of the brain that stores information about different brain structures together with their elated information. An object-oriented hierarchical hyper-voxel space (HHVS) is introduced to integrate anatomical and functional structures. Spatial queries based on position of interest, line segment of interest, and volume of interest are introduced in this paper. The virtual brain environment is integrated with existing surgical pre-planning and intra-operative tracking systems to provide information for planning optimization and on-line surgical guidance. The neurosurgeon is alerted automatically if the planned treatment affects any critical structures. Architectures such as HHVS and algorithms, such as spatial querying, normalizing, and warping are presented in the paper. A prototype has shown that the virtual brain is intuitive in its hierarchical 3D appearance. It also showed that HHVS, as the key structure for virtual brain counseling, efficiently integrates multi-scale brain structures based on their spatial relationships.This is a promising development for optimization of treatment plans and online surgical intelligent guidance.

Simulation study of a high performance brain PET system with dodecahedral geometry.

PubMed

Tao, Weijie; Chen, Gaoyu; Weng, Fenghua; Zan, Yunlong; Zhao, Zhixiang; Peng, Qiyu; Xu, Jianfeng; Huang, Qiu

2018-05-25

In brain imaging, the spherical PET system achieves the highest sensitivity when the solid angle is concerned. However it is not practical. In this work we designed an alternative sphere-like scanner, the dodecahedral scanner, which has a high sensitivity in imaging and a high feasibility to manufacture. We simulated this system and compared the performance with a few other dedicated brain PET systems. Monte Carlo simulations were conducted to generate data of the dedicated brain PET system with the dodecahedral geometry (11 regular pentagon detectors). The data were then reconstructed using the in-house developed software with the fully three-dimensional maximum-likelihood expectation maximization (3D-MLEM) algorithm. Results show that the proposed system has a high sensitivity distribution for the whole field of view (FOV). With a depth-of-interaction (DOI) resolution around 6.67 mm, the proposed system achieves the spatial resolution of 1.98 mm. Our simulation study also shows that the proposed system improves the image contrast and reduces noise compared with a few other dedicated brain PET systems. Finally, simulations with the Hoffman phantom show the potential application of the proposed system in clinical applications. In conclusion, the proposed dodecahedral PET system is potential for widespread applications in high-sensitivity, high-resolution PET imaging, to lower the injected dose. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

A systematic review of associations between functional MRI activity and polygenic risk for schizophrenia and bipolar disorder.

PubMed

Dezhina, Zalina; Ranlund, Siri; Kyriakopoulos, Marinos; Williams, Steve C R; Dima, Danai

2018-05-10

Genetic factors account for up to 80% of the liability for schizophrenia (SCZ) and bipolar disorder (BD). Genome-wide association studies have successfully identified several genes associated with increased risk for both disorders. This has allowed researchers to model the aggregate effect of genes associated with disease status and create a polygenic risk score (PGRS) for each individual. The interest in imaging genetics using PGRS has grown in recent years, with several studies now published. We have conducted a systematic review to examine the effects of PGRS of SCZ, BD and cross psychiatric disorders on brain function and connectivity using fMRI data. Results indicate that the effect of genetic load for SCZ and BD on brain function affects task-related recruitment, with frontal areas having a more prominent role, independent of task. Additionally, the results suggest that the polygenic architecture of psychotic disorders is not regionally confined but impacts on the task-dependent recruitment of multiple brain regions. Future imaging genetics studies with large samples, especially population studies, would be uniquely informative in mapping the spatial distribution of the genetic risk to psychiatric disorders on brain processes during various cognitive tasks and may lead to the discovery of biological pathways that could be crucial in mediating the link between genetic factors and alterations in brain networks.

Spatial constancy mechanisms in motor control

PubMed Central

Medendorp, W. Pieter

2011-01-01

The success of the human species in interacting with the environment depends on the ability to maintain spatial stability despite the continuous changes in sensory and motor inputs owing to movements of eyes, head and body. In this paper, I will review recent advances in the understanding of how the brain deals with the dynamic flow of sensory and motor information in order to maintain spatial constancy of movement goals. The first part summarizes studies in the saccadic system, showing that spatial constancy is governed by a dynamic feed-forward process, by gaze-centred remapping of target representations in anticipation of and across eye movements. The subsequent sections relate to other oculomotor behaviour, such as eye–head gaze shifts, smooth pursuit and vergence eye movements, and their implications for feed-forward mechanisms for spatial constancy. Work that studied the geometric complexities in spatial constancy and saccadic guidance across head and body movements, distinguishing between self-generated and passively induced motion, indicates that both feed-forward and sensory feedback processing play a role in spatial updating of movement goals. The paper ends with a discussion of the behavioural mechanisms of spatial constancy for arm motor control and their physiological implications for the brain. Taken together, the emerging picture is that the brain computes an evolving representation of three-dimensional action space, whose internal metric is updated in a nonlinear way, by optimally integrating noisy and ambiguous afferent and efferent signals. PMID:21242137

Brain activity during auditory and visual phonological, spatial and simple discrimination tasks.

PubMed

Salo, Emma; Rinne, Teemu; Salonen, Oili; Alho, Kimmo

2013-02-16

We used functional magnetic resonance imaging to measure human brain activity during tasks demanding selective attention to auditory or visual stimuli delivered in concurrent streams. Auditory stimuli were syllables spoken by different voices and occurring in central or peripheral space. Visual stimuli were centrally or more peripherally presented letters in darker or lighter fonts. The participants performed a phonological, spatial or "simple" (speaker-gender or font-shade) discrimination task in either modality. Within each modality, we expected a clear distinction between brain activations related to nonspatial and spatial processing, as reported in previous studies. However, within each modality, different tasks activated largely overlapping areas in modality-specific (auditory and visual) cortices, as well as in the parietal and frontal brain regions. These overlaps may be due to effects of attention common for all three tasks within each modality or interaction of processing task-relevant features and varying task-irrelevant features in the attended-modality stimuli. Nevertheless, brain activations caused by auditory and visual phonological tasks overlapped in the left mid-lateral prefrontal cortex, while those caused by the auditory and visual spatial tasks overlapped in the inferior parietal cortex. These overlapping activations reveal areas of multimodal phonological and spatial processing. There was also some evidence for intermodal attention-related interaction. Most importantly, activity in the superior temporal sulcus elicited by unattended speech sounds was attenuated during the visual phonological task in comparison with the other visual tasks. This effect might be related to suppression of processing irrelevant speech presumably distracting the phonological task involving the letters. Copyright © 2012 Elsevier B.V. All rights reserved.

The Relation between Gray Matter Morphology and Divergent Thinking in Adolescents and Young Adults

PubMed Central

Zanolie, Kiki; Kleibeuker, Sietske W.; Crone, Eveline A.

2014-01-01

Adolescence and early adulthood are developmental time periods during which creative cognition is highly important for adapting to environmental changes. Divergent thinking, which refers to generating novel and useful solutions to open-ended problems, has often been used as a measure of creative cognition. The first goal of this structural neuroimaging study was to elucidate the relationship between gray matter morphology and performance in the verbal (AUT; alternative uses task) and visuo-spatial (CAT; creative ability test) domain of divergent thinking in adolescents and young adults. The second goal was to test if gray matter morphology is related to brain activity during AUT performance. Neural and behavioral data were combined from a cross-sectional study including 25 adolescents aged 15–17 and 20 young adults aged 25–30. Brain-behavior relationships were assessed without a priori location assumptions and within areas that were activated during an AUT-scanner task. Gray matter volume and cortical thickness were not significantly associated with verbal divergent thinking. However, visuo-spatial divergent thinking (CAT originality and fluency) was positively associated with cortical thickness of the right middle temporal gyrus and left brain areas including the superior frontal gyrus and various occipital, parietal, and temporal areas, independently of age. AUT brain activity was not associated with cortical thickness. The results support an important role of a widespread brain network involved in flexible visuo-spatial divergent thinking, providing evidence for a relation between cortical thickness and visuo-spatial divergent thinking in adolescents and young adults. However, studies including visuo-spatial divergent thinking tasks in the scanner are warranted. PMID:25514366

3D Holographic Observatory for Long-term Monitoring of Complex Behaviors in Drosophila

NASA Astrophysics Data System (ADS)

Kumar, S. Santosh; Sun, Yaning; Zou, Sige; Hong, Jiarong

2016-09-01

Drosophila is an excellent model organism towards understanding the cognitive function, aging and neurodegeneration in humans. The effects of aging and other long-term dynamics on the behavior serve as important biomarkers in identifying such changes to the brain. In this regard, we are presenting a new imaging technique for lifetime monitoring of Drosophila in 3D at spatial and temporal resolutions capable of resolving the motion of limbs and wings using holographic principles. The developed system is capable of monitoring and extracting various behavioral parameters, such as ethograms and spatial distributions, from a group of flies simultaneously. This technique can image complicated leg and wing motions of flies at a resolution, which allows capturing specific landing responses from the same data set. Overall, this system provides a unique opportunity for high throughput screenings of behavioral changes in 3D over a long term in Drosophila.

Endocannabinoid dysregulation in cognitive and stress-related brain regions in the Nrg1 mouse model of schizophrenia.

PubMed

Clarke, David J; Stuart, Jordyn; McGregor, Iain S; Arnold, Jonathon C

2017-01-04

The endocannabinoid system is dysregulated in schizophrenia. Mice with heterozygous deletion of neuregulin 1 (Nrg1 HET mice) provide a well-characterised animal model of schizophrenia, and display enhanced sensitivity to stress and cannabinoids during adolescence. However, no study has yet determined whether these mice have altered brain endocannabinoid concentrations. Nrg1 application to hippocampal slices decreased 2-arachidonoylglycerol (2-AG) signalling and disrupted long-term depression, a form of synaptic plasticity critical to spatial learning. Therefore we specifically aimed to examine whether Nrg1 HET mice exhibit increased 2-AG concentrations and disruption of spatial learning. As chronic stress influences brain endocannabinoids, we also sought to examine whether Nrg1 deficiency moderates adolescent stress-induced alterations in brain endocannabinoids. Adolescent Nrg1 HET and wild-type (WT) mice were submitted to chronic restraint stress and brain endocannabinoid concentrations were analysed. A separate cohort of WT and Nrg1 HET mice was also assessed for spatial learning performance in the Morris Water Maze. Partial genetic deletion of Nrg1 increased anandamide concentrations in the amygdala and decreased 2-AG concentrations in the hypothalamus. Further, Nrg1 HET mice exhibited increased 2-AG concentrations in the hippocampus and impaired spatial learning performance. Chronic adolescent stress increased anandamide concentrations in the amygdala, however, Nrg1 disruption did not influence this stress-induced change. These results demonstrate for the first time in vivo interplay between Nrg1 and endocannabinoids in the brain. Our results demonstrate that aberrant Nrg1 and endocannabinoid signalling may cooperate in the hippocampus to impair cognition, and that Nrg1 deficiency alters endocannabinoid signalling in brain stress circuitry. Copyright © 2016 Elsevier Inc. All rights reserved.

Reducing Sensor Noise in MEG and EEG Recordings Using Oversampled Temporal Projection.

PubMed

Larson, Eric; Taulu, Samu

2018-05-01

Here, we review the theory of suppression of spatially uncorrelated, sensor-specific noise in electro- and magentoencephalography (EEG and MEG) arrays, and introduce a novel method for suppression. Our method requires only that the signals of interest are spatially oversampled, which is a reasonable assumption for many EEG and MEG systems. Our method is based on a leave-one-out procedure using overlapping temporal windows in a mathematical framework to project spatially uncorrelated noise in the temporal domain. This method, termed "oversampled temporal projection" (OTP), has four advantages over existing methods. First, sparse channel-specific artifacts are suppressed while limiting mixing with other channels, whereas existing linear, time-invariant spatial operators can spread such artifacts to other channels with a spatial distribution which can be mistaken for one produced by an electrophysiological source. Second, OTP minimizes distortion of the spatial configuration of the data. During source localization (e.g., dipole fitting), many spatial methods require corresponding modification of the forward model to avoid bias, while OTP does not. Third, noise suppression factors at the sensor level are maintained during source localization, whereas bias compensation removes the denoising benefit for spatial methods that require such compensation. Fourth, OTP uses a time-window duration parameter to control the tradeoff between noise suppression and adaptation to time-varying sensor characteristics. OTP efficiently optimizes noise suppression performance while controlling for spatial bias of the signal of interest. This is important in applications where sensor noise significantly limits the signal-to-noise ratio, such as high-frequency brain oscillations.

Visuo-Spatial Processing in Autism--Testing the Predictions of Extreme Male Brain Theory

ERIC Educational Resources Information Center

Falter, Christine M.; Plaisted, Kate C.; Davis, Greg

2008-01-01

It has been hypothesised that autism is an extreme version of the male brain, caused by high levels of prenatal testosterone (Baron-Cohen 1999). To test this proposal, associations were assessed between three visuo-spatial tasks and prenatal testosterone, indexed in second-to-fourth digit length ratios (2D:4D). The study included children with…

Brain Regions Involved in the Retrieval of Spatial and Episodic Details Associated with a Familiar Environment: An fMRI Study

ERIC Educational Resources Information Center

Hirshhorn, Marnie; Grady, Cheryl; Rosenbaum, R. Shayna; Winocur, Gordon; Moscovitch, Morris

2012-01-01

Functional magnetic resonance imaging (fMRI) was used to compare brain activity during the retrieval of coarse- and fine-grained spatial details and episodic details associated with a familiar environment. Long-time Toronto residents compared pairs of landmarks based on their absolute geographic locations (requiring either coarse or fine…

Asymmetrical Brain Activity Induced by Voluntary Spatial Attention Depends on the Visual Hemifield: A Functional Near-Infrared Spectroscopy Study

ERIC Educational Resources Information Center

Harasawa, Masamitsu; Shioiri, Satoshi

2011-01-01

The effect of the visual hemifield to which spatial attention was oriented on the activities of the posterior parietal and occipital visual cortices was examined using functional near-infrared spectroscopy in order to investigate the neural substrates of voluntary visuospatial attention. Our brain imaging data support the theory put forth in a…

Connectopic mapping with resting-state fMRI.

PubMed

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.

A variational Bayes spatiotemporal model for electromagnetic brain mapping.

PubMed

Nathoo, F S; Babul, A; Moiseev, A; Virji-Babul, N; Beg, M F

2014-03-01

In this article, we present a new variational Bayes approach for solving the neuroelectromagnetic inverse problem arising in studies involving electroencephalography (EEG) and magnetoencephalography (MEG). This high-dimensional spatiotemporal estimation problem involves the recovery of time-varying neural activity at a large number of locations within the brain, from electromagnetic signals recorded at a relatively small number of external locations on or near the scalp. Framing this problem within the context of spatial variable selection for an underdetermined functional linear model, we propose a spatial mixture formulation where the profile of electrical activity within the brain is represented through location-specific spike-and-slab priors based on a spatial logistic specification. The prior specification accommodates spatial clustering in brain activation, while also allowing for the inclusion of auxiliary information derived from alternative imaging modalities, such as functional magnetic resonance imaging (fMRI). We develop a variational Bayes approach for computing estimates of neural source activity, and incorporate a nonparametric bootstrap for interval estimation. The proposed methodology is compared with several alternative approaches through simulation studies, and is applied to the analysis of a multimodal neuroimaging study examining the neural response to face perception using EEG, MEG, and fMRI. © 2013, The International Biometric Society.

Design analysis of an MPI human functional brain scanner

PubMed Central

Mason, Erica E.; Cooley, Clarissa Z.; Cauley, Stephen F.; Griswold, Mark A.; Conolly, Steven M.; Wald, Lawrence L.

2017-01-01

MPI’s high sensitivity makes it a promising modality for imaging brain function. Functional contrast is proposed based on blood SPION concentration changes due to Cerebral Blood Volume (CBV) increases during activation, a mechanism utilized in fMRI studies. MPI offers the potential for a direct and more sensitive measure of SPION concentration, and thus CBV, than fMRI. As such, fMPI could surpass fMRI in sensitivity, enhancing the scientific and clinical value of functional imaging. As human-sized MPI systems have not been attempted, we assess the technical challenges of scaling MPI from rodent to human brain. We use a full-system MPI simulator to test arbitrary hardware designs and encoding practices, and we examine tradeoffs imposed by constraints that arise when scaling to human size as well as safety constraints (PNS and central nervous system stimulation) not considered in animal scanners, thereby estimating spatial resolutions and sensitivities achievable with current technology. Using a projection FFL MPI system, we examine coil hardware options and their implications for sensitivity and spatial resolution. We estimate that an fMPI brain scanner is feasible, although with reduced sensitivity (20×) and spatial resolution (5×) compared to existing rodent systems. Nonetheless, it retains sufficient sensitivity and spatial resolution to make it an attractive future instrument for studying the human brain; additional technical innovations can result in further improvements. PMID:28752130

Effects of inhibitory theta burst TMS to different brain sites involved in visuospatial attention - a combined neuronavigated cTBS and behavioural study.

PubMed

Platz, Thomas; Schüttauf, Johannes; Aschenbach, Julia; Mengdehl, Christine; Lotze, Martin

2016-01-01

The study sought to alter visual spatial attention in young healthy subjects by a neuronavigated inhibitory rTMS protocol (cTBS-600) to right brain areas thought to be involved in visual attentional processes, i.e. the temporoparietal junction (TPJ) and the posterior middle frontal gyrus (pMFG), and to test the reversibility of effects by an additional consecutive cTBS to the homologue left brain cortical areas. Healthy subjects showed a leftward bias of the egocentric perspective for both visual-perceptive and visual-exploratory tasks specifically for items presented in the left hemifield. cTBS to the right TPJ, and less systematically to the right pMFG reduced this bias for visuo-spatial and exploratory visuo-motor behaviour. Further, a consecutive cTBS to the left TPJ changed the bias again towards the left for a visual-perceptive task. The evidence supports the notion of an involvement of the right TPJ (and pMFG) in spatial visual attention. The observations further indicate that inhibitory non-invasive brain stimulation (cTBS) to the left TPJ has a potential for reversing a rightward bias of spatial attention when the right TPJ is dysfunctional. Accordingly, the findings could have implications for therapeutic rTMS development for right brain damaged patients with visual neglect.

Spatial Segregation of γ-Secretase and Substrates in Distinct Membrane Domains*

PubMed Central

Vetrivel, Kulandaivelu S.; Cheng, Haipeng; Kim, Seong-Hun; Chen, Ying; Barnes, Natalie Y.; Parent, Ange‘le T.; Sisodia, Sangram S.; Thinakaran, Gopal

2005-01-01

γ-Secretase facilitates the regulated intramembrane proteolysis of select type I membrane proteins that play diverse physiological roles in multiple cell types and tissue. In this study, we used biochemical approaches to examine the distribution of amyloid precursor protein (APP) and several additional γ-secretase substrates in membrane microdomains. We report that APP C-terminal fragments (CTFs) and γ-secretase reside in Lubrol WX detergent-insoluble membranes (DIM) of cultured cells and adult mouse brain. APP CTFs that accumulate in cells lacking γ-secretase activity preferentially associate with DIM. Cholesterol depletion and magnetic im-munoisolation studies indicate recruitment of APP CTFs into cholesterol- and sphingolipid-rich lipid rafts, and co-residence of APP CTFs, PS1, and syntaxin 6 in DIM patches derived from the trans-Golgi network. Photoaffinity cross-linking studies provided evidence for the preponderance of active γ-secretase in lipid rafts of cultured cells and adult brain. Remarkably, unlike the case of APP, CTFs derived from Notch1, Jagged2, deleted in colorectal cancer (DCC), and N-cadherin remain largely detergent-soluble, indicative of their spatial segregation in non-raft domains. In embryonic brain, the majority of PS1 and nicastrin is present in Lubrol WX-soluble membranes, wherein the CTFs derived from APP, Notch1, DCC, and N-cadherin also reside. We suggest that γ-secretase residence in non-raft membranes facilitates proteolysis of diverse substrates during embryonic development but that the translocation of γ-secretase to lipid rafts in adults ensures processing of certain substrates, including APP CTFs, while limiting processing of other potential substrates. PMID:15886206

Spatial segregation of gamma-secretase and substrates in distinct membrane domains.

PubMed

Vetrivel, Kulandaivelu S; Cheng, Haipeng; Kim, Seong-Hun; Chen, Ying; Barnes, Natalie Y; Parent, Angèle T; Sisodia, Sangram S; Thinakaran, Gopal

2005-07-08

Gamma-secretase facilitates the regulated intramembrane proteolysis of select type I membrane proteins that play diverse physiological roles in multiple cell types and tissue. In this study, we used biochemical approaches to examine the distribution of amyloid precursor protein (APP) and several additional gamma-secretase substrates in membrane microdomains. We report that APP C-terminal fragments (CTFs) and gamma-secretase reside in Lubrol WX detergent-insoluble membranes (DIM) of cultured cells and adult mouse brain. APP CTFs that accumulate in cells lacking gamma-secretase activity preferentially associate with DIM. Cholesterol depletion and magnetic immunoisolation studies indicate recruitment of APP CTFs into cholesterol- and sphingolipid-rich lipid rafts, and co-residence of APP CTFs, PS1, and syntaxin 6 in DIM patches derived from the trans-Golgi network. Photoaffinity cross-linking studies provided evidence for the preponderance of active gamma-secretase in lipid rafts of cultured cells and adult brain. Remarkably, unlike the case of APP, CTFs derived from Notch1, Jagged2, deleted in colorectal cancer (DCC), and N-cadherin remain largely detergent-soluble, indicative of their spatial segregation in non-raft domains. In embryonic brain, the majority of PS1 and nicastrin is present in Lubrol WX-soluble membranes, wherein the CTFs derived from APP, Notch1, DCC, and N-cadherin also reside. We suggest that gamma-secretase residence in non-raft membranes facilitates proteolysis of diverse substrates during embryonic development but that the translocation of gamma-secretase to lipid rafts in adults ensures processing of certain substrates, including APP CTFs, while limiting processing of other potential substrates.

Application of fast-scan cyclic voltammetry for the in vivo characterization of optically evoked dopamine in the olfactory tubercle of the rat brain.

PubMed

Wakabayashi, Ken T; Bruno, Michael J; Bass, Caroline E; Park, Jinwoo

2016-06-21

The olfactory tubercle (OT), as a component of the ventral striatum, serves as an important multisensory integration center for reward-related processes in the brain. Recent studies show that dense dopaminergic innervation from the ventral tegmental area (VTA) into the OT may play an outsized role in disorders such as psychostimulant addiction and disorders of motivation, increasing recent scientific interest in this brain region. However, due to its anatomical inaccessibility, relative small size, and proximity to other dopamine-rich structures, neurochemical assessments using conventional methods cannot be readily employed. Here, we investigated dopamine (DA) regulation in the OT of urethane-anesthetized rats using in vivo fast-scan voltammetry (FSCV) coupled with carbon-fiber microelectrodes, following optogenetic stimulation of the VTA. The results were compared with DA regulation in the nucleus accumbens (NAc), a structure located adjacent to the OT and which also receives dense DA innervation from the VTA. FSCV coupled with optically evoked release allowed us to investigate the spatial distribution of DA in the OT and characterize OT DA dynamics (release and clearance) with subsecond temporal and micrometer spatial resolution for the first time. In this study, we demonstrated that DA transporters play an important role in regulating DA in the OT. However, the control of extracellular DA by uptake in the OT was less than in the NAc. The difference in DA transmission in the terminal fields of the OT and NAc may be involved in region-specific responses to drugs of abuse and contrasting roles in mediating reward-related behavior.

Multi-scale integration and predictability in resting state brain activity

PubMed Central

Kolchinsky, Artemy; van den Heuvel, Martijn P.; Griffa, Alessandra; Hagmann, Patric; Rocha, Luis M.; Sporns, Olaf; Goñi, Joaquín

2014-01-01

The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales. PMID:25104933

Reconstruction of human brain spontaneous activity based on frequency-pattern analysis of magnetoencephalography data

PubMed Central

Llinás, Rodolfo R.; Ustinin, Mikhail N.; Rykunov, Stanislav D.; Boyko, Anna I.; Sychev, Vyacheslav V.; Walton, Kerry D.; Rabello, Guilherme M.; Garcia, John

2015-01-01

A new method for the analysis and localization of brain activity has been developed, based on multichannel magnetic field recordings, over minutes, superimposed on the MRI of the individual. Here, a high resolution Fourier Transform is obtained over the entire recording period, leading to a detailed multi-frequency spectrum. Further analysis implements a total decomposition of the frequency components into functionally invariant entities, each having an invariant field pattern localizable in recording space. The method, addressed as functional tomography, makes it possible to find the distribution of magnetic field sources in space. Here, the method is applied to the analysis of simulated data, to oscillating signals activating a physical current dipoles phantom, and to recordings of spontaneous brain activity in 10 healthy adults. In the analysis of simulated data, 61 dipoles are localized with 0.7 mm precision. Concerning the physical phantom the method is able to localize three simultaneously activated current dipoles with 1 mm precision. Spatial resolution 3 mm was attained when localizing spontaneous alpha rhythm activity in 10 healthy adults, where the alpha peak was specified for each subject individually. Co-registration of the functional tomograms with each subject's head MRI localized alpha range activity to the occipital and/or posterior parietal brain region. This is the first application of this new functional tomography to human brain activity. The method successfully provides an overall view of brain electrical activity, a detailed spectral description and, combined with MRI, the localization of sources in anatomical brain space. PMID:26528119

Optically enhanced blood-brain-barrier crossing of plasmonic-active nanoparticles in preclinical brain tumor animal models

NASA Astrophysics Data System (ADS)

Yuan, Hsiangkuo; Wilson, Christy M.; Li, Shuqin; Fales, Andrew M.; Liu, Yang; Grant, Gerald; Vo-Dinh, Tuan

2014-02-01

Nanotechnology provides tremendous biomedical opportunities for cancer diagnosis, imaging, and therapy. In contrast to conventional chemotherapeutic agents where their actual target delivery cannot be easily imaged, integrating imaging and therapeutic properties into one platform facilitates the understanding of pharmacokinetic profiles, and enables monitoring of the therapeutic process in each individual. Such a concept dubbed "theranostics" potentiates translational research and improves precision medicine. One particular challenging application of theranostics involves imaging and controlled delivery of nanoplatforms across blood-brain-barrier (BBB) into brain tissues. Typically, the BBB hinders paracellular flux of drug molecules into brain parenchyma. BBB disrupting agents (e.g. mannitol, focused ultrasound), however, suffer from poor spatial confinement. It has been a challenge to design a nanoplatform not only acts as a contrast agent but also improves the BBB permeation. In this study, we demonstrated the feasibility of plasmonic gold nanoparticles as both high-resolution optical contrast agent and focalized tumor BBB permeation-inducing agent. We specifically examined the microscopic distribution of nanoparticles in tumor brain animal models. We observed that most nanoparticles accumulated at the tumor periphery or perivascular spaces. Nanoparticles were present in both endothelial cells and interstitial matrices. This study also demonstrated a novel photothermal-induced BBB permeation. Fine-tuning the irradiating energy induced gentle disruption of the vascular integrity, causing short-term extravasation of nanomaterials but without hemorrhage. We conclude that our gold nanoparticles are a powerful biocompatible contrast agent capable of inducing focal BBB permeation, and therefore envision a strong potential of plasmonic gold nanoparticle in future brain tumor imaging and therapy.

The corpus callosum in primates: processing speed of axons and the evolution of hemispheric asymmetry

PubMed Central

Phillips, Kimberley A.; Stimpson, Cheryl D.; Smaers, Jeroen B.; Raghanti, Mary Ann; Jacobs, Bob; Popratiloff, Anastas; Hof, Patrick R.; Sherwood, Chet C.

2015-01-01

Interhemispheric communication may be constrained as brain size increases because of transmission delays in action potentials over the length of axons. Although one might expect larger brains to have progressively thicker axons to compensate, spatial packing is a limiting factor. Axon size distributions within the primate corpus callosum (CC) may provide insights into how these demands affect conduction velocity. We used electron microscopy to explore phylogenetic variation in myelinated axon density and diameter of the CC from 14 different anthropoid primate species, including humans. The majority of axons were less than 1 µm in diameter across all species, indicating that conduction velocity for most interhemispheric communication is relatively constant regardless of brain size. The largest axons within the upper 95th percentile scaled with a progressively higher exponent than the median axons towards the posterior region of the CC. While brain mass among the primates in our analysis varied by 97-fold, estimates of the fastest cross-brain conduction times, as conveyed by axons at the 95th percentile, varied within a relatively narrow range between 3 and 9 ms across species, whereas cross-brain conduction times for the median axon diameters differed more substantially between 11 and 38 ms. Nonetheless, for both size classes of axons, an increase in diameter does not entirely compensate for the delay in interhemispheric transmission time that accompanies larger brain size. Such biophysical constraints on the processing speed of axons conveyed by the CC may play an important role in the evolution of hemispheric asymmetry. PMID:26511047

A Plea for Right Brain Usage.

ERIC Educational Resources Information Center

Lord, Thomas R.

1984-01-01

The visuo-spatial centers of the right brain are crucial to being able to problem solve or conceptualize (two abilities necessary for success in understanding science). Yet, current educational format is almost exclusively a left-brain undertaking. Reasons why educators should emphasize right-brain understanding in educational curricula at all…

Relationship of grey and white matter abnormalities with distance from the surface of the brain in multiple sclerosis.

PubMed

Pardini, Matteo; Sudre, Carole H; Prados, Ferran; Yaldizli, Özgür; Sethi, Varun; Muhlert, Nils; Samson, Rebecca S; van de Pavert, Steven H; Cardoso, M Jorge; Ourselin, Sebastien; Gandini Wheeler-Kingshott, Claudia A M; Miller, David H; Chard, Declan T

2016-11-01

To assess the association between proximity to the inner (ventricular and aqueductal) and outer (pial) surfaces of the brain and the distribution of normal appearing white matter (NAWM) and grey matter (GM) abnormalities, and white matter (WM) lesions, in multiple sclerosis (MS). 67 people with relapse-onset MS and 30 healthy controls were included in the study. Volumetric T1 images and high-resolution (1 mm 3 ) magnetisation transfer ratio (MTR) images were acquired and segmented into 12 bands between the inner and outer surfaces of the brain. The first and last bands were discarded to limit partial volume effects with cerebrospinal fluid. MTR values were computed for all bands in supratentorial NAWM, cerebellar NAWM and brainstem NA tissue, and deep and cortical GM. Band WM lesion volumes were also measured. Proximity to the ventricular surfaces was associated with progressively lower MTR values in the MS group but not in controls in supratentorial and cerebellar NAWM, brainstem NA and in deep and cortical GM. The density of WM lesions was associated with proximity to the ventricles only in the supratentorial compartment, and no link was found with distance from the pial surfaces. In MS, MTR abnormalities in NAWM and GM are related to distance from the inner and outer surfaces of the brain, and this suggests that there is a common factor underlying their spatial distribution. A similar pattern was not found for WM lesions, raising the possibility that different factors promote their formation. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Tracking the Spatiotemporal Neural Dynamics of Real-world Object Size and Animacy in the Human Brain.

PubMed

Khaligh-Razavi, Seyed-Mahdi; Cichy, Radoslaw Martin; Pantazis, Dimitrios; Oliva, Aude

2018-06-07

Animacy and real-world size are properties that describe any object and thus bring basic order into our perception of the visual world. Here, we investigated how the human brain processes real-world size and animacy. For this, we applied representational similarity to fMRI and MEG data to yield a view of brain activity with high spatial and temporal resolutions, respectively. Analysis of fMRI data revealed that a distributed and partly overlapping set of cortical regions extending from occipital to ventral and medial temporal cortex represented animacy and real-world size. Within this set, parahippocampal cortex stood out as the region representing animacy and size stronger than most other regions. Further analysis of the detailed representational format revealed differences among regions involved in processing animacy. Analysis of MEG data revealed overlapping temporal dynamics of animacy and real-world size processing starting at around 150 msec and provided the first neuromagnetic signature of real-world object size processing. Finally, to investigate the neural dynamics of size and animacy processing simultaneously in space and time, we combined MEG and fMRI with a novel extension of MEG-fMRI fusion by representational similarity. This analysis revealed partly overlapping and distributed spatiotemporal dynamics, with parahippocampal cortex singled out as a region that represented size and animacy persistently when other regions did not. Furthermore, the analysis highlighted the role of early visual cortex in representing real-world size. A control analysis revealed that the neural dynamics of processing animacy and size were distinct from the neural dynamics of processing low-level visual features. Together, our results provide a detailed spatiotemporal view of animacy and size processing in the human brain.

Molecules of various pharmacologically-relevant sizes can cross the ultrasound-induced blood-brain barrier opening in vivo

PubMed Central

Choi, James J.; Wang, Shougang; Tung, Yao-Sheng; Morrison, Barclay; Konofagou, Elisa E.

2009-01-01

Focused ultrasound (FUS) is hereby shown to noninvasively and selectively deliver compounds at pharmacologically relevant molecular weights through the opened blood-brain barrier (BBB). A complete examination on the size of the FUS-induced BBB opening, the spatial distribution of the delivered agents and its dependence on the agent's molecular weight were imaged and quantified using fluorescence microscopy. BBB opening in mice (n=13) was achieved in vivo after systemic administration of microbubbles and subsequent application of pulsed FUS (frequency: 1.525 MHz, peak-rarefactional pressure in situ: 569 kPa) to the left murine hippocampus through the intact skin and skull. BBB-impermeant, fluorescent-tagged dextrans at three distinct molecular weights spanning over several orders of magnitude were systemically administered and acted as model therapeutic compounds. First, dextrans of 3 and 70 kDa were delivered trans-BBB while 2000 kDa dextran was not. Second, compared to 70 kDa dextran, a higher concentration of 3 kDa dextran was delivered through the opened BBB. Third, the 3 and 70 kDa dextrans were both diffusely distributed throughout the targeted brain region. However, high concentrations of 70 kDa dextran appeared more punctated throughout the targeted region. In conclusion, FUS combined with microbubbles opened the BBB sufficiently to allow passage of compounds of at least 70 kDa, but not greater than 2000 kDa, into the brain parenchyma. This noninvasive and localized BBB opening technique could thus provide a unique means for the delivery of compounds of several magnitudes of kDa that include agents with shown therapeutic promise in vitro, but whose in vivo translation has been hampered by their associated BBB impermeability. PMID:19900750

Discovering Cortical Folding Patterns in Neonatal Cortical Surfaces Using Large-Scale Dataset

PubMed Central

Meng, Yu; Li, Gang; Wang, Li; Lin, Weili; Gilmore, John H.

2017-01-01

The cortical folding of the human brain is highly complex and variable across individuals. Mining the major patterns of cortical folding from modern large-scale neuroimaging datasets is of great importance in advancing techniques for neuroimaging analysis and understanding the inter-individual variations of cortical folding and its relationship with cognitive function and disorders. As the primary cortical folding is genetically influenced and has been established at term birth, neonates with the minimal exposure to the complicated postnatal environmental influence are the ideal candidates for understanding the major patterns of cortical folding. In this paper, for the first time, we propose a novel method for discovering the major patterns of cortical folding in a large-scale dataset of neonatal brain MR images (N = 677). In our method, first, cortical folding is characterized by the distribution of sulcal pits, which are the locally deepest points in cortical sulci. Because deep sulcal pits are genetically related, relatively consistent across individuals, and also stable during brain development, they are well suitable for representing and characterizing cortical folding. Then, the similarities between sulcal pit distributions of any two subjects are measured from spatial, geometrical, and topological points of view. Next, these different measurements are adaptively fused together using a similarity network fusion technique, to preserve their common information and also catch their complementary information. Finally, leveraging the fused similarity measurements, a hierarchical affinity propagation algorithm is used to group similar sulcal folding patterns together. The proposed method has been applied to 677 neonatal brains (the largest neonatal dataset to our knowledge) in the central sulcus, superior temporal sulcus, and cingulate sulcus, and revealed multiple distinct and meaningful folding patterns in each region. PMID:28229131

Modeling deep brain stimulation: point source approximation versus realistic representation of the electrode

NASA Astrophysics Data System (ADS)

Zhang, Tianhe C.; Grill, Warren M.

2010-12-01

Deep brain stimulation (DBS) has emerged as an effective treatment for movement disorders; however, the fundamental mechanisms by which DBS works are not well understood. Computational models of DBS can provide insights into these fundamental mechanisms and typically require two steps: calculation of the electrical potentials generated by DBS and, subsequently, determination of the effects of the extracellular potentials on neurons. The objective of this study was to assess the validity of using a point source electrode to approximate the DBS electrode when calculating the thresholds and spatial distribution of activation of a surrounding population of model neurons in response to monopolar DBS. Extracellular potentials in a homogenous isotropic volume conductor were calculated using either a point current source or a geometrically accurate finite element model of the Medtronic DBS 3389 lead. These extracellular potentials were coupled to populations of model axons, and thresholds and spatial distributions were determined for different electrode geometries and axon orientations. Median threshold differences between DBS and point source electrodes for individual axons varied between -20.5% and 9.5% across all orientations, monopolar polarities and electrode geometries utilizing the DBS 3389 electrode. Differences in the percentage of axons activated at a given amplitude by the point source electrode and the DBS electrode were between -9.0% and 12.6% across all monopolar configurations tested. The differences in activation between the DBS and point source electrodes occurred primarily in regions close to conductor-insulator interfaces and around the insulating tip of the DBS electrode. The robustness of the point source approximation in modeling several special cases—tissue anisotropy, a long active electrode and bipolar stimulation—was also examined. Under the conditions considered, the point source was shown to be a valid approximation for predicting excitation of populations of neurons in response to DBS.

Mice lacking hippocampal left-right asymmetry show non-spatial learning deficits.

PubMed

Shimbo, Akihiro; Kosaki, Yutaka; Ito, Isao; Watanabe, Shigeru

2018-01-15

Left-right asymmetry is known to exist at several anatomical levels in the brain and recent studies have provided further evidence to show that it also exists at a molecular level in the hippocampal CA3-CA1 circuit. The distribution of N-methyl-d-aspartate (NMDA) receptor NR2B subunits in the apical and basal synapses of CA1 pyramidal neurons is asymmetrical if the input arrives from the left or right CA3 pyramidal neurons. In the present study, we examined the role of hippocampal asymmetry in cognitive function using β2-microglobulin knock-out (β2m KO) mice, which lack hippocampal asymmetry. We tested β2m KO mice in a series of spatial and non-spatial learning tasks and compared the performances of β2m KO and C57BL6/J wild-type (WT) mice. The β2m KO mice appeared normal in both spatial reference memory and spatial working memory tasks but they took more time than WT mice in learning the two non-spatial learning tasks (i.e., a differential reinforcement of lower rates of behavior (DRL) task and a straight runway task). The β2m KO mice also showed less precision in their response timing in the DRL task and showed weaker spontaneous recovery during extinction in the straight runway task. These results indicate that hippocampal asymmetry is important for certain characteristics of non-spatial learning. Copyright © 2017 Elsevier B.V. All rights reserved.

Feasibility study for positron emission mammography.

PubMed

Thompson, C J; Murthy, K; Weinberg, I N; Mako, F

1994-04-01

A feasibility study is presented for a small, low-cost, dedicated device for positron emission mammography. Two detector arrays above and below the breast would be placed in a conventional mammography unit. These detectors are sensitive to positron annihilation radiation, and are connected to a coincidence circuit and a multiplane image memory. Images of the distribution of positron-emitting isotope are obtained in real time by incrementing the memory location at the intersection of each line of response. Monte Carlo simulations of a breast phantom are compared with actual scans of this phantom in a conventional PET scanner. The simulations and experimental data are used to predict the performance of the proposed system. Spatial resolution experiments using very narrow bismuth germanate BGO crystals suggest that spatial resolutions of about 2 mm should be possible. The efficiency of the proposed device is about ten times that of a conventional brain scanner. The scatter fraction is greater, but the scattered radiation has a very flat distribution. By designing the device to fit in an existing mammography unit, conventional mammograms can be taken after the injection of the radio-pharmaceutical allowing exact registration of the emission and conventional mammographic images.

Preattentive representation of feature conjunctions for concurrent spatially distributed auditory objects.

PubMed

Takegata, Rika; Brattico, Elvira; Tervaniemi, Mari; Varyagina, Olga; Näätänen, Risto; Winkler, István

2005-09-01

The role of attention in conjoining features of an object has been a topic of much debate. Studies using the mismatch negativity (MMN), an index of detecting acoustic deviance, suggested that the conjunctions of auditory features are preattentively represented in the brain. These studies, however, used sequentially presented sounds and thus are not directly comparable with visual studies of feature integration. Therefore, the current study presented an array of spatially distributed sounds to determine whether the auditory features of concurrent sounds are correctly conjoined without focal attention directed to the sounds. Two types of sounds differing from each other in timbre and pitch were repeatedly presented together while subjects were engaged in a visual n-back working-memory task and ignored the sounds. Occasional reversals of the frequent pitch-timbre combinations elicited MMNs of a very similar amplitude and latency irrespective of the task load. This result suggested preattentive integration of auditory features. However, performance in a subsequent target-search task with the same stimuli indicated the occurrence of illusory conjunctions. The discrepancy between the results obtained with and without focal attention suggests that illusory conjunctions may occur during voluntary access to the preattentively encoded object representations.

Brain regions involved in the retrieval of spatial and episodic details associated with a familiar environment: an fMRI study.

PubMed

Hirshhorn, Marnie; Grady, Cheryl; Rosenbaum, R Shayna; Winocur, Gordon; Moscovitch, Morris

2012-11-01

Functional magnetic resonance imaging (fMRI) was used to compare brain activity during the retrieval of coarse- and fine-grained spatial details and episodic details associated with a familiar environment. Long-time Toronto residents compared pairs of landmarks based on their absolute geographic locations (requiring either coarse or fine discriminations) or based on previous visits to those landmarks (requiring episodic details). An ROI analysis of the hippocampus showed that all three conditions activated the hippocampus bilaterally. Fine-grained spatial judgments recruited an additional region of the right posterior hippocampus, while episodic judgments recruited an additional region of the right anterior hippocampus, and a more extensive region along the length of the left hippocampus. To examine whole-brain patterns of activity, Partial Least Squares (PLS) analysis was used to identify sets of brain regions whose activity covaried with the three conditions. All three comparison judgments recruited the default mode network including the posterior cingulate/retrosplenial cortex, middle frontal gyrus, hippocampus, and precuneus. Fine-grained spatial judgments also recruited additional regions of the precuneus, parahippocampal cortex and the supramarginal gyrus. Episodic judgments recruited the posterior cingulate and medial frontal lobes as well as the angular gyrus. These results are discussed in terms of their implications for theories of hippocampal function and spatial and episodic memory. Copyright © 2012 Elsevier Ltd. All rights reserved.

FIB/SEM technology and Alzheimer's disease: three-dimensional analysis of human cortical synapses.

PubMed

Blazquez-Llorca, Lidia; Merchán-Pérez, Ángel; Rodríguez, José-Rodrigo; Gascón, Jorge; DeFelipe, Javier

2013-01-01

The quantification and measurement of synapses is a major goal in the study of brain organization in both health and disease. Serial section electron microscopy (EM) is the ideal method since it permits the direct quantification of crucial features such as the number of synapses per unit volume or the distribution and size of synapses. However, a major limitation is that obtaining long series of ultrathin sections is extremely time-consuming and difficult. Consequently, quantitative EM studies are scarce and the most common method employed to estimate synaptic density in the human brain is indirect, by counting at the light microscopic level immunoreactive puncta using synaptic markers. The recent development of automatic EM methods in experimental animals, such as the combination of focused ion beam milling and scanning electron microscopy (FIB/SEM), are opening new avenues. Here we explored the utility of FIB/SEM to examine the cerebral cortex of Alzheimer's disease patients. We found that FIB/SEM is an excellent tool to study in detail the ultrastructure and alterations of the synaptic organization of the human brain. Using this technology, it is possible to reconstruct different types of plaques and the surrounding neuropil to find new aspects of the pathological process associated with the disease, namely; to count the exact number and types of synapses in different regions of the plaques, to study the spatial distribution of synapses, and to analyze the morphology and nature of the various types of dystrophic neurites and amyloid deposits.

Mentalizing regions represent distributed, continuous, and abstract dimensions of others' beliefs.

PubMed

Koster-Hale, Jorie; Richardson, Hilary; Velez, Natalia; Asaba, Mika; Young, Liane; Saxe, Rebecca

2017-11-01

The human capacity to reason about others' minds includes making causal inferences about intentions, beliefs, values, and goals. Previous fMRI research has suggested that a network of brain regions, including bilateral temporo-parietal junction (TPJ), superior temporal sulcus (STS), and medial prefrontal-cortex (MPFC), are reliably recruited for mental state reasoning. Here, in two fMRI experiments, we investigate the representational content of these regions. Building on existing computational and neural evidence, we hypothesized that social brain regions contain at least two functionally and spatially distinct components: one that represents information related to others' motivations and values, and another that represents information about others' beliefs and knowledge. Using multi-voxel pattern analysis, we find evidence that motivational versus epistemic features are independently represented by theory of mind (ToM) regions: RTPJ contains information about the justification of the belief, bilateral TPJ represents the modality of the source of knowledge, and VMPFC represents the valence of the resulting emotion. These representations are found only in regions implicated in social cognition and predict behavioral responses at the level of single items. We argue that cortical regions implicated in mental state inference contain complementary, but distinct, representations of epistemic and motivational features of others' beliefs, and that, mirroring the processes observed in sensory systems, social stimuli are represented in distinct and distributed formats across the human brain. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Short-term Music Training Enhances Complex, Distributed Neural Communication during Music and Linguistic Tasks

PubMed Central

Carpentier, Sarah M.; Moreno, Sylvain; McIntosh, Anthony R.

2016-01-01

Musical training is frequently associated with benefits to linguistic abilities, and recent focus has been placed on possible benefits of bilingualism to lifelong executive functions; however, the neural mechanisms for such effects are unclear. The aim of this study was to gain better understanding of the whole-brain functional effects of music and second-language training that could support such previously observed cognitive transfer effects. We conducted a 28-day longitudinal study of monolingual English-speaking 4- to 6-year-old children randomly selected to receive daily music or French language training, excluding weekends. Children completed passive EEG music note and French vowel auditory oddball detection tasks before and after training. Brain signal complexity was measured on source waveforms at multiple temporal scales as an index of neural information processing and network communication load. Comparing pretraining with posttraining, musical training was associated with increased EEG complexity at coarse temporal scales during the music and French vowel tasks in widely distributed cortical regions. Conversely, very minimal decreases in complexity at fine scales and trends toward coarse-scale increases were displayed after French training during the tasks. Spectral analysis failed to distinguish between training types and found overall theta (3.5–7.5 Hz) power increases after all training forms, with spatially fewer decreases in power at higher frequencies (>10 Hz). These findings demonstrate that musical training increased diversity of brain network states to support domain-specific music skill acquisition and music-to-language transfer effects. PMID:27243611

Short-term Music Training Enhances Complex, Distributed Neural Communication during Music and Linguistic Tasks.

PubMed

Carpentier, Sarah M; Moreno, Sylvain; McIntosh, Anthony R

2016-10-01

Musical training is frequently associated with benefits to linguistic abilities, and recent focus has been placed on possible benefits of bilingualism to lifelong executive functions; however, the neural mechanisms for such effects are unclear. The aim of this study was to gain better understanding of the whole-brain functional effects of music and second-language training that could support such previously observed cognitive transfer effects. We conducted a 28-day longitudinal study of monolingual English-speaking 4- to 6-year-old children randomly selected to receive daily music or French language training, excluding weekends. Children completed passive EEG music note and French vowel auditory oddball detection tasks before and after training. Brain signal complexity was measured on source waveforms at multiple temporal scales as an index of neural information processing and network communication load. Comparing pretraining with posttraining, musical training was associated with increased EEG complexity at coarse temporal scales during the music and French vowel tasks in widely distributed cortical regions. Conversely, very minimal decreases in complexity at fine scales and trends toward coarse-scale increases were displayed after French training during the tasks. Spectral analysis failed to distinguish between training types and found overall theta (3.5-7.5 Hz) power increases after all training forms, with spatially fewer decreases in power at higher frequencies (>10 Hz). These findings demonstrate that musical training increased diversity of brain network states to support domain-specific music skill acquisition and music-to-language transfer effects.

Large-scale recording of thalamocortical circuits: in vivo electrophysiology with the two-dimensional electronic depth control silicon probe

PubMed Central

Fiáth, Richárd; Beregszászi, Patrícia; Horváth, Domonkos; Wittner, Lucia; Aarts, Arno A. A.; Ruther, Patrick; Neves, Hercules P.; Bokor, Hajnalka; Acsády, László

2016-01-01

Recording simultaneous activity of a large number of neurons in distributed neuronal networks is crucial to understand higher order brain functions. We demonstrate the in vivo performance of a recently developed electrophysiological recording system comprising a two-dimensional, multi-shank, high-density silicon probe with integrated complementary metal-oxide semiconductor electronics. The system implements the concept of electronic depth control (EDC), which enables the electronic selection of a limited number of recording sites on each of the probe shafts. This innovative feature of the system permits simultaneous recording of local field potentials (LFP) and single- and multiple-unit activity (SUA and MUA, respectively) from multiple brain sites with high quality and without the actual physical movement of the probe. To evaluate the in vivo recording capabilities of the EDC probe, we recorded LFP, MUA, and SUA in acute experiments from cortical and thalamic brain areas of anesthetized rats and mice. The advantages of large-scale recording with the EDC probe are illustrated by investigating the spatiotemporal dynamics of pharmacologically induced thalamocortical slow-wave activity in rats and by the two-dimensional tonotopic mapping of the auditory thalamus. In mice, spatial distribution of thalamic responses to optogenetic stimulation of the neocortex was examined. Utilizing the benefits of the EDC system may result in a higher yield of useful data from a single experiment compared with traditional passive multielectrode arrays, and thus in the reduction of animals needed for a research study. PMID:27535370

Direct mapping of 19F in 19FDG-6P in brain tissue at subcellular resolution using soft X-ray fluorescence

NASA Astrophysics Data System (ADS)

Poitry-Yamate, C.; Gianoncelli, A.; Kourousias, G.; Kaulich, B.; Lepore, M.; Gruetter, R.; Kiskinova, M.

2013-10-01

Low energy x-ray fluorescence (LEXRF) detection was optimized for imaging cerebral glucose metabolism by mapping the fluorine LEXRF signal of 19F in 19FDG, trapped as intracellular 19F-deoxyglucose-6-phosphate (19FDG-6P) at 1μm spatial resolution from 3μm thick brain slices. 19FDG metabolism was evaluated in brain structures closely resembling the general cerebral cytoarchitecture following formalin fixation of brain slices and their inclusion in an epon matrix. 2-dimensional distribution maps of 19FDG-6P were placed in a cytoarchitectural and morphological context by simultaneous LEXRF mapping of N and O, and scanning transmission x-ray (STXM) imaging. A disproportionately high uptake and metabolism of glucose was found in neuropil relative to intracellular domains of the cell body of hypothalamic neurons, showing directly that neurons, like glial cells, also metabolize glucose. As 19F-deoxyglucose-6P is structurally identical to 18F-deoxyglucose-6P, LEXRF of subcellular 19F provides a link to in vivo 18FDG PET, forming a novel basis for understanding the physiological mechanisms underlying the 18FDG PET image, and the contribution of neurons and glia to the PET signal.

Automated segmentation of the actively stained mouse brain using multi-spectral MR microscopy.

PubMed

Sharief, Anjum A; Badea, Alexandra; Dale, Anders M; Johnson, G Allan

2008-01-01

Magnetic resonance microscopy (MRM) has created new approaches for high-throughput morphological phenotyping of mouse models of diseases. Transgenic and knockout mice serve as a test bed for validating hypotheses that link genotype to the phenotype of diseases, as well as developing and tracking treatments. We describe here a Markov random fields based segmentation of the actively stained mouse brain, as a prerequisite for morphological phenotyping. Active staining achieves higher signal to noise ratio (SNR) thereby enabling higher resolution imaging per unit time than obtained in previous formalin-fixed mouse brain studies. The segmentation algorithm was trained on isotropic 43-mum T1- and T2-weighted MRM images. The mouse brain was segmented into 33 structures, including the hippocampus, amygdala, hypothalamus, thalamus, as well as fiber tracts and ventricles. Probabilistic information used in the segmentation consisted of (a) intensity distributions in the T1- and T2-weighted data, (b) location, and (c) contextual priors for incorporating spatial information. Validation using standard morphometric indices showed excellent consistency between automatically and manually segmented data. The algorithm has been tested on the widely used C57BL/6J strain, as well as on a selection of six recombinant inbred BXD strains, chosen especially for their largely variant hippocampus.

A brain-based account of “basic-level” concepts

PubMed Central

Bauer, Andrew James; Just, Marcel Adam

2017-01-01

This study provides a brain-based account of how object concepts at an intermediate (basic) level of specificity are represented, offering an enriched view of what it means for a concept to be a basic-level concept, a research topic pioneered by Rosch and others (Rosch et al., 1976). Applying machine learning techniques to fMRI data, it was possible to determine the semantic content encoded in the neural representations of object concepts at basic and subordinate levels of abstraction. The representation of basic-level concepts (e.g. bird) was spatially broad, encompassing sensorimotor brain areas that encode concrete object properties, and also language and heteromodal integrative areas that encode abstract semantic content. The representation of subordinate-level concepts (robin) was less widely distributed, concentrated in perceptual areas that underlie concrete content. Furthermore, basic-level concepts were representative of their subordinates in that they were neurally similar to their typical but not atypical subordinates (bird was neurally similar to robin but not woodpecker). The findings provide a brain-based account of the advantages that basic-level concepts enjoy in everyday life over subordinate-level concepts: the basic level is a broad topographical representation that encompasses both concrete and abstract semantic content, reflecting the multifaceted yet intuitive meaning of basic-level concepts. PMID:28826947

A brain-based account of "basic-level" concepts.

PubMed

Bauer, Andrew James; Just, Marcel Adam

2017-11-01

This study provides a brain-based account of how object concepts at an intermediate (basic) level of specificity are represented, offering an enriched view of what it means for a concept to be a basic-level concept, a research topic pioneered by Rosch and others (Rosch et al., 1976). Applying machine learning techniques to fMRI data, it was possible to determine the semantic content encoded in the neural representations of object concepts at basic and subordinate levels of abstraction. The representation of basic-level concepts (e.g. bird) was spatially broad, encompassing sensorimotor brain areas that encode concrete object properties, and also language and heteromodal integrative areas that encode abstract semantic content. The representation of subordinate-level concepts (robin) was less widely distributed, concentrated in perceptual areas that underlie concrete content. Furthermore, basic-level concepts were representative of their subordinates in that they were neurally similar to their typical but not atypical subordinates (bird was neurally similar to robin but not woodpecker). The findings provide a brain-based account of the advantages that basic-level concepts enjoy in everyday life over subordinate-level concepts: the basic level is a broad topographical representation that encompasses both concrete and abstract semantic content, reflecting the multifaceted yet intuitive meaning of basic-level concepts. Copyright © 2017 Elsevier Inc. All rights reserved.

Dissociable brain biomarkers of fluid intelligence.

PubMed

Paul, Erick J; Larsen, Ryan J; Nikolaidis, Aki; Ward, Nathan; Hillman, Charles H; Cohen, Neal J; Kramer, Arthur F; Barbey, Aron K

2016-08-15

Cognitive neuroscience has long sought to understand the biological foundations of human intelligence. Decades of research have revealed that general intelligence is correlated with two brain-based biomarkers: the concentration of the brain biochemical N-acetyl aspartate (NAA) measured by proton magnetic resonance spectroscopy (MRS) and total brain volume measured using structural MR imaging (MRI). However, the relative contribution of these biomarkers in predicting performance on core facets of human intelligence remains to be well characterized. In the present study, we sought to elucidate the role of NAA and brain volume in predicting fluid intelligence (Gf). Three canonical tests of Gf (BOMAT, Number Series, and Letter Sets) and three working memory tasks (Reading, Rotation, and Symmetry span tasks) were administered to a large sample of healthy adults (n=211). We conducted exploratory factor analysis to investigate the factor structure underlying Gf independent from working memory and observed two Gf components (verbal/spatial and quantitative reasoning) and one working memory component. Our findings revealed a dissociation between two brain biomarkers of Gf (controlling for age and sex): NAA concentration correlated with verbal/spatial reasoning, whereas brain volume correlated with quantitative reasoning and working memory. A follow-up analysis revealed that this pattern of findings is observed for males and females when analyzed separately. Our results provide novel evidence that distinct brain biomarkers are associated with specific facets of human intelligence, demonstrating that NAA and brain volume are independent predictors of verbal/spatial and quantitative facets of Gf. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Measurement of absorbed dose during the phantom torso experiment on the International Space Station

NASA Astrophysics Data System (ADS)

Semones, E.; Gibbons, F.; Golightly, M.; Weyland, M.; Johnson, A.; Smith, G.; Shelfer, T.; Zapp, N.

The Phantom Torso Experiment (PTE) was flown on the International Space Station (ISS) during Increment 2 (April-August 2001). The experiment was located in the US Lab module Human Research Facility (HRF) rack. The objective of the passive dosimetry portion of the experiment was to measure spatial distributions of absorbed dose in the 34, 1 inch sections of a modified RandoTM phantom. In each section of the phantom, thermoluminescent detectors (TLDs) were placed at various locations (depths) to provide the spatial measurement. TLDs were also located at several radiosensitive organ locations (brain, thyroid, heart/lung, stomach and colon) and two locations on the surface (skin). Active silicon detectors were also placed at these organ locations to provide time resolved results of the absorbed dose rates. Using these detectors, it is possible to separate the trapped and galactic cosmic ray components of the absorbed dose. The TLD results of the spatial and organ dose measurements will be presented and comparisons of the TLD and silicon detector organ absorbed doses will be made.

Abnormal functional specialization within medial prefrontal cortex in high-functioning autism: a multi-voxel similarity analysis

PubMed Central

Meuwese, Julia D.I.; Towgood, Karren J.; Frith, Christopher D.; Burgess, Paul W.

2009-01-01

Multi-voxel pattern analyses have proved successful in ‘decoding’ mental states from fMRI data, but have not been used to examine brain differences associated with atypical populations. We investigated a group of 16 (14 males) high-functioning participants with autism spectrum disorder (ASD) and 16 non-autistic control participants (12 males) performing two tasks (spatial/verbal) previously shown to activate medial rostral prefrontal cortex (mrPFC). Each task manipulated: (i) attention towards perceptual versus self-generated information and (ii) reflection on another person's mental state (‘mentalizing'versus ‘non-mentalizing’) in a 2 × 2 design. Behavioral performance and group-level fMRI results were similar between groups. However, multi-voxel similarity analyses revealed strong differences. In control participants, the spatial distribution of activity generalized significantly between task contexts (spatial/verbal) when examining the same function (attention/mentalizing) but not when comparing different functions. This pattern was disrupted in the ASD group, indicating abnormal functional specialization within mrPFC, and demonstrating the applicability of multi-voxel pattern analysis to investigations of atypical populations. PMID:19174370

Spatial ability and training in virtual neuroanatomy.

PubMed

Plumley, Leah; Armstrong, Ryan; De Ribaupierre, Sandrine; Eagleson, Roy

2013-01-01

Neuroanatomy is one of the most challenging sections of anatomy to learn, partially related to the intricate relation of multiple 3D structures. As part of the medical student curriculum, it is usually taught in 2D using illustrations and plastinated brain section, since the number of hours devoted to anatomy have dropped in the curriculum, making the dissection of brain too time-consuming to be done. In this study we are analyzing the role of innate spatial ability of novices in learning some basic structures and placing them back in a 3D volumetric brain. Two tasks are performed after a short training session: the first one is to localize the ventricular tip as would be required during a temporal lobectomy, and the second task requires that the subject 'reconstruct' 3D anatomical structures within the context of our 3D brain model. We report our findings on the performance scores obtained from a population of subjects of differing backgrounds and spatial abilities.

Spatial learning, monoamines and oxidative stress in rats exposed to 900 MHz electromagnetic field in combination with iron overload.

PubMed

Maaroufi, Karima; Had-Aissouni, Laurence; Melon, Christophe; Sakly, Mohsen; Abdelmelek, Hafedh; Poucet, Bruno; Save, Etienne

2014-01-01

The increasing use of mobile phone technology over the last decade raises concerns about the impact of high frequency electromagnetic fields (EMF) on health. More recently, a link between EMF, iron overload in the brain and neurodegenerative disorders including Parkinson's and Alzheimer's diseases has been suggested. Co-exposure to EMF and brain iron overload may have a greater impact on brain tissues and cognitive processes than each treatment by itself. To examine this hypothesis, Long-Evans rats submitted to 900 MHz exposure or combined 900 MHz EMF and iron overload treatments were tested in various spatial learning tasks (navigation task in the Morris water maze, working memory task in the radial-arm maze, and object exploration task involving spatial and non spatial processing). Biogenic monoamines and metabolites (dopamine, serotonin) and oxidative stress were measured. Rats exposed to EMF were impaired in the object exploration task but not in the navigation and working memory tasks. They also showed alterations of monoamine content in several brain areas but mainly in the hippocampus. Rats that received combined treatment did not show greater behavioral and neurochemical deficits than EMF-exposed rats. None of the two treatments produced global oxidative stress. These results show that there is an impact of EMF on the brain and cognitive processes but this impact is revealed only in a task exploiting spontaneous exploratory activity. In contrast, there are no synergistic effects between EMF and a high content of iron in the brain. Copyright © 2013 Elsevier B.V. All rights reserved.

Multiscale Imaging of the Mouse Cortex Using Two-Photon Microscopy and Wide-Field Illumination

NASA Astrophysics Data System (ADS)

Bumstead, Jonathan R.

The mouse brain can be studied over vast spatial scales ranging from microscopic imaging of single neurons to macroscopic measurements of hemodynamics acquired over the majority of the mouse cortex. However, most neuroimaging modalities are limited by a fundamental trade-off between the spatial resolution and the field-of-view (FOV) over which the brain can be imaged, making it difficult to fully understand the functional and structural architecture of the healthy mouse brain and its disruption in disease. My dissertation has focused on developing multiscale optical systems capable of imaging the mouse brain at both microscopic and mesoscopic spatial scales, specifically addressing the difference in spatial scales imaged with two-photon microscopy (TPM) and optical intrinsic signal imaging (OISI). Central to this work has been the formulation of a principled design strategy for extending the FOV of the two-photon microscope. Using this design approach, we constructed a TPM system with subcellular resolution and a FOV area 100 times greater than a conventional two-photon microscope. To image the ellipsoidal shape of the mouse cortex, we also developed the microscope to image arbitrary surfaces within a single frame using an electrically tunable lens. Finally, to address the speed limitations of the TPM systems developed during my dissertation, I also conducted research in large-scale neural phenomena occurring in the mouse brain imaged with high-speed OISI. The work conducted during my dissertation addresses some of the fundamental principles in designing and applying optical systems for multiscale imaging of the mouse brain.

Spatially Regularized Machine Learning for Task and Resting-state fMRI

PubMed Central

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

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.

Minocycline Transiently Reduces Microglia/Macrophage Activation but Exacerbates Cognitive Deficits Following Repetitive Traumatic Brain Injury in the Neonatal Rat

PubMed Central

Hanlon, Lauren A.; Huh, Jimmy W.

2016-01-01

Elevated microglial/macrophage-associated biomarkers in the cerebrospinal fluid of infant victims of abusive head trauma (AHT) suggest that these cells play a role in the pathophysiology of the injury. In a model of AHT in 11-day-old rats, 3 impacts (24 hours apart) resulted in spatial learning and memory deficits and increased brain microglial/macrophage reactivity, traumatic axonal injury, neuronal degeneration, and cortical and white-matter atrophy. The antibiotic minocycline has been effective in decreasing injury-induced microglial/macrophage activation while simultaneously attenuating cellular and functional deficits in models of neonatal hypoxic ischemia, but the potential for this compound to rescue deficits after impact-based trauma to the immature brain remains unexplored. Acute minocycline administration in this model of AHT decreased microglial/macrophage reactivity in the corpus callosum of brain-injured animals at 3 days postinjury, but this effect was lost by 7 days postinjury. Additionally, minocycline treatment had no effect on traumatic axonal injury, neurodegeneration, tissue atrophy, or spatial learning deficits. Interestingly, minocycline-treated animals demonstrated exacerbated injury-induced spatial memory deficits. These results contrast with previous findings in other models of brain injury and suggest that minocycline is ineffective in reducing microglial/macrophage activation and ameliorating injury-induced deficits following repetitive neonatal traumatic brain injury. PMID:26825312

Structural variations in prefrontal cortex mediate the relationship between early childhood stress and spatial working memory

PubMed Central

Hanson, Jamie L.; Chung, Moo K.; Avants, Brian B.; Rudolph, Karen D.; Shirtcliff, Elizabeth A.; Gee, James C.; Davidson, Richard J.; Pollak, Seth D.

2012-01-01

A large corpus of research indicates exposure to stress impairs cognitive abilities, specifically executive functioning dependent on the prefrontal cortex (PFC). We collected structural MRI scans (n=61), well-validated assessments of executive functioning, and detailed interviews assessing stress exposure in humans, to examine whether cumulative life stress affected brain morphometry and one type of executive functioning, spatial working memory, during adolescence—a critical time of brain development and reorganization. Analysis of variations in brain structure revealed that cumulative life stress and spatial working memory were related to smaller volumes in the PFC, specifically prefrontal gray and white matter between the anterior cingulate and the frontal poles. Mediation analyses revealed that individual differences in prefrontal volumes accounted for the association between cumulative life stress and spatial working memory. These results suggest that structural changes in the PFC may serve as a mediating mechanism through which greater cumulative life stress engenders decrements in cognitive functioning. PMID:22674267

Task relevance modulates the behavioural and neural effects of sensory predictions

PubMed Central

Friston, Karl J.; Nobre, Anna C.

2017-01-01

The brain is thought to generate internal predictions to optimize behaviour. However, it is unclear whether predictions signalling is an automatic brain function or depends on task demands. Here, we manipulated the spatial/temporal predictability of visual targets, and the relevance of spatial/temporal information provided by auditory cues. We used magnetoencephalography (MEG) to measure participants’ brain activity during task performance. Task relevance modulated the influence of predictions on behaviour: spatial/temporal predictability improved spatial/temporal discrimination accuracy, but not vice versa. To explain these effects, we used behavioural responses to estimate subjective predictions under an ideal-observer model. Model-based time-series of predictions and prediction errors (PEs) were associated with dissociable neural responses: predictions correlated with cue-induced beta-band activity in auditory regions and alpha-band activity in visual regions, while stimulus-bound PEs correlated with gamma-band activity in posterior regions. Crucially, task relevance modulated these spectral correlates, suggesting that current goals influence PE and prediction signalling. PMID:29206225

Modelling the electric field and the current density generated by cerebellar transcranial DC stimulation in humans.

PubMed

Parazzini, Marta; Rossi, Elena; Ferrucci, Roberta; Liorni, Ilaria; Priori, Alberto; Ravazzani, Paolo

2014-03-01

Transcranial Direct Current Stimulation (tDCS) over the cerebellum (or cerebellar tDCS) modulates working memory, changes cerebello-brain interaction, and affects locomotion in humans. Also, the use of tDCS has been proposed for the treatment of disorders characterized by cerebellar dysfunction. Nonetheless, the electric field (E) and current density (J) spatial distributions generated by cerebellar tDCS are unknown. This work aimed to estimate E and J distributions during cerebellar tDCS. Computational electromagnetics techniques were applied in three human realistic models of different ages and gender. The stronger E and J occurred mainly in the cerebellar cortex, with some spread (up to 4%) toward the occipital cortex. Also, changes by ±1cm in the position of the active electrode resulted in a small effect (up to 4%) in the E and J spatial distribution in the cerebellum. Finally, the E and J spreads to the brainstem and the heart were negligible, thus further supporting the safety of this technique. Despite inter-individual differences, our modeling study confirms that the cerebellum is the structure mainly involved by cerebellar tDCS. Modeling approach reveals that during cerebellar tDCS the current spread to other structures outside the cerebellum is unlike to produce functional effects. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

An Exploratory Study of the Possible Impact of Cerebral Hemisphericity on the Performance of Select Linear, Non-Linear, and Spatial Computer Tasks.

ERIC Educational Resources Information Center

McCluskey, James J.

1997-01-01

A study of 160 undergraduate journalism students trained to design projects (stacks) using HyperCard on Macintosh computers determined that right-brain dominant subjects outperformed left-brain and mixed-brain dominant subjects, whereas left-brain dominant subjects out performed mixed-brain dominant subjects in several areas. Recommends future…

Brain-wide Maps Reveal Stereotyped Cell-Type-Based Cortical Architecture and Subcortical Sexual Dimorphism.

PubMed

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.

Learning from our failures in blood-brain permeability: what can be done for new drug discovery?

PubMed

Martel, Sylvain

2015-03-01

Many existing pharmaceuticals are rendered ineffective in the treatment of cerebral diseases due to a permeability barrier well known as the blood-brain barrier (BBB). Such barrier between the blood within brain capillaries and the extracellular fluid in brain tissue has motivated several approaches aimed at delivering therapeutics to the brain. These approaches rely on strategies that can be classified as molecular modifications, the use of BBB bypassing pathways, and BBB disruptions. Although several of these approaches that have been investigated so far show promising results, none has addressed the optimization of the ratio of the dose of the drug molecules that contributes to the therapeutic effects. As such, the extensive research efforts, such as prioritizing the enhancement of the BBB permeability alone is likely to fail to provide the best therapeutic effects for a given dose if prior systemic circulation is not avoided while enhancing the spatial targeting only to regions of the brain that need treatment. Hence, new therapeutics for the brain could be synthesized to take advantage of recent technologies for non-systemic delivery and spatially targeted brain uptake.

Spherical Deconvolution of Multichannel Diffusion MRI Data with Non-Gaussian Noise Models and Spatial Regularization

PubMed Central

Canales-Rodríguez, Erick J.; Caruyer, Emmanuel; Aja-Fernández, Santiago; Radua, Joaquim; Yurramendi Mendizabal, Jesús M.; Iturria-Medina, Yasser; Melie-García, Lester; Alemán-Gómez, Yasser; Thiran, Jean-Philippe; Sarró, Salvador; Pomarol-Clotet, Edith; Salvador, Raymond

2015-01-01

Spherical deconvolution (SD) methods are widely used to estimate the intra-voxel white-matter fiber orientations from diffusion MRI data. However, while some of these methods assume a zero-mean Gaussian distribution for the underlying noise, its real distribution is known to be non-Gaussian and to depend on many factors such as the number of coils and the methodology used to combine multichannel MRI signals. Indeed, the two prevailing methods for multichannel signal combination lead to noise patterns better described by Rician and noncentral Chi distributions. Here we develop a Robust and Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD) technique, intended to deal with realistic MRI noise, based on a Richardson-Lucy (RL) algorithm adapted to Rician and noncentral Chi likelihood models. To quantify the benefits of using proper noise models, RUMBA-SD was compared with dRL-SD, a well-established method based on the RL algorithm for Gaussian noise. Another aim of the study was to quantify the impact of including a total variation (TV) spatial regularization term in the estimation framework. To do this, we developed TV spatially-regularized versions of both RUMBA-SD and dRL-SD algorithms. The evaluation was performed by comparing various quality metrics on 132 three-dimensional synthetic phantoms involving different inter-fiber angles and volume fractions, which were contaminated with noise mimicking patterns generated by data processing in multichannel scanners. The results demonstrate that the inclusion of proper likelihood models leads to an increased ability to resolve fiber crossings with smaller inter-fiber angles and to better detect non-dominant fibers. The inclusion of TV regularization dramatically improved the resolution power of both techniques. The above findings were also verified in human brain data. PMID:26470024

Effects of exercise intensity on spatial memory performance and hippocampal synaptic plasticity in transient brain ischemic rats.

PubMed

Shih, Pei-Cheng; Yang, Yea-Ru; Wang, Ray-Yau

2013-01-01

Memory impairment is commonly noted in stroke survivors, and can lead to delay of functional recovery. Exercise has been proved to improve memory in adult healthy subjects. Such beneficial effects are often suggested to relate to hippocampal synaptic plasticity, which is important for memory processing. Previous evidence showed that in normal rats, low intensity exercise can improve synaptic plasticity better than high intensity exercise. However, the effects of exercise intensities on hippocampal synaptic plasticity and spatial memory after brain ischemia remain unclear. In this study, we investigated such effects in brain ischemic rats. The middle cerebral artery occlusion (MCAO) procedure was used to induce brain ischemia. After the MCAO procedure, rats were randomly assigned to sedentary (Sed), low-intensity exercise (Low-Ex), or high-intensity exercise (High-Ex) group. Treadmill training began from the second day post MCAO procedure, 30 min/day for 14 consecutive days for the exercise groups. The Low-Ex group was trained at the speed of 8 m/min, while the High-Ex group at the speed of 20 m/min. The spatial memory, hippocampal brain-derived neurotrophic factor (BDNF), synapsin-I, postsynaptic density protein 95 (PSD-95), and dendritic structures were examined to document the effects. Serum corticosterone level was also quantified as stress marker. Our results showed the Low-Ex group, but not the High-Ex group, demonstrated better spatial memory performance than the Sed group. Dendritic complexity and the levels of BDNF and PSD-95 increased significantly only in the Low-Ex group as compared with the Sed group in bilateral hippocampus. Notably, increased level of corticosterone was found in the High-Ex group, implicating higher stress response. In conclusion, after brain ischemia, low intensity exercise may result in better synaptic plasticity and spatial memory performance than high intensity exercise; therefore, the intensity is suggested to be considered during exercise training.

The role of right frontal brain regions in integration of spatial relation.

PubMed

Han, Jiahui; Cao, Bihua; Cao, Yunfei; Gao, Heming; Li, Fuhong

2016-06-01

Previous studies have explored the neural mechanisms of spatial reasoning on a two-dimensional (2D) plane; however, it remains unclear how spatial reasoning is conducted in a three-dimensional (3D) condition. In the present study, we presented 3D geometric objects to 16 adult participants, and asked them to process the spatial relationship between different corners of the geometric objects. In premise-1, the first two corners of a geometric shape (e.g., A vs. B) were displayed. In premise-2, the second and third corners (e.g., B vs. C) were displayed. After integrating the two premises, participants were required to infer the spatial relationship between the first and the third corners (e.g., A and C). Finally, the participants were presented with a conclusion object, and they were required to judge whether the conclusion was true or false based on their inference. The event-related potential evoked by premise-2 revealed that (1) compared with 2D spatial reasoning, 3D reasoning elicited a smaller P3b component, and (2) in the right frontal areas, increased negativities were found in the 3D condition during the N400 and late negative components (LNC). These findings imply that higher brain activity in the right frontal brain regions were related with the integration and maintenance of spatial information in working memory for reasoning. Copyright © 2016 Elsevier Ltd. All rights reserved.

Slime mold uses an externalized spatial “memory” to navigate in complex environments

PubMed Central

Reid, Chris R.; Latty, Tanya; Dussutour, Audrey; Beekman, Madeleine

2012-01-01

Spatial memory enhances an organism’s navigational ability. Memory typically resides within the brain, but what if an organism has no brain? We show that the brainless slime mold Physarum polycephalum constructs a form of spatial memory by avoiding areas it has previously explored. This mechanism allows the slime mold to solve the U-shaped trap problem—a classic test of autonomous navigational ability commonly used in robotics—requiring the slime mold to reach a chemoattractive goal behind a U-shaped barrier. Drawn into the trap, the organism must rely on other methods than gradient-following to escape and reach the goal. Our data show that spatial memory enhances the organism’s ability to navigate in complex environments. We provide a unique demonstration of a spatial memory system in a nonneuronal organism, supporting the theory that an externalized spatial memory may be the functional precursor to the internal memory of higher organisms. PMID:23045640

Slime mold uses an externalized spatial "memory" to navigate in complex environments.

PubMed

Reid, Chris R; Latty, Tanya; Dussutour, Audrey; Beekman, Madeleine

2012-10-23

Spatial memory enhances an organism's navigational ability. Memory typically resides within the brain, but what if an organism has no brain? We show that the brainless slime mold Physarum polycephalum constructs a form of spatial memory by avoiding areas it has previously explored. This mechanism allows the slime mold to solve the U-shaped trap problem--a classic test of autonomous navigational ability commonly used in robotics--requiring the slime mold to reach a chemoattractive goal behind a U-shaped barrier. Drawn into the trap, the organism must rely on other methods than gradient-following to escape and reach the goal. Our data show that spatial memory enhances the organism's ability to navigate in complex environments. We provide a unique demonstration of a spatial memory system in a nonneuronal organism, supporting the theory that an externalized spatial memory may be the functional precursor to the internal memory of higher organisms.

Electrical Stimulation in Hippocampus and Entorhinal Cortex Impairs Spatial and Temporal Memory.

PubMed

Goyal, Abhinav; Miller, Jonathan; Watrous, Andrew J; Lee, Sang Ah; Coffey, Tom; Sperling, Michael R; Sharan, Ashwini; Worrell, Gregory; Berry, Brent; Lega, Bradley; Jobst, Barbara C; Davis, Kathryn A; Inman, Cory; Sheth, Sameer A; Wanda, Paul A; Ezzyat, Youssef; Das, Sandhitsu R; Stein, Joel; Gorniak, Richard; Jacobs, Joshua

2018-05-09

The medial temporal lobe (MTL) is widely implicated in supporting episodic memory and navigation, but its precise functional role in organizing memory across time and space remains elusive. Here we examine the specific cognitive processes implemented by MTL structures (hippocampus and entorhinal cortex) to organize memory by using electrical brain stimulation, leveraging its ability to establish causal links between brain regions and features of behavior. We studied neurosurgical patients of both sexes who performed spatial-navigation and verbal-episodic memory tasks while brain stimulation was applied in various regions during learning. During the verbal memory task, stimulation in the MTL disrupted the temporal organization of encoded memories such that items learned with stimulation tended to be recalled in a more randomized order. During the spatial task, MTL stimulation impaired subjects' abilities to remember items located far away from boundaries. These stimulation effects were specific to the MTL. Our findings thus provide the first causal demonstration in humans of the specific memory processes that are performed by the MTL to encode when and where events occurred. SIGNIFICANCE STATEMENT Numerous studies have implicated the medial temporal lobe (MTL) in encoding spatial and temporal memories, but they have not been able to causally demonstrate the nature of the cognitive processes by which this occurs in real-time. Electrical brain stimulation is able to demonstrate causal links between a brain region and a given function with high temporal precision. By examining behavior in a memory task as subjects received MTL stimulation, we provide the first causal evidence demonstrating the role of the MTL in organizing the spatial and temporal aspects of episodic memory. Copyright © 2018 the authors 0270-6474/18/384471-11$15.00/0.

Matrix-free mass spectrometric imaging using laser desorption ionisation Fourier transform ion cyclotron resonance mass spectrometry.

PubMed

Goodwin, Richard J A; Pitt, Andrew R; Harrison, David; Weidt, Stefan K; Langridge-Smith, Pat R R; Barrett, Michael P; Logan Mackay, C

2011-04-15

Mass spectrometry imaging (MSI) is a powerful tool in metabolomics and proteomics for the spatial localization and identification of pharmaceuticals, metabolites, lipids, peptides and proteins in biological tissues. However, sample preparation remains a crucial variable in obtaining the most accurate distributions. Common washing steps used to remove salts, and solvent-based matrix application, allow analyte spreading to occur. Solvent-free matrix applications can reduce this risk, but increase the possibility of ionisation bias due to matrix adhesion to tissue sections. We report here the use of matrix-free MSI using laser desorption ionisation performed on a 12 T Fourier transform ion cyclotron resonance (FTICR) mass spectrometer. We used unprocessed tissue with no post-processing following thaw-mounting on matrix-assisted laser desorption ionisation (MALDI) indium-tin oxide (ITO) target plates. The identification and distribution of a range of phospholipids in mouse brain and kidney sections are presented and compared with previously published MALDI time-of-flight (TOF) MSI distributions. Copyright © 2011 John Wiley & Sons, Ltd.

Characterization of dynamic changes of current source localization based on spatiotemporal fMRI constrained EEG source imaging

NASA Astrophysics Data System (ADS)

Nguyen, Thinh; Potter, Thomas; Grossman, Robert; Zhang, Yingchun

2018-06-01

Objective. Neuroimaging has been employed as a promising approach to advance our understanding of brain networks in both basic and clinical neuroscience. Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) represent two neuroimaging modalities with complementary features; EEG has high temporal resolution and low spatial resolution while fMRI has high spatial resolution and low temporal resolution. Multimodal EEG inverse methods have attempted to capitalize on these properties but have been subjected to localization error. The dynamic brain transition network (DBTN) approach, a spatiotemporal fMRI constrained EEG source imaging method, has recently been developed to address these issues by solving the EEG inverse problem in a Bayesian framework, utilizing fMRI priors in a spatial and temporal variant manner. This paper presents a computer simulation study to provide a detailed characterization of the spatial and temporal accuracy of the DBTN method. Approach. Synthetic EEG data were generated in a series of computer simulations, designed to represent realistic and complex brain activity at superficial and deep sources with highly dynamical activity time-courses. The source reconstruction performance of the DBTN method was tested against the fMRI-constrained minimum norm estimates algorithm (fMRIMNE). The performances of the two inverse methods were evaluated both in terms of spatial and temporal accuracy. Main results. In comparison with the commonly used fMRIMNE method, results showed that the DBTN method produces results with increased spatial and temporal accuracy. The DBTN method also demonstrated the capability to reduce crosstalk in the reconstructed cortical time-course(s) induced by neighboring regions, mitigate depth bias and improve overall localization accuracy. Significance. The improved spatiotemporal accuracy of the reconstruction allows for an improved characterization of complex neural activity. This improvement can be extended to any subsequent brain connectivity analyses used to construct the associated dynamic brain networks.

Line and word bisection in right-brain-damaged patients with left spatial neglect.

PubMed

Veronelli, Laura; Vallar, Giuseppe; Marinelli, Chiara V; Primativo, Silvia; Arduino, Lisa S

2014-01-01

Right-brain-damaged patients with left unilateral spatial neglect typically set the mid-point of horizontal lines to the right of the objective center. By contrast, healthy participants exhibit a reversed bias (pseudoneglect). The same effect has been described also when bisecting orthographic strings. In particular, for this latter kind of stimulus, some recent studies have shown that visuo-perceptual characteristics, like stimulus length, may contribute to both the magnitude and the direction bias of the bisection performance (Arduino et al. in Neuropsychologia 48:2140-2146, 2010). Furthermore, word stress was shown to modulate reading performances in both healthy participants, and patients with left spatial neglect and neglect dyslexia (Cubelli and Beschin in Brain Lang 95:319-326, 2005; Rusconi et al. in Neuropsychology 18:135-140, 2004). In Experiment I, 22 right-brain-damaged patients (11 with left visuo-spatial neglect) and 11 matched neurologically unimpaired control participants were asked to set the subjective mid-point of word letter strings, and of lines of comparable length. Most patients exhibited an overall disproportionate rightward bias, sensitive to stimulus length, and similar for words and lines. Importantly, in individual patients, biases differed according to stimulus type (words vs. lines), indicating that at least partly different mechanisms may be involved. In Experiment II, the putative effects on the bisection bias of ortho-phonological information (i.e., word stress endings), arising from the non-neglected right hand side of the stimulus were investigated. The orthographic cue induced a rightward shift of the perceived mid-point in both patients and controls, with short words stressed on the antepenultimate final sequence inducing a smaller rightward deviation with respect to short words stressed on the penultimate final sequence. In conclusion, partly different mechanisms, including both visuo-spatial and lexical factors, may support line and word bisection performance of right-brain-damaged patients with left spatial neglect, and healthy participants.

Brain Distribution of a Novel MEK Inhibitor E6201: Implications in the Treatment of Melanoma Brain Metastases.

PubMed

Gampa, Gautham; Kim, Minjee; Cook-Rostie, Nicholas; Laramy, Janice K; Sarkaria, Jann N; Paradiso, Linda; DePalatis, Louis; Elmquist, William F

2018-05-01

Clinically meaningful efficacy in the treatment of brain tumors, including melanoma brain metastases (MBM), requires selection of a potent inhibitor against a suitable target, and adequate drug distribution to target sites in the brain. Deregulated constitutive signaling of mitogen-activated protein kinase (MAPK) pathway has been frequently observed in melanoma, and mitogen-activated protein/extracellular signal-regulated kinase (MEK) has been identified to be an important target. E6201 is a potent synthetic small-molecule MEK inhibitor. The purpose of this study was to evaluate brain distribution of E6201, and examine the impact of active efflux transport at the blood-brain barrier on the central nervous system (CNS) exposure of E6201. In vitro studies utilizing transfected Madin-Darby canine kidney II (MDCKII) cells indicate that E6201 is not a substrate of P-glycoprotein (P-gp) and breast cancer resistance protein (Bcrp). In vivo studies also suggest a minimal involvement of P-gp and Bcrp in E6201's brain distribution. The total concentrations in brain were higher than in plasma, resulting in a brain-to-plasma AUC ratio (Kp) of 2.66 in wild-type mice. The brain distribution was modestly enhanced in Mdr1a/b -/- , Bcrp1 -/- , and Mdr1a/b -/- Bcrp1 -/- knockout mice. The nonspecific binding of E6201 was higher in brain compared with plasma. However, free-drug concentrations in brain following 40 mg/kg intravenous dose reach levels that exceed reported in vitro half-maximal inhibitory concentration (IC 50 ) values, suggesting that E6201 may be efficacious in inhibiting MEK-driven brain tumors. The brain distribution characteristics of E6201 make it an attractive targeted agent for clinical testing in MBM, glioblastoma, and other CNS tumors that may be effectively targeted with inhibition of MEK signaling. Copyright © 2018 by The American Society for Pharmacology and Experimental Therapeutics.

Mean phase coherence as a measure for phase synchronization and its application to the EEG of epilepsy patients

NASA Astrophysics Data System (ADS)

Mormann, Florian; Lehnertz, Klaus; David, Peter; E. Elger, Christian

2000-10-01

We apply the concept of phase synchronization of chaotic and/or noisy systems and the statistical distribution of the relative instantaneous phases to electroencephalograms (EEGs) recorded from patients with temporal lobe epilepsy. Using the mean phase coherence as a statistical measure for phase synchronization, we observe characteristic spatial and temporal shifts in synchronization that appear to be strongly related to pathological activity. In particular, we observe distinct differences in the degree of synchronization between recordings from seizure-free intervals and those before an impending seizure, indicating an altered state of brain dynamics prior to seizure activity.

High Slew-Rate Head-Only Gradient for Improving Distortion in Echo Planar Imaging: Preliminary Experience

PubMed Central

Tan, Ek T.; Lee, Seung-Kyun; Weavers, Paul T.; Graziani, Dominic; Piel, Joseph E.; Shu, Yunhong; Huston, John; Bernstein, Matt A.; Foo, Thomas K.F.

2016-01-01

Purpose To investigate the effects on echo planar imaging (EPI) distortion of using high gradient slew rates (SR) of up to 700 T/m/s for in-vivo human brain imaging, with a dedicated, head-only gradient coil. Materials and Methods Simulation studies were first performed to determine the expected echo spacing and distortion reduction in EPI. A head gradient of 42-cm inner diameter and with asymmetric transverse coils was then installed in a whole-body, conventional 3T MRI system. Human subject imaging was performed on five subjects to determine the effects of EPI on echo spacing and signal dropout at various gradient slew rates. The feasibility of whole-brain imaging at 1.5 mm-isotropic spatial resolution was demonstrated with gradient-echo and spin-echo diffusion-weighted EPI. Results As compared to a whole-body gradient coil, the EPI echo spacing in the head-only gradient coil was reduced by 48%. Simulation and in vivo results, respectively, showed up to 25-26% and 19% improvement in signal dropout. Whole-brain imaging with EPI at 1.5 mm spatial resolution provided good whole-brain coverage, spatial linearity, and low spatial distortion effects. Conclusion Our results of human brain imaging with EPI using the compact head gradient coil at slew rates higher than in conventional whole-body MR systems demonstrate substantially improved image distortion, and point to a potential for benefits to non-EPI pulse sequences. PMID:26921117

Distribution and chemical forms of gadolinium in the brain: a review.

PubMed

Kanda, Tomonori; Nakai, Yudai; Hagiwara, Akifumi; Oba, Hiroshi; Toyoda, Keiko; Furui, Shigeru

2017-11-01

In the 3 years since residual gadolinium-based contrast agent (GBCA) in the brain was first reported, much has been learned about its accumulation, including the pathway of GBCA entry into the brain, the brain distribution of GBCA and its excretion. Here we review recent progress in understanding the routes of gadolinium deposition in brain structures.

Attenuation of brain edema and spatial learning deficits by the inhibition of NADPH oxidase activity using apocynin following diffuse traumatic brain injury in rats.

PubMed

Song, Si-Xin; Gao, Jun-Ling; Wang, Kai-Jie; Li, Ran; Tian, Yan-Xia; Wei, Jian-Qiang; Cui, Jian-Zhong

2013-01-01

Diffuse brain injury (DBI) is a leading cause of mortality and disability among young individuals and adults worldwide. In specific cases, DBI is associated with permanent spatial learning dysfunction and motor deficits due to primary and secondary brain damage. Nicotinamide adenine dinucleotide phosphate (NADPH) oxidase (NOX) is a major complex that produces reactive oxygen species (ROS) during the ischemic period. The complex aggravates brain damage and cell death following ischemia/reperfusion injury; however, its role in DBI remains unclear. The present study aimed to investigate the hypothesis that levels of NOX2 (a catalytic subunit of NOX) protein expression and the activation of NOX are enhanced following DBI induction in rats and are involved in aggravating secondary brain damage. A rat model of DBI was created using a modified weight-drop device. Our results demonstrated that NOX2 protein expression and NOX activity were enhanced in the CA1 subfield of the hippocampus at 48 and 72 h following DBI induction. Treatment with apocynin (50 mg/kg body weight), a specific inhibitor of NOX, injected intraperitoneally 30 min prior to DBI significantly attenuated NOX2 protein expression and NOX activation. Moreover, treatment with apocynin reduced brain edema and improved spatial learning function assessed using the Morris water maze. These results reveal that treatment with apocynin may provide a new neuroprotective therapeutic strategy against DBI by diminishing the upregulation of NOX2 protein and NOX activity.

In vivo High Angular Resolution Diffusion-Weighted Imaging of Mouse Brain at 16.4 Tesla

PubMed Central

Alomair, Othman I.; Brereton, Ian M.; Smith, Maree T.; Galloway, Graham J.; Kurniawan, Nyoman D.

2015-01-01

Magnetic Resonance Imaging (MRI) of the rodent brain at ultra-high magnetic fields (> 9.4 Tesla) offers a higher signal-to-noise ratio that can be exploited to reduce image acquisition time or provide higher spatial resolution. However, significant challenges are presented due to a combination of longer T 1 and shorter T 2/T2* relaxation times and increased sensitivity to magnetic susceptibility resulting in severe local-field inhomogeneity artefacts from air pockets and bone/brain interfaces. The Stejskal-Tanner spin echo diffusion-weighted imaging (DWI) sequence is often used in high-field rodent brain MRI due to its immunity to these artefacts. To accurately determine diffusion-tensor or fibre-orientation distribution, high angular resolution diffusion imaging (HARDI) with strong diffusion weighting (b >3000 s/mm2) and at least 30 diffusion-encoding directions are required. However, this results in long image acquisition times unsuitable for live animal imaging. In this study, we describe the optimization of HARDI acquisition parameters at 16.4T using a Stejskal-Tanner sequence with echo-planar imaging (EPI) readout. EPI segmentation and partial Fourier encoding acceleration were applied to reduce the echo time (TE), thereby minimizing signal decay and distortion artefacts while maintaining a reasonably short acquisition time. The final HARDI acquisition protocol was achieved with the following parameters: 4 shot EPI, b = 3000 s/mm2, 64 diffusion-encoding directions, 125×150 μm2 in-plane resolution, 0.6 mm slice thickness, and 2h acquisition time. This protocol was used to image a cohort of adult C57BL/6 male mice, whereby the quality of the acquired data was assessed and diffusion tensor imaging (DTI) derived parameters were measured. High-quality images with high spatial and angular resolution, low distortion and low variability in DTI-derived parameters were obtained, indicating that EPI-DWI is feasible at 16.4T to study animal models of white matter (WM) diseases. PMID:26110770

The role of serotonin 5-HT2A receptors in memory and cognition

PubMed Central

Zhang, Gongliang; Stackman, Robert W.

2015-01-01

Serotonin 5-HT2A receptors (5-HT2ARs) are widely distributed in the central nervous system, especially in brain region essential for learning and cognition. In addition to endogenous 5-HT, several hallucinogens, antipsychotics, and antidepressants function by targeting 5-HT2ARs. Preclinical studies show that 5-HT2AR antagonists have antipsychotic and antidepressant properties, whereas agonist ligands possess cognition-enhancing and hallucinogenic properties. Abnormal 5-HT2AR activity is associated with a number of psychiatric disorders and conditions, including depression, schizophrenia, and drug addiction. In addition to its traditional activity as a G protein-coupled receptor (GPCR), recent studies have defined novel operations of 5-HT2ARs. Here we review progress in the (1) receptor anatomy and biology: distribution, signaling, polymerization and allosteric modulation; and (2) receptor functions: learning and memory, hallucination and spatial cognition, and mental disorders. Based on the recent progress in basic research on the 5-HT2AR, it appears that post-training 5-HT2AR activation enhances non-spatial memory consolidation, while pre-training 5-HT2AR activation facilitates fear extinction. Further, the potential influence that 5-HT2AR-elicited visual hallucinations may have on visual cue (i.e., landmark) guided spatial cognition is discussed. We conclude that the development of selective 5-HT2AR modulators to target distinct signaling pathways and neural circuits represents a new possibility for treating emotional, neuropsychiatric, and neurodegenerative disorders. PMID:26500553

A critical review of the allocentric spatial representation and its neural underpinnings: toward a network-based perspective

PubMed Central

Ekstrom, Arne D.; Arnold, Aiden E. G. F.; Iaria, Giuseppe

2014-01-01

While the widely studied allocentric spatial representation holds a special status in neuroscience research, its exact nature and neural underpinnings continue to be the topic of debate, particularly in humans. Here, based on a review of human behavioral research, we argue that allocentric representations do not provide the kind of map-like, metric representation one might expect based on past theoretical work. Instead, we suggest that almost all tasks used in past studies involve a combination of egocentric and allocentric representation, complicating both the investigation of the cognitive basis of an allocentric representation and the task of identifying a brain region specifically dedicated to it. Indeed, as we discuss in detail, past studies suggest numerous brain regions important to allocentric spatial memory in addition to the hippocampus, including parahippocampal, retrosplenial, and prefrontal cortices. We thus argue that although allocentric computations will often require the hippocampus, particularly those involving extracting details across temporally specific routes, the hippocampus is not necessary for all allocentric computations. We instead suggest that a non-aggregate network process involving multiple interacting brain areas, including hippocampus and extra-hippocampal areas such as parahippocampal, retrosplenial, prefrontal, and parietal cortices, better characterizes the neural basis of spatial representation during navigation. According to this model, an allocentric representation does not emerge from the computations of a single brain region (i.e., hippocampus) nor is it readily decomposable into additive computations performed by separate brain regions. Instead, an allocentric representation emerges from computations partially shared across numerous interacting brain regions. We discuss our non-aggregate network model in light of existing data and provide several key predictions for future experiments. PMID:25346679

Effects of geometrical structure on spatial distribution of thermal energy in two-dimensional triangular lattices

NASA Astrophysics Data System (ADS)

Liu, Yong-Yang; Xu, Yu-Liang; Liu, Zhong-Qiang; Li, Jing; Wang, Chun-Yang; Kong, Xiang-Mu

2018-07-01

Employing the correlation matrix technique, the spatial distribution of thermal energy in two-dimensional triangular lattices in equilibrium, interacting with linear springs, is studied. It is found that the spatial distribution of thermal energy varies with the included angle of the springs. In addition, the average thermal energy of the longer springs is lower. Springs with different included angle and length will lead to an inhomogeneous spatial distribution of thermal energy. This suggests that the spatial distribution of thermal energy is affected by the geometrical structure of the system: the more asymmetric the geometrical structure of the system is, the more inhomogeneous is the spatial distribution of thermal energy.

Tough times call for bigger brains

PubMed Central

Pravosudov, Vladimir V

2009-01-01

Memory is crucial for survival in many animals. Spatial memory in particular is important for food-caching species and may be influenced by selective pressures such as climate. The influence of climate on memory may be facilitated through the hippocampus (Hp), the part of the brain responsible in part for spatial memory. In a recent paper, we conducted the first large-scale test of the relationship between memory, the climate and the brain in a single food-caching species, the black-capped chickadee (Poecile atricapillus). We found that birds from more harsh northern climates had significantly larger hippocampal volumes and more neurons than those from more mild southern latitudes. This work suggests that environmental pressures are capable of influencing specific brain regions, which may result in enhanced memory, and hence survival, in harsh climates. This work gives us a better understanding of how the brain responds to different environments and how animals can adapt to their environment in general. PMID:19641741

Flexible, foldable, actively multiplexed, high-density electrode array for mapping brain activity in vivo.

PubMed

Viventi, Jonathan; Kim, Dae-Hyeong; Vigeland, Leif; Frechette, Eric S; Blanco, Justin A; Kim, Yun-Soung; Avrin, Andrew E; Tiruvadi, Vineet R; Hwang, Suk-Won; Vanleer, Ann C; Wulsin, Drausin F; Davis, Kathryn; Gelber, Casey E; Palmer, Larry; Van der Spiegel, Jan; Wu, Jian; Xiao, Jianliang; Huang, Yonggang; Contreras, Diego; Rogers, John A; Litt, Brian

2011-11-13

Arrays of electrodes for recording and stimulating the brain are used throughout clinical medicine and basic neuroscience research, yet are unable to sample large areas of the brain while maintaining high spatial resolution because of the need to individually wire each passive sensor at the electrode-tissue interface. To overcome this constraint, we developed new devices that integrate ultrathin and flexible silicon nanomembrane transistors into the electrode array, enabling new dense arrays of thousands of amplified and multiplexed sensors that are connected using fewer wires. We used this system to record spatial properties of cat brain activity in vivo, including sleep spindles, single-trial visual evoked responses and electrographic seizures. We found that seizures may manifest as recurrent spiral waves that propagate in the neocortex. The developments reported here herald a new generation of diagnostic and therapeutic brain-machine interface devices.

The riddle of style changes in the visual arts after interference with the right brain.

PubMed

Blanke, Olaf; Pasqualini, Isabella

2011-01-01

We here analyze the paintings and films of several visual artists, who suffered from a well-defined neuropsychological deficit, visuo-spatial hemineglect, following vascular stroke to the right brain. In our analysis we focus in particular on the oeuvre of Lovis Corinth and Luchino Visconti as both major artists continued to be highly productive over many years after their right brain damage. We analyzed their post-stroke paintings and films, indicate several aspects that differ from their pre-stroke work (omissions, use of color, perseveration, deformation), and propose-although both artists come from different times, countries, genres, and styles-that their post-stroke oeuvre reveals important similarities in style. We argue that these changes may be associated with visuo-spatial hemineglect and the right brain. We discuss future avenues of how the neuropsychological investigation of visual artists with and without neglect may allow us to investigate the relationship between brain and art.

Metronidazole and hydroxymetronidazole central nervous system distribution: 1. microdialysis assessment of brain extracellular fluid concentrations in patients with acute brain injury.

PubMed

Frasca, Denis; Dahyot-Fizelier, Claire; Adier, Christophe; Mimoz, Olivier; Debaene, Bertrand; Couet, William; Marchand, Sandrine

2014-01-01

The distribution of metronidazole in the central nervous system has only been described based on cerebrospinal fluid data. However, extracellular fluid (ECF) concentrations may better predict its antimicrobial effect and/or side effects. We sought to explore by microdialysis brain ECF metronidazole distribution in patients with acute brain injury. Four brain-injured patients monitored by cerebral microdialysis received 500 mg of metronidazole over 0.5 h every 8 h. Brain dialysates and blood samples were collected at steady state over 8 h. Probe recoveries were evaluated by in vivo retrodialysis in each patient for metronidazole. Metronidazole and OH-metronidazole were assayed by high-pressure liquid chromatography, and a noncompartmental pharmacokinetic analysis was performed. Probe recovery was equal to 78.8% ± 1.3% for metronidazole in patients. Unbound brain metronidazole concentration-time curves were delayed compared to unbound plasma concentration-time curves but with a mean metronidazole unbound brain/plasma AUC0-τ ratio equal to 102% ± 19% (ranging from 87 to 124%). The unbound plasma concentration-time profiles for OH-metronidazole were flat, with mean average steady-state concentrations equal to 4.0 ± 0.7 μg ml(-1). This microdialysis study describes the steady-state brain distribution of metronidazole in patients and confirms its extensive distribution.

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

PubMed Central

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

2015-01-01

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

Investigating intracranial tumour growth patterns with multiparametric MRI incorporating Gd‐DTPA and USPIO‐enhanced imaging

PubMed Central

Borri, Marco; Jury, Alexa; Popov, Sergey; Box, Gary; Perryman, Lara; Eccles, Suzanne A.; Jones, Chris; Robinson, Simon P.

2016-01-01

Abstract High grade and metastatic brain tumours exhibit considerable spatial variations in proliferation, angiogenesis, invasion, necrosis and oedema. Vascular heterogeneity arising from vascular co‐option in regions of invasive growth (in which the blood–brain barrier remains intact) and neoangiogenesis is a major challenge faced in the assessment of brain tumours by conventional MRI. A multiparametric MRI approach, incorporating native measurements and both Gd‐DTPA (Magnevist) and ultrasmall superparamagnetic iron oxide (P904)‐enhanced imaging, was used in combination with histogram and unsupervised cluster analysis using a k‐means algorithm to examine the spatial distribution of vascular parameters, water diffusion characteristics and invasion in intracranially propagated rat RG2 gliomas and human MDA‐MB‐231 LM2–4 breast adenocarcinomas in mice. Both tumour models presented with higher ΔR 1 (the change in transverse relaxation rate R 1 induced by Gd‐DTPA), fractional blood volume (fBV) and apparent diffusion coefficient than uninvolved regions of the brain. MDA‐MB‐231 LM2–4 tumours were less densely cellular than RG2 tumours and exhibited substantial local invasion, associated with oedema, whereas invasion in RG2 tumours was minimal. These additional features were reflected in the more heterogeneous appearance of MDA‐MB‐231 LM2–4 tumours on T 2‐weighted images and maps of functional MRI parameters. Unsupervised cluster analysis separated subregions with distinct functional properties; areas with a low fBV and relatively impermeable blood vessels (low ΔR 1) were predominantly located at the tumour margins, regions of MDA‐MB‐231 LM2–4 tumours with relatively high levels of water diffusion and low vascular permeability and/or fBV corresponded to histologically identified regions of invasion and oedema, and areas of mismatch between vascular permeability and blood volume were identified. We demonstrate that dual contrast MRI and evaluation of tissue diffusion properties, coupled with cluster analysis, allows for the assessment of heterogeneity within invasive brain tumours and the designation of functionally diverse subregions that may provide more informative predictive biomarkers. PMID:27671990

Investigating intracranial tumour growth patterns with multiparametric MRI incorporating Gd-DTPA and USPIO-enhanced imaging.

PubMed

Boult, Jessica K R; Borri, Marco; Jury, Alexa; Popov, Sergey; Box, Gary; Perryman, Lara; Eccles, Suzanne A; Jones, Chris; Robinson, Simon P

2016-11-01

High grade and metastatic brain tumours exhibit considerable spatial variations in proliferation, angiogenesis, invasion, necrosis and oedema. Vascular heterogeneity arising from vascular co-option in regions of invasive growth (in which the blood-brain barrier remains intact) and neoangiogenesis is a major challenge faced in the assessment of brain tumours by conventional MRI. A multiparametric MRI approach, incorporating native measurements and both Gd-DTPA (Magnevist) and ultrasmall superparamagnetic iron oxide (P904)-enhanced imaging, was used in combination with histogram and unsupervised cluster analysis using a k-means algorithm to examine the spatial distribution of vascular parameters, water diffusion characteristics and invasion in intracranially propagated rat RG2 gliomas and human MDA-MB-231 LM2-4 breast adenocarcinomas in mice. Both tumour models presented with higher ΔR 1 (the change in transverse relaxation rate R 1 induced by Gd-DTPA), fractional blood volume (fBV) and apparent diffusion coefficient than uninvolved regions of the brain. MDA-MB-231 LM2-4 tumours were less densely cellular than RG2 tumours and exhibited substantial local invasion, associated with oedema, whereas invasion in RG2 tumours was minimal. These additional features were reflected in the more heterogeneous appearance of MDA-MB-231 LM2-4 tumours on T 2 -weighted images and maps of functional MRI parameters. Unsupervised cluster analysis separated subregions with distinct functional properties; areas with a low fBV and relatively impermeable blood vessels (low ΔR 1 ) were predominantly located at the tumour margins, regions of MDA-MB-231 LM2-4 tumours with relatively high levels of water diffusion and low vascular permeability and/or fBV corresponded to histologically identified regions of invasion and oedema, and areas of mismatch between vascular permeability and blood volume were identified. We demonstrate that dual contrast MRI and evaluation of tissue diffusion properties, coupled with cluster analysis, allows for the assessment of heterogeneity within invasive brain tumours and the designation of functionally diverse subregions that may provide more informative predictive biomarkers. © 2016 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.

The modulation of EEG variability between internally- and externally-driven cognitive states varies with maturation and task performance

PubMed Central

Willatt, Stephanie E.; Cortese, Filomeno; Protzner, Andrea B.

2017-01-01

Increasing evidence suggests that brain signal variability is an important measure of brain function reflecting information processing capacity and functional integrity. In this study, we examined how maturation from childhood to adulthood affects the magnitude and spatial extent of state-to-state transitions in brain signal variability, and how this relates to cognitive performance. We looked at variability changes between resting-state and task (a symbol-matching task with three levels of difficulty), and within trial (fixation, post-stimulus, and post-response). We calculated variability with multiscale entropy (MSE), and additionally examined spectral power density (SPD) from electroencephalography (EEG) in children aged 8–14, and in adults aged 18–33. Our results suggest that maturation is characterized by increased local information processing (higher MSE at fine temporal scales) and decreased long-range interactions with other neural populations (lower MSE at coarse temporal scales). Children show MSE changes that are similar in magnitude, but greater in spatial extent when transitioning between internally- and externally-driven brain states. Additionally, we found that in children, greater changes in task difficulty were associated with greater magnitude of modulation in MSE. Our results suggest that the interplay between maturational and state-to-state changes in brain signal variability manifest across different spatial and temporal scales, and influence information processing capacity in the brain. PMID:28750035

Incorporating spatial constraint in co-activation pattern analysis to explore the dynamics of resting-state networks: An application to Parkinson's disease.

PubMed

Zhuang, Xiaowei; Walsh, Ryan R; Sreenivasan, Karthik; Yang, Zhengshi; Mishra, Virendra; Cordes, Dietmar

2018-05-15

The dynamics of the brain's intrinsic networks have been recently studied using co-activation pattern (CAP) analysis. The CAP method relies on few model assumptions and CAP-based measurements provide quantitative information of network temporal dynamics. One limitation of existing CAP-related methods is that the computed CAPs share considerable spatial overlap that may or may not be functionally distinct relative to specific network dynamics. To more accurately describe network dynamics with spatially distinct CAPs, and to compare network dynamics between different populations, a novel data-driven CAP group analysis method is proposed in this study. In the proposed method, a dominant-CAP (d-CAP) set is synthesized across CAPs from multiple clustering runs for each group with the constraint of low spatial similarities among d-CAPs. Alternating d-CAPs with less overlapping spatial patterns can better capture overall network dynamics. The number of d-CAPs, the temporal fraction and spatial consistency of each d-CAP, and the subject-specific switching probability among all d-CAPs are then calculated for each group and used to compare network dynamics between groups. The spatial dissimilarities among d-CAPs computed with the proposed method were first demonstrated using simulated data. High consistency between simulated ground-truth and computed d-CAPs was achieved, and detailed comparisons between the proposed method and existing CAP-based methods were conducted using simulated data. In an effort to physiologically validate the proposed technique and investigate network dynamics in a relevant brain network disorder, the proposed method was then applied to data from the Parkinson's Progression Markers Initiative (PPMI) database to compare the network dynamics in Parkinson's disease (PD) and normal control (NC) groups. Fewer d-CAPs, skewed distribution of temporal fractions of d-CAPs, and reduced switching probabilities among final d-CAPs were found in most networks in the PD group, as compared to the NC group. Furthermore, an overall negative association between switching probability among d-CAPs and disease severity was observed in most networks in the PD group as well. These results expand upon previous findings from in vivo electrophysiological recording studies in PD. Importantly, this novel analysis also demonstrates that changes in network dynamics can be measured using resting-state fMRI data from subjects with early stage PD. Copyright © 2018 Elsevier Inc. All rights reserved.

Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition

PubMed Central

Bill, Johannes; Buesing, Lars; Habenschuss, Stefan; Nessler, Bernhard; Maass, Wolfgang; Legenstein, Robert

2015-01-01

During the last decade, Bayesian probability theory has emerged as a framework in cognitive science and neuroscience for describing perception, reasoning and learning of mammals. However, our understanding of how probabilistic computations could be organized in the brain, and how the observed connectivity structure of cortical microcircuits supports these calculations, is rudimentary at best. In this study, we investigate statistical inference and self-organized learning in a spatially extended spiking network model, that accommodates both local competitive and large-scale associative aspects of neural information processing, under a unified Bayesian account. Specifically, we show how the spiking dynamics of a recurrent network with lateral excitation and local inhibition in response to distributed spiking input, can be understood as sampling from a variational posterior distribution of a well-defined implicit probabilistic model. This interpretation further permits a rigorous analytical treatment of experience-dependent plasticity on the network level. Using machine learning theory, we derive update rules for neuron and synapse parameters which equate with Hebbian synaptic and homeostatic intrinsic plasticity rules in a neural implementation. In computer simulations, we demonstrate that the interplay of these plasticity rules leads to the emergence of probabilistic local experts that form distributed assemblies of similarly tuned cells communicating through lateral excitatory connections. The resulting sparse distributed spike code of a well-adapted network carries compressed information on salient input features combined with prior experience on correlations among them. Our theory predicts that the emergence of such efficient representations benefits from network architectures in which the range of local inhibition matches the spatial extent of pyramidal cells that share common afferent input. PMID:26284370

The Brain as a Distributed Intelligent Processing System: An EEG Study

PubMed Central

da Rocha, Armando Freitas; Rocha, Fábio Theoto; Massad, Eduardo

2011-01-01

Background Various neuroimaging studies, both structural and functional, have provided support for the proposal that a distributed brain network is likely to be the neural basis of intelligence. The theory of Distributed Intelligent Processing Systems (DIPS), first developed in the field of Artificial Intelligence, was proposed to adequately model distributed neural intelligent processing. In addition, the neural efficiency hypothesis suggests that individuals with higher intelligence display more focused cortical activation during cognitive performance, resulting in lower total brain activation when compared with individuals who have lower intelligence. This may be understood as a property of the DIPS. Methodology and Principal Findings In our study, a new EEG brain mapping technique, based on the neural efficiency hypothesis and the notion of the brain as a Distributed Intelligence Processing System, was used to investigate the correlations between IQ evaluated with WAIS (Whechsler Adult Intelligence Scale) and WISC (Wechsler Intelligence Scale for Children), and the brain activity associated with visual and verbal processing, in order to test the validity of a distributed neural basis for intelligence. Conclusion The present results support these claims and the neural efficiency hypothesis. PMID:21423657

The activity of thalamic nucleus reuniens is critical for memory retrieval, but not essential for the early phase of "off-line" consolidation.

PubMed

Mei, Hao; Logothetis, Nikos K; Eschenko, Oxana

2018-03-01

Spatial navigation depends on the hippocampal function, but also requires bidirectional interactions between the hippocampus (HPC) and the prefrontal cortex (PFC). The cross-regional communication is typically regulated by critical nodes of a distributed brain network. The thalamic nucleus reuniens (RE) is reciprocally connected to both HPC and PFC and may coordinate the information flow within the HPC-PFC pathway. Here we examined if RE activity contributes to the spatial memory consolidation. Rats were trained to find reward following a complex trajectory on a crossword-like maze. Immediately after each of the five daily learning sessions the RE was reversibly inactivated by local injection of muscimol. The post-training RE inactivation affected neither the spatial task acquisition nor the memory retention, which was tested after a 20-d "forgetting" period. In contrast, the RE inactivation in well-trained rats prior to the maze exposure impaired the task performance without affecting locomotion or appetitive motivation. Our results support the role of the RE in memory retrieval and/or "online" processing of spatial information, but do not provide evidence for its engagement in "off-line" processing, at least within a time window immediately following learning experience. © 2018 Mei et al.; Published by Cold Spring Harbor Laboratory Press.

Increased power spectral density in resting-state pain-related brain networks in fibromyalgia.

PubMed

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.

Rough Sets and Stomped Normal Distribution for Simultaneous Segmentation and Bias Field Correction in Brain MR Images.

PubMed

Banerjee, Abhirup; Maji, Pradipta

2015-12-01

The segmentation of brain MR images into different tissue classes is an important task for automatic image analysis technique, particularly due to the presence of intensity inhomogeneity artifact in MR images. In this regard, this paper presents a novel approach for simultaneous segmentation and bias field correction in brain MR images. It integrates judiciously the concept of rough sets and the merit of a novel probability distribution, called stomped normal (SN) distribution. The intensity distribution of a tissue class is represented by SN distribution, where each tissue class consists of a crisp lower approximation and a probabilistic boundary region. The intensity distribution of brain MR image is modeled as a mixture of finite number of SN distributions and one uniform distribution. The proposed method incorporates both the expectation-maximization and hidden Markov random field frameworks to provide an accurate and robust segmentation. The performance of the proposed approach, along with a comparison with related methods, is demonstrated on a set of synthetic and real brain MR images for different bias fields and noise levels.

Uniform distributions of glucose oxidation and oxygen extraction in gray matter of normal human brain: No evidence of regional differences of aerobic glycolysis.

PubMed

Hyder, Fahmeed; Herman, Peter; Bailey, Christopher J; Møller, Arne; Globinsky, Ronen; Fulbright, Robert K; Rothman, Douglas L; Gjedde, Albert

2016-05-01

Regionally variable rates of aerobic glycolysis in brain networks identified by resting-state functional magnetic resonance imaging (R-fMRI) imply regionally variable adenosine triphosphate (ATP) regeneration. When regional glucose utilization is not matched to oxygen delivery, affected regions have correspondingly variable rates of ATP and lactate production. We tested the extent to which aerobic glycolysis and oxidative phosphorylation power R-fMRI networks by measuring quantitative differences between the oxygen to glucose index (OGI) and the oxygen extraction fraction (OEF) as measured by positron emission tomography (PET) in normal human brain (resting awake, eyes closed). Regionally uniform and correlated OEF and OGI estimates prevailed, with network values that matched the gray matter means, regardless of size, location, and origin. The spatial agreement between oxygen delivery (OEF≈0.4) and glucose oxidation (OGI ≈ 5.3) suggests that no specific regions have preferentially high aerobic glycolysis and low oxidative phosphorylation rates, with globally optimal maximum ATP turnover rates (VATP ≈ 9.4 µmol/g/min), in good agreement with (31)P and (13)C magnetic resonance spectroscopy measurements. These results imply that the intrinsic network activity in healthy human brain powers the entire gray matter with ubiquitously high rates of glucose oxidation. Reports of departures from normal brain-wide homogeny of oxygen extraction fraction and oxygen to glucose index may be due to normalization artefacts from relative PET measurements. © The Author(s) 2016.

C145 as a short-latency electrophysiological index of cognitive compensation in Alzheimer's disease

PubMed Central

Chapman, Robert M.; Porsteinsson, Anton P.; Gardner, Margaret N.; Mapstone, Mark; McCrary, John W.; Sandoval, Tiffany C.; Guillily, Maria D.; DeGrush, Elizabeth; Reilly, Lindsey A.

2012-01-01

Brain plasticity and cognitive compensation in the elderly are of increasing interest, and Alzheimer's disease (AD) offers an opportunity to elucidate how the brain may overcome damage. We provide neurophysiological evidence of a short-latency ERP component (C145) linked to stimulus relevancy that may reflect cognitive compensation in early-stage Alzheimer's disease (AD). Thirty-six subjects with early-stage, mild AD and 36 like-aged normal elderly (Controls) had their EEG recorded while performing our Number-Letter task, a cognitive/perceptual paradigm that manipulates stimulus relevancies. ERP components, including C145, were extracted from ERPs using Principal Components Analysis. C145 amplitudes and spatial distributions were compared among Controls, AD subjects with high performance on the Number-Letter task, and AD subjects with low performance. Compared to AD subjects, Control subjects showed enhanced C145 processing of visual stimuli in the occipital region where differential processing of relevant stimuli occurred. AD high performers recruited central brain areas in processing task relevancy. Controls and AD low performers did not show a significant task relevancy effect in these areas. We conclude that short-latency ERP components can detect electrophysiological differences in early-stage AD that reflect altered cognition. Differences in C145 amplitudes between AD and normal elderly groups regarding brain locations and types of task effects suggest compensatory mechanisms can occur in the AD brain to overcome loss of normal functionality, and this early compensation may have a profound effect on the cognitive efficiency of AD individuals. PMID:22886016

ViSimpl: Multi-View Visual Analysis of Brain Simulation Data

PubMed Central

Galindo, Sergio E.; Toharia, Pablo; Robles, Oscar D.; Pastor, Luis

2016-01-01

After decades of independent morphological and functional brain research, a key point in neuroscience nowadays is to understand the combined relationships between the structure of the brain and its components and their dynamics on multiple scales, ranging from circuits of neurons at micro or mesoscale to brain regions at macroscale. With such a goal in mind, there is a vast amount of research focusing on modeling and simulating activity within neuronal structures, and these simulations generate large and complex datasets which have to be analyzed in order to gain the desired insight. In such context, this paper presents ViSimpl, which integrates a set of visualization and interaction tools that provide a semantic view of brain data with the aim of improving its analysis procedures. ViSimpl provides 3D particle-based rendering that allows visualizing simulation data with their associated spatial and temporal information, enhancing the knowledge extraction process. It also provides abstract representations of the time-varying magnitudes supporting different data aggregation and disaggregation operations and giving also focus and context clues. In addition, ViSimpl tools provide synchronized playback control of the simulation being analyzed. Finally, ViSimpl allows performing selection and filtering operations relying on an application called NeuroScheme. All these views are loosely coupled and can be used independently, but they can also work together as linked views, both in centralized and distributed computing environments, enhancing the data exploration and analysis procedures. PMID:27774062

ViSimpl: Multi-View Visual Analysis of Brain Simulation Data.

PubMed

Galindo, Sergio E; Toharia, Pablo; Robles, Oscar D; Pastor, Luis

2016-01-01

After decades of independent morphological and functional brain research, a key point in neuroscience nowadays is to understand the combined relationships between the structure of the brain and its components and their dynamics on multiple scales, ranging from circuits of neurons at micro or mesoscale to brain regions at macroscale. With such a goal in mind, there is a vast amount of research focusing on modeling and simulating activity within neuronal structures, and these simulations generate large and complex datasets which have to be analyzed in order to gain the desired insight. In such context, this paper presents ViSimpl, which integrates a set of visualization and interaction tools that provide a semantic view of brain data with the aim of improving its analysis procedures. ViSimpl provides 3D particle-based rendering that allows visualizing simulation data with their associated spatial and temporal information, enhancing the knowledge extraction process. It also provides abstract representations of the time-varying magnitudes supporting different data aggregation and disaggregation operations and giving also focus and context clues. In addition, ViSimpl tools provide synchronized playback control of the simulation being analyzed. Finally, ViSimpl allows performing selection and filtering operations relying on an application called NeuroScheme. All these views are loosely coupled and can be used independently, but they can also work together as linked views, both in centralized and distributed computing environments, enhancing the data exploration and analysis procedures.

High-throughput isotropic mapping of whole mouse brain using multi-view light-sheet microscopy

NASA Astrophysics Data System (ADS)

Nie, Jun; Li, Yusha; Zhao, Fang; Ping, Junyu; Liu, Sa; Yu, Tingting; Zhu, Dan; Fei, Peng

2018-02-01

Light-sheet fluorescence microscopy (LSFM) uses an additional laser-sheet to illuminate selective planes of the sample, thereby enabling three-dimensional imaging at high spatial-temporal resolution. These advantages make LSFM a promising tool for high-quality brain visualization. However, even by the use of LSFM, the spatial resolution remains insufficient to resolve the neural structures across a mesoscale whole mouse brain in three dimensions. At the same time, the thick-tissue scattering prevents a clear observation from the deep of brain. Here we use multi-view LSFM strategy to solve this challenge, surpassing the resolution limit of standard light-sheet microscope under a large field-of-view (FOV). As demonstrated by the imaging of optically-cleared mouse brain labelled with thy1-GFP, we achieve a brain-wide, isotropic cellular resolution of 3μm. Besides the resolution enhancement, multi-view braining imaging can also recover complete signals from deep tissue scattering and attenuation. The identification of long distance neural projections across encephalic regions can be identified and annotated as a result.

How Does the Sparse Memory "Engram" Neurons Encode the Memory of a Spatial-Temporal Event?

PubMed

Guan, Ji-Song; Jiang, Jun; Xie, Hong; Liu, Kai-Yuan

2016-01-01

Episodic memory in human brain is not a fixed 2-D picture but a highly dynamic movie serial, integrating information at both the temporal and the spatial domains. Recent studies in neuroscience reveal that memory storage and recall are closely related to the activities in discrete memory engram (trace) neurons within the dentate gyrus region of hippocampus and the layer 2/3 of neocortex. More strikingly, optogenetic reactivation of those memory trace neurons is able to trigger the recall of naturally encoded memory. It is still unknown how the discrete memory traces encode and reactivate the memory. Considering a particular memory normally represents a natural event, which consists of information at both the temporal and spatial domains, it is unknown how the discrete trace neurons could reconstitute such enriched information in the brain. Furthermore, as the optogenetic-stimuli induced recall of memory did not depend on firing pattern of the memory traces, it is most likely that the spatial activation pattern, but not the temporal activation pattern of the discrete memory trace neurons encodes the memory in the brain. How does the neural circuit convert the activities in the spatial domain into the temporal domain to reconstitute memory of a natural event? By reviewing the literature, here we present how the memory engram (trace) neurons are selected and consolidated in the brain. Then, we will discuss the main challenges in the memory trace theory. In the end, we will provide a plausible model of memory trace cell network, underlying the conversion of neural activities between the spatial domain and the temporal domain. We will also discuss on how the activation of sparse memory trace neurons might trigger the replay of neural activities in specific temporal patterns.

The influence of damage distribution on serious brain injury in occupants in frontal motor vehicle crashes.

PubMed

Coimbra, Raul; Conroy, Carol; Hoyt, David B; Pacyna, Sharon; May, MarSue; Erwin, Steve; Tominaga, Gail; Kennedy, Frank; Sise, Michael; Velky, Tom

2008-07-01

In spite of improvements in motor vehicle safety systems and crashworthiness, motor vehicle crashes remain one of the leading causes of brain injury. The purpose of this study was to determine if the damage distribution across the frontal plane affected brain injury severity of occupants in frontal impacts. Occupants in "head on" frontal impacts with a Principal Direction of Force (PDOF) equal to 11, 12, or 1o'clock who sustained serious brain injury were identified using the Crash Injury Research Engineering Network (CIREN) database. Impacts were further classified based on the damage distribution across the frontal plane as distributed, offset, and extreme offset (corner). Overall, there was no significant difference for brain injury severity (based on Glasgow Coma Scale<9, or brain injury AIS>2) comparing occupants in the different impact categories. For occupants in distributed frontal impacts, safety belt use was protective (odds ratio (OR)=0.61) and intrusion at the occupant's seat position was four times more likely to result in severe (Glasgow Coma Scale (GCS)<9) brain injury (OR=4.35). For occupants in offset frontal impacts, again safety belt use was protective against severe brain injury (OR=0.25). Possibly due to the small number of brain-injured occupants in corner impacts, safety belts did not significantly protect against increased brain injury severity during corner impacts. This study supports the importance of safety belt use to decrease brain injury severity for occupants in distributed and offset frontal crashes. It also illustrates how studying "real world" crashes may provide useful information on occupant injuries under impact circumstances not currently covered by crash testing.

A highly accurate symmetric optical flow based high-dimensional nonlinear spatial normalization of brain images.

PubMed

Wen, Ying; Hou, Lili; He, Lianghua; Peterson, Bradley S; Xu, Dongrong

2015-05-01

Spatial normalization plays a key role in voxel-based analyses of brain images. We propose a highly accurate algorithm for high-dimensional spatial normalization of brain images based on the technique of symmetric optical flow. We first construct a three dimension optical model with the consistency assumption of intensity and consistency of the gradient of intensity under a constraint of discontinuity-preserving spatio-temporal smoothness. Then, an efficient inverse consistency optical flow is proposed with aims of higher registration accuracy, where the flow is naturally symmetric. By employing a hierarchical strategy ranging from coarse to fine scales of resolution and a method of Euler-Lagrange numerical analysis, our algorithm is capable of registering brain images data. Experiments using both simulated and real datasets demonstrated that the accuracy of our algorithm is not only better than that of those traditional optical flow algorithms, but also comparable to other registration methods used extensively in the medical imaging community. Moreover, our registration algorithm is fully automated, requiring a very limited number of parameters and no manual intervention. Copyright © 2015 Elsevier Inc. All rights reserved.

An Automated Platform for High-Resolution Tissue Imaging Using Nanospray Desorption Electrospray Ionization Mass Spectrometry

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

Lanekoff, Ingela T.; Heath, Brandi S.; Liyu, Andrey V.

2012-10-02

An automated platform has been developed for acquisition and visualization of mass spectrometry imaging (MSI) data using nanospray desorption electrospray ionization (nano-DESI). The new system enables robust operation of the nano-DESI imaging source over many hours. This is achieved by controlling the distance between the sample and the probe by mounting the sample holder onto an automated XYZ stage and defining the tilt of the sample plane. This approach is useful for imaging of relatively flat samples such as thin tissue sections. Custom software called MSI QuickView was developed for visualization of large data sets generated in imaging experiments. MSImore » QuickView enables fast visualization of the imaging data during data acquisition and detailed processing after the entire image is acquired. The performance of the system is demonstrated by imaging rat brain tissue sections. High resolution mass analysis combined with MS/MS experiments enabled identification of lipids and metabolites in the tissue section. In addition, high dynamic range and sensitivity of the technique allowed us to generate ion images of low-abundance isobaric lipids. High-spatial resolution image acquired over a small region of the tissue section revealed the spatial distribution of an abundant brain metabolite, creatine, in the white and gray matter that is consistent with the literature data obtained using magnetic resonance spectroscopy.« less

On the feasibility of concurrent human TMS-EEG-fMRI measurements

PubMed Central

Reithler, Joel; Schuhmann, Teresa; de Graaf, Tom; Uludağ, Kâmil; Goebel, Rainer; Sack, Alexander T.

2013-01-01

Simultaneously combining the complementary assets of EEG, functional MRI (fMRI), and transcranial magnetic stimulation (TMS) within one experimental session provides synergetic results, offering insights into brain function that go beyond the scope of each method when used in isolation. The steady increase of concurrent EEG-fMRI, TMS-EEG, and TMS-fMRI studies further underlines the added value of such multimodal imaging approaches. Whereas concurrent EEG-fMRI enables monitoring of brain-wide network dynamics with high temporal and spatial resolution, the combination with TMS provides insights in causal interactions within these networks. Thus the simultaneous use of all three methods would allow studying fast, spatially accurate, and distributed causal interactions in the perturbed system and its functional relevance for intact behavior. Concurrent EEG-fMRI, TMS-EEG, and TMS-fMRI experiments are already technically challenging, and the three-way combination of TMS-EEG-fMRI might yield additional difficulties in terms of hardware strain or signal quality. The present study explored the feasibility of concurrent TMS-EEG-fMRI studies by performing safety and quality assurance tests based on phantom and human data combining existing commercially available hardware. Results revealed that combined TMS-EEG-fMRI measurements were technically feasible, safe in terms of induced temperature changes, allowed functional MRI acquisition with comparable image quality as during concurrent EEG-fMRI or TMS-fMRI, and provided artifact-free EEG before and from 300 ms after TMS pulse application. Based on these empirical findings, we discuss the conceptual benefits of this novel complementary approach to investigate the working human brain and list a number of precautions and caveats to be heeded when setting up such multimodal imaging facilities with current hardware. PMID:23221407

The Neural Correlates of Chronic Symptoms of Vertigo Proneness in Humans

PubMed Central

Alsalman, Ola; Ost, Jan; Vanspauwen, Robby; Blaivie, Catherine; De Ridder, Dirk; Vanneste, Sven

2016-01-01

Vestibular signals are of significant importance for variable functions including gaze stabilization, spatial perception, navigation, cognition, and bodily self-consciousness. The vestibular network governs functions that might be impaired in patients affected with vestibular dysfunction. It is currently unclear how different brain regions/networks process vestibular information and integrate the information into a unified spatial percept related to somatosensory awareness and whether people with recurrent balance complaints have a neural signature as a trait affecting their development of chronic symptoms of vertigo. Pivotal evidence points to a vestibular-related brain network in humans that is widely distributed in nature. By using resting state source localized electroencephalography in non-vertiginous state, electrophysiological changes in activity and functional connectivity of 23 patients with balance complaints where chronic symptoms of vertigo and dizziness are among the most common reported complaints are analyzed and compared to healthy subjects. The analyses showed increased alpha2 activity within the posterior cingulate cortex and the precuneues/cuneus and reduced beta3 and gamma activity within the pregenual and subgenual anterior cingulate cortex for the subjects with balance complaints. These electrophysiological variations were correlated with reported chronic symptoms of vertigo intensity. A region of interest analysis found reduced functional connectivity for gamma activity within the vestibular cortex, precuneus, frontal eye field, intra-parietal sulcus, orbitofrontal cortex, and the dorsal anterior cingulate cortex. In addition, there was a positive correlation between chronic symptoms of vertigo intensity and increased alpha-gamma nesting in the left frontal eye field. When compared to healthy subjects, there is evidence of electrophysiological changes in the brain of patients with balance complaints even outside chronic symptoms of vertigo episodes. This suggests that these patients have a neural signature or trait that makes them prone to developing chronic balance problems. PMID:27089185

Modalities of Thinking: State and Trait Effects on Cross-Frequency Functional Independent Brain Networks.

PubMed

Milz, Patricia; Pascual-Marqui, Roberto D; Lehmann, Dietrich; Faber, Pascal L

2016-05-01

Functional states of the brain are constituted by the temporally attuned activity of spatially distributed neural networks. Such networks can be identified by independent component analysis (ICA) applied to frequency-dependent source-localized EEG data. This methodology allows the identification of networks at high temporal resolution in frequency bands of established location-specific physiological functions. EEG measurements are sensitive to neural activity changes in cortical areas of modality-specific processing. We tested effects of modality-specific processing on functional brain networks. Phasic modality-specific processing was induced via tasks (state effects) and tonic processing was assessed via modality-specific person parameters (trait effects). Modality-specific person parameters and 64-channel EEG were obtained from 70 male, right-handed students. Person parameters were obtained using cognitive style questionnaires, cognitive tests, and thinking modality self-reports. EEG was recorded during four conditions: spatial visualization, object visualization, verbalization, and resting. Twelve cross-frequency networks were extracted from source-localized EEG across six frequency bands using ICA. RMANOVAs, Pearson correlations, and path modelling examined effects of tasks and person parameters on networks. Results identified distinct state- and trait-dependent functional networks. State-dependent networks were characterized by decreased, trait-dependent networks by increased alpha activity in sub-regions of modality-specific pathways. Pathways of competing modalities showed opposing alpha changes. State- and trait-dependent alpha were associated with inhibitory and automated processing, respectively. Antagonistic alpha modulations in areas of competing modalities likely prevent intruding effects of modality-irrelevant processing. Considerable research suggested alpha modulations related to modality-specific states and traits. This study identified the distinct electrophysiological cortical frequency-dependent networks within which they operate.

The Neural Correlates of Chronic Symptoms of Vertigo Proneness in Humans.

PubMed

Alsalman, Ola; Ost, Jan; Vanspauwen, Robby; Blaivie, Catherine; De Ridder, Dirk; Vanneste, Sven

2016-01-01

Vestibular signals are of significant importance for variable functions including gaze stabilization, spatial perception, navigation, cognition, and bodily self-consciousness. The vestibular network governs functions that might be impaired in patients affected with vestibular dysfunction. It is currently unclear how different brain regions/networks process vestibular information and integrate the information into a unified spatial percept related to somatosensory awareness and whether people with recurrent balance complaints have a neural signature as a trait affecting their development of chronic symptoms of vertigo. Pivotal evidence points to a vestibular-related brain network in humans that is widely distributed in nature. By using resting state source localized electroencephalography in non-vertiginous state, electrophysiological changes in activity and functional connectivity of 23 patients with balance complaints where chronic symptoms of vertigo and dizziness are among the most common reported complaints are analyzed and compared to healthy subjects. The analyses showed increased alpha2 activity within the posterior cingulate cortex and the precuneues/cuneus and reduced beta3 and gamma activity within the pregenual and subgenual anterior cingulate cortex for the subjects with balance complaints. These electrophysiological variations were correlated with reported chronic symptoms of vertigo intensity. A region of interest analysis found reduced functional connectivity for gamma activity within the vestibular cortex, precuneus, frontal eye field, intra-parietal sulcus, orbitofrontal cortex, and the dorsal anterior cingulate cortex. In addition, there was a positive correlation between chronic symptoms of vertigo intensity and increased alpha-gamma nesting in the left frontal eye field. When compared to healthy subjects, there is evidence of electrophysiological changes in the brain of patients with balance complaints even outside chronic symptoms of vertigo episodes. This suggests that these patients have a neural signature or trait that makes them prone to developing chronic balance problems.

Saturable active efflux by p-glycoprotein and breast cancer resistance protein at the blood-brain barrier leads to nonlinear distribution of elacridar to the central nervous system.

PubMed

Sane, Ramola; Agarwal, Sagar; Mittapalli, Rajendar K; Elmquist, William F

2013-04-01

The study objective was to investigate factors that affect the central nervous system (CNS) distribution of elacridar. Elacridar inhibits transport mediated by P-glycoprotein (P-gp) and breast cancer resistance protein (Bcrp) and has been used to study the influence of transporters on brain distribution of chemotherapeutics. Adequate distribution of elacridar across the blood-brain barrier (BBB) and into the brain parenchyma is necessary to target tumor cells in the brain that overexpress transporters and reside behind an intact BBB. We examined the role of P-gp and Bcrp on brain penetration of elacridar using Friend leukemia virus strain B wild-type, Mdr1a/b(-/-), Bcrp1(-/-), and Mdr1a/b(-/-)Bcrp1(-/-) mice. Initially, the mice were administered 2.5 mg/kg of elacridar intravenously, and the plasma and brain concentrations were determined. The brain-to-plasma partition coefficient of elacridar in the wild-type mice was 0.82, as compared with 3.5 in Mdr1a/b(-/-) mice, 6.6 in Bcrp1(-/-) mice, and 15 in Mdr1a/b(-/-)Bcrp1(-/-) mice, indicating that both P-gp and Bcrp limit the brain distribution of elacridar. The four genotypes were then administered increasing doses of elacridar, and the CNS distribution of elacridar was determined. The observed and model predicted maximum brain-to-plasma ratios (Emax) at the highest dose were not significantly different in all genotypes. However, the ED50 was lower for Mdr1a/b(-/-) mice compared with Bcrp1(-/-) mice. These findings correlate with the relative expression of P-gp and Bcrp at the BBB in these mice and demonstrate the quantitative enhancement in elacridar CNS distribution as a function of its dose. Overall, this study provides useful concepts for future applications of elacridar as an adjuvant therapy to improve targeting of chemotherapeutic agents to tumor cells in the brain parenchyma.

Spatial Working Memory Performance and fMRI Activation Interactions in Abstinent Adolescent Marijuana Users

PubMed Central

Padula, Claudia B.; Schweinsburg, Alecia D.; Tapert, Susan F.

2008-01-01

Previous studies have suggested neural disruption and reorganization in adult marijuana users. However, it remains unclear whether these effects persist in adolescents after 28 days of abstinence and, if they do, what Performance × Brain Response interactions occur. Adolescent marijuana users (n = 17) and controls (n = 17) aged 16–18 years were recruited from local schools. Functional magnetic resonance imaging data were collected after 28 days’ monitored abstinence as participants performed a spatial working memory task. Marijuana users show Performance × Brain Response interactions in the bilateral temporal lobes, left anterior cingulate, left parahippocampal gyrus, and right thalamus (clusters ≥ 1358 μl; p <.05), although groups do not differ on behavioral measures of task performance. Marijuana users show differences in brain response to a spatial working memory task despite adequate performance, suggesting a different approach to the task via altered neural pathways. PMID:18072830

Spatial distribution of traffic in a cellular mobile data network

NASA Astrophysics Data System (ADS)

Linnartz, J. P. M. G.

1987-02-01

The use of integral transforms of the probability density function for the received power to analyze the relation between the spatial distributions of offered and throughout packet traffic in a mobile radio network with Rayleigh fading channels and ALOHA multiple access was assessed. A method to obtain the spatial distribution of throughput traffic from a prescribed spatial distribution of offered traffic is presented. Incoherent and coherent addition of interference signals is considered. The channel behavior for heavy traffic loads is studied. In both the incoherent and coherent case, the spatial distribution of offered traffic required to ensure a prescribed spatially uniform throughput is synthesized numerically.

Category-dependent and category-independent goal-value codes in human ventromedial prefrontal cortex

PubMed Central

McNamee, Daniel; Rangel, Antonio; O’Doherty, John P

2013-01-01

To choose between manifestly distinct options, it is suggested that the brain assigns values to goals using a common currency. Although previous studies have reported activity in ventromedial prefrontal cortex (vmPFC) correlating with the value of different goal stimuli, it remains unclear whether such goal-value representations are independent of the associated stimulus categorization, as required by a common currency. Using multivoxel pattern analyses on functional magnetic resonance imaging (fMRI) data, we found a region of medial prefrontal cortex to contain a distributed goal-value code that is independent of stimulus category. More ventrally in the vmPFC, we found spatially distinct areas of the medial orbitofrontal cortex to contain unique category-dependent distributed value codes for food and consumer items. These results implicate the medial prefrontal cortex in the implementation of a common currency and suggest a ventral versus dorsal topographical organization of value signals in the vmPFC. PMID:23416449

State-space receptive fields of semicircular canal afferent neurons in the bullfrog

NASA Technical Reports Server (NTRS)

Paulin, M. G.; Hoffman, L. F.

2001-01-01

Receptive fields are commonly used to describe spatial characteristics of sensory neuron responses. They can be extended to characterize temporal or dynamical aspects by mapping neural responses in dynamical state spaces. The state-space receptive field of a neuron is the probability distribution of the dynamical state of the stimulus-generating system conditioned upon the occurrence of a spike. We have computed state-space receptive fields for semicircular canal afferent neurons in the bullfrog (Rana catesbeiana). We recorded spike times during broad-band Gaussian noise rotational velocity stimuli, computed the frequency distribution of head states at spike times, and normalized these to obtain conditional pdfs for the state. These state-space receptive fields quantify what the brain can deduce about the dynamical state of the head when a single spike arrives from the periphery. c2001 Elsevier Science B.V. All rights reserved.

Developmental gender differences in children in a virtual spatial memory task.

PubMed

León, Irene; Cimadevilla, José Manuel; Tascón, Laura

2014-07-01

Behavioral achievements are the product of brain maturation. During postnatal development, the medial temporal lobe completes its maturation, and children acquire new memory abilities. In recent years, virtual reality-based tasks have been introduced in the neuropsychology field to assess different cognitive functions. In this work, desktop virtual reality tasks are combined with classic psychometric tests to assess spatial abilities in 4- to 10-year-old children. Fifty boys and 50 girls 4-10-years of age participated in this study. Spatial reference memory and spatial working memory were assessed using a desktop virtual reality-based task. Other classic psychometric tests were also included in this work (e.g., the Corsi Block Tapping Test, digit tests, 10/36 Spatial Recall Test). In general terms, 4- and 5-year-old groups showed poorer performance than the older groups. However, 5-year-old children showed basic spatial navigation abilities with little difficulty. In addition, boys outperformed girls from the 6-8-year-old groups. Gender differences only emerged in the reference-memory version of the spatial task, whereas both sexes displayed similar performances in the working-memory version. There was general improvement in the performance of different tasks in children older than 5 years. However, results also suggest that brain regions involved in allocentric memory are functional even at the age of 5. In addition, the brain structures underlying reference memory mature later in girls than those required for the working memory.

The Savant Syndrome Registry: A Preliminary Report.

PubMed

Treffert, Darold A; Rebedew, David L

2015-08-01

A registry has been established to document certain characteristics on a sizeable worldwide sample of individuals with savant syndrome, a rare but remarkable condition in which persons with developmental disabilities, brain injury, or brain disease have some spectacular "islands" of skill or ability that stand in jarring, marked contrast to overall handicap. Of the 319 savants included in the registry, 90% are congenital savants, while 10% are acquired savants. The registry includes individuals from 33 countries, with 70% from the United States or Canada. Sex distribution was 79% male vs. 21% female (4:1). This report summarizes the findings in the congenital savant syndrome category of the registry. Among the individuals with congenital savant syndrome, the most common underlying disability was Autistic Spectrum Disorder (75%); various other central nervous system (CNS) disorders were present in the other 25%. Fifty-five percent possessed a single special skill, while 45% had multiple skills. Music was the most frequent principal skill followed by art, memory, mathematics, calendar calculating, language, visual-spatial/mechanical, athletic, computer, extrasensory perception, and other skills.

What happens when spins meet for ionizing radiation dosimetry?

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

Pavoni, Juliana F.; Baffa, Oswaldo, E-mail: baffa@usp.br; Neves-Junior, Wellington F. P.

2016-07-07

Electron spin resonance (ESR) and magnetic resonance imaging (MRI) can be used to measure radiation dose deposited in different milieu through its effects. Radiation can break chemical bonds and if they produce stable free radicals, ESR can measure their concentration through their spins and a dose can be inferred. Ionizing radiation can also promote polymerization and in this case proton relaxation times can be measured and an image weighed by T2 can be produced giving spatial information about dose. A review of the basics of these applications is presented concluding with an end-to-end test using a composite Gel-Alanine phantom tomore » validate 3-dimensionally dose distribution delivered in a simulation of Volume Modulated Arch Therapy on the simultaneous treatment of multiple brain metastases. The results obtained with the gel and alanine dosimeters are consistent with the expected by the treatment planning system, showing the potential of this multidosimetric approach and validating dosimetrically the multiple brain metastases treatment using VMAT.« less

What happens when spins meet for ionizing radiation dosimetry?

NASA Astrophysics Data System (ADS)

Pavoni, Juliana F.; Neves-Junior, Wellington F. P.; Baffa, Oswaldo

2016-07-01

Electron spin resonance (ESR) and magnetic resonance imaging (MRI) can be used to measure radiation dose deposited in different milieu through its effects. Radiation can break chemical bonds and if they produce stable free radicals, ESR can measure their concentration through their spins and a dose can be inferred. Ionizing radiation can also promote polymerization and in this case proton relaxation times can be measured and an image weighed by T2 can be produced giving spatial information about dose. A review of the basics of these applications is presented concluding with an end-to-end test using a composite Gel-Alanine phantom to validate 3-dimensionally dose distribution delivered in a simulation of Volume Modulated Arch Therapy on the simultaneous treatment of multiple brain metastases. The results obtained with the gel and alanine dosimeters are consistent with the expected by the treatment planning system, showing the potential of this multidosimetric approach and validating dosimetrically the multiple brain metastases treatment using VMAT.

Three-dimensional optical topography of brain activity in infants watching videos of human movement

NASA Astrophysics Data System (ADS)

Correia, Teresa; Lloyd-Fox, Sarah; Everdell, Nick; Blasi, Anna; Elwell, Clare; Hebden, Jeremy C.; Gibson, Adam

2012-03-01

We present 3D optical topography images reconstructed from data obtained previously while infants observed videos of adults making natural movements of their eyes and hands. The optical topography probe was placed over the temporal cortex, which in adults is responsible for cognitive processing of similar stimuli. Increases in oxyhaemoglobin were measured and reconstructed using a multispectral imaging algorithm with spatially variant regularization to optimize depth discrimination. The 3D optical topography images suggest that similar brain regions are activated in infants and adults. Images were presented showing the distribution of activation in a plane parallel to the surface, as well as changes in activation with depth. The time-course of activation was followed in the pixel which demonstrated the largest change, showing that changes could be measured with high temporal resolution. These results suggest that infants a few months old have regions which are specialized for reacting to human activity, and that these subtle changes can be effectively analysed using 3D optical topography.

Sparsity enables estimation of both subcortical and cortical activity from MEG and EEG

PubMed Central

Krishnaswamy, Pavitra; Obregon-Henao, Gabriel; Ahveninen, Jyrki; Khan, Sheraz; Iglesias, Juan Eugenio; Hämäläinen, Matti S.; Purdon, Patrick L.

2017-01-01

Subcortical structures play a critical role in brain function. However, options for assessing electrophysiological activity in these structures are limited. Electromagnetic fields generated by neuronal activity in subcortical structures can be recorded noninvasively, using magnetoencephalography (MEG) and electroencephalography (EEG). However, these subcortical signals are much weaker than those generated by cortical activity. In addition, we show here that it is difficult to resolve subcortical sources because distributed cortical activity can explain the MEG and EEG patterns generated by deep sources. We then demonstrate that if the cortical activity is spatially sparse, both cortical and subcortical sources can be resolved with M/EEG. Building on this insight, we develop a hierarchical sparse inverse solution for M/EEG. We assess the performance of this algorithm on realistic simulations and auditory evoked response data, and show that thalamic and brainstem sources can be correctly estimated in the presence of cortical activity. Our work provides alternative perspectives and tools for characterizing electrophysiological activity in subcortical structures in the human brain. PMID:29138310

Gender similarities and differences in brain activation strategies: Voxel-based meta-analysis on fMRI studies.

PubMed

AlRyalat, Saif Aldeen

2017-01-01

Gender similarities and differences have long been a matter of debate in almost all human research, especially upon reaching the discussion about brain functions. This large scale meta-analysis was performed on functional MRI studies. It included more than 700 active brain foci from more than 70 different experiments to study gender related similarities and differences in brain activation strategies for three of the main brain functions: Visual-spatial cognition, memory, and emotion. Areas that are significantly activated by both genders (i.e. core areas) for the tested brain function are mentioned, whereas those areas significantly activated exclusively in one gender are the gender specific areas. During visual-spatial cognition task, and in addition to the core areas, males significantly activated their left superior frontal gyrus, compared with left superior parietal lobule in females. For memory tasks, several different brain areas activated by each gender, but females significantly activated two areas from the limbic system during memory retrieval tasks. For emotional task, males tend to recruit their bilateral prefrontal regions, whereas females tend to recruit their bilateral amygdalae. This meta-analysis provides an overview based on functional MRI studies on how males and females use their brain.

3D Data Mapping and Real-Time Experiment Control and Visualization in Brain Slices.

PubMed

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.

Large-scale recording of thalamocortical circuits: in vivo electrophysiology with the two-dimensional electronic depth control silicon probe.

PubMed

Fiáth, Richárd; Beregszászi, Patrícia; Horváth, Domonkos; Wittner, Lucia; Aarts, Arno A A; Ruther, Patrick; Neves, Hercules P; Bokor, Hajnalka; Acsády, László; Ulbert, István

2016-11-01

Recording simultaneous activity of a large number of neurons in distributed neuronal networks is crucial to understand higher order brain functions. We demonstrate the in vivo performance of a recently developed electrophysiological recording system comprising a two-dimensional, multi-shank, high-density silicon probe with integrated complementary metal-oxide semiconductor electronics. The system implements the concept of electronic depth control (EDC), which enables the electronic selection of a limited number of recording sites on each of the probe shafts. This innovative feature of the system permits simultaneous recording of local field potentials (LFP) and single- and multiple-unit activity (SUA and MUA, respectively) from multiple brain sites with high quality and without the actual physical movement of the probe. To evaluate the in vivo recording capabilities of the EDC probe, we recorded LFP, MUA, and SUA in acute experiments from cortical and thalamic brain areas of anesthetized rats and mice. The advantages of large-scale recording with the EDC probe are illustrated by investigating the spatiotemporal dynamics of pharmacologically induced thalamocortical slow-wave activity in rats and by the two-dimensional tonotopic mapping of the auditory thalamus. In mice, spatial distribution of thalamic responses to optogenetic stimulation of the neocortex was examined. Utilizing the benefits of the EDC system may result in a higher yield of useful data from a single experiment compared with traditional passive multielectrode arrays, and thus in the reduction of animals needed for a research study. Copyright © 2016 the American Physiological Society.

Midsagittal Brain Shape Correlation with Intelligence and Cognitive Performance

ERIC Educational Resources Information Center

Bruner, Emiliano; Martin-Loeches, Manuel; Burgaleta, Miguel; Colom, Roberto

2011-01-01

Brain shape might influence cognitive performance because of the relationships between functions, spatial organization, and differential volumetric development of cortical areas. Here we analyze the relationships between midsagittal brain shape variation and a set of basic psychological measures. Coordinates in 2D from 102 MRI-scanned young adult…

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

Wu, Pei-Hsin; Chung, Hsiao-Wen; Tsai, Ping-Huei

Purpose: One of the technical advantages of functional magnetic resonance imaging (fMRI) is its precise localization of changes from neuronal activities. While current practice of fMRI acquisition at voxel size around 3 × 3 × 3 mm{sup 3} achieves satisfactory results in studies of basic brain functions, higher spatial resolution is required in order to resolve finer cortical structures. This study investigated spatial resolution effects on brain fMRI experiments using balanced steady-state free precession (bSSFP) imaging with 0.37 mm{sup 3} voxel volume at 3.0 T. Methods: In fMRI experiments, full and unilateral visual field 5 Hz flashing checkerboard stimulations weremore » given to healthy subjects. The bSSFP imaging experiments were performed at three different frequency offsets to widen the coverage, with functional activations in the primary visual cortex analyzed using the general linear model. Variations of the spatial resolution were achieved by removing outerk-space data components. Results: Results show that a reduction in voxel volume from 3.44 × 3.44 × 2 mm{sup 3} to 0.43 × 0.43 × 2 mm{sup 3} has resulted in an increase of the functional activation signals from (7.7 ± 1.7)% to (20.9 ± 2.0)% at 3.0 T, despite of the threefold SNR decreases in the original images, leading to nearly invariant functional contrast-to-noise ratios (fCNR) even at high spatial resolution. Activation signals aligning nicely with gray matter sulci at high spatial resolution would, on the other hand, have possibly been mistaken as noise at low spatial resolution. Conclusions: It is concluded that the bSSFP sequence is a plausible technique for fMRI investigations at submillimeter voxel widths without compromising fCNR. The reduction of partial volume averaging with nonactivated brain tissues to retain fCNR is uniquely suitable for high spatial resolution applications such as the resolving of columnar organization in the brain.« less

A stereotaxic, population-averaged T1w ovine brain atlas including cerebral morphology and tissue volumes

PubMed Central

Nitzsche, Björn; Frey, Stephen; Collins, Louis D.; Seeger, Johannes; Lobsien, Donald; Dreyer, Antje; Kirsten, Holger; Stoffel, Michael H.; Fonov, Vladimir S.; Boltze, Johannes

2015-01-01

Standard stereotaxic reference systems play a key role in human brain studies. Stereotaxic coordinate systems have also been developed for experimental animals including non-human primates, dogs, and rodents. However, they are lacking for other species being relevant in experimental neuroscience including sheep. Here, we present a spatial, unbiased ovine brain template with tissue probability maps (TPM) that offer a detailed stereotaxic reference frame for anatomical features and localization of brain areas, thereby enabling inter-individual and cross-study comparability. Three-dimensional data sets from healthy adult Merino sheep (Ovis orientalis aries, 12 ewes and 26 neutered rams) were acquired on a 1.5 T Philips MRI using a T1w sequence. Data were averaged by linear and non-linear registration algorithms. Moreover, animals were subjected to detailed brain volume analysis including examinations with respect to body weight (BW), age, and sex. The created T1w brain template provides an appropriate population-averaged ovine brain anatomy in a spatial standard coordinate system. Additionally, TPM for gray (GM) and white (WM) matter as well as cerebrospinal fluid (CSF) classification enabled automatic prior-based tissue segmentation using statistical parametric mapping (SPM). Overall, a positive correlation of GM volume and BW explained about 15% of the variance of GM while a positive correlation between WM and age was found. Absolute tissue volume differences were not detected, indeed ewes showed significantly more GM per bodyweight as compared to neutered rams. The created framework including spatial brain template and TPM represent a useful tool for unbiased automatic image preprocessing and morphological characterization in sheep. Therefore, the reported results may serve as a starting point for further experimental and/or translational research aiming at in vivo analysis in this species. PMID:26089780

Source-based neurofeedback methods using EEG recordings: training altered brain activity in a functional brain source derived from blind source separation

PubMed Central

White, David J.; Congedo, Marco; Ciorciari, Joseph

2014-01-01

A developing literature explores the use of neurofeedback in the treatment of a range of clinical conditions, particularly ADHD and epilepsy, whilst neurofeedback also provides an experimental tool for studying the functional significance of endogenous brain activity. A critical component of any neurofeedback method is the underlying physiological signal which forms the basis for the feedback. While the past decade has seen the emergence of fMRI-based protocols training spatially confined BOLD activity, traditional neurofeedback has utilized a small number of electrode sites on the scalp. As scalp EEG at a given electrode site reflects a linear mixture of activity from multiple brain sources and artifacts, efforts to successfully acquire some level of control over the signal may be confounded by these extraneous sources. Further, in the event of successful training, these traditional neurofeedback methods are likely influencing multiple brain regions and processes. The present work describes the use of source-based signal processing methods in EEG neurofeedback. The feasibility and potential utility of such methods were explored in an experiment training increased theta oscillatory activity in a source derived from Blind Source Separation (BSS) of EEG data obtained during completion of a complex cognitive task (spatial navigation). Learned increases in theta activity were observed in two of the four participants to complete 20 sessions of neurofeedback targeting this individually defined functional brain source. Source-based EEG neurofeedback methods using BSS may offer important advantages over traditional neurofeedback, by targeting the desired physiological signal in a more functionally and spatially specific manner. Having provided preliminary evidence of the feasibility of these methods, future work may study a range of clinically and experimentally relevant brain processes where individual brain sources may be targeted by source-based EEG neurofeedback. PMID:25374520

Is functional integration of resting state brain networks an unspecific biomarker for working memory performance?

PubMed

Alavash, Mohsen; Doebler, Philipp; Holling, Heinz; Thiel, Christiane M; Gießing, Carsten

2015-03-01

Is there one optimal topology of functional brain networks at rest from which our cognitive performance would profit? Previous studies suggest that functional integration of resting state brain networks is an important biomarker for cognitive performance. However, it is still unknown whether higher network integration is an unspecific predictor for good cognitive performance or, alternatively, whether specific network organization during rest predicts only specific cognitive abilities. Here, we investigated the relationship between network integration at rest and cognitive performance using two tasks that measured different aspects of working memory; one task assessed visual-spatial and the other numerical working memory. Network clustering, modularity and efficiency were computed to capture network integration on different levels of network organization, and to statistically compare their correlations with the performance in each working memory test. The results revealed that each working memory aspect profits from a different resting state topology, and the tests showed significantly different correlations with each of the measures of network integration. While higher global network integration and modularity predicted significantly better performance in visual-spatial working memory, both measures showed no significant correlation with numerical working memory performance. In contrast, numerical working memory was superior in subjects with highly clustered brain networks, predominantly in the intraparietal sulcus, a core brain region of the working memory network. Our findings suggest that a specific balance between local and global functional integration of resting state brain networks facilitates special aspects of cognitive performance. In the context of working memory, while visual-spatial performance is facilitated by globally integrated functional resting state brain networks, numerical working memory profits from increased capacities for local processing, especially in brain regions involved in working memory performance. Copyright © 2014 Elsevier Inc. All rights reserved.

Persistent neurochemical and behavioral abnormalities in adulthood despite early iron supplementation for perinatal iron deficiency anemia in rats⋆

PubMed Central

Felt, Barbara T.; Beard, John L.; Schallert, Timothy; Shao, Jie; Aldridge, J. Wayne; Connor, James R.; Georgieff, Michael K.; Lozoff, Betsy

2006-01-01

Background Iron deficiency anemia (IDA) has been associated with altered cognitive, motor, and social-emotional outcomes in human infants. We recently reported that rats with chronic perinatal IDA, had altered regional brain iron, monoamines, and sensorimotor skill emergence during early development. Objective To examine the long-term consequences of chronic perinatal IDA on behavior, brain iron and monoamine systems after dietary iron treatment in rats. Methods Sixty dams were randomly assigned to iron-sufficient (CN) or low-iron (EID) diets during gestation and lactation. Thereafter, all offspring were fed the iron-sufficient diet, assessed for hematology and behavior after weaning and into adulthood and for brain measures as adults (regional brain iron, monoamines, dopamine and serotonin transporters, and dopamine receptor). Behavioral assessments included sensorimotor function, general activity, response to novelty, spatial alternation, and spatial water maze performance. Results Hematology and growth were similar for EID and CN rats by postnatal day 35. In adulthood, EID thalamic iron content was lower. Monoamines, dopamine transporter, and dopamine receptor concentrations did not differ from CN. EID serotonin transporter concentration was reduced in striatum and related regions. EID rats had persisting sensorimotor deficits (delayed vibrissae-evoked forelimb placing, longer sticker removal time, and more imperfect grooming chains), were more hesitant in novel settings, and had poorer spatial water maze performance than CN. General activity and spatial alternation were similar for EID and CN. Conclusion Rats that had chronic perinatal IDA showed behavioral impairments that suggest persistent striatal dopamine and hippocampal dysfunction despite normalization of hematology, growth and most brain measures. PMID:16713640

Same task, different strategies: How brain networks can be influenced by memory strategy

PubMed Central

Sanfratello, Lori; Caprihan, Arvind; Stephen, Julia M.; Knoefel, Janice E.; Adair, John C.; Qualls, Clifford; Lundy, S. Laura; Aine, Cheryl J.

2015-01-01

Previous functional neuroimaging studies demonstrated that different neural networks underlie different types of cognitive processing by engaging participants in particular tasks, such as verbal or spatial working memory (WM) tasks. However, we report here that even when a working memory task is defined as verbal or spatial, different types of memory strategies may be employed to complete it, with concomitant variations in brain activity. We developed a questionnaire to characterize the type of strategy used by individual members in a group of 28 young healthy participants (18–25 years) during a spatial WM task. A cluster analysis was performed to differentiate groups. We acquired functional magnetoencephalography (MEG) and structural diffusion tensor imaging (DTI) measures to characterize the brain networks associated with the use of different strategies. We found two types of strategies were utilized during the spatial WM task, a visuospatial and a verbal strategy, and brain regions and timecourses of activation differed between participants who used each. Task performance also varied by type of strategy used, with verbal strategies showing an advantage. In addition, performance on neuropsychological tests (indices from WAIS-IV, REY-D Complex Figure) correlated significantly with fractional anisotropy (FA) measures for the visuospatial strategy group in white matter tracts implicated in other WM/attention studies. We conclude that differences in memory strategy can have a pronounced effect on the locations and timing of brain activation, and that these differences need further investigation as a possible confounding factor for studies using group averaging as a means for summarizing results. PMID:24931401

High slew-rate head-only gradient for improving distortion in echo planar imaging: Preliminary experience.

PubMed

Tan, Ek T; Lee, Seung-Kyun; Weavers, Paul T; Graziani, Dominic; Piel, Joseph E; Shu, Yunhong; Huston, John; Bernstein, Matt A; Foo, Thomas K F

2016-09-01

To investigate the effects on echo planar imaging (EPI) distortion of using high gradient slew rates (SR) of up to 700 T/m/s for in vivo human brain imaging, with a dedicated, head-only gradient coil. Simulation studies were first performed to determine the expected echo spacing and distortion reduction in EPI. A head gradient of 42-cm inner diameter and with asymmetric transverse coils was then installed in a whole-body, conventional 3T magnetic resonance imaging (MRI) system. Human subject imaging was performed on five subjects to determine the effects of EPI on echo spacing and signal dropout at various gradient slew rates. The feasibility of whole-brain imaging at 1.5 mm-isotropic spatial resolution was demonstrated with gradient-echo and spin-echo diffusion-weighted EPI. As compared to a whole-body gradient coil, the EPI echo spacing in the head-only gradient coil was reduced by 48%. Simulation and in vivo results, respectively, showed up to 25-26% and 19% improvement in signal dropout. Whole-brain imaging with EPI at 1.5 mm spatial resolution provided good whole-brain coverage, spatial linearity, and low spatial distortion effects. Our results of human brain imaging with EPI using the compact head gradient coil at slew rates higher than in conventional whole-body MR systems demonstrate substantially improved image distortion, and point to a potential for benefits to non-EPI pulse sequences. J. Magn. Reson. Imaging 2016;44:653-664. © 2016 International Society for Magnetic Resonance in Medicine.

Slow Spatial Recruitment of Neocortex during Secondarily Generalized Seizures and Its Relation to Surgical Outcome

PubMed Central

Martinet, Louis-Emmanuel; Ahmed, Omar J.; Lepage, Kyle Q.; Cash, Sydney S.

2015-01-01

Understanding the spatiotemporal dynamics of brain activity is crucial for inferring the underlying synaptic and nonsynaptic mechanisms of brain dysfunction. Focal seizures with secondary generalization are traditionally considered to begin in a limited spatial region and spread to connected areas, which can include both pathological and normal brain tissue. The mechanisms underlying this spread are important to our understanding of seizures and to improve therapies for surgical intervention. Here we study the properties of seizure recruitment—how electrical brain activity transitions to large voltage fluctuations characteristic of spike-and-wave seizures. We do so using invasive subdural electrode arrays from a population of 16 patients with pharmacoresistant epilepsy. We find an average delay of ∼30 s for a broad area of cortex (8 × 8 cm) to be recruited into the seizure, at an estimated speed of ∼4 mm/s. The spatiotemporal characteristics of recruitment reveal two categories of patients: one in which seizure recruitment of neighboring cortical regions follows a spatially organized pattern consistent from seizure to seizure, and a second group without consistent spatial organization of activity during recruitment. The consistent, organized recruitment correlates with a more regular, compared with small-world, connectivity pattern in simulation and successful surgical treatment of epilepsy. We propose that an improved understanding of how the seizure recruits brain regions into large amplitude voltage fluctuations provides novel information to improve surgical treatment of epilepsy and highlights the slow spread of massive local activity across a vast extent of cortex during seizure. PMID:26109670

Same task, different strategies: how brain networks can be influenced by memory strategy.

PubMed

Sanfratello, Lori; Caprihan, Arvind; Stephen, Julia M; Knoefel, Janice E; Adair, John C; Qualls, Clifford; Lundy, S Laura; Aine, Cheryl J

2014-10-01

Previous functional neuroimaging studies demonstrated that different neural networks underlie different types of cognitive processing by engaging participants in particular tasks, such as verbal or spatial working memory (WM) tasks. However, we report here that even when a WM task is defined as verbal or spatial, different types of memory strategies may be used to complete it, with concomitant variations in brain activity. We developed a questionnaire to characterize the type of strategy used by individual members in a group of 28 young healthy participants (18-25 years) during a spatial WM task. A cluster analysis was performed to differentiate groups. We acquired functional magnetoencephalography and structural diffusion tensor imaging measures to characterize the brain networks associated with the use of different strategies. We found two types of strategies were used during the spatial WM task, a visuospatial and a verbal strategy, and brain regions and time courses of activation differed between participants who used each. Task performance also varied by type of strategy used with verbal strategies showing an advantage. In addition, performance on neuropsychological tests (indices from Wechsler Adult Intelligence Scale-IV, Rey Complex Figure Test) correlated significantly with fractional anisotropy measures for the visuospatial strategy group in white matter tracts implicated in other WM and attention studies. We conclude that differences in memory strategy can have a pronounced effect on the locations and timing of brain activation and that these differences need further investigation as a possible confounding factor for studies using group averaging as a means for summarizing results. Copyright © 2014 Wiley Periodicals, Inc.

Investigation of relationships between fMRI brain networks in the spectral domain using ICA and Granger causality reveals distinct differences between schizophrenia patients and healthy controls

PubMed Central

Demirci, Oguz; Stevens, Michael C.; Andreasen, Nancy C.; Michael, Andrew; Liu, Jingyu; White, Tonya; Pearlson, Godfrey D.; Clark, Vincent P.; Calhoun, Vince D.

2009-01-01

Functional network connectivity (FNC) is an approach that examines the relationships between brain networks (as opposed to functional connectivity (FC) that focuses upon the relationships between single voxels). FNC may help explain the complex relationships between distributed cerebral sites in the brain and possibly provide new understanding of neurological and psychiatric disorders such as schizophrenia. In this paper, we use independent component analysis (ICA) to extract the time courses of spatially independent components and then use these in Granger causality test (GCT) to investigate causal relationships between brain activation networks. We present results using both simulations and fMRI data of 155 subjects obtained during two different tasks. Unlike previous research, causal relationships are presented over different portions of the frequency spectrum in order to differentiate high and low frequency effects and not merged in a scalar. The results obtained using Sternberg item recognition paradigm (SIRP) and auditory oddball (AOD) tasks showed FNC differentiations between schizophrenia and control groups, and explained how the two groups differed during these tasks. During the SIRP task, secondary visual and cerebellum activation networks served as hubs and included most complex relationships between the activated regions. Secondary visual and temporal lobe activations replaced these components during the AOD task. PMID:19245841

In vivo imaging of tissue scattering parameter and cerebral hemodynamics in rat brain with a digital red-green-blue camera

NASA Astrophysics Data System (ADS)

Nishidate, Izumi; Mustari, Afrina; Kawauchi, Satoko; Sato, Shunichi; Sato, Manabu; Kokubo, Yasuaki

2017-02-01

We propose a rapid imaging method to monitor the spatial distribution of total hemoglobin concentration (CHbT), the tissue oxygen saturation, and the scattering power b in the expression of μs'=aλ-b as the scattering parameters in cerebral cortex using a digital red-green-blue camera. In the method, the RGB-values are converted into the tristimulus values in CIEXYZ color space which is compatible with the common RGB working spaces. Monte Carlo simulation (MCS) for light transport in tissue is used to specify a relation among the tristimulus XYZ-values and the concentration of oxygenated hemoglobin, that of deoxygenated hemoglobin, and the scattering power b. In the present study, we performed sequential recordings of RGB images of in vivo exposed rat brain during the cortical spreading depolarization evoked by the topical application of KCl. Changes in the total hemoglobin concentration and the tissue oxygen saturation imply the temporary change in cerebral blood flow during CSD. Decrease in the scattering power b was observed before the profound increase in the total hemoglobin concentration, which is indicative of the reversible morphological changes in brain tissue during CSD. The results in this study indicate potential of the method to evaluate the pathophysiological conditions in brain tissue with a digital red-green-blue camera.

Inhomogeneity in optical properties of rat brain: a study for LLLT dosimetry

NASA Astrophysics Data System (ADS)

Sousa, Marcelo V. P.; Prates, Renato; Kato, Ilka T.; Sabino, Caetano P.; Yoshimura, Tania M.; Suzuki, Luis C.; Magalhães, Ana C.; Yoshimura, Elisabeth M.; Ribeiro, Martha S.

2013-03-01

Over the last few years, low-level light therapy (LLLT) has shown an incredible suitability for a wide range of applications for central nervous system (CNS) related diseases. In this therapeutic modality light dosimetry is extremely critical so the study of light propagation through the CNS organs is of great importance. To better understand how light intensity is delivered to the most relevant neural sites we evaluated optical transmission through slices of rat brain point by point. We experimented red (λ = 660 nm) and near infrared (λ = 808 nm) diode laser light analyzing the light penetration and distribution in the whole brain. A fresh Wistar rat (Rattus novergicus) brain was cut in sagittal slices and illuminated with a broad light beam. A high-resolution digital camera was employed to acquire data of transmitted light. Spatial profiles of the light transmitted through the sample were obtained from the images. Peaks and valleys in the profiles show sites where light was less or more attenuated. The peak intensities provide information about total attenuation and the peak widths are correlated to the scattering coefficient at that individual portion of the sample. The outcomes of this study provide remarkable information for LLLT dose-dependent studies involving CNS and highlight the importance of LLLT dosimetry in CNS organs for large range of applications in animal and human diseases.

Spatial patterns of distribution and abundance of Harrisia portoricensis, an endangered Caribbean cactus

Treesearch

J. Rojas-Sandoval; E. J. Melendez-Ackerman; NO-VALUE

2013-01-01

Aims The spatial distribution of biotic and abiotic factors may play a dominant role in determining the distribution and abundance of plants in arid and semiarid environments. In this study, we evaluated how spatial patterns of microhabitat variables and the degree of spatial dependence of these variables influence the distribution and abundance of the endangered...

Instantaneous brain dynamics mapped to a continuous state space.

PubMed

Billings, Jacob C W; Medda, Alessio; Shakil, Sadia; Shen, Xiaohong; Kashyap, Amrit; Chen, Shiyang; Abbas, Anzar; Zhang, Xiaodi; Nezafati, Maysam; Pan, Wen-Ju; Berman, Gordon J; Keilholz, Shella D

2017-11-15

Measures of whole-brain activity, from techniques such as functional Magnetic Resonance Imaging, provide a means to observe the brain's dynamical operations. However, interpretation of whole-brain dynamics has been stymied by the inherently high-dimensional structure of brain activity. The present research addresses this challenge through a series of scale transformations in the spectral, spatial, and relational domains. Instantaneous multispectral dynamics are first developed from input data via a wavelet filter bank. Voxel-level signals are then projected onto a representative set of spatially independent components. The correlation distance over the instantaneous wavelet-ICA state vectors is a graph that may be embedded onto a lower-dimensional space to assist the interpretation of state-space dynamics. Applying this procedure to a large sample of resting-state and task-active data (acquired through the Human Connectome Project), we segment the empirical state space into a continuum of stimulus-dependent brain states. Upon observing the local neighborhood of brain-states adopted subsequent to each stimulus, we may conclude that resting brain activity includes brain states that are, at times, similar to those adopted during tasks, but that are at other times distinct from task-active brain states. As task-active brain states often populate a local neighborhood, back-projection of segments of the dynamical state space onto the brain's surface reveals the patterns of brain activity that support many experimentally-defined states. Copyright © 2017 Elsevier Inc. All rights reserved.

Constructing fine-granularity functional brain network atlases via deep convolutional autoencoder.

PubMed

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.