WorldWideScience

Sample records for brain functional networks

  1. Aging and Functional Brain Networks

    OpenAIRE

    Tomasi, Dardo; Volkow, Nora D.

    2011-01-01

    Aging is associated with changes in human brain anatomy and function and cognitive decline. Recent studies suggest the aging decline of major functional connectivity hubs in the “default-mode” network (DMN). Aging effects on other networks, however, are largely unknown. We hypothesized that aging would be associated with a decline of short- and long-range functional connectivity density (FCD) hubs in the DMN. To test this hypothesis we evaluated resting-state datasets corresponding to 913 hea...

  2. Aging and functional brain networks

    Energy Technology Data Exchange (ETDEWEB)

    Tomasi D.; Tomasi, D.; Volkow, N.D.

    2011-07-11

    Aging is associated with changes in human brain anatomy and function and cognitive decline. Recent studies suggest the aging decline of major functional connectivity hubs in the 'default-mode' network (DMN). Aging effects on other networks, however, are largely unknown. We hypothesized that aging would be associated with a decline of short- and long-range functional connectivity density (FCD) hubs in the DMN. To test this hypothesis, we evaluated resting-state data sets corresponding to 913 healthy subjects from a public magnetic resonance imaging database using functional connectivity density mapping (FCDM), a voxelwise and data-driven approach, together with parallel computing. Aging was associated with pronounced long-range FCD decreases in DMN and dorsal attention network (DAN) and with increases in somatosensory and subcortical networks. Aging effects in these networks were stronger for long-range than for short-range FCD and were also detected at the level of the main functional hubs. Females had higher short- and long-range FCD in DMN and lower FCD in the somatosensory network than males, but the gender by age interaction effects were not significant for any of the networks or hubs. These findings suggest that long-range connections may be more vulnerable to aging effects than short-range connections and that, in addition to the DMN, the DAN is also sensitive to aging effects, which could underlie the deterioration of attention processes that occurs with aging.

  3. Functional network organization of the human brain

    OpenAIRE

    Power, Jonathan D.; Cohen, Alexander L.; Nelson, Steven M.; Wig, Gagan S.; Barnes, Kelly Anne; Church, Jessica A.; Vogel, Alecia C.; Laumann, Timothy O.; Miezin, Fran M.; Schlaggar, Bradley L.; Petersen, Steven E.

    2011-01-01

    Real-world complex systems may be mathematically modeled as graphs, revealing properties of the system. Here we study graphs of functional brain organization in healthy adults using resting state functional connectivity MRI. We propose two novel brain-wide graphs, one of 264 putative functional areas, the other a modification of voxelwise networks that eliminates potentially artificial short-distance relationships. These graphs contain many subgraphs in good agreement with known functional br...

  4. Hierarchical modularity in human brain functional networks

    CERN Document Server

    Meunier, D; Fornito, A; Ersche, K D; Bullmore, E T; 10.3389/neuro.11.037.2009

    2010-01-01

    The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or "modules-within-modules") decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI) in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at ...

  5. Functional connectivity and brain networks in schizophrenia

    OpenAIRE

    Lynall, Mary-Ellen; Bassett, Danielle S.; Kerwin, Robert; McKenna, Peter J.; Kitzbichler, Manfred; Müller, Ulrich; Bullmore, Ed

    2010-01-01

    Schizophrenia has often been conceived as a disorder of connectivity between components of large-scale brain networks. We tested this hypothesis by measuring aspects of both functional connectivity and functional network topology derived from resting state fMRI time series acquired at 72 cerebral regions over 17 minutes from 15 healthy volunteers (14 male, 1 female) and 12 people diagnosed with schizophrenia (10 male, 2 female). We investigated between-group differences in strength and divers...

  6. Individual diversity of functional brain network economy.

    Science.gov (United States)

    Hahn, Andreas; Kranz, Georg S; Sladky, Ronald; Ganger, Sebastian; Windischberger, Christian; Kasper, Siegfried; Lanzenberger, Rupert

    2015-04-01

    On average, brain network economy represents a trade-off between communication efficiency, robustness, and connection cost, although an analogous understanding on an individual level is largely missing. Evaluating resting-state networks of 42 healthy participants with seven Tesla functional magnetic resonance imaging and graph theory revealed that not even half of all possible connections were common across subjects. The strongest similarities among individuals were observed for interhemispheric and/or short-range connections, which may relate to the essential feature of the human brain to develop specialized systems within each hemisphere. Despite this marked variability in individual network architecture, all subjects exhibited equal small-world properties. Furthermore, interdependency between four major network economy metrics was observed across healthy individuals. The characteristic path length was associated with the clustering coefficient (peak correlation r=0.93), the response to network attacks (r=-0.97), and the physical connection cost in three-dimensional space (r=-0.62). On the other hand, clustering was negatively related to attack response (r=-0.75) and connection cost (r=-0.59). Finally, increased connection cost was associated with better response to attacks (r=0.65). This indicates that functional brain networks with high global information transfer also exhibit strong network resilience. However, it seems that these advantages come at the cost of decreased local communication efficiency and increased physical connection cost. Except for wiring length, the results were replicated on a subsample at three Tesla (n=20). These findings highlight the finely tuned interrelationships between different parameters of brain network economy. Moreover, the understanding of the individual diversity of functional brain network economy may provide further insights in the vulnerability to mental and neurological disorders. PMID:25411715

  7. An Adaptive Complex Network Model for Brain Functional Networks

    OpenAIRE

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

    2009-01-01

    Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence) of a hierarchical structure are not robust, and show diffe...

  8. Hierarchical modularity in human brain functional networks

    Directory of Open Access Journals (Sweden)

    Renaud Lambiotte

    2009-10-01

    Full Text Available The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or “modules-within-modules” decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at the highest level of the hierarchy were medial occipital, lateral occipital, central, parieto-frontal and fronto-temporal systems; occipital modules demonstrated less sub-modular organization than modules comprising regions of multimodal association cortex. Connector nodes and hubs, with a key role in inter-modular connectivity, were also concentrated in association cortical areas. We conclude that methods are available for hierarchical modular decomposition of large numbers of high resolution brain functional networks using computationally expedient algorithms. This could enable future investigations of Simon's original hypothesis that hierarchy or near-decomposability of physical symbol systems is a critical design feature for their fast adaptivity to changing environmental conditions.

  9. Changes in cognitive state alter human functional brain networks

    Directory of Open Access Journals (Sweden)

    Malaak Nasser Moussa

    2011-08-01

    Full Text Available The study of the brain as a whole system can be accomplished using network theory principles. Research has shown that human functional brain networks during a resting state exhibit small-world properties and high degree nodes, or hubs, localized to brain areas consistent with the default mode network (DMN. However, the study of brain networks across different tasks and or cognitive states has been inconclusive. Research in this field is important because the underpinnings of behavioral output are inherently dependent on whether or not brain networks are dynamic. This is the first comprehensive study to evaluate multiple network metrics at a voxel-wise resolution in the human brain at both the whole brain and regional level under various conditions: resting state, visual stimulation, and multisensory (auditory and visual stimulation. Our results show that despite global network stability, functional brain networks exhibit considerable task-induced changes in connectivity, efficiency, and community structure at the regional level.

  10. The Union of Shortest Path Trees of Functional Brain Networks.

    Science.gov (United States)

    Meier, Jil; Tewarie, Prejaas; Van Mieghem, Piet

    2015-11-01

    Communication between brain regions is still insufficiently understood. Applying concepts from network science has shown to be successful in gaining insight in the functioning of the brain. Recent work has implicated that especially shortest paths in the structural brain network seem to play a major role in the communication within the brain. So far, for the functional brain network, only the average length of the shortest paths has been analyzed. In this article, we propose to construct the union of shortest path trees (USPT) as a new topology for the functional brain network. The minimum spanning tree, which has been successful in a lot of recent studies to comprise important features of the functional brain network, is always included in the USPT. After interpreting the link weights of the functional brain network as communication probabilities, the USPT of this network can be uniquely defined. Using data from magnetoencephalography, we applied the USPT as a method to find differences in the network topology of multiple sclerosis patients and healthy controls. The new concept of the USPT of the functional brain network also allows interesting interpretations and may represent the highways of the brain. PMID:26027712

  11. The Union of Shortest Path Trees of Functional Brain Networks

    NARCIS (Netherlands)

    Meier, J.; Tewarie, P.; Van Mieghem, P.

    2015-01-01

    Communication between brain regions is still insufficiently understood. Applying concepts from network science has shown to be successful in gaining insight in the functioning of the brain. Recent work has implicated that especially shortest paths in the structural brain network seem to play a major

  12. Cognitive fitness of cost-efficient brain functional networks

    OpenAIRE

    Bassett, Danielle S; Bullmore, Edward T.; Meyer-Lindenberg, Andreas; Apud, José A; Weinberger, Daniel R.; Coppola, Richard

    2009-01-01

    The human brain's capacity for cognitive function is thought to depend on coordinated activity in sparsely connected, complex networks organized over many scales of space and time. Recent work has demonstrated that human brain networks constructed from neuroimaging data have economical small-world properties that confer high efficiency of information processing at relatively low connection cost. However, it has been unclear how the architecture of complex brain networks functioning at differe...

  13. Human brain networks function in connectome-specific harmonic waves

    OpenAIRE

    Atasoy, Selen; Donnelly, Isaac; Pearson, Joel

    2016-01-01

    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...

  14. Functional brain networks associated with eating behaviors in obesity

    OpenAIRE

    Bo-yong Park; Jongbum Seo; Hyunjin Park

    2016-01-01

    Obesity causes critical health problems including diabetes and hypertension that affect billions of people worldwide. Obesity and eating behaviors are believed to be closely linked but their relationship through brain networks has not been fully explored. We identified functional brain networks associated with obesity and examined how the networks were related to eating behaviors. Resting state functional magnetic resonance imaging (MRI) scans were obtained for 82 participants. Data were from...

  15. Hyper-connectivity of functional networks for brain disease diagnosis.

    Science.gov (United States)

    Jie, Biao; Wee, Chong-Yaw; Shen, Dinggang; Zhang, Daoqiang

    2016-08-01

    Exploring structural and functional interactions among various brain regions enables better understanding of pathological underpinnings of neurological disorders. Brain connectivity network, as a simplified representation of those structural and functional interactions, has been widely used for diagnosis and classification of neurodegenerative diseases, especially for Alzheimer's disease (AD) and its early stage - mild cognitive impairment (MCI). However, the conventional functional connectivity network is usually constructed based on the pairwise correlation among different brain regions and thus ignores their higher-order relationships. Such loss of high-order information could be important for disease diagnosis, since neurologically a brain region predominantly interacts with more than one other brain regions. Accordingly, in this paper, we propose a novel framework for estimating the hyper-connectivity network of brain functions and then use this hyper-network for brain disease diagnosis. Here, the functional connectivity hyper-network denotes a network where each of its edges representing the interactions among multiple brain regions (i.e., an edge can connect with more than two brain regions), which can be naturally represented by a hyper-graph. Specifically, we first construct connectivity hyper-networks from the resting-state fMRI (R-fMRI) time series by using sparse representation. Then, we extract three sets of brain-region specific features from the connectivity hyper-networks, and further exploit a manifold regularized multi-task feature selection method to jointly select the most discriminative features. Finally, we use multi-kernel support vector machine (SVM) for classification. The experimental results on both MCI dataset and attention deficit hyperactivity disorder (ADHD) dataset demonstrate that, compared with the conventional connectivity network-based methods, the proposed method can not only improve the classification performance, but also help

  16. Development of large-scale functional brain networks in children.

    Directory of Open Access Journals (Sweden)

    Kaustubh Supekar

    2009-07-01

    Full Text Available The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7-9 y and 22 young-adults (ages 19-22 y. Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar "small-world" organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism.

  17. Development of large-scale functional brain networks in children.

    Science.gov (United States)

    Supekar, Kaustubh; Musen, Mark; Menon, Vinod

    2009-07-01

    The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7-9 y) and 22 young-adults (ages 19-22 y). Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar "small-world" organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism. PMID:19621066

  18. The Efficiency of a Small-World Functional Brain Network

    Institute of Scientific and Technical Information of China (English)

    ZHAO Qing-Bai; ZHANG Xiao-Fei; SUI Dan-Ni; ZHOU Zhi-Jin; CHEN Qi-Cai; TANG Yi-Yuan

    2012-01-01

    We investigate whether the small-world topology of a functional brain network means high information processing efficiency by calculating the correlation between the small-world measures of a functional brain network and behavioral reaction during an imagery task.Functional brain networks are constructed by multichannel eventrelated potential data,in which the electrodes are the nodes and the functional connectivities between them are the edges.The results show that the correlation between small-world measures and reaction time is task-specific,such that in global imagery,there is a positive correlation between the clustering coefficient and reaction time,while in local imagery the average path length is positively correlated with the reaction time.This suggests that the efficiency of a functional brain network is task-dependent.%We investigate whether the small-world topology of a functional brain network means high information processing efficiency by calculating the correlation between the small-world measures of a functional brain network and behavioral reaction during an imagery task. Functional brain networks are constructed by multichannel event-related potential data, in which the electrodes are the nodes and the functional connectivities between them are the edges. The results show that the correlation between small-world measures and reaction time is task-specific, such that in global imagery, there is a positive correlation between the clustering coefficient and reaction time, while in local imagery the average path length is positively correlated with the reaction time. This suggests that the efficiency of a functional brain network is task-dependent.

  19. EEG-based research on brain functional networks in cognition.

    Science.gov (United States)

    Wang, Niannian; Zhang, Li; Liu, Guozhong

    2015-01-01

    Recently, exploring the cognitive functions of the brain by establishing a network model to understand the working mechanism of the brain has become a popular research topic in the field of neuroscience. In this study, electroencephalography (EEG) was used to collect data from subjects given four different mathematical cognitive tasks: recite numbers clockwise and counter-clockwise, and letters clockwise and counter-clockwise to build a complex brain function network (BFN). By studying the connectivity features and parameters of those brain functional networks, it was found that the average clustering coefficient is much larger than its corresponding random network and the average shortest path length is similar to the corresponding random networks, which clearly shows the characteristics of the small-world network. The brain regions stimulated during the experiment are consistent with traditional cognitive science regarding learning, memory, comprehension, and other rational judgment results. The new method of complex networking involves studying the mathematical cognitive process of reciting, providing an effective research foundation for exploring the relationship between brain cognition and human learning skills and memory. This could help detect memory deficits early in young and mentally handicapped children, and help scientists understand the causes of cognitive brain disorders. PMID:26405867

  20. Assortative mixing in functional brain networks during epileptic seizures

    CERN Document Server

    Bialonski, Stephan

    2013-01-01

    We investigate assortativity of functional brain networks before, during, and after one-hundred epileptic seizures with different anatomical onset locations. We construct binary functional networks from multi-channel electroencephalographic data recorded from 60 epilepsy patients, and from time-resolved estimates of the assortativity coefficient we conclude that positive degree-degree correlations are inherent to seizure dynamics. While seizures evolve, an increasing assortativity indicates a segregation of the underlying functional network into groups of brain regions that are only sparsely interconnected, if at all. Interestingly, assortativity decreases already prior to seizure end. Together with previous observations of characteristic temporal evolutions of global statistical properties and synchronizability of epileptic brain networks, our findings may help to gain deeper insights into the complicated dynamics underlying generation, propagation, and termination of seizures.

  1. Functional brain networks associated with eating behaviors in obesity

    Science.gov (United States)

    Park, Bo-yong; Seo, Jongbum; Park, Hyunjin

    2016-01-01

    Obesity causes critical health problems including diabetes and hypertension that affect billions of people worldwide. Obesity and eating behaviors are believed to be closely linked but their relationship through brain networks has not been fully explored. We identified functional brain networks associated with obesity and examined how the networks were related to eating behaviors. Resting state functional magnetic resonance imaging (MRI) scans were obtained for 82 participants. Data were from an equal number of people of healthy weight (HW) and non-healthy weight (non-HW). Connectivity matrices were computed with spatial maps derived using a group independent component analysis approach. Brain networks and associated connectivity parameters with significant group-wise differences were identified and correlated with scores on a three-factor eating questionnaire (TFEQ) describing restraint, disinhibition, and hunger eating behaviors. Frontoparietal and cerebellum networks showed group-wise differences between HW and non-HW groups. Frontoparietal network showed a high correlation with TFEQ disinhibition scores. Both frontoparietal and cerebellum networks showed a high correlation with body mass index (BMI) scores. Brain networks with significant group-wise differences between HW and non-HW groups were identified. Parts of the identified networks showed a high correlation with eating behavior scores. PMID:27030024

  2. Functional brain networks associated with eating behaviors in obesity.

    Science.gov (United States)

    Park, Bo-Yong; Seo, Jongbum; Park, Hyunjin

    2016-01-01

    Obesity causes critical health problems including diabetes and hypertension that affect billions of people worldwide. Obesity and eating behaviors are believed to be closely linked but their relationship through brain networks has not been fully explored. We identified functional brain networks associated with obesity and examined how the networks were related to eating behaviors. Resting state functional magnetic resonance imaging (MRI) scans were obtained for 82 participants. Data were from an equal number of people of healthy weight (HW) and non-healthy weight (non-HW). Connectivity matrices were computed with spatial maps derived using a group independent component analysis approach. Brain networks and associated connectivity parameters with significant group-wise differences were identified and correlated with scores on a three-factor eating questionnaire (TFEQ) describing restraint, disinhibition, and hunger eating behaviors. Frontoparietal and cerebellum networks showed group-wise differences between HW and non-HW groups. Frontoparietal network showed a high correlation with TFEQ disinhibition scores. Both frontoparietal and cerebellum networks showed a high correlation with body mass index (BMI) scores. Brain networks with significant group-wise differences between HW and non-HW groups were identified. Parts of the identified networks showed a high correlation with eating behavior scores. PMID:27030024

  3. Bayesian network models in brain functional connectivity analysis

    OpenAIRE

    Ide, Jaime S.; Zhang, Sheng; Chiang-shan R. Li

    2013-01-01

    Much effort has been made to better understand the complex integration of distinct parts of the human brain using functional magnetic resonance imaging (fMRI). Altered functional connectivity between brain regions is associated with many neurological and mental illnesses, such as Alzheimer and Parkinson diseases, addiction, and depression. In computational science, Bayesian networks (BN) have been used in a broad range of studies to model complex data set in the presence of uncertainty and wh...

  4. The brain's default network: anatomy, function, and relevance to disease.

    Science.gov (United States)

    Buckner, Randy L; Andrews-Hanna, Jessica R; Schacter, Daniel L

    2008-03-01

    Thirty years of brain imaging research has converged to define the brain's default network-a novel and only recently appreciated brain system that participates in internal modes of cognition. Here we synthesize past observations to provide strong evidence that the default network is a specific, anatomically defined brain system preferentially active when individuals are not focused on the external environment. Analysis of connectional anatomy in the monkey supports the presence of an interconnected brain system. Providing insight into function, the default network is active when individuals are engaged in internally focused tasks including autobiographical memory retrieval, envisioning the future, and conceiving the perspectives of others. Probing the functional anatomy of the network in detail reveals that it is best understood as multiple interacting subsystems. The medial temporal lobe subsystem provides information from prior experiences in the form of memories and associations that are the building blocks of mental simulation. The medial prefrontal subsystem facilitates the flexible use of this information during the construction of self-relevant mental simulations. These two subsystems converge on important nodes of integration including the posterior cingulate cortex. The implications of these functional and anatomical observations are discussed in relation to possible adaptive roles of the default network for using past experiences to plan for the future, navigate social interactions, and maximize the utility of moments when we are not otherwise engaged by the external world. We conclude by discussing the relevance of the default network for understanding mental disorders including autism, schizophrenia, and Alzheimer's disease. PMID:18400922

  5. Mapping Multiplex Hubs in Human Functional Brain Networks.

    Science.gov (United States)

    De Domenico, Manlio; Sasai, Shuntaro; Arenas, Alex

    2016-01-01

    Typical brain networks consist of many peripheral regions and a few highly central ones, i.e., hubs, playing key functional roles in cerebral inter-regional interactions. Studies have shown that networks, obtained from the analysis of specific frequency components of brain activity, present peculiar architectures with unique profiles of region centrality. However, the identification of hubs in networks built from different frequency bands simultaneously is still a challenging problem, remaining largely unexplored. Here we identify each frequency component with one layer of a multiplex network and face this challenge by exploiting the recent advances in the analysis of multiplex topologies. First, we show that each frequency band carries unique topological information, fundamental to accurately model brain functional networks. We then demonstrate that hubs in the multiplex network, in general different from those ones obtained after discarding or aggregating the measured signals as usual, provide a more accurate map of brain's most important functional regions, allowing to distinguish between healthy and schizophrenic populations better than conventional network approaches. PMID:27471443

  6. Functional Connectivity Hubs and Networks in the Awake Marmoset Brain

    Directory of Open Access Journals (Sweden)

    Annabelle Marie Belcher

    2016-03-01

    Full Text Available In combination with advances in analytical methods, resting-state fMRI is allowing unprecedented access to achieve a better understanding of the network organization of the brain. Increasing evidence suggests that this architecture may incorporate highly functionally connected nodes, or hubs, and we have recently proposed local functional connectivity density (lFCD mapping to identify highly-connected nodes in the human brain. Here we imaged awake nonhuman primates to test whether, like the human brain, the marmoset brain contains functional connectivity hubs. Ten adult common marmosets (Callithrix jacchus were acclimated to mild, comfortable restraint using individualized helmets. Following restraint training, resting BOLD data were acquired during eight consecutive 10 min scans for each subject. lFCD revealed prominent cortical and subcortical hubs of connectivity across the marmoset brain; specifically, in primary and secondary visual cortices (V1/V2, higher-order visual association areas (A19M/V6[DM], posterior parietal and posterior cingulate areas (PGM and A23b/A31, thalamus, dorsal and ventral striatal areas (caudate, putamen, lateral septal nucleus, and anterior cingulate cortex (A24a. lFCD hubs were highly connected to widespread areas of the brain, and further revealed significant network-network interactions. These data provide a baseline platform for future investigations in a nonhuman primate model of the brain’s network topology.

  7. Functional Reorganizations of Brain Network in Prelingually Deaf Adolescents

    Science.gov (United States)

    Li, Wenjing; Li, Jianhong; Wang, Jieqiong; Zhou, Peng; Wang, Zhenchang; Xian, Junfang; He, Huiguang

    2016-01-01

    Previous neuroimaging studies suggested structural or functional brain reorganizations occurred in prelingually deaf subjects. However, little is known about the reorganizations of brain network architectures in prelingually deaf adolescents. The present study aims to investigate alterations of whole-brain functional network using resting-state fMRI and graph theory analysis. We recruited 16 prelingually deaf adolescents (10~18 years) and 16 normal controls matched in age and gender. Brain networks were constructed from mean time courses of 90 regions. Widely distributed network was observed in deaf subjects, with increased connectivity between the limbic system and regions involved in visual and language processing, suggesting reinforcement of the processing for the visual and verbal information in deaf adolescents. Decreased connectivity was detected between the visual regions and language regions possibly due to inferior reading or speaking skills in deaf subjects. Using graph theory analysis, we demonstrated small-worldness property did not change in prelingually deaf adolescents relative to normal controls. However, compared with healthy adolescents, eight regions involved in visual, language, and auditory processing were identified as hubs only present in prelingually deaf adolescents. These findings revealed reorganization of brain functional networks occurred in prelingually deaf adolescents to adapt to deficient auditory input. PMID:26819781

  8. Functional Reorganizations of Brain Network in Prelingually Deaf Adolescents.

    Science.gov (United States)

    Li, Wenjing; Li, Jianhong; Wang, Jieqiong; Zhou, Peng; Wang, Zhenchang; Xian, Junfang; He, Huiguang

    2016-01-01

    Previous neuroimaging studies suggested structural or functional brain reorganizations occurred in prelingually deaf subjects. However, little is known about the reorganizations of brain network architectures in prelingually deaf adolescents. The present study aims to investigate alterations of whole-brain functional network using resting-state fMRI and graph theory analysis. We recruited 16 prelingually deaf adolescents (10~18 years) and 16 normal controls matched in age and gender. Brain networks were constructed from mean time courses of 90 regions. Widely distributed network was observed in deaf subjects, with increased connectivity between the limbic system and regions involved in visual and language processing, suggesting reinforcement of the processing for the visual and verbal information in deaf adolescents. Decreased connectivity was detected between the visual regions and language regions possibly due to inferior reading or speaking skills in deaf subjects. Using graph theory analysis, we demonstrated small-worldness property did not change in prelingually deaf adolescents relative to normal controls. However, compared with healthy adolescents, eight regions involved in visual, language, and auditory processing were identified as hubs only present in prelingually deaf adolescents. These findings revealed reorganization of brain functional networks occurred in prelingually deaf adolescents to adapt to deficient auditory input. PMID:26819781

  9. Effect of tumor resection on the characteristics of functional brain networks

    NARCIS (Netherlands)

    Wang, H.; Douw, L.; Hernández, J.M.; Reijneveld, J.C.; Stam, C.J.; Van Mieghem, P.

    2010-01-01

    Brain functioning such as cognitive performance depends on the functional interactions between brain areas, namely, the functional brain networks. The functional brain networks of a group of patients with brain tumors are measured before and after tumor resection. In this work, we perform a weighted

  10. Joint Modelling of Structural and Functional Brain Networks

    DEFF Research Database (Denmark)

    Andersen, Kasper Winther; Herlau, Tue; Mørup, Morten;

    -parametric Bayesian network model which allows for joint modelling and integration of multiple networks. We demonstrate the model’s ability to detect vertices that share structure across networks jointly in functional MRI (fMRI) and diffusion MRI (dMRI) data. Using two fMRI and dMRI scans per subject, we establish...... significant structures that are consistently shared across subjects and data splits. This provides an unsupervised approach for modeling of structure-function relations in the brain and provides a general framework for multimodal integration....

  11. Changes in brain functional network connectivity after stroke

    Institute of Scientific and Technical Information of China (English)

    Wei Li; Yapeng Li; Wenzhen Zhu; Xi Chen

    2014-01-01

    Studies have shown that functional network connection models can be used to study brain net-work changes in patients with schizophrenia. In this study, we inferred that these models could also be used to explore functional network connectivity changes in stroke patients. We used independent component analysis to find the motor areas of stroke patients, which is a novel way to determine these areas. In this study, we collected functional magnetic resonance imaging datasets from healthy controls and right-handed stroke patients following their ifrst ever stroke. Using independent component analysis, six spatially independent components highly correlat-ed to the experimental paradigm were extracted. Then, the functional network connectivity of both patients and controls was established to observe the differences between them. The results showed that there were 11 connections in the model in the stroke patients, while there were only four connections in the healthy controls. Further analysis found that some damaged connections may be compensated for by new indirect connections or circuits produced after stroke. These connections may have a direct correlation with the degree of stroke rehabilitation. Our ifndings suggest that functional network connectivity in stroke patients is more complex than that in hea-lthy controls, and that there is a compensation loop in the functional network following stroke. This implies that functional network reorganization plays a very important role in the process of rehabilitation after stroke.

  12. Disrupted Brain Functional Network Architecture in Chronic Tinnitus Patients

    Science.gov (United States)

    Chen, Yu-Chen; Feng, Yuan; Xu, Jin-Jing; Mao, Cun-Nan; Xia, Wenqing; Ren, Jun; Yin, Xindao

    2016-01-01

    Purpose: Resting-state functional magnetic resonance imaging (fMRI) studies have demonstrated the disruptions of multiple brain networks in tinnitus patients. Nonetheless, several studies found no differences in network processing between tinnitus patients and healthy controls (HCs). Its neural bases are poorly understood. To identify aberrant brain network architecture involved in chronic tinnitus, we compared the resting-state fMRI (rs-fMRI) patterns of tinnitus patients and HCs. Materials and Methods: Chronic tinnitus patients (n = 24) with normal hearing thresholds and age-, sex-, education- and hearing threshold-matched HCs (n = 22) participated in the current study and underwent the rs-fMRI scanning. We used degree centrality (DC) to investigate functional connectivity (FC) strength of the whole-brain network and Granger causality to analyze effective connectivity in order to explore directional aspects involved in tinnitus. Results: Compared to HCs, we found significantly increased network centrality in bilateral superior frontal gyrus (SFG). Unidirectionally, the left SFG revealed increased effective connectivity to the left middle orbitofrontal cortex (OFC), left posterior lobe of cerebellum (PLC), left postcentral gyrus, and right middle occipital gyrus (MOG) while the right SFG exhibited enhanced effective connectivity to the right supplementary motor area (SMA). In addition, the effective connectivity from the bilateral SFG to the OFC and SMA showed positive correlations with tinnitus distress. Conclusions: Rs-fMRI provides a new and novel method for identifying aberrant brain network architecture. Chronic tinnitus patients have disrupted FC strength and causal connectivity mostly in non-auditory regions, especially the prefrontal cortex (PFC). The current findings will provide a new perspective for understanding the neuropathophysiological mechanisms in chronic tinnitus. PMID:27458377

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

    Directory of Open Access Journals (Sweden)

    Damien A Fair

    2009-05-01

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

  14. Memory Networks in Tinnitus: A Functional Brain Image Study

    OpenAIRE

    Laureano, Maura Regina; Onishi, Ektor Tsuneo; Bressan, Rodrigo Affonseca; Castiglioni, Mario Luiz Vieira; Batista, Ilza Rosa; Reis, Marilia Alves; Garcia, Michele Vargas; de Andrade, Adriana Neves; de Almeida, Roberta Ribeiro; Garrido, Griselda J.; Jackowski, Andrea Parolin

    2014-01-01

    Tinnitus is characterized by the perception of sound in the absence of an external auditory stimulus. The network connectivity of auditory and non-auditory brain structures associated with emotion, memory and attention are functionally altered in debilitating tinnitus. Current studies suggest that tinnitus results from neuroplastic changes in the frontal and limbic temporal regions. The objective of this study was to use Single-Photon Emission Computed Tomography (SPECT) to evaluate changes i...

  15. Dynamic functional brain networks involved in simple visual discrimination learning.

    Science.gov (United States)

    Fidalgo, Camino; Conejo, Nélida María; González-Pardo, Héctor; Arias, Jorge Luis

    2014-10-01

    Visual discrimination tasks have been widely used to evaluate many types of learning and memory processes. However, little is known about the brain regions involved at different stages of visual discrimination learning. We used cytochrome c oxidase histochemistry to evaluate changes in regional brain oxidative metabolism during visual discrimination learning in a water-T maze at different time points during training. As compared with control groups, the results of the present study reveal the gradual activation of cortical (prefrontal and temporal cortices) and subcortical brain regions (including the striatum and the hippocampus) associated to the mastery of a simple visual discrimination task. On the other hand, the brain regions involved and their functional interactions changed progressively over days of training. Regions associated with novelty, emotion, visuo-spatial orientation and motor aspects of the behavioral task seem to be relevant during the earlier phase of training, whereas a brain network comprising the prefrontal cortex was found along the whole learning process. This study highlights the relevance of functional interactions among brain regions to investigate learning and memory processes. PMID:24937013

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

    Science.gov (United States)

    Bressler, Steven L.

    2014-09-01

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

  17. Local inhibitory plasticity tunes macroscopic brain dynamics and allows the emergence of functional brain networks.

    Science.gov (United States)

    Hellyer, Peter J; Jachs, Barbara; Clopath, Claudia; Leech, Robert

    2016-01-01

    Rich, spontaneous brain activity has been observed across a range of different temporal and spatial scales. These dynamics are thought to be important for efficient neural functioning. A range of experimental evidence suggests that these neural dynamics are maintained across a variety of different cognitive states, in response to alterations of the environment and to changes in brain configuration (e.g., across individuals, development and in many neurological disorders). This suggests that the brain has evolved mechanisms to maintain rich dynamics across a broad range of situations. Several mechanisms based around homeostatic plasticity have been proposed to explain how these dynamics emerge from networks of neurons at the microscopic scale. Here we explore how a homeostatic mechanism may operate at the macroscopic scale: in particular, focusing on how it interacts with the underlying structural network topology and how it gives rise to well-described functional connectivity networks. We use a simple mean-field model of the brain, constrained by empirical white matter structural connectivity where each region of the brain is simulated using a pool of excitatory and inhibitory neurons. We show, as with the microscopic work, that homeostatic plasticity regulates network activity and allows for the emergence of rich, spontaneous dynamics across a range of brain configurations, which otherwise show a very limited range of dynamic regimes. In addition, the simulated functional connectivity of the homeostatic model better resembles empirical functional connectivity network. To accomplish this, we show how the inhibitory weights adapt over time to capture important graph theoretic properties of the underlying structural network. Therefore, this work presents suggests how inhibitory homeostatic mechanisms facilitate stable macroscopic dynamics to emerge in the brain, aiding the formation of functional connectivity networks. PMID:26348562

  18. Quetiapine modulates functional connectivity in brain aggression networks.

    Science.gov (United States)

    Klasen, Martin; Zvyagintsev, Mikhail; Schwenzer, Michael; Mathiak, Krystyna A; Sarkheil, Pegah; Weber, René; Mathiak, Klaus

    2013-07-15

    Aggressive behavior is associated with dysfunctions in an affective regulation network encompassing amygdala and prefrontal areas such as orbitofrontal (OFC), anterior cingulate (ACC), and dorsolateral prefrontal cortex (DLPFC). In particular, prefrontal regions have been postulated to control amygdala activity by inhibitory projections, and this process may be disrupted in aggressive individuals. The atypical antipsychotic quetiapine successfully attenuates aggressive behavior in various disorders; the underlying neural processes, however, are unknown. A strengthened functional coupling in the prefrontal-amygdala system may account for these anti-aggressive effects. An inhibition of this network has been reported for virtual aggression in violent video games as well. However, there have been so far no in-vivo observations of pharmacological influences on corticolimbic projections during human aggressive behavior. In a double-blind, placebo-controlled study, quetiapine and placebo were administered for three successive days prior to an fMRI experiment. In this experiment, functional brain connectivity was assessed during virtual aggressive behavior in a violent video game and an aggression-free control task in a non-violent modification. Quetiapine increased the functional connectivity of ACC and DLPFC with the amygdala during virtual aggression, whereas OFC-amygdala coupling was attenuated. These effects were observed neither for placebo nor for the non-violent control. These results demonstrate for the first time a pharmacological modification of aggression-related human brain networks in a naturalistic setting. The violence-specific modulation of prefrontal-amygdala networks appears to control aggressive behavior and provides a neurobiological model for the anti-aggressive effects of quetiapine. PMID:23501053

  19. Functional Brain Network Changes Associated with Maintenance of Cognitive Function in Multiple Sclerosis

    Directory of Open Access Journals (Sweden)

    Santosh A Helekar

    2010-11-01

    Full Text Available In multiple sclerosis (MS functional changes in connectivity due to cortical reorganization could lead to cognitive impairment (CI, or reflect a re-adjustment to reduce the clinical effects of widespread tissue damage. Such alterations in connectivity could result in changes in neural activation as assayed by executive function tasks. We examined cognitive function in MS patients with mild to moderate cognitive impairment and age-matched controls. We evaluated brain activity using functional magnetic resonance imaging (fMRI during the successful performance of the Wisconsin-card sorting (WCS task by MS patients, showing compensatory maintenance of normal function, as measured by response latency and error rate. To assess changes in functional connectivity throughout the brain, we performed a global functional brain network analysis by computing voxel by voxel correlations on the fMRI time series data and carrying out a hierarchical cluster analysis. We found that during the WCS task there is a significant reduction in the number of smaller size brain functional networks, and a change in the brain areas representing the nodes of these networks in MS patients compared to age-matched controls. There is also a concomitant increase in the strength of functional connections between brain loci separated at intermediate scale distances in these patients. These functional alterations might reflect compensatory neuroplastic reorganization underlying maintenance of relatively normal cognitive function in the face of white matter lesions and cortical atrophy produced by MS.

  20. Exploring functional connectivity networks with multichannel brain array coils.

    Science.gov (United States)

    Anteraper, Sheeba Arnold; Whitfield-Gabrieli, Susan; Keil, Boris; Shannon, Steven; Gabrieli, John D; Triantafyllou, Christina

    2013-01-01

    The use of multichannel array head coils in functional and structural magnetic resonance imaging (MRI) provides increased signal-to-noise ratio (SNR), higher sensitivity, and parallel imaging capabilities. However, their benefits remain to be systematically explored in the context of resting-state functional connectivity MRI (fcMRI). In this study, we compare signal detectability within and between commercially available multichannel brain coils, a 32-Channel (32Ch), and a 12-Channel (12Ch) at 3T, in a high-resolution regime to accurately map resting-state networks. We investigate whether the 32Ch coil can extract and map fcMRI more efficiently and robustly than the 12Ch coil using seed-based and graph-theory-based analyses. Our findings demonstrate that although the 12Ch coil can be used to reveal resting-state connectivity maps, the 32Ch coil provides increased detailed functional connectivity maps (using seed-based analysis) as well as increased global and local efficiency, and cost (using graph-theory-based analysis), in a number of widely reported resting-state networks. The exploration of subcortical networks, which are scarcely reported due to limitations in spatial-resolution and coil sensitivity, also proved beneficial with the 32Ch coil. Further, comparisons regarding the data acquisition time required to successfully map these networks indicated that scan time can be significantly reduced by 50% when a coil with increased number of channels (i.e., 32Ch) is used. Switching to multichannel arrays in resting-state fcMRI could, therefore, provide both detailed functional connectivity maps and acquisition time reductions, which could further benefit imaging special subject populations, such as patients or pediatrics who have less tolerance in lengthy imaging sessions. PMID:23510203

  1. The brain's functional network architecture reveals human motives.

    Science.gov (United States)

    Hein, Grit; Morishima, Yosuke; Leiberg, Susanne; Sul, Sunhae; Fehr, Ernst

    2016-03-01

    Goal-directed human behaviors are driven by motives. Motives are, however, purely mental constructs that are not directly observable. Here, we show that the brain's functional network architecture captures information that predicts different motives behind the same altruistic act with high accuracy. In contrast, mere activity in these regions contains no information about motives. Empathy-based altruism is primarily characterized by a positive connectivity from the anterior cingulate cortex (ACC) to the anterior insula (AI), whereas reciprocity-based altruism additionally invokes strong positive connectivity from the AI to the ACC and even stronger positive connectivity from the AI to the ventral striatum. Moreover, predominantly selfish individuals show distinct functional architectures compared to altruists, and they only increase altruistic behavior in response to empathy inductions, but not reciprocity inductions. PMID:26941317

  2. Memory Networks in Tinnitus: A Functional Brain Image Study

    Science.gov (United States)

    Laureano, Maura Regina; Onishi, Ektor Tsuneo; Bressan, Rodrigo Affonseca; Castiglioni, Mario Luiz Vieira; Batista, Ilza Rosa; Reis, Marilia Alves; Garcia, Michele Vargas; de Andrade, Adriana Neves; de Almeida, Roberta Ribeiro; Garrido, Griselda J.; Jackowski, Andrea Parolin

    2014-01-01

    Tinnitus is characterized by the perception of sound in the absence of an external auditory stimulus. The network connectivity of auditory and non-auditory brain structures associated with emotion, memory and attention are functionally altered in debilitating tinnitus. Current studies suggest that tinnitus results from neuroplastic changes in the frontal and limbic temporal regions. The objective of this study was to use Single-Photon Emission Computed Tomography (SPECT) to evaluate changes in the cerebral blood flow in tinnitus patients with normal hearing compared with healthy controls. Methods: Twenty tinnitus patients with normal hearing and 17 healthy controls, matched for sex, age and years of education, were subjected to Single Photon Emission Computed Tomography using the radiotracer ethylenedicysteine diethyl ester, labeled with Technetium 99 m (99 mTc-ECD SPECT). The severity of tinnitus was assessed using the “Tinnitus Handicap Inventory” (THI). The images were processed and analyzed using “Statistical Parametric Mapping” (SPM8). Results: A significant increase in cerebral perfusion in the left parahippocampal gyrus (pFWE <0.05) was observed in patients with tinnitus compared with healthy controls. The average total THI score was 50.8+18.24, classified as moderate tinnitus. Conclusion: It was possible to identify significant changes in the limbic system of the brain perfusion in tinnitus patients with normal hearing, suggesting that central mechanisms, not specific to the auditory pathway, are involved in the pathophysiology of symptoms, even in the absence of clinically diagnosed peripheral changes. PMID:24516567

  3. Memory networks in tinnitus: a functional brain image study.

    Directory of Open Access Journals (Sweden)

    Maura Regina Laureano

    Full Text Available Tinnitus is characterized by the perception of sound in the absence of an external auditory stimulus. The network connectivity of auditory and non-auditory brain structures associated with emotion, memory and attention are functionally altered in debilitating tinnitus. Current studies suggest that tinnitus results from neuroplastic changes in the frontal and limbic temporal regions. The objective of this study was to use Single-Photon Emission Computed Tomography (SPECT to evaluate changes in the cerebral blood flow in tinnitus patients with normal hearing compared with healthy controls.Twenty tinnitus patients with normal hearing and 17 healthy controls, matched for sex, age and years of education, were subjected to Single Photon Emission Computed Tomography using the radiotracer ethylenedicysteine diethyl ester, labeled with Technetium 99 m (99 mTc-ECD SPECT. The severity of tinnitus was assessed using the "Tinnitus Handicap Inventory" (THI. The images were processed and analyzed using "Statistical Parametric Mapping" (SPM8.A significant increase in cerebral perfusion in the left parahippocampal gyrus (pFWE <0.05 was observed in patients with tinnitus compared with healthy controls. The average total THI score was 50.8+18.24, classified as moderate tinnitus.It was possible to identify significant changes in the limbic system of the brain perfusion in tinnitus patients with normal hearing, suggesting that central mechanisms, not specific to the auditory pathway, are involved in the pathophysiology of symptoms, even in the absence of clinically diagnosed peripheral changes.

  4. An abnormal resting-state functional brain network indicates progression towards Alzheimer’s disease*****

    Institute of Scientific and Technical Information of China (English)

    Jie Xiang; Hao Guo; Rui Cao; Hong Liang; Junjie Chen

    2013-01-01

    Brain structure and cognitive function change in the temporal lobe, hippocampus, and prefrontal cortex of patients with mild cognitive impairment and Alzheimer’s disease, and brain network-connection strength, network efficiency, and nodal attributes are abnormal. However, existing research has only analyzed the differences between these patients and normal controls. In this study, we constructed brain networks using resting-state functional MRI data that was extracted from four populations mal controls, patients with early mild cognitive impairment, patients with late mild cognitive impairment, and patients with Alzheimer’s disease) using the Alzheimer’s Disease Neuroimaging Initiative data set. The aim was to analyze the characteristics of resting-state functional neural networks, and to observe mild cognitive impairment at different stages before the transformation to Alzheimer’s disease. Results showed that as cognitive deficits increased across the four groups, the shortest path in the rest-ing-state functional network gradual y increased, while clustering coefficients gradual y decreased. This evidence indicates that dementia is associated with a decline of brain network efficiency. In tion, the changes in functional networks revealed the progressive deterioration of network function across brain regions from healthy elderly adults to those with mild cognitive impairment and Alzhei-mer’s disease. The alterations of node attributes in brain regions may reflect the cognitive functions in brain regions, and we speculate that early impairments in memory, hearing, and language function can eventual y lead to diffuse brain injury and other cognitive impairments.

  5. Large-Scale Networks in the Human Brain revealed by Functional Connectivity MRI

    OpenAIRE

    Krienen, Fenna Marie

    2013-01-01

    The human brain is composed of distributed networks that connect a disproportionately large neocortex to the brainstem, cerebellum and other subcortical structures. New methods for analyzing non-invasive imaging data have begun to reveal new insights into human brain organization. These methods permit characterization of functional interactions within and across brain networks, and allow us to appreciate points of departure between the human brain and non-human primates.

  6. Functional brain network changes associated with clinical and biochemical measures of the severity of hepatic encephalopathy.

    Science.gov (United States)

    Jao, Tun; Schröter, Manuel; Chen, Chao-Long; Cheng, Yu-Fan; Lo, Chun-Yi Zac; Chou, Kun-Hsien; Patel, Ameera X; Lin, Wei-Che; Lin, Ching-Po; Bullmore, Edward T

    2015-11-15

    Functional properties of the brain may be associated with changes in complex brain networks. However, little is known about how properties of large-scale functional brain networks may be altered stepwise in patients with disturbance of consciousness, e.g., an encephalopathy. We used resting-state fMRI data on patients suffering from various degrees of hepatic encephalopathy (HE) to explore how topological and spatial network properties of functional brain networks changed at different cognitive and consciousness states. Severity of HE was measured clinically and by neuropsychological tests. Fifty-eight non-alcoholic liver cirrhosis patients and 62 normal controls were studied. Patients were subdivided into liver cirrhosis with no outstanding HE (NoHE, n=23), minimal HE with cognitive impairment only detectable by neuropsychological tests (MHE, n=28), and clinically overt HE (OHE, n=7). From the earliest stage, the NoHE, functional brain networks were progressively more random, less clustered, and less modular. Since the intermediate stage (MHE), increased ammonia level was accompanied by concomitant exponential decay of mean connectivity strength, especially in the primary cortical areas and midline brain structures. Finally, at the OHE stage, there were radical reorganization of the topological centrality-i.e., the relative importance-of the hubs and reorientation of functional connections between nodes. In summary, this study illustrated progressively greater abnormalities in functional brain network organization in patients with clinical and biochemical evidence of more severe hepatic encephalopathy. The early-than-expected brain network dysfunction in cirrhotic patients suggests that brain functional connectivity and network analysis may provide useful and complementary biomarkers for more aggressive and earlier intervention of hepatic encephalopathy. Moreover, the stepwise deterioration of functional brain networks in HE patients may suggest that hierarchical

  7. Large-Scale Functional Brain Network Abnormalities in Alzheimer’s Disease: Insights from Functional Neuroimaging

    Directory of Open Access Journals (Sweden)

    Bradford C. Dickerson

    2009-01-01

    Full Text Available Functional MRI (fMRI studies of mild cognitive impairment (MCI and Alzheimer’s disease (AD have begun to reveal abnormalities in large-scale memory and cognitive brain networks. Since the medial temporal lobe (MTL memory system is a site of very early pathology in AD, a number of studies have focused on this region of the brain. Yet it is clear that other regions of the large-scale episodic memory network are affected early in the disease as well, and fMRI has begun to illuminate functional abnormalities in frontal, temporal, and parietal cortices as well in MCI and AD. Besides predictable hypoactivation of brain regions as they accrue pathology and undergo atrophy, there are also areas of hyperactivation in brain memory and cognitive circuits, possibly representing attempted compensatory activity. Recent fMRI data in MCI and AD are beginning to reveal relationships between abnormalities of functional activity in the MTL memory system and in functionally connected brain regions, such as the precuneus. Additional work with “resting state” fMRI data is illuminating functional-anatomic brain circuits and their disruption by disease. As this work continues to mature, it will likely contribute to our understanding of fundamental memory processes in the human brain and how these are perturbed in memory disorders. We hope these insights will translate into the incorporation of measures of task-related brain function into diagnostic assessment or therapeutic monitoring, which will hopefully one day be useful for demonstrating beneficial effects of treatments being tested in clinical trials.

  8. Influence of APOE Genotype on Whole-Brain Functional Networks in Cognitively Normal Elderly

    OpenAIRE

    Seo, Eun Hyun; Lee, Dong Young; Lee, Jong-Min; Park, Jun-Sung; Sohn, Bo Kyung; Choe, Young Min; Byun, Min Soo; Choi, Hyo Jung; Woo, Jong Inn

    2013-01-01

    This study aimed to investigate the influence of apolipoprotein E (APOE) ε4 allele on whole-brain functional networks in cognitively normal (CN) elderly by applying graph theoretical analysis to brain glucose metabolism. Eighty-six CN elderly [28 APOE ε4 carriers (ε4+) and 58 non-carriers (ε4-)] underwent clinical evaluation and resting [18F] fluorodeoxyglucose positron emission tomography scan. Whole-brain functional networks were constructed from correlations of the 90 regions of interest u...

  9. The conundrum of functional brain networks: small-world efficiency or fractal modularity

    CERN Document Server

    Gallos, Lazaros K; Makse, Hernan A

    2012-01-01

    The human brain has been studied at multiple scales, from neurons, circuits, areas with well defined anatomical and functional boundaries, to large-scale functional networks which mediate coherent cognition. In a recent work, we addressed the problem of the hierarchical organization in the brain through network analysis. Our analysis identified functional brain modules of fractal structure that were inter-connected in a small-world topology. Here, we provide more details on the use of network science tools to elaborate on this behavior. We indicate the importance of using percolation theory to highlight the modular character of the functional brain network. These modules present a fractal, self-similar topology, identified through fractal network methods. When we lower the threshold of correlations to include weaker ties, the network as a whole assumes a small-world character. These weak ties are organized precisely as predicted by theory maximizing information transfer with minimal wiring costs.

  10. Modeling dynamic functional information flows on large-scale brain networks.

    Science.gov (United States)

    Lv, Peili; Guo, Lei; Hu, Xintao; Li, Xiang; Jin, Changfeng; Han, Junwei; Li, Lingjiang; Liu, Tianming

    2013-01-01

    Growing evidence from the functional neuroimaging field suggests that human brain functions are realized via dynamic functional interactions on large-scale structural networks. Even in resting state, functional brain networks exhibit remarkable temporal dynamics. However, it has been rarely explored to computationally model such dynamic functional information flows on large-scale brain networks. In this paper, we present a novel computational framework to explore this problem using multimodal resting state fMRI (R-fMRI) and diffusion tensor imaging (DTI) data. Basically, recent literature reports including our own studies have demonstrated that the resting state brain networks dynamically undergo a set of distinct brain states. Within each quasi-stable state, functional information flows from one set of structural brain nodes to other sets of nodes, which is analogous to the message package routing on the Internet from the source node to the destination. Therefore, based on the large-scale structural brain networks constructed from DTI data, we employ a dynamic programming strategy to infer functional information transition routines on structural networks, based on which hub routers that most frequently participate in these routines are identified. It is interesting that a majority of those hub routers are located within the default mode network (DMN), revealing a possible mechanism of the critical functional hub roles played by the DMN in resting state. Also, application of this framework on a post trauma stress disorder (PTSD) dataset demonstrated interesting difference in hub router distributions between PTSD patients and healthy controls. PMID:24579202

  11. Dynamic brain architectures in local brain activity and functional network efficiency associate with efficient reading in bilinguals.

    Science.gov (United States)

    Feng, Gangyi; Chen, Hsuan-Chih; Zhu, Zude; He, Yong; Wang, Suiping

    2015-10-01

    The human brain is organized as a dynamic network, in which both regional brain activity and inter-regional connectivity support high-level cognitive processes, such as reading. However, it is still largely unknown how the functional brain network organizes to enable fast and effortless reading processing in the native language (L1) but not in a non-proficient second language (L2), and whether the mechanisms underlying local activity are associated with connectivity dynamics in large-scale brain networks. In the present study, we combined activation-based and multivariate graph-theory analysis with functional magnetic resonance imaging data to address these questions. Chinese-English unbalanced bilinguals read narratives for comprehension in Chinese (L1) and in English (L2). Compared with L2, reading in L1 evoked greater brain activation and recruited a more globally efficient but less clustered network organization. Regions with both increased network efficiency and enhanced brain activation in L1 reading were mostly located in the fronto-temporal reading-related network (RN), whereas regions with decreased global network efficiency, increased clustering, and more deactivation in L2 reading were identified in the default mode network (DMN). Moreover, functional network efficiency was closely associated with local brain activation, and such associations were also modulated by reading efficiency in the two languages. Our results demonstrate that an economical and integrative brain network topology is associated with efficient reading, and further reveal a dynamic association between network efficiency and local activation for both RN and DMN. These findings underscore the importance of considering interregional connectivity when interpreting local BOLD signal changes in bilingual reading. PMID:26095088

  12. Exploring Functional Connectivity Networks with Multichannel Brain Array Coils

    OpenAIRE

    Anteraper, Sheeba Arnold; Keil, Boris; Triantafyllou, Christina; Gabrieli, Susan; Shannon, Steven P.; Gabrieli, John D.E.

    2013-01-01

    The use of multichannel array head coils in functional and structural magnetic resonance imaging (MRI) provides increased signal-to-noise ratio (SNR), higher sensitivity, and parallel imaging capabilities. However, their benefits remain to be systematically explored in the context of resting-state functional connectivity MRI (fcMRI). In this study, we compare signal detectability within and between commercially available multichannel brain coils, a 32-Channel (32Ch), and a 12-Channel (12Ch) a...

  13. Altered functional brain network connectivity and glutamate system function in transgenic mice expressing truncated Disrupted-in-Schizophrenia 1

    OpenAIRE

    Dawson, N.; Kurihara, M.; Thomson, D. M.; Winchester, C L; McVie, A.; Hedde, J.R.; Randall, A.D.; Shen, S.; Seymour, P.A.; Hughes, Z.A.; Dunlop, J; Brown, J.T.; Brandon, N. J.; Morris, B J; Pratt, J.A.

    2015-01-01

    Considerable evidence implicates DISC1 as a susceptibility gene for multiple psychiatric diseases. DISC1 has been intensively studied at the molecular, cellular and behavioral level, but its role in regulating brain connectivity and brain network function remains unknown. Here, we utilize a set of complementary approaches to assess the functional brain network abnormalities present in mice expressing a truncated Disc1 gene (Disc1tr Hemi mice). Disc1tr Hemi mice exhibited hypometabolism in the...

  14. Is functional integration of resting state brain networks an unspecific biomarker for working memory performance?

    Science.gov (United States)

    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

  15. Functional brain networks formed using cross-sample entropy are scale free.

    Science.gov (United States)

    Pritchard, Walter S; Laurienti, Paul J; Burdette, Jonathan H; Hayasaka, Satoru

    2014-08-01

    Over the previous decade, there has been an explosion of interest in network science, in general, and its application to the human brain, in particular. Most brain network investigations to date have used linear correlations (LinCorr) between brain areas to construct and then interpret brain networks. In this study, we applied an entropy-based method to establish functional connectivity between brain areas. This method is sensitive to both nonlinear and linear associations. The LinCorr-based and entropy-based techniques were applied to resting-state functional magnetic resonance imaging data from 10 subjects, and the resulting networks were compared. The networks derived from the entropy-based method exhibited power-law degree distributions. Moreover, the entropy-based networks had a higher clustering coefficient and a shorter path length compared with that of the LinCorr-based networks. While the LinCorr-based networks were assortative, with nodes with similar degrees preferentially connected, the entropy-based networks were disassortative, with high-degree hubs directly connected to low-degree nodes. It is likely that the differences in clustering and assortativity are due to "mega-hubs" in the entropy-based networks. These mega-hubs connect to a large majority of the nodes in the network. This is the first work clearly demonstrating differences between functional brain networks using linear and nonlinear techniques. The key finding is that the nonlinear technique produced networks with scale-free degree distributions. There remains debate among the neuroscience community as to whether human brains are scale free. These data support the argument that at least some aspects of the human brain are perhaps scale free. PMID:24946057

  16. Additional Brain Functional Network in Adults with Attention-Deficit/Hyperactivity Disorder: A Phase Synchrony Analysis

    OpenAIRE

    Yu, Dongchuan

    2013-01-01

    We develop a method to construct a new type of functional networks by the usage of phase synchrony degree that is different from the widely used Pearson's correlation approach. By a series of very strict statistical tests, we found that there is an additional network in attention-deficit/hyperactivity disorder (ADHD) subjects, superimposing the original (normal) brain functional network corresponding to healthy controls. The additional network leads to the increase in clustering coefficient, ...

  17. Adaptive reconfiguration of fractal small-world human brain functional networks

    OpenAIRE

    Bassett, Danielle S; Meyer-Lindenberg, Andreas; Achard, Sophie; Duke, Thomas; Bullmore, Edward

    2006-01-01

    Brain function depends on adaptive self-organization of large-scale neural assemblies, but little is known about quantitative network parameters governing these processes in humans. Here, we describe the topology and synchronizability of frequency-specific brain functional networks using wavelet decomposition of magnetoencephalographic time series, followed by construction and analysis of undirected graphs. Magnetoencephalographic data were acquired from 22 subjects, half of whom performed a ...

  18. Modular Segregation of Structural Brain Networks Supports the Development of Executive Function in Youth

    OpenAIRE

    Baum, Graham L.; Ciric, Rastko; Roalf, David R.; Richard F Betzel; Moore, Tyler M; Shinohara, Russel T.; Kahn, Ari E.; Quarmley, Megan; Cook, Philip A.; Elliot, Mark A.; Ruparel, Kosha; Gur, Raquel E; Gur, Ruben C.; Bassett, Danielle S.; Satterthwaite, Theodore D

    2016-01-01

    The human brain is organized into large-scale functional modules that have been shown to evolve in childhood and adolescence. However, it remains unknown whether structural brain networks are similarly refined during development, potentially allowing for improvements in executive function. In a sample of 882 participants (ages 8-22) who underwent diffusion imaging as part of the Philadelphia Neurodevelopmental Cohort, we demonstrate that structural network modules become more segregated with ...

  19. Distinct disruptions of resting-state functional brain networks in familial and sporadic schizophrenia.

    Science.gov (United States)

    Zhu, Jiajia; Zhuo, Chuanjun; Liu, Feng; Qin, Wen; Xu, Lixue; Yu, Chunshui

    2016-01-01

    Clinical and brain structural differences have been reported between patients with familial and sporadic schizophrenia; however, little is known about the brain functional differences between the two subtypes of schizophrenia. Twenty-six patients with familial schizophrenia (PFS), 26 patients with sporadic schizophrenia (PSS) and 26 healthy controls (HC) underwent a resting-state functional magnetic resonance imaging. The whole-brain functional network was constructed and analyzed using graph theoretical approaches. Topological properties (including global, nodal and edge measures) were compared among the three groups. We found that PFS, PSS and HC exhibited common small-world architecture of the functional brain networks. However, at a global level, only PFS showed significantly lower normalized clustering coefficient, small-worldness, and local efficiency, indicating a randomization shift of their brain networks. At a regional level, PFS and PSS disrupted different neural circuits, consisting of abnormal nodes (increased or decreased nodal centrality) and edges (decreased functional connectivity strength), which were widely distributed throughout the entire brain. Furthermore, some of these altered network measures were significantly correlated with severity of psychotic symptoms. These results suggest that familial and sporadic schizophrenia had segregated disruptions in the topological organization of the intrinsic functional brain network, which may be due to different etiological contributions. PMID:27032817

  20. Mapping Thalamocortical Networks in Rat Brain using Resting-State Functional Connectivity

    OpenAIRE

    Liang, Zhifeng; Li, Tao; King, Jean; Zhang, Nanyin

    2013-01-01

    Thalamocortical connectivity plays a vital role in brain function. The anatomy and function of thalamocortical networks have been extensively studied in animals by numerous invasive techniques. Non-invasively mapping thalamocortical networks in humans has also been demonstrated by utilizing resting-state functional magnetic resonance imaging (rsfMRI). However, success in simultaneously imaging multiple thalamocortical networks in animals is rather limited. This is largely due to the profound ...

  1. Spontaneous Functional Network Dynamics and Associated Structural Substrates in the Human Brain

    Directory of Open Access Journals (Sweden)

    Xuhong Liao

    2015-09-01

    Full Text Available Recent imaging connectomics studies have demonstrated that the spontaneous human brain functional networks derived from resting-state functional MRI (R-fMRI include many non-trivial topological properties, such as highly efficient small-world architecture and densely connected hub regions. However, very little is known about dynamic functional connectivity (D-FC patterns of spontaneous human brain networks during rest and about how these spontaneous brain dynamics are constrained by the underlying structural connectivity. Here, we combined sub-second multiband R-fMRI data with graph-theoretical approaches to comprehensively investigate the dynamic characteristics of the topological organization of human whole-brain functional networks, and then employed diffusion imaging data in the same participants to further explore the associated structural substrates. At the connection level, we found that human whole-brain D-FC patterns spontaneously fluctuated over time, while homotopic D-FC exhibited high connectivity strength and low temporal variability. At the network level, dynamic functional networks exhibited time-varying but evident small-world and assortativity architecture, with several regions (e.g., insula, sensorimotor cortex and medial prefrontal cortex emerging as functionally persistent hubs (i.e., highly connected regions while possessing large temporal variability in their degree centrality. Finally, the temporal characteristics (i.e., strength and variability of the connectional and nodal properties of the dynamic brain networks were significantly associated with their structural counterparts. Collectively, we demonstrate the economical, efficient and flexible characteristics of dynamic functional coordination in large-scale human brain networks during rest, and highlight their relationship with underlying structural connectivity, which deepens our understandings of spontaneous brain network dynamics in humans.

  2. Positron Emission Tomography Reveals Abnormal Topological Organization in Functional Brain Network in Diabetic Patients.

    Science.gov (United States)

    Qiu, Xiangzhe; Zhang, Yanjun; Feng, Hongbo; Jiang, Donglang

    2016-01-01

    Recent studies have demonstrated alterations in the topological organization of structural brain networks in diabetes mellitus (DM). However, the DM-related changes in the topological properties in functional brain networks are unexplored so far. We therefore used fluoro-D-glucose positron emission tomography (FDG-PET) data to construct functional brain networks of 73 DM patients and 91 sex- and age-matched normal controls (NCs), followed by a graph theoretical analysis. We found that both DM patients and NCs had a small-world topology in functional brain network. In comparison to the NC group, the DM group was found to have significantly lower small-world index, lower normalized clustering coefficients and higher normalized characteristic path length. Moreover, for diabetic patients, the nodal centrality was significantly reduced in the right rectus, the right cuneus, the left middle occipital gyrus, and the left postcentral gyrus, and it was significantly increased in the orbitofrontal region of the left middle frontal gyrus, the left olfactory region, and the right paracentral lobule. Our results demonstrated that the diabetic brain was associated with disrupted topological organization in the functional PET network, thus providing functional evidence for the abnormalities of brain networks in DM. PMID:27303259

  3. Positron Emission Tomography Reveals Abnormal Topological Organization in Functional Brain Network in Diabetic Patients

    Directory of Open Access Journals (Sweden)

    Qiu eXiangzhe

    2016-05-01

    Full Text Available Recent studies have demonstrated alterations in the topological organization of structural brain networks in diabetes mellitus (DM. However, the DM-related changes in the topological properties in functional brain networks are almost unexplored so far. We therefore used fluoro-D-glucose positron emission tomography (FDG-PET data to construct functional brain networks of 73 DM patients and 91 sex- and age-matched normal controls (NCs, followed by a graph theoretical analysis. We found that both DM patients and NCs had a small-world topology in functional brain network. In comparison to the NC group, the DM group was found to have significantly lower small-world index, lower normalized clustering coefficients and higher normalized shortest path length. Moreover, for diabetic patients, the nodal centrality was significantly reduced in the right rectus, the right cuneus, the left middle occipital gyrus, and the left postcentral gyrus, and it was significantly increased in the orbitofrontal region of the left middle frontal gyrus, the left olfactory region, and the right paracentral lobule. Our results demonstrated that the diabetic brain was associated with disrupted topological organization in the functional PET network, thus providing the functional evidence for the abnormalities of brain networks in DM.

  4. Graph Analysis of Functional Brain Networks for Cognitive Control of Action in Traumatic Brain Injury

    Science.gov (United States)

    Caeyenberghs, Karen; Leemans, Alexander; Heitger, Marcus H.; Leunissen, Inge; Dhollander, Thijs; Sunaert, Stefan; Dupont, Patrick; Swinnen, Stephan P.

    2012-01-01

    Patients with traumatic brain injury show clear impairments in behavioural flexibility and inhibition that often persist beyond the time of injury, affecting independent living and psychosocial functioning. Functional magnetic resonance imaging studies have shown that patients with traumatic brain injury typically show increased and more broadly…

  5. Altered resting state functional brain network topology in chemotherapy-treated breast cancer survivors

    OpenAIRE

    Bruno, Jennifer; Hosseini, SM Hadi; Kesler, Shelli

    2012-01-01

    Many women with breast cancer, especially those treated with chemotherapy, experience cognitive decline due in part to neurotoxic brain injury. Recent neuroimaging studies suggest widespread brain structural abnormalities pointing to disruption of large-scale brain networks. We applied resting state functional magnetic resonance imaging and graph theoretical analysis to examine the connectome in breast cancer survivors treated with chemotherapy relative to healthy comparison women. Compared t...

  6. Aberrant topologies and reconfiguration pattern of functional brain network in children with second language reading impairment.

    Science.gov (United States)

    Liu, Lanfang; Li, Hehui; Zhang, Manli; Wang, Zhengke; Wei, Na; Liu, Li; Meng, Xiangzhi; Ding, Guosheng

    2016-07-01

    Prior work has extensively studied neural deficits in children with reading impairment (RI) in their native language but has rarely examined those of RI children in their second language (L2). A recent study revealed that the function of the local brain regions was disrupted in children with RI in L2, but it is not clear whether the disruption also occurs at a large-scale brain network level. Using fMRI and graph theoretical analysis, we explored the topology of the whole-brain functional network during a phonological rhyming task and network reconfigurations across task and short resting phases in Chinese children with English reading impairment versus age-matched typically developing (TD) children. We found that, when completing the phonological task, the RI group exhibited higher local network efficiency and network modularity compared with the TD group. When switching between the phonological task and the short resting phase, the RI group showed difficulty with network reconfiguration, as reflected in fewer changes in the local efficiency and modularity properties and less rearrangement of the modular communities. These findings were reproducible after controlling for the effects of in-scanner accuracy, participant gender, and L1 reading performance. The results from the whole-brain network analyses were largely replicated in the task-activated network. These findings provide preliminary evidence supporting that RI in L2 is associated with not only abnormal functional network organization but also poor flexibility of the neural system in responding to changing cognitive demands. PMID:27321248

  7. Whole-brain functional networks in cognitively normal, mild cognitive impairment, and Alzheimer's disease.

    Directory of Open Access Journals (Sweden)

    Eun Hyun Seo

    Full Text Available The conceptual significance of understanding functional brain alterations and cognitive deficits associated with Alzheimer's disease (AD process has been widely established. However, the whole-brain functional networks of AD and its prodromal stage, mild cognitive impairment (MCI, are not well clarified yet. In this study, we compared the characteristics of the whole-brain functional networks among cognitively normal (CN, MCI, and AD individuals by applying graph theoretical analyses to [(18F] fluorodeoxyglucose positron emission tomography (FDG-PET data. Ninety-four CN elderly, 183 with MCI, and 216 with AD underwent clinical evaluation and FDG-PET scan. The overall small-world property as seen in the CN whole-brain network was preserved in MCI and AD. In contrast, individual parameters of the network were altered with the following patterns of changes: local clustering of networks was lower in both MCI and AD compared to CN, while path length was not different among the three groups. Then, MCI had a lower level of local clustering than AD. Subgroup analyses for AD also revealed that very mild AD had lower local clustering and shorter path length compared to mild AD. Regarding the local properties of the whole-brain networks, MCI and AD had significantly decreased normalized betweenness centrality in several hubs regionally associated with the default mode network compared to CN. Our results suggest that the functional integration in whole-brain network progressively declines due to the AD process. On the other hand, functional relatedness between neighboring brain regions may not gradually decrease, but be the most severely altered in MCI stage and gradually re-increase in clinical AD stages.

  8. Intrinsic intranasal chemosensory brain networks shown by resting-state functional MRI.

    Science.gov (United States)

    Tobia, Michael J; Yang, Qing X; Karunanayaka, Prasanna

    2016-05-01

    The human brain is organized into functional networks for sensory-motor and cognitive processing. Intrinsic networks are detectable in the absence of stimulation or task demands, whereas extrinsic networks are detectable when stimulated by sensory or cognitive demands. Intranasal chemosensory processing relies on two dissociable networks for processing incoming trigeminal and olfactory stimulation, but it is not known whether these networks are intrinsically organized. The aim of this study was to identify whether brain networks for intranasal chemosensory processing are detectable in functional connectivity resting-state functional MRI (fMRI). Sixteen healthy adults participated in a 5-min resting-state fMRI study. Functional connectivity seeds were defined from coordinates that anchor olfactory (i.e. bilateral piriform and orbitofrontal cortex) and trigeminal (bilateral anterior insula and cingulate cortex) networks in published task activation studies, and the resulting networks were thresholded at P less than 0.001. The olfactory network showed extended functional connectivity to the thalamus, medial prefrontal cortex, caudate, nucleus accumbens, parahippocampal gyrus, and hippocampus. The trigeminal network showed extended functional connectivity to the precuneus, thalamus, caudate, brainstem, and cerebellum. Both networks overlapped in the thalamus, caudate, medial prefrontal cortex, and insula. These results show that brain networks for intranasal chemosensory processing are intrinsically organized, not just extrinsically instantiated in response to task demands, and resemble networks for processing olfactory and trigeminal stimulation. As such, it may be possible to study the functional organization and dynamics of the olfactory network in resting-state fMRI as well as its implications for aging and disease. PMID:27031873

  9. Graph theoretical analysis of structural and functional connectivity MRI in normal and pathological brain networks.

    Science.gov (United States)

    Guye, Maxime; Bettus, Gaelle; Bartolomei, Fabrice; Cozzone, Patrick J

    2010-12-01

    Graph theoretical analysis of structural and functional connectivity MRI data (ie. diffusion tractography or cortical volume correlation and resting-state or task-related (effective) fMRI, respectively) has provided new measures of human brain organization in vivo. The most striking discovery is that the whole-brain network exhibits "small-world" properties shared with many other complex systems (social, technological, information, biological). This topology allows a high efficiency at different spatial and temporal scale with a very low wiring and energy cost. Its modular organization also allows for a high level of adaptation. In addition, degree distribution of brain networks demonstrates highly connected hubs that are crucial for the whole-network functioning. Many of these hubs have been identified in regions previously defined as belonging to the default-mode network (potentially explaining the high basal metabolism of this network) and the attentional networks. This could explain the crucial role of these hub regions in physiology (task-related fMRI data) as well as in pathophysiology. Indeed, such topological definition provides a reliable framework for predicting behavioral consequences of focal or multifocal lesions such as stroke, tumors or multiple sclerosis. It also brings new insights into a better understanding of pathophysiology of many neurological or psychiatric diseases affecting specific local or global brain networks such as epilepsy, Alzheimer's disease or schizophrenia. Graph theoretical analysis of connectivity MRI data provides an outstanding framework to merge anatomical and functional data in order to better understand brain pathologies. PMID:20349109

  10. SSVEP response is related to functional brain network topology entrained by the flickering stimulus.

    Directory of Open Access Journals (Sweden)

    Yangsong Zhang

    Full Text Available Previous studies have shown that the brain network topology correlates with the cognitive function. However, few studies have investigated the relationship between functional brain networks that process sensory inputs and outputs. In this study, we focus on steady-state paradigms using a periodic visual stimulus, which are increasingly being used in both brain-computer interface (BCI and cognitive neuroscience researches. Using the graph theoretical analysis, we investigated the relationship between the topology of functional networks entrained by periodic stimuli and steady state visually evoked potentials (SSVEP using two frequencies and eleven subjects. First, the entire functional network (Network 0 of each frequency for each subject was constructed according to the coherence between electrode pairs. Next, Network 0 was divided into three sub-networks, in which the connection strengths were either significantly (positively for Network 1, negatively for Network 3 or non-significantly (Network 2 correlated with the SSVEP responses. Our results revealed that the SSVEP responses were positively correlated to the mean functional connectivity, clustering coefficient, and global and local efficiencies, while these responses were negatively correlated with the characteristic path length of Networks 0, 1 and 2. Furthermore, the strengths of these connections that significantly correlated with the SSVEP (both positively and negatively were mainly found to be long-range connections between the parietal-occipital and frontal regions. These results indicate that larger SSVEP responses correspond with better functional network topology structures. This study may provide new insights for understanding brain mechanisms when using SSVEPs as frequency tags.

  11. Properties of functional brain networks correlate frequency of psychogenic non-epileptic seizures

    OpenAIRE

    Mahdi Jalili; Rossetti, Andrea O

    2012-01-01

    Abnormalities in the topology of brain networks may be an important feature and etiological factor for psychogenic non-epileptic seizures (PNES). To explore this possibility, we applied a graph theoretical approach to functional networks based on resting state EEGs from 13 PNES patients and 13 age- and gender-matched controls. The networks were extracted from Laplacian-transformed time-series by a cross-correlation method. PNES patients showed close to normal local and global connectivity and...

  12. Properties of functional brain networks correlate with frequency of psychogenic non-epileptic seizures.

    OpenAIRE

    Barzegaran, Elham; Joudaki, Amir; Jalili, Mahdi; Rossetti, Andrea O; Frackowiak, Richard S.; Knyazeva, Maria G.

    2012-01-01

    Abnormalities in the topology of brain networks may be an important feature and etiological factor for psychogenic non-epileptic seizures (PNES). To explore this possibility, we applied a graph theoretical approach to functional networks based on resting state EEGs from 13 PNES patients and 13 age- and gender-matched controls. The networks were extracted from Laplacian-transformed time-series by a cross-correlation method. PNES patients showed close to normal local and global connectivity and...

  13. Complexity in relational processing predicts changes in functional brain network dynamics.

    Science.gov (United States)

    Cocchi, Luca; Halford, Graeme S; Zalesky, Andrew; Harding, Ian H; Ramm, Brentyn J; Cutmore, Tim; Shum, David H K; Mattingley, Jason B

    2014-09-01

    The ability to link variables is critical to many high-order cognitive functions, including reasoning. It has been proposed that limits in relating variables depend critically on relational complexity, defined formally as the number of variables to be related in solving a problem. In humans, the prefrontal cortex is known to be important for reasoning, but recent studies have suggested that such processes are likely to involve widespread functional brain networks. To test this hypothesis, we used functional magnetic resonance imaging and a classic measure of deductive reasoning to examine changes in brain networks as a function of relational complexity. As expected, behavioral performance declined as the number of variables to be related increased. Likewise, increments in relational complexity were associated with proportional enhancements in brain activity and task-based connectivity within and between 2 cognitive control networks: A cingulo-opercular network for maintaining task set, and a fronto-parietal network for implementing trial-by-trial control. Changes in effective connectivity as a function of increased relational complexity suggested a key role for the left dorsolateral prefrontal cortex in integrating and implementing task set in a trial-by-trial manner. Our findings show that limits in relational processing are manifested in the brain as complexity-dependent modulations of large-scale networks. PMID:23563963

  14. Electro-acupuncture at different acupoints modulating the relative specific brain functional network

    Science.gov (United States)

    Fang, Jiliang; Wang, Xiaoling; Wang, Yin; Liu, Hesheng; Hong, Yang; Liu, Jun; Zhou, Kehua; Wang, Lei; Xue, Chao; Song, Ming; Liu, Baoyan; Zhu, Bing

    2010-11-01

    Objective: The specific brain effects of acupoint are important scientific concern in acupuncture. However, previous acupuncture fMRI studies focused on acupoints in muscle layer on the limb. Therefore, researches on acupoints within connective tissue at trunk are warranted. Material and Methods: Brain effects of acupuncture on abdomen at acupoints Guanyuan (CV4) and Zhongwan (CV12) were tested using fMRI on 21 healthy volunteers. The data acquisition was performed at resting state, during needle retention, electroacupuncture (EA) and post-EA resting state. Needling sensations were rated after every electroacupuncture (EA) procedure. The needling sensations and the brain functional activity and connectivity were compared between CV4 and CV12 using SPSS, SPM2 and the local and remote connectivity maps. Results and conclusion: EA at CV4 and CV12 induced apparent deactivation effects in the limbic-paralimbic-neocortical network. The default mode of the brain was modified by needle retention and EA, respectively. The functional brain network was significantly changed post EA. However, the minor differences existed between these two acupoints. The results demonstrated similarity between functional brain network mode of acupuncture modulation and functional circuits of emotional and cognitive regulation. Acupuncture may produce analgesia, anti-anxiety and anti-depression via the limbic-paralimbic-neocortical network (LPNN).

  15. Functional Brain Networks: Does the Choice of Dependency Estimator and Binarization Method Matter?

    Science.gov (United States)

    Jalili, Mahdi

    2016-07-01

    The human brain can be modelled as a complex networked structure with brain regions as individual nodes and their anatomical/functional links as edges. Functional brain networks are constructed by first extracting weighted connectivity matrices, and then binarizing them to minimize the noise level. Different methods have been used to estimate the dependency values between the nodes and to obtain a binary network from a weighted connectivity matrix. In this work we study topological properties of EEG-based functional networks in Alzheimer’s Disease (AD). To estimate the connectivity strength between two time series, we use Pearson correlation, coherence, phase order parameter and synchronization likelihood. In order to binarize the weighted connectivity matrices, we use Minimum Spanning Tree (MST), Minimum Connected Component (MCC), uniform threshold and density-preserving methods. We find that the detected AD-related abnormalities highly depend on the methods used for dependency estimation and binarization. Topological properties of networks constructed using coherence method and MCC binarization show more significant differences between AD and healthy subjects than the other methods. These results might explain contradictory results reported in the literature for network properties specific to AD symptoms. The analysis method should be seriously taken into account in the interpretation of network-based analysis of brain signals.

  16. Functional Brain Networks: Does the Choice of Dependency Estimator and Binarization Method Matter?

    Science.gov (United States)

    Jalili, Mahdi

    2016-01-01

    The human brain can be modelled as a complex networked structure with brain regions as individual nodes and their anatomical/functional links as edges. Functional brain networks are constructed by first extracting weighted connectivity matrices, and then binarizing them to minimize the noise level. Different methods have been used to estimate the dependency values between the nodes and to obtain a binary network from a weighted connectivity matrix. In this work we study topological properties of EEG-based functional networks in Alzheimer's Disease (AD). To estimate the connectivity strength between two time series, we use Pearson correlation, coherence, phase order parameter and synchronization likelihood. In order to binarize the weighted connectivity matrices, we use Minimum Spanning Tree (MST), Minimum Connected Component (MCC), uniform threshold and density-preserving methods. We find that the detected AD-related abnormalities highly depend on the methods used for dependency estimation and binarization. Topological properties of networks constructed using coherence method and MCC binarization show more significant differences between AD and healthy subjects than the other methods. These results might explain contradictory results reported in the literature for network properties specific to AD symptoms. The analysis method should be seriously taken into account in the interpretation of network-based analysis of brain signals. PMID:27417262

  17. Graph theoretical analysis of organization of functional brain networks in ADHD.

    Science.gov (United States)

    Ahmadlou, Mehran; Adeli, Hojjat; Adeli, Amir

    2012-01-01

    This article presents a new methodology for investigation of the organization of the overall and hemispheric brain network of patients with attention-deficit hyperactivity disorder (ADHD) using theoretical analysis of a weighted graph with the goal of discovering how the brain topology is affected in such patients. The synchronization measure used is the nonlinear fuzzy synchronization likelihood (FSL) developed by the authors recently. Recent evidence indicates a normal neocortex has a small-world (SW) network with a balance between local structure and global structure characteristics. Such a network results in optimal balance between segregation and integration which is essential for high synchronizabilty and fast information transmission in a complex network. The SW network is characterized by the coexistence of dense clustering of connections (C) and short path lengths (L) among the network units. The results of investigation of C show the local structure of functional left-hemisphere brain networks of ADHD diverges from that of non-ADHD which is recognizable in the delta electroencephalograph (EEG) sub-band. Also, the results of investigation for L show the global structure of functional left-hemisphere brain networks of ADHD diverges from that of non-ADHD which is observable in the delta EEG sub-band. It is concluded that the changes in left-hemisphere brain's structure of ADHD from that of the non-ADHD are so much that L and C can distinguish the ADHD brain from the non-ADHD brain in the delta EEG sub-band. PMID:22423545

  18. Additional brain functional network in adults with attention-deficit/hyperactivity disorder: a phase synchrony analysis.

    Directory of Open Access Journals (Sweden)

    Dongchuan Yu

    Full Text Available We develop a method to construct a new type of functional networks by the usage of phase synchrony degree that is different from the widely used Pearson's correlation approach. By a series of very strict statistical tests, we found that there is an additional network in attention-deficit/hyperactivity disorder (ADHD subjects, superimposing the original (normal brain functional network corresponding to healthy controls. The additional network leads to the increase in clustering coefficient, cost, local efficiency, and global efficiency. Our findings are inconsistent with many previous researches (using the Pearson's correlation approach revealing both increased and decreased functional connections between brain regions and many reports revealing that the brain functional networks of ADHD patients have slow information flow and low global efficiency. We also confirm that the additional network in ADHD subjects contains 6 communities, and three of them are associated with emotional control, sensory information integration, and motor control, respectively. Furthermore, we find that there is a pathway connecting the left insula and left anterior cingular gyrus via the frontal gyrus and putamen in the additional network in ADHD subjects. This implies that due to the pathway connecting brain regions in the salience network, the ADHD patients are more sensitive to external stimuli or internal thoughts and are easier to switch to the executive network and hence harder to inhibit. For clinical diagnostic purposes, we apply the k-means clustering method to distinguish ADHD patients with healthy controls at the individual subject level, and obtain a meaningful diagnostic result. More interestingly, we find that the suggested technique using phase synchrony degree to construct functional networks may obtain higher classification accuracy than the method using the Pearson's correlation coefficient.

  19. Functional magnetic resonance imaging of intrinsic brain networks for translational drug discovery

    OpenAIRE

    Smucny, Jason; Wylie, Korey P.; Tregellas, Jason R.

    2014-01-01

    Developing translational biomarkers is a priority for psychiatry research. Task-independent functional brain imaging is a relatively novel technique that allows examination of the brain’s intrinsic networks, defined as functionally and (often) structurally connected populations of neurons whose properties reflect fundamental neurobiological organizational principles of the central nervous system. The ability to study the activity and organization of these networks has opened a promising new a...

  20. Modular structure of brain functional networks: breaking the resolution limit by Surprise

    Science.gov (United States)

    Nicolini, Carlo; Bifone, Angelo

    2016-01-01

    The modular organization of brain networks has been widely investigated using graph theoretical approaches. Recently, it has been demonstrated that graph partitioning methods based on the maximization of global fitness functions, like Newman’s Modularity, suffer from a resolution limit, as they fail to detect modules that are smaller than a scale determined by the size of the entire network. Here we explore the effects of this limitation on the study of brain connectivity networks. We demonstrate that the resolution limit prevents detection of important details of the brain modular structure, thus hampering the ability to appreciate differences between networks and to assess the topological roles of nodes. We show that Surprise, a recently proposed fitness function based on probability theory, does not suffer from these limitations. Surprise maximization in brain co-activation and functional connectivity resting state networks reveals the presence of a rich structure of heterogeneously distributed modules, and differences in networks’ partitions that are undetectable by resolution-limited methods. Moreover, Surprise leads to a more accurate identification of the network’s connector hubs, the elements that integrate the brain modules into a cohesive structure.

  1. Coherence in a simple network: Implication for brain function

    OpenAIRE

    Ye, Zhen

    2000-01-01

    In a many body system, constituents interact with each other, forming a recursive pattern of interaction and giving rise to many interesting phenomena. Based upon concepts of the modern many body theory, a model for a generic many body system is developed. A novel approach is proposed to investigate the general features in such a system. An interesting phase transition in the system is found. Possible link to brain dynamics is discussed. It is shown how some of the basic brain processes, such...

  2. Aberrant Functional Whole-Brain Network Architecture in Patients With Schizophrenia: A Meta-analysis.

    Science.gov (United States)

    Kambeitz, Joseph; Kambeitz-Ilankovic, Lana; Cabral, Carlos; Dwyer, Dominic B; Calhoun, Vince D; van den Heuvel, Martijn P; Falkai, Peter; Koutsouleris, Nikolaos; Malchow, Berend

    2016-07-01

    Findings from multiple lines of research provide evidence of aberrant functional brain connectivity in schizophrenia. By using graph-analytical measures, recent studies indicate that patients with schizophrenia exhibit changes in the organizational principles of whole-brain networks and that these changes relate to cognitive symptoms. However, there has not been a systematic investigation of functional brain network changes in schizophrenia to test the consistency of these changes across multiple studies. A comprehensive literature search was conducted to identify all available functional graph-analytical studies in patients with schizophrenia. Effect size measures were derived from each study and entered in a random-effects meta-analytical model. All models were tested for effects of potential moderator variables as well as for the presence of publication bias. The results of a total of n = 13 functional neuroimaging studies indicated that brain networks in patients with schizophrenia exhibit significant decreases in measures of local organization (g = -0.56, P = .02) and significant decreases in small-worldness (g = -0.65, P = .01) whereas global short communication paths seemed to be preserved (g = 0.26, P = .32). There was no evidence for a publication bias or moderator effects. The present meta- analysis demonstrates significant changes in whole brain network architecture associated with schizophrenia across studies. PMID:27460615

  3. Functional brain networks contributing to the Parieto-Frontal Integration Theory of Intelligence.

    Science.gov (United States)

    Vakhtin, Andrei A; Ryman, Sephira G; Flores, Ranee A; Jung, Rex E

    2014-12-01

    The refinement of localization of intelligence in the human brain is converging onto a distributed network that broadly conforms to the Parieto-Frontal Integration Theory (P-FIT). While this theory has received support in the neuroimaging literature, no functional magnetic resonance imaging study to date has conducted a whole-brain network-wise examination of the changes during engagement in tasks that are reliable measures of general intelligence (e.g., Raven's Progressive Matrices Test; RPM). Seventy-nine healthy subjects were scanned while solving RPM problems and during rest. Functional networks were extracted from the RPM and resting state data using Independent Component Analysis. Twenty-nine networks were identified, 26 of which were detected in both conditions. Fourteen networks were significantly correlated with the RPM task. The networks' spatial maps and functional connectivity measures at 3 frequency levels (low, medium, & high) were compared between the RPM and rest conditions. The regions involved in the networks that were found to be task related were consistent with the P-FIT, localizing to the bilateral medial frontal and parietal regions, right superior frontal lobule, and the right cingulate gyrus. Functional connectivity in multiple component pairs was differentially affected across all frequency levels during the RPM task. Our findings demonstrate that functional brain networks are more stable than previously thought, and maintain their general features across resting state and engagement in a complex cognitive task. The described spatial and functional connectivity alterations that such components undergo during fluid reasoning provide a network-wise framework of the P-FIT that can be valuable for further, network based, neuroimaging inquiries regarding the neural underpinnings of intelligence. PMID:25284305

  4. Brain Network Modelling

    DEFF Research Database (Denmark)

    Andersen, Kasper Winther

    Three main topics are presented in this thesis. The first and largest topic concerns network modelling of functional Magnetic Resonance Imaging (fMRI) and Diffusion Weighted Imaging (DWI). In particular nonparametric Bayesian methods are used to model brain networks derived from resting state f...... for their ability to reproduce node clustering and predict unseen data. Comparing the models on whole brain networks, BCD and IRM showed better reproducibility and predictability than IDM, suggesting that resting state networks exhibit community structure. This also points to the importance of using models, which...... allow for complex interactions between all pairs of clusters. In addition, it is demonstrated how the IRM can be used for segmenting brain structures into functionally coherent clusters. A new nonparametric Bayesian network model is presented. The model builds upon the IRM and can be used to infer...

  5. Topological correlations of structural and functional networks in patients with traumatic brain injury

    Directory of Open Access Journals (Sweden)

    Karen Caeyenberghs

    2013-11-01

    Full Text Available Despite an increasing amount of specific correlation studies between structural and functional connectivity, there is still a need for combined studies, especially in pathological conditions. Impairments of brain white matter and diffuse axonal injuries are commonly suspected to be responsible for the disconnection hypothesis in traumatic brain injury (TBI patients. Moreover, our previous research on TBI patients shows a strong relationship between abnormalities in topological organization of brain networks and behavioral deficits. In this study, we combined task-related functional connectivity (using event-related fMRI with structural connectivity (derived from fiber tractography using diffusion MRI data estimates in the same participants (17 adults with TBI and 16 controls, allowing for direct comparison between graph metrics of the different imaging modalities. Connectivity matrices were computed covering the switching motor network, which includes the basal ganglia, anterior cingulate cortex/supplementary motor area, and anterior insula/inferior frontal gyrus. The edges constituting this network consisted of the partial correlations between the fMRI time series from each node of the switching motor network. The interregional anatomical connections between the switching-related areas were determined using the fiber tractography results. We found that graph metrics and hubs obtained showed no agreement in both groups. The topological properties of brain functional networks could not be solely accounted for the properties of the underlying structural networks. However, combining complementary information from both different imaging modalities could improve accuracy in prediction of switching performance. Direct comparison between functional task-related and anatomical structural connectivity, presented here for the first time in TBI patients, links two powerful approaches to map the patterns of brain connectivity that may underlie behavioral

  6. A Multimodal Approach for Determining Brain Networks by Jointly Modeling Functional and Structural Connectivity

    Directory of Open Access Journals (Sweden)

    Wenqiong eXue

    2015-02-01

    Full Text Available Recent innovations in neuroimaging technology have provided opportunities for researchers to investigate connectivity in the human brain by examining the anatomical circuitry as well as functional relationships between brain regions. Existing statistical approaches for connectivity generally examine resting-state or task-related functional connectivity (FC between brain regions or separately examine structural linkages. As a means to determine brain networks, we present a unified Bayesian framework for analyzing FC utilizing the knowledge of associated structural connections, which extends an approach by Patel et al.(2006a that considers only functional data. We introduce an FC measure that rests upon assessments of functional coherence between regional brain activity identified from functional magnetic resonance imaging (fMRI data. Our structural connectivity (SC information is drawn from diffusion tensor imaging (DTI data, which is used to quantify probabilities of SC between brain regions. We formulate a prior distribution for FC that depends upon the probability of SC between brain regions, with this dependence adhering to structural-functional links revealed by our fMRI and DTI data. We further characterize the functional hierarchy of functionally connected brain regions by defining an ascendancy measure that compares the marginal probabilities of elevated activity between regions. In addition, we describe topological properties of the network, which is composed of connected region pairs, by performing graph theoretic analyses. We demonstrate the use of our Bayesian model using fMRI and DTI data from a study of auditory processing. We further illustrate the advantages of our method by comparisons to methods that only incorporate functional information.

  7. Frontoparietal Connectivity and Hierarchical Structure of the Brain's Functional Network during Sleep.

    Science.gov (United States)

    Spoormaker, Victor I; Gleiser, Pablo M; Czisch, Michael

    2012-01-01

    Frontal and parietal regions are associated with some of the most complex cognitive functions, and several frontoparietal resting-state networks can be observed in wakefulness. We used functional magnetic resonance imaging data acquired in polysomnographically validated wakefulness, light sleep, and slow-wave sleep to examine the hierarchical structure of a low-frequency functional brain network, and to examine whether frontoparietal connectivity would disintegrate in sleep. Whole-brain analyses with hierarchical cluster analysis on predefined atlases were performed, as well as regression of inferior parietal lobules (IPL) seeds against all voxels in the brain, and an evaluation of the integrity of voxel time-courses in subcortical regions-of-interest. We observed that frontoparietal functional connectivity disintegrated in sleep stage 1 and was absent in deeper sleep stages. Slow-wave sleep was characterized by strong hierarchical clustering of local submodules. Frontoparietal connectivity between IPL and superior medial and right frontal gyrus was lower in sleep stages than in wakefulness. Moreover, thalamus voxels showed maintained integrity in sleep stage 1, making intrathalamic desynchronization an unlikely source of reduced thalamocortical connectivity in this sleep stage. Our data suggest a transition from a globally integrated functional brain network in wakefulness to a disintegrated network consisting of local submodules in slow-wave sleep, in which frontoparietal inter-modular nodes may play a role, possibly in combination with the thalamus. PMID:22629253

  8. Test-retest reliability of graph metrics of resting state MRI functional brain networks: A review.

    Science.gov (United States)

    Andellini, Martina; Cannatà, Vittorio; Gazzellini, Simone; Bernardi, Bruno; Napolitano, Antonio

    2015-09-30

    The employment of graph theory to analyze spontaneous fluctuations in resting state BOLD fMRI data has become a dominant theme in brain imaging studies and neuroscience. Analysis of resting state functional brain networks based on graph theory has proven to be a powerful tool to quantitatively characterize functional architecture of the brain and it has provided a new platform to explore the overall structure of local and global functional connectivity in the brain. Due to its increased use and possible expansion to clinical use, it is essential that the reliability of such a technique is very strongly assessed. In this review, we explore the outcome of recent studies in network reliability which apply graph theory to analyze connectome resting state networks. Therefore, we investigate which preprocessing steps may affect reproducibility the most. In order to investigate network reliability, we compared the test-retest (TRT) reliability of functional data of published neuroimaging studies with different preprocessing steps. In particular we tested influence of global signal regression, correlation metric choice, binary versus weighted link definition, frequency band selection and length of time-series. Statistical analysis shows that only frequency band selection and length of time-series seem to affect TRT reliability. Our results highlight the importance of the choice of the preprocessing steps to achieve more reproducible measurements. PMID:26072249

  9. Brain functional connectivity, dopamine and the default mode network in ADHD

    OpenAIRE

    Richard Bernard Silberstein

    2015-01-01

    Recent evidence suggests that Attention Deficit Hyperactivity Disorder (ADHD) is associated with reduced inhibition of the default mode network (DMN) while performing a cognitive task. In this study, we use steady state visual evoked potential event related partial coherence as a measure of brain functional connectivity to examine functional connectivity differences between a control group of 25 boys and an age/IQ matched group of 42 boys newly diagnosed with ADHD. Functional connectivity w...

  10. Motor Network Plasticity and Low-Frequency Oscillations Abnormalities in Patients with Brain Gliomas: A Functional MRI Study

    OpenAIRE

    Niu, Chen; Zhang, Ming; Min, Zhigang; Rana, Netra; Zhang, Qiuli; Liu, Xin; Li, Min; Lin, Pan

    2014-01-01

    Brain plasticity is often associated with the process of slow-growing tumor formation, which remodels neural organization and optimizes brain network function. In this study, we aimed to investigate whether motor function plasticity would display deficits in patients with slow-growing brain tumors located in or near motor areas, but who were without motor neurological deficits. We used resting-state functional magnetic resonance imaging to probe motor networks in 15 patients with histopatholo...

  11. Spatiotemporal reconfiguration of large-scale brain functional networks during propofol-induced loss of consciousness.

    Science.gov (United States)

    Schröter, Manuel S; Spoormaker, Victor I; Schorer, Anna; Wohlschläger, Afra; Czisch, Michael; Kochs, Eberhard F; Zimmer, Claus; Hemmer, Bernhard; Schneider, Gerhard; Jordan, Denis; Ilg, Rüdiger

    2012-09-12

    Applying graph theoretical analysis of spontaneous BOLD fluctuations in functional magnetic resonance imaging (fMRI), we investigated whole-brain functional connectivity of 11 healthy volunteers during wakefulness and propofol-induced loss of consciousness (PI-LOC). After extraction of regional fMRI time series from 110 cortical and subcortical regions, we applied a maximum overlap discrete wavelet transformation and investigated changes in the brain's intrinsic spatiotemporal organization. During PI-LOC, we observed a breakdown of subcortico-cortical and corticocortical connectivity. Decrease of connectivity was pronounced in thalamocortical connections, whereas no changes were found for connectivity within primary sensory cortices. Graph theoretical analyses revealed significant changes in the degree distribution and local organization metrics of brain functional networks during PI-LOC: compared with a random network, normalized clustering was significantly increased, as was small-worldness. Furthermore we observed a profound decline in long-range connections and a reduction in whole-brain spatiotemporal integration, supporting a topological reconfiguration during PI-LOC. Our findings shed light on the functional significance of intrinsic brain activity as measured by spontaneous BOLD signal fluctuations and help to understand propofol-induced loss of consciousness. PMID:22973006

  12. Stress-induced alterations in large-scale functional networks of the rodent brain.

    Science.gov (United States)

    Henckens, Marloes J A G; van der Marel, Kajo; van der Toorn, Annette; Pillai, Anup G; Fernández, Guillén; Dijkhuizen, Rick M; Joëls, Marian

    2015-01-15

    Stress-related psychopathology is associated with altered functioning of large-scale brain networks. Animal research into chronic stress, one of the most prominent environmental risk factors for development of psychopathology, has revealed molecular and cellular mechanisms potentially contributing to human mental disease. However, so far, these studies have not addressed the system-level changes in extended brain networks, thought to critically contribute to mental disorders. We here tested the effects of chronic stress exposure (10 days immobilization) on the structural integrity and functional connectivity patterns in the brain, using high-resolution structural MRI, diffusion kurtosis imaging, and resting-state functional MRI, while confirming the expected changes in neuronal dendritic morphology using Golgi-staining. Stress effectiveness was confirmed by a significantly lower body weight and increased adrenal weight. In line with previous research, stressed animals displayed neuronal dendritic hypertrophy in the amygdala and hypotrophy in the hippocampal and medial prefrontal cortex. Using independent component analysis of resting-state fMRI data, we identified ten functional connectivity networks in the rodent brain. Chronic stress appeared to increase connectivity within the somatosensory, visual, and default mode networks. Moreover, chronic stress exposure was associated with an increased volume and diffusivity of the lateral ventricles, whereas no other volumetric changes were observed. This study shows that chronic stress exposure in rodents induces alterations in functional network connectivity strength which partly resemble those observed in stress-related psychopathology. Moreover, these functional consequences of stress seem to be more prominent than the effects on gross volumetric change, indicating their significance for future research. PMID:25462693

  13. Abnormal Brain Default-Mode Network Functional Connectivity in Drug Addicts

    OpenAIRE

    Ma, Ning; Liu, Ying; Fu, Xian-ming; Li, Nan; Wang, Chang-Xin; Zhang, Hao; Qian, Ruo-Bing; Xu, Hu-Sheng; Hu, Xiaoping; Zhang, Da-Ren

    2011-01-01

    Background The default mode network (DMN) is a set of brain regions that exhibit synchronized low frequency oscillations at resting-state, and is believed to be relevant to attention and self-monitoring. As the anterior cingulate cortex and hippocampus are impaired in drug addiction and meanwhile are parts of the DMN, the present study examined addiction-related alteration of functional connectivity of the DMN. Methodology Resting-state functional magnetic resonance imaging data of chronic he...

  14. Modalities of Thinking: State and Trait Effects on Cross-Frequency Functional Independent Brain Networks.

    Science.gov (United States)

    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

  15. The conundrum of functional brain networks: small-world or fractal modularity

    CERN Document Server

    Gallos, Lazaros K; Sigman, Mariano

    2011-01-01

    The human brain is organized in functional modules. Such an organization poses a conundrum: modules ought to be sufficiently independent to guarantee functional specialization and sufficiently connected to bind multiple processors for efficient information transfer. It is commonly accepted that small-world architecture may solve this problem. However, there is intrinsic tension between shortcuts generating small-worlds and the persistence of modules. Here we provide a solution to this puzzle. We show that the functional brain network formed by percolation of strong links is highly modular. Contrary to the common view, modules are self-similar and therefore are very far from being small-world. Incorporating the weak ties to the network converts it into a small-world preserving an underlying backbone of well-defined modules. Weak ties are organized precisely as predicted by theory maximizing information transfer with minimal wiring costs. This trade-off architecture is reminiscent of the "strength of weak ties"...

  16. Understanding brain networks and brain organization

    Science.gov (United States)

    Pessoa, Luiz

    2014-09-01

    What is the relationship between brain and behavior? The answer to this question necessitates characterizing the mapping between structure and function. The aim of this paper is to discuss broad issues surrounding the link between structure and function in the brain that will motivate a network perspective to understanding this question. However, as others in the past, I argue that a network perspective should supplant the common strategy of understanding the brain in terms of individual regions. Whereas this perspective is needed for a fuller characterization of the mind-brain, it should not be viewed as panacea. For one, the challenges posed by the many-to-many mapping between regions and functions is not dissolved by the network perspective. Although the problem is ameliorated, one should not anticipate a one-to-one mapping when the network approach is adopted. Furthermore, decomposition of the brain network in terms of meaningful clusters of regions, such as the ones generated by community-finding algorithms, does not by itself reveal "true" subnetworks. Given the hierarchical and multi-relational relationship between regions, multiple decompositions will offer different "slices" of a broader landscape of networks within the brain. Finally, I described how the function of brain regions can be characterized in a multidimensional manner via the idea of diversity profiles. The concept can also be used to describe the way different brain regions participate in networks.

  17. Creativity and the default network: A functional connectivity analysis of the creative brain at rest☆

    Science.gov (United States)

    Beaty, Roger E.; Benedek, Mathias; Wilkins, Robin W.; Jauk, Emanuel; Fink, Andreas; Silvia, Paul J.; Hodges, Donald A.; Koschutnig, Karl; Neubauer, Aljoscha C.

    2014-01-01

    The present research used resting-state functional magnetic resonance imaging (fMRI) to examine whether the ability to generate creative ideas corresponds to differences in the intrinsic organization of functional networks in the brain. We examined the functional connectivity between regions commonly implicated in neuroimaging studies of divergent thinking, including the inferior prefrontal cortex and the core hubs of the default network. Participants were prescreened on a battery of divergent thinking tests and assigned to high- and low-creative groups based on task performance. Seed-based functional connectivity analysis revealed greater connectivity between the left inferior frontal gyrus (IFG) and the entire default mode network in the high-creative group. The right IFG also showed greater functional connectivity with bilateral inferior parietal cortex and the left dorsolateral prefrontal cortex in the high-creative group. The results suggest that the ability to generate creative ideas is characterized by increased functional connectivity between the inferior prefrontal cortex and the default network, pointing to a greater cooperation between brain regions associated with cognitive control and low-level imaginative processes. PMID:25245940

  18. Characterization of the Community Structure of Large Scale Functional Brain Networks During Ketamine-Medetomidine Anesthetic Induction

    OpenAIRE

    Padovani, Eduardo C.

    2016-01-01

    One of the central questions in neuroscience is to understand the way communication is organized in the brain, trying to comprehend how cognitive capacities or physiological states of the organism are potentially related to brain activities involving interactions of several brain areas. One important characteristic of the functional brain networks is that they are modularly structured, being this modular architecture regarded to account for a series of properties and functional dynamics. In t...

  19. Effects of meditation experience on functional connectivity of distributed brain networks

    Directory of Open Access Journals (Sweden)

    Wendy eHasenkamp

    2012-03-01

    Full Text Available This study sought to examine the effect of meditation experience on brain networks underlying cognitive actions employed during contemplative practice. In a previous study, we proposed a basic model of naturalistic cognitive fluctuations that occur during the practice of focused attention meditation. This model specifies four intervals in a cognitive cycle: mind wandering, awareness of mind wandering, shifting of attention, and sustained attention. Using subjective input from experienced practitioners during meditation, we identified activity in salience network regions during awareness of mind wandering and executive network regions during shifting and sustained attention. Brain regions associated with the default mode were active during mind wandering. In the present study, we reasoned that repeated activation of attentional brain networks over years of practice may induce lasting functional connectivity changes within relevant circuits. To investigate this possibility, we created seeds representing the networks that were active during the four phases of the earlier study, and examined functional connectivity during the resting state in the same participants. Connectivity maps were then contrasted between participants with high vs. low meditation experience. Participants with more meditation experience exhibited increased connectivity within attentional networks, as well as between attentional regions and medial frontal regions. These neural relationships may be involved in the development of cognitive skills, such as maintaining attention and disengaging from distraction, that are often reported with meditation practice. Furthermore, because altered connectivity of brain regions in experienced meditators was observed in a non-meditative (resting state, this may represent a transference of cognitive abilities off the cushion into daily life.

  20. Altered functional brain network connectivity and glutamate system function in transgenic mice expressing truncated Disrupted-in-Schizophrenia 1.

    Science.gov (United States)

    Dawson, N; Kurihara, M; Thomson, D M; Winchester, C L; McVie, A; Hedde, J R; Randall, A D; Shen, S; Seymour, P A; Hughes, Z A; Dunlop, J; Brown, J T; Brandon, N J; Morris, B J; Pratt, J A

    2015-01-01

    Considerable evidence implicates DISC1 as a susceptibility gene for multiple psychiatric diseases. DISC1 has been intensively studied at the molecular, cellular and behavioral level, but its role in regulating brain connectivity and brain network function remains unknown. Here, we utilize a set of complementary approaches to assess the functional brain network abnormalities present in mice expressing a truncated Disc1 gene (Disc1tr Hemi mice). Disc1tr Hemi mice exhibited hypometabolism in the prefrontal cortex (PFC) and reticular thalamus along with a reorganization of functional brain network connectivity that included compromised hippocampal-PFC connectivity. Altered hippocampal-PFC connectivity in Disc1tr Hemi mice was confirmed by electrophysiological analysis, with Disc1tr Hemi mice showing a reduced probability of presynaptic neurotransmitter release in the monosynaptic glutamatergic hippocampal CA1-PFC projection. Glutamate system dysfunction in Disc1tr Hemi mice was further supported by the attenuated cerebral metabolic response to the NMDA receptor (NMDAR) antagonist ketamine and decreased hippocampal expression of NMDAR subunits 2A and 2B in these animals. These data show that the Disc1 truncation in Disc1tr Hemi mice induces a range of translationally relevant endophenotypes underpinned by glutamate system dysfunction and altered brain connectivity. PMID:25989143

  1. Fetal functional imaging portrays heterogeneous development of emerging human brain networks

    Directory of Open Access Journals (Sweden)

    Andras Jakab

    2014-10-01

    Full Text Available The functional connectivity architecture of the adult human brain enables complex cognitive processes, and exhibits a remarkably complex structure shared across individuals. We are only beginning to understand its heterogeneous structure, ranging from a strongly hierarchical organization in sensorimotor areas to widely distributed networks in areas such as the parieto-frontal cortex. Our study relied on the functional magnetic resonance imaging data of 32 fetuses with no detectable morphological abnormalities. After adapting functional magnetic resonance acquisition, motion correction and nuisance signal reduction procedures of resting-state functional data analysis to fetuses, we extracted neural activity information for major cortical and subcortical structures. Resting fMRI networks were observed for increasing regional functional connectivity from 21st – 38th gestational weeks (GW with a network-based statistical inference approach. The overall connectivity network, short range and interhemispheric connections showed sigmoid expansion curve peaking at the 26-29. GW. In contrast, long-range connections exhibited linear increase with no periods of peaking development. Region-specific increase of functional signal synchrony followed a sequence of occipital (peak: 24.8 GW, temporal (peak: 26 GW, frontal (peak: 26.4 GW and parietal expansion (peak: 27.5 GW. We successfully adapted functional neuroimaging and image post-processing approaches to correlate macroscopical scale activations in the fetal brain with gestational age. This in vivo study reflects the fact that the mid-fetal period hosts events that cause the architecture of the brain circuitry to mature, which presumably manifests in increasing strength of intra- and interhemispheric functional macroconnectivity.

  2. [Functional connectivity analysis of the brain network using resting-state FMRI].

    Science.gov (United States)

    Hayashi, Toshihiro

    2011-12-01

    Spatial patterns of spontaneous fluctuations in blood oxygenation level-dependent (BOLD) signals reflect the underlying neural architecture. The study of the brain network based on these self-organized patterns is termed resting-state functional MRI (fMRI). This review article aims at briefly reviewing a basic concept of this technology and discussing its implications for neuropsychological studies. First, the technical aspects of resting-state fMRI, including signal sources, physiological artifacts, image acquisition, and analytical methods such as seed-based correlation analysis and independent component analysis, are explained, followed by a discussion on the major resting-state networks, including the default mode network. In addition, the structure-function correlation studied using diffuse tensor imaging and resting-state fMRI is briefly discussed. Second, I have discussed the reservations and potential pitfalls of 2 major imaging methods: voxel-based lesion-symptom mapping and task fMRI. Problems encountered with voxel-based lesion-symptom mapping can be overcome by using resting-state fMRI and evaluating undamaged brain networks in patients. Regarding task fMRI in patients, I have also emphasized the importance of evaluating the baseline brain activity because the amplitude of activation in BOLD fMRI is hard to interpret as the same baseline cannot be assumed for both patient and normal groups. PMID:22147450

  3. Functional connectivity analysis of the brain network using resting-state fMRI

    International Nuclear Information System (INIS)

    Spatial patterns of spontaneous fluctuations in blood oxygenation level-dependent (BOLD) signals reflect the underlying neural architecture. The study of the brain network based on these self-organized patterns is termed resting-state functional MRI (fMRI). This review article aims at briefly reviewing a basic concept of this technology and discussing its implications for neuropsychological studies. First, the technical aspects of resting-state fMRI, including signal sources, physiological artifacts, image acquisition, and analytical methods such as seed-based correlation analysis and independent component analysis, are explained, followed by a discussion on the major resting-state networks, including the default mode network. In addition, the structure-function correlation studied using diffuse tensor imaging and resting-state fMRI is briefly discussed. Second, I have discussed the reservations and potential pitfalls of 2 major imaging methods: voxel-based lesion-symptom mapping and task fMRI. Problems encountered with voxel-based lesion-symptom mapping can be overcome by using resting-state fMRI and evaluating undamaged brain networks in patients. Regarding task fMRI in patients, I have also emphasized the importance of evaluating the baseline brain activity because the amplitude of activation in BOLD fMRI is hard to interpret as the same baseline cannot be assumed for both patient and normal groups. (author)

  4. Changes in functional brain networks following sports-related concussion in adolescents.

    Science.gov (United States)

    Virji-Babul, Naznin; Hilderman, Courtney G E; Makan, Nadia; Liu, Aiping; Smith-Forrester, Jenna; Franks, Chris; Wang, Z J

    2014-12-01

    Sports-related concussion is a major public health issue; however, little is known about the underlying changes in functional brain networks in adolescents following injury. Our aim was to use the tools from graph theory to evaluate the changes in brain network properties following concussion in adolescent athletes. We recorded resting state electroencephalography (EEG) in 33 healthy adolescent athletes and 9 adolescent athletes with a clinical diagnosis of subacute concussion. Graph theory analysis was applied to these data to evaluate changes in brain networks. Global and local metrics of the structural properties of the graph were calculated for each group and correlated with Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) scores. Brain networks of both groups showed small-world topology with no statistically significant differences in the global metrics; however, significant differences were found in the local metrics. Specifically, in the concussed group, we noted: 1) increased values of betweenness and degree in frontal electrode sites corresponding to the (R) dorsolateral prefrontal cortex and the (R) inferior frontal gyrus and 2) decreased values of degree in the region corresponding to the (R) frontopolar prefrontal cortex. In addition, there was significant negative correlation between degree and hub value, with total symptom score at the electrode site corresponding to the (R) prefrontal cortex. This preliminary report in adolescent athletes shows for the first time that resting-state EEG combined with graph theoretical analysis may provide an objective method of evaluating changes in brain networks following concussion. This approach may be useful in identifying individuals at risk for future injury. PMID:24956041

  5. Resolving anatomical and functional structure in human brain organization: identifying mesoscale organization in weighted network representations.

    Directory of Open Access Journals (Sweden)

    Christian Lohse

    2014-10-01

    Full Text Available Human brain anatomy and function display a combination of modular and hierarchical organization, suggesting the importance of both cohesive structures and variable resolutions in the facilitation of healthy cognitive processes. However, tools to simultaneously probe these features of brain architecture require further development. We propose and apply a set of methods to extract cohesive structures in network representations of brain connectivity using multi-resolution techniques. We employ a combination of soft thresholding, windowed thresholding, and resolution in community detection, that enable us to identify and isolate structures associated with different weights. One such mesoscale structure is bipartivity, which quantifies the extent to which the brain is divided into two partitions with high connectivity between partitions and low connectivity within partitions. A second, complementary mesoscale structure is modularity, which quantifies the extent to which the brain is divided into multiple communities with strong connectivity within each community and weak connectivity between communities. Our methods lead to multi-resolution curves of these network diagnostics over a range of spatial, geometric, and structural scales. For statistical comparison, we contrast our results with those obtained for several benchmark null models. Our work demonstrates that multi-resolution diagnostic curves capture complex organizational profiles in weighted graphs. We apply these methods to the identification of resolution-specific characteristics of healthy weighted graph architecture and altered connectivity profiles in psychiatric disease.

  6. Neural network plasticity in the human brain

    OpenAIRE

    Rizk, Sviatlana

    2013-01-01

    The human brain is highly organized within networks. Functionally related neural-assemblies communicate by oscillating synchronously. Intrinsic brain activity contains information on healthy and damaged brain functioning. This thesis investigated the relationship between functional networks and behavior. Furthermore, we assessed functional network plasticity after brain damage and as a result of brain stimulation. In different groups of patients we observed reduced functional connectivity bet...

  7. Network science and the effects of music preference on functional brain connectivity: from Beethoven to Eminem.

    Science.gov (United States)

    Wilkins, R W; Hodges, D A; Laurienti, P J; Steen, M; Burdette, J H

    2014-01-01

    Most people choose to listen to music that they prefer or 'like' such as classical, country or rock. Previous research has focused on how different characteristics of music (i.e., classical versus country) affect the brain. Yet, when listening to preferred music--regardless of the type--people report they often experience personal thoughts and memories. To date, understanding how this occurs in the brain has remained elusive. Using network science methods, we evaluated differences in functional brain connectivity when individuals listened to complete songs. We show that a circuit important for internally-focused thoughts, known as the default mode network, was most connected when listening to preferred music. We also show that listening to a favorite song alters the connectivity between auditory brain areas and the hippocampus, a region responsible for memory and social emotion consolidation. Given that musical preferences are uniquely individualized phenomena and that music can vary in acoustic complexity and the presence or absence of lyrics, the consistency of our results was unexpected. These findings may explain why comparable emotional and mental states can be experienced by people listening to music that differs as widely as Beethoven and Eminem. The neurobiological and neurorehabilitation implications of these results are discussed. PMID:25167363

  8. Different topological organization of human brain functional networks with eyes open versus eyes closed.

    Science.gov (United States)

    Xu, Pengfei; Huang, Ruiwang; Wang, Jinhui; Van Dam, Nicholas T; Xie, Teng; Dong, Zhangye; Chen, Chunping; Gu, Ruolei; Zang, Yu-Feng; He, Yong; Fan, Jin; Luo, Yue-jia

    2014-04-15

    Opening and closing the eyes are fundamental behaviors for directing attention to the external versus internal world. However, it remains unclear whether the states of eyes-open (EO) relative to eyes-closed (EC) are associated with different topological organizations of functional neural networks for exteroceptive and interoceptive processing (processing the external world and internal state, respectively). Here, we used resting-state functional magnetic resonance imaging and neural network analysis to investigate the topological properties of functional networks of the human brain when the eyes were open versus closed. The brain networks exhibited higher cliquishness and local efficiency, but lower global efficiency during the EO state compared to the EC state. These properties suggest an increase in specialized information processing along with a decrease in integrated information processing in EO (vs. EC). More importantly, the "exteroceptive" network, including the attentional system (e.g., superior parietal gyrus and inferior parietal lobule), ocular motor system (e.g., precentral gyrus and superior frontal gyrus), and arousal system (e.g., insula and thalamus), showed higher regional nodal properties (nodal degree, efficiency and betweenness centrality) in EO relative to EC. In contrast, the "interoceptive" network, composed of visual system (e.g., lingual gyrus, fusiform gyrus and cuneus), auditory system (e.g., Heschl's gyurs), somatosensory system (e.g., postcentral gyrus), and part of the default mode network (e.g., angular gyrus and anterior cingulate gyrus), showed significantly higher regional properties in EC vs. EO. In addition, the connections across sensory modalities were altered by volitional eye opening. The synchronicity between the visual system and the motor, somatosensory and auditory systems, characteristic of EC, was attenuated in EO. Further, the connections between the visual system and the attention, arousal and subcortical systems were

  9. Resting-state EEG oscillatory dynamics in fragile X syndrome: abnormal functional connectivity and brain network organization.

    Directory of Open Access Journals (Sweden)

    Melle J W van der Molen

    Full Text Available Disruptions in functional connectivity and dysfunctional brain networks are considered to be a neurological hallmark of neurodevelopmental disorders. Despite the vast literature on functional brain connectivity in typical brain development, surprisingly few attempts have been made to characterize brain network integrity in neurodevelopmental disorders. Here we used resting-state EEG to characterize functional brain connectivity and brain network organization in eight males with fragile X syndrome (FXS and 12 healthy male controls. Functional connectivity was calculated based on the phase lag index (PLI, a non-linear synchronization index that is less sensitive to the effects of volume conduction. Brain network organization was assessed with graph theoretical analysis. A decrease in global functional connectivity was observed in FXS males for upper alpha and beta frequency bands. For theta oscillations, we found increased connectivity in long-range (fronto-posterior and short-range (frontal-frontal and posterior-posterior clusters. Graph theoretical analysis yielded evidence of increased path length in the theta band, suggesting that information transfer between brain regions is particularly impaired for theta oscillations in FXS. These findings are discussed in terms of aberrant maturation of neuronal oscillatory dynamics, resulting in an imbalance in excitatory and inhibitory neuronal circuit activity.

  10. Brain Functional Effects of Psychopharmacological Treatments in Schizophrenia: A Network-based Functional Perspective Beyond Neurotransmitter Systems.

    Science.gov (United States)

    De Rossi, Pietro; Chiapponi, Chiara; Spalletta, Gianfranco

    2015-01-01

    Psychopharmacological treatments for schizophrenia have always been a matter of debate and a very important issue in public health given the chronic, relapsing and disabling nature of the disorder. A thorough understanding of the pros and cons of currently available pharmacological treatments for schizophrenia is critical to better capture the features of treatment-refractory clinical pictures and plan the developing of new treatment strategies. This review focuses on brain functional changes induced by antipsychotic drugs as assessed by modern functional neuroimaging techniques (i.e. fMRI, PET, SPECT, MRI spectroscopy). The most important papers on this topic are reviewed in order to draw an ideal map of the main functional changes occurring in the brain during antipsychotic treatment. This supports the hypothesis that a network-based perspective and a functional connectivity approach are needed to fill the currently existing gap of knowledge in the field of psychotropic drugs and their mechanisms of action beyond neurotransmitter systems. PMID:26412063

  11. Hyperthermia-induced disruption of functional connectivity in the human brain network.

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    Gang Sun

    Full Text Available BACKGROUND: Passive hyperthermia is a potential risk factor to human cognitive performance and work behavior in many extreme work environments. Previous studies have demonstrated significant effects of passive hyperthermia on human cognitive performance and work behavior. However, there is a lack of a clear understanding of the exact affected brain regions and inter-regional connectivities. METHODOLOGY AND PRINCIPAL FINDINGS: We simulated 1 hour environmental heat exposure to thirty-six participants under two environmental temperature conditions (25 °C and 50 °C, and collected resting-state functional brain activity. The functional connectivities with a preselected region of interest (ROI in the posterior cingulate cortex and precuneus (PCC/PCu, furthermore, inter-regional connectivities throughout the entire brain using a prior Anatomical Automatic Labeling (AAL atlas were calculated. We identified decreased correlations of a set of regions with the PCC/PCu, including the medial orbitofrontal cortex (mOFC and bilateral medial temporal cortex, as well as increased correlations with the partial orbitofrontal cortex particularly in the bilateral orbital superior frontal gyrus. Compared with the normal control (NC group, the hyperthermia (HT group showed 65 disturbed functional connectivities with 50 of them being decreased and 15 of them being increased. While the decreased correlations mainly involved with the mOFC, temporal lobe and occipital lobe, increased correlations were mainly located within the limbic system. In consideration of physiological system changes, we explored the correlations of the number of significantly altered inter-regional connectivities with differential rectal temperatures and weight loss, but failed to obtain significant correlations. More importantly, during the attention network test (ANT we found that the number of significantly altered functional connectivities was positively correlated with an increase in

  12. Brain functional network changes following Prelimbic area inactivation in a spatial memory extinction task.

    Science.gov (United States)

    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. PMID:25813749

  13. Analysis of CT Brain Images using Radial Basis Function Neural Network

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    T. Joshva Devadas

    2012-07-01

    Full Text Available Medical image processing and analysis is the tool to assist radiologists in the diagnosis process to obtain a more accurate and faster diagnosis. In this work, we have developed a neural network to classify the computer tomography (CT brain tumor image for automatic diagnosis. This system is divided into four steps namely enhancement, segmentation, feature extraction and classification. In the first phase, an edge-based selective median filter is used to improve the visibility of the loss of the gray-white matter interface in CT brain tumor images. Second phase uses a modified version of shift genetic algorithm for the segmentation. Next phase extracts the textural features using statistical texture analysis method. These features are fed into classifiers like BPN, Fuzzy k-NN, and radial basis function network. The performances of these classifiers are analyzed in the final phase with receiver operating characteristic and precision-recall curve. The result shows that the CAD system is only to develop the tool for brain tumor and proposed method is very accurate and computationally more efficient and less time consuming.

  14. Extrasynaptic neurotransmission in the modulation of brain function. Focus on the striatal neuronal-glial networks

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    Kjell eFuxe

    2012-06-01

    Full Text Available Extrasynaptic neurotransmission is an important short distance form of volume transmission (VT and describes the extracellular diffusion of transmitters and modulators after synaptic spillover or extrasynaptic release in the local circuit regions binding to and activating mainly extrasynaptic neuronal and glial receptors in the neuroglial networks of the brain. Receptor-receptor interactions in G protein-coupled receptor (GPCR heteromers play a major role, on dendritic spines and nerve terminals including glutamate synapses, in the integrative processes of the extrasynaptic signaling. Heteromeric complexes between GPCR and ion-channel receptors play a special role in the integration of the synaptic and extrasynaptic signals. Changes in extracellular concentrations of the classical synaptic neurotransmitters glutamate and GABA found with microdialysis is likely an expression of the activity of the neuron-astrocyte unit of the brain and can be used as an index of VT-mediated actions of these two neurotransmitters in the brain. Thus, the activity of neurons may be functionally linked to the activity of astrocytes, which may release glutamate and GABA to the extracellular space where extrasynaptic glutamate and GABA receptors do exist. Wiring transmission (WT and VT are fundamental properties of all neurons of the CNS but the balance between WT and VT varies from one nerve cell population to the other. The focus is on the striatal cellular networks, and the WT and VT and their integration via receptor heteromers are described in the GABA projection neurons, the glutamate, dopamine, 5-hydroxytryptamine (5-HT and histamine striatal afferents, the cholinergic interneurons and different types of GABA interneurons. In addition, the role in these networks of VT signaling of the energy-dependent modulator adenosine and of endocannabinoids mainly formed in the striatal projection neurons will be underlined to understand the communication in the striatal

  15. The effect of epoch length on estimated EEG functional connectivity and brain network organisation

    Science.gov (United States)

    Fraschini, Matteo; Demuru, Matteo; Crobe, Alessandra; Marrosu, Francesco; Stam, Cornelis J.; Hillebrand, Arjan

    2016-06-01

    Objective. Graph theory and network science tools have revealed fundamental mechanisms of functional brain organization in resting-state M/EEG analysis. Nevertheless, it is still not clearly understood how several methodological aspects may bias the topology of the reconstructed functional networks. In this context, the literature shows inconsistency in the chosen length of the selected epochs, impeding a meaningful comparison between results from different studies. Approach. The aim of this study was to provide a network approach insensitive to the effects that epoch length has on functional connectivity and network reconstruction. Two different measures, the phase lag index (PLI) and the amplitude envelope correlation (AEC) were applied to EEG resting-state recordings for a group of 18 healthy volunteers using non-overlapping epochs with variable length (1, 2, 4, 6, 8, 10, 12, 14 and 16 s). Weighted clustering coefficient (CCw), weighted characteristic path length (L w) and minimum spanning tree (MST) parameters were computed to evaluate the network topology. The analysis was performed on both scalp and source-space data. Main results. Results from scalp analysis show a decrease in both mean PLI and AEC values with an increase in epoch length, with a tendency to stabilize at a length of 12 s for PLI and 6 s for AEC. Moreover, CCw and L w show very similar behaviour, with metrics based on AEC more reliable in terms of stability. In general, MST parameters stabilize at short epoch lengths, particularly for MSTs based on PLI (1–6 s versus 4–8 s for AEC). At the source-level the results were even more reliable, with stability already at 1 s duration for PLI-based MSTs. Significance. The present work suggests that both PLI and AEC depend on epoch length and that this has an impact on the reconstructed network topology, particularly at the scalp-level. Source-level MST topology is less sensitive to differences in epoch length, therefore enabling the comparison of

  16. Epigenetics, stress and their potential impact on brain network function: A focus on the schizophrenia diatheses

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    Vaibhav A. Diwadkar

    2014-06-01

    Full Text Available The recent sociodevelopmental cognitive model of schizophrenia/psychosis is a highly influential and compelling compendium of research findings. Here we present logical extensions to this model incorporating ideas drawn from epigenetic mediation of psychiatric disease, and the plausible effects of epigenetics on the emergence of brain network function and dysfunction in adolescence. We discuss how gene-environment interactions, effected by epigenetic mechanisms, might in particular mediate the stress response (itself heavily implicated in the emergence of schizophrenia. Next, we discuss the plausible relevance of this framework for adolescent genetic risk populations, a risk group characterized by vexing and difficult-to-explain heterogeneity. We then discuss how exploring relationships between epigenetics and brain network dysfunction (a strongly validated finding in risk populations can enhance understanding of the relationship between stress, epigenetics and functional neurobiology, and the relevance of this relationship for the eventual emergence of schizophrenia/psychosis. We suggest that these considerations can expand the impact of models such as the sociodevelopmental cognitive model, increasing their explanatory reach. Ultimately, integration of these lines of research may enhance efforts of early identification, intervention and treatment in adolescents at risk for schizophrenia.

  17. Brain functional network connectivity based on a visual task: visual information processing-related brain regions are significantly activated in the task state

    Directory of Open Access Journals (Sweden)

    Yan-li Yang

    2015-01-01

    Full Text Available It is not clear whether the method used in functional brain-network related research can be applied to explore the feature binding mechanism of visual perception. In this study, we investigated feature binding of color and shape in visual perception. Functional magnetic resonance imaging data were collected from 38 healthy volunteers at rest and while performing a visual perception task to construct brain networks active during resting and task states. Results showed that brain regions involved in visual information processing were obviously activated during the task. The components were partitioned using a greedy algorithm, indicating the visual network existed during the resting state. Z-values in the vision-related brain regions were calculated, confirming the dynamic balance of the brain network. Connectivity between brain regions was determined, and the result showed that occipital and lingual gyri were stable brain regions in the visual system network, the parietal lobe played a very important role in the binding process of color features and shape features, and the fusiform and inferior temporal gyri were crucial for processing color and shape information. Experimental findings indicate that understanding visual feature binding and cognitive processes will help establish computational models of vision, improve image recognition technology, and provide a new theoretical mechanism for feature binding in visual perception.

  18. Functional Brain Networks Are Altered in Type 2 Diabetes and Prediabetes: Signs for Compensation of Cognitive Decrements? The Maastricht Study.

    Science.gov (United States)

    van Bussel, Frank C G; Backes, Walter H; van Veenendaal, Tamar M; Hofman, Paul A M; van Boxtel, Martin P J; Schram, Miranda T; Sep, Simone J S; Dagnelie, Pieter C; Schaper, Nicolaas; Stehouwer, Coen D A; Wildberger, Joachim E; Jansen, Jacobus F A

    2016-08-01

    Type 2 diabetes is associated with cognitive decrements, accelerated cognitive decline, and increased risk for dementia. Patients with the metabolic syndrome, a major risk factor for diabetes, may display comparable cognitive decrements as seen in type 2 diabetes. Currently, the impact of diabetes and prediabetes on cognition and the underlying organization of functional brain networks still remain to be elucidated. This study investigated whether functional brain networks are affected in type 2 diabetes and prediabetes. Forty-seven participants with diabetes, 47 participants with prediabetes, and 45 control participants underwent detailed cognitive testing and 3-Tesla resting state functional MRI. Graph theoretical network analysis was performed to investigate alterations in functional cerebral networks. Participants with diabetes displayed altered network measures, characterized by a higher normalized cluster coefficient and higher local efficiency, compared with control participants. The network measures of the participants with prediabetes fell between those with diabetes and control participants. Lower processing speed was associated with shorter path length and higher global efficiency. Participants with type 2 diabetes have altered functional brain networks. This alteration is already apparent in the prediabetic stage to a somewhat lower level, hinting at functional reorganization of the cerebral networks as a compensatory mechanism for cognitive decrements. PMID:27217484

  19. The role of nonlinearity in computing graph-theoretical properties of resting-state functional magnetic resonance imaging brain networks

    OpenAIRE

    Hartman, D.; Hlinka, J.; Paluš, M.; Mantini, D.; Corbetta, M.

    2011-01-01

    In recent years, there has been an increasing interest in the study of large-scale brain activity interaction structure from the perspective of complex networks, based on functional magnetic resonance imaging (fMRI) measurements. To assess the strength of interaction (functional connectivity, FC) between two brain regions, the linear (Pearson) correlation coefficient of the respective time series is most commonly used. Since a potential use of nonlinear FC measures has recently been discussed...

  20. Modulation of large-scale brain networks by transcranial direct current stimulation evidenced by resting-state functional MRI

    Science.gov (United States)

    Peña-Gómez, Cleofé; Sala-Lonch, Roser; Junqué, Carme; Clemente, Immaculada C.; Vidal, Dídac; Bargalló, Núria; Falcón, Carles; Valls-Solé, Josep; Pascual-Leone, Álvaro; Bartrés-Faz, David

    2013-01-01

    Background Brain areas interact mutually to perform particular complex brain functions such as memory or language. Furthermore, under resting-state conditions several spatial patterns have been identified that resemble functional systems involved in cognitive functions. Among these, the default-mode network (DMN), which is consistently deactivated during task periods and is related to a variety of cognitive functions, has attracted most attention. In addition, in resting-state conditions some brain areas engaged in focused attention (such as the anticorrelated network, AN) show a strong negative correlation with DMN; as task demand increases, AN activity rises, and DMN activity falls. Objective We combined transcranial direct current stimulation (tDCS) with functional magnetic resonance imaging (fMRI) to investigate these brain network dynamics. Methods Ten healthy young volunteers underwent four blocks of resting-state fMRI (10-minutes), each of them immediately after 20 minutes of sham or active tDCS (2 mA), on two different days. On the first day the anodal electrode was placed over the left dorsolateral prefrontal cortex (DLPFC) (part of the AN) with the cathode over the contralateral supraorbital area, and on the second day, the electrode arrangement was reversed (anode right-DLPFC, cathode left-supraorbital). Results After active stimulation, functional network connectivity revealed increased synchrony within the AN components and reduced synchrony in the DMN components. Conclusions Our study reveals a reconfiguration of intrinsic brain activity networks after active tDCS. These effects may help to explain earlier reports of improvements in cognitive functions after anodal-tDCS, where increasing cortical excitability may have facilitated reconfiguration of functional brain networks to address upcoming cognitive demands. PMID:21962981

  1. Analyzing topological characteristics of neuronal functional networks in the rat brain

    International Nuclear Information System (INIS)

    In this study, we recorded spike trains from brain cortical neurons of several behavioral rats in vivo by using multi-electrode recordings. An NFN was constructed in each trial, obtaining a total of 150 NFNs in this study. The topological characteristics of NFNs were analyzed by using the two most important characteristics of complex networks, namely, small-world structure and community structure. We found that the small-world properties exist in different NFNs constructed in this study. Modular function Q was used to determine the existence of community structure in NFNs, through which we found that community-structure characteristics, which are related to recorded spike train data sets, are more evident in the Y-maze task than in the DM-GM task. Our results can also be used to analyze further the relationship between small-world characteristics and the cognitive behavioral responses of rats. - Highlights: • We constructed the neuronal function networks based on the recorded neurons. • We analyzed the two main complex network characteristics, namely, small-world structure and community structure. • NFNs which were constructed based on the recorded neurons in this study exhibit small-world properties. • Some NFNs have community structure characteristics

  2. Analyzing topological characteristics of neuronal functional networks in the rat brain

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Hu [School of Computer Science and Communication Engineering, Jiangsu University, Jiangsu 212003 (China); School of Computer Science, Fudan University, Shanghai 200433 (China); Yang, Shengtao [Institutes of Brain Science, Fudan University, Shanghai 200433 (China); Song, Yuqing [School of Computer Science and Communication Engineering, Jiangsu University, Jiangsu 212003 (China); Wei, Hui [School of Computer Science, Fudan University, Shanghai 200433 (China)

    2014-08-28

    In this study, we recorded spike trains from brain cortical neurons of several behavioral rats in vivo by using multi-electrode recordings. An NFN was constructed in each trial, obtaining a total of 150 NFNs in this study. The topological characteristics of NFNs were analyzed by using the two most important characteristics of complex networks, namely, small-world structure and community structure. We found that the small-world properties exist in different NFNs constructed in this study. Modular function Q was used to determine the existence of community structure in NFNs, through which we found that community-structure characteristics, which are related to recorded spike train data sets, are more evident in the Y-maze task than in the DM-GM task. Our results can also be used to analyze further the relationship between small-world characteristics and the cognitive behavioral responses of rats. - Highlights: • We constructed the neuronal function networks based on the recorded neurons. • We analyzed the two main complex network characteristics, namely, small-world structure and community structure. • NFNs which were constructed based on the recorded neurons in this study exhibit small-world properties. • Some NFNs have community structure characteristics.

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

    OpenAIRE

    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 correla...

  4. Analysis of CT Brain Images using Radial Basis Function Neural Network

    Directory of Open Access Journals (Sweden)

    T. Joshva Devadas

    2012-07-01

    Full Text Available Medical image processing and analysis is the tool to assist radiologists in the diagnosis process to obtain a moreaccurate and faster diagnosis. In this work, we have developed a neural network to classify the computer tomography(CT brain tumor image for automatic diagnosis. This system is divided into four steps namely enhancement, segmentation, feature extraction and classification. In the first phase, an edge-based selective median filter is usedto improve the visibility of the loss of the gray-white matter interface in CT brain tumor images. Second phaseuses a modified version of shift genetic algorithm for the segmentation. Next phase extracts the textural featuresusing statistical texture analysis method. These features are fed into classifiers like BPN, Fuzzy k-NN, and radialbasis function network. The performances of these classifiers are analyzed in the final phase with receiver operating characteristic and precision-recall curve. The result shows that the CAD system is only to develop the tool for braintumor and proposed method is very accurate and computationally more efficient and less time consuming.Defence Science Journal, 2012, 62(4, pp.212-218, DOI:http://dx.doi.org/10.14429/dsj.62.1830

  5. Functional mapping of language networks in the normal brain using a word-association task

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    Ghosh Shantanu

    2010-01-01

    Full Text Available Background: Language functions are known to be affected in diverse neurological conditions, including ischemic stroke, traumatic brain injury, and brain tumors. Because language networks are extensive, interpretation of functional data depends on the task completed during evaluation. Aim: The aim was to map the hemodynamic consequences of word association using functional magnetic resonance imaging (fMRI in normal human subjects. Materials and Methods: Ten healthy subjects underwent fMRI scanning with a postlexical access semantic association task vs lexical processing task. The fMRI protocol involved a T2FNx01-weighted gradient-echo echo-planar imaging (GE-EPI sequence (TR 4523 ms, TE 64 ms, flip angle 90º with alternate baseline and activation blocks. A total of 78 scans were taken (interscan interval = 3 s with a total imaging time of 587 s. Functional data were processed in Statistical Parametric Mapping software (SPM2 with 8-mm Gaussian kernel by convolving the blood oxygenation level-dependent (BOLD signal with an hemodynamic response function estimated by general linear method to generate SPM{t} and SPM{F} maps. Results: Single subject analysis of the functional data (FWE-corrected, P≤0.001 revealed extensive activation in the frontal lobes, with overlaps among middle frontal gyrus (MFG, superior, and inferior frontal gyri. BOLD activity was also found in the medial frontal gyrus, middle occipital gyrus (MOG, anterior fusiform gyrus, superior and inferior parietal lobules, and to a smaller extent, the thalamus and right anterior cerebellum. Group analysis (FWE-corrected, P≤0.001 revealed neural recruitment of bilateral lingual gyri, left MFG, bilateral MOG, left superior occipital gyrus, left fusiform gyrus, bilateral thalami, and right cerebellar areas. Conclusions: Group data analysis revealed a cerebellar-occipital-fusiform-thalamic network centered around bilateral lingual gyri for word association, thereby indicating how these

  6. Functional mapping of language networks in the normal brain using a word-association task

    International Nuclear Information System (INIS)

    Language functions are known to be affected in diverse neurological conditions, including ischemic stroke, traumatic brain injury, and brain tumors. Because language networks are extensive, interpretation of functional data depends on the task completed during evaluation. The aim was to map the hemodynamic consequences of word association using functional magnetic resonance imaging (fMRI) in normal human subjects. Ten healthy subjects underwent fMRI scanning with a postlexical access semantic association task vs lexical processing task. The fMRI protocol involved a T2*-weighted gradient-echo echo-planar imaging (GE-EPI) sequence (TR 4523 ms, TE 64 ms, flip angle 90°) with alternate baseline and activation blocks. A total of 78 scans were taken (interscan interval = 3 s) with a total imaging time of 587 s. Functional data were processed in Statistical Parametric Mapping software (SPM2) with 8-mm Gaussian kernel by convolving the blood oxygenation level-dependent (BOLD) signal with an hemodynamic response function estimated by general linear method to generate SPM{t} and SPM{F} maps. Single subject analysis of the functional data (FWE-corrected, P≤0.001) revealed extensive activation in the frontal lobes, with overlaps among middle frontal gyrus (MFG), superior, and inferior frontal gyri. BOLD activity was also found in the medial frontal gyrus, middle occipital gyrus (MOG), anterior fusiform gyrus, superior and inferior parietal lobules, and to a smaller extent, the thalamus and right anterior cerebellum. Group analysis (FWE-corrected, P≤0.001) revealed neural recruitment of bilateral lingual gyri, left MFG, bilateral MOG, left superior occipital gyrus, left fusiform gyrus, bilateral thalami, and right cerebellar areas. Group data analysis revealed a cerebellar–occipital–fusiform–thalamic network centered around bilateral lingual gyri for word association, thereby indicating how these areas facilitate language comprehension by activating a semantic

  7. Frequency-specific Alterations of Large-scale Functional Brain Networks in Patients with Alzheimer's Disease

    Institute of Scientific and Technical Information of China (English)

    Yuan-Yuan Qin; Ya-Peng Li; Shun Zhang; Ying Xiong; Lin-Ying Guo; Shi-Qi Yang; Yi-Hao Yao

    2015-01-01

    Background:Previous studies have indicated that the cognitive deficits in patients with Alzheimer's disease (AD) may be due to topological deteriorations of the brain network.However,whether the selection of a specific frequency band could impact the topological properties is still not clear.Our hypothesis is that the topological properties of AD patients are also frequency-specific.Methods:Resting state functional magnetic resonance imaging data from l0 right-handed moderate AD patients (mean age:64.3 years; mean mini mental state examination [MMSE]:18.0) and 10 age and gender-matched healthy controls (mean age:63.6 years; mean MMSE:28.2) were enrolled in this study.The global efficiency,the clustering coefficient (CC),the characteristic path length (CpL),and "small-world" property were calculated in a wide range of thresholds and averaged within each group,at three different frequency bands (0.01-0.06 Hz,0.06-0.11 Hz,and 0.11-0.25 Hz).Results:At lower-frequency bands (0.01-0.06 Hz,0.06-0.11 Hz),the global efficiency,the CC and the "small-world" properties of AD patients decreased compared to controls.While at higher-frequency bands (0.11-0.25 Hz),the CpL was much longer,and the "small-world" property was disrupted in AD,particularly at a higher threshold.The topological properties changed with different frequency bands,suggesting the existence of disrupted global and local functional organization associated with AD.Conclusions:This study demonstrates that the topological alterations of large-scale functional brain networks inAD patients are frequency dependent,thus providing fundamental support for optimal frequency selection in future related research.

  8. Abnormal brain default-mode network functional connectivity in drug addicts.

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    Ning Ma

    Full Text Available BACKGROUND: The default mode network (DMN is a set of brain regions that exhibit synchronized low frequency oscillations at resting-state, and is believed to be relevant to attention and self-monitoring. As the anterior cingulate cortex and hippocampus are impaired in drug addiction and meanwhile are parts of the DMN, the present study examined addiction-related alteration of functional connectivity of the DMN. METHODOLOGY: Resting-state functional magnetic resonance imaging data of chronic heroin users (14 males, age: 30.1±5.3 years, range from 22 to 39 years and non-addicted controls (13 males, age: 29.8±7.2 years, range from 20 to 39 years were investigated with independent component analysis to address their functional connectivity of the DMN. PRINCIPAL FINDINGS: Compared with controls, heroin users showed increased functional connectivity in right hippocampus and decreased functional connectivity in right dorsal anterior cingulate cortex and left caudate in the DMN. CONCLUSIONS: These findings suggest drug addicts' abnormal functional organization of the DMN, and are discussed as addiction-related abnormally increased memory processing but diminished cognitive control related to attention and self-monitoring, which may underlie the hypersensitivity toward drug related cues but weakened strength of cognitive control in the state of addiction.

  9. Properties of functional brain networks correlate with frequency of psychogenic non-epileptic seizures.

    Science.gov (United States)

    Barzegaran, Elham; Joudaki, Amir; Jalili, Mahdi; Rossetti, Andrea O; Frackowiak, Richard S; Knyazeva, Maria G

    2012-01-01

    Abnormalities in the topology of brain networks may be an important feature and etiological factor for psychogenic non-epileptic seizures (PNES). To explore this possibility, we applied a graph theoretical approach to functional networks based on resting state EEGs from 13 PNES patients and 13 age- and gender-matched controls. The networks were extracted from Laplacian-transformed time-series by a cross-correlation method. PNES patients showed close to normal local and global connectivity and small-world structure, estimated with clustering coefficient, modularity, global efficiency, and small-worldness (SW) metrics, respectively. Yet the number of PNES attacks per month correlated with a weakness of local connectedness and a skewed balance between local and global connectedness quantified with SW, all in EEG alpha band. In beta band, patients demonstrated above-normal resiliency, measured with assortativity coefficient, which also correlated with the frequency of PNES attacks. This interictal EEG phenotype may help improve differentiation between PNES and epilepsy. The results also suggest that local connectivity could be a target for therapeutic interventions in PNES. Selective modulation (strengthening) of local connectivity might improve the skewed balance between local and global connectivity and so prevent PNES events. PMID:23267325

  10. Properties of functional brain networks correlate frequency of psychogenic non-epileptic seizures

    Directory of Open Access Journals (Sweden)

    Elham eBarzegaran

    2012-12-01

    Full Text Available Abnormalities in the topology of brain networks may be an important feature and etiological factor for psychogenic non-epileptic seizures (PNES. To explore this possibility, we applied a graph theoretical approach to functional networks based on resting state EEGs from 13 PNES patients and 13 age- and gender-matched controls. The networks were extracted from Laplacian-transformed time-series by a cross-correlation method. PNES patients showed close to normal local and global connectivity and small-world structure, estimated with clustering coefficient, modularity, global efficiency, and small-worldness metrics, respectively. Yet the number of PNES attacks per month correlated with a weakness of local connectedness and a skewed balance between local and global connectedness quantified with small-worldness, all in EEG alpha band. In beta band, patients demonstrated above-normal resiliency, measured with assortativity coefficient, which also correlated with the frequency of PNES attacks. This interictal EEG phenotype may help improve differentiation between PNES and epilepsy. The results also suggest that local connectivity could be a target for therapeutic interventions in PNES. Selective modulation (strengthening of local connectivity might improve the skewed balance between local and global connectivity and so prevent PNES events.

  11. Voxel Scale Complex Networks of Functional Connectivity in the Rat Brain: Neurochemical State Dependence of Global and Local Topological Properties

    Directory of Open Access Journals (Sweden)

    Adam J. Schwarz

    2012-01-01

    Full Text Available Network analysis of functional imaging data reveals emergent features of the brain as a function of its topological properties. However, the brain is not a homogeneous network, and the dependence of functional connectivity parameters on neuroanatomical substrate and parcellation scale is a key issue. Moreover, the extent to which these topological properties depend on underlying neurochemical changes remains unclear. In the present study, we investigated both global statistical properties and the local, voxel-scale distribution of connectivity parameters of the rat brain. Different neurotransmitter systems were stimulated by pharmacological challenge (d-amphetamine, fluoxetine, and nicotine to discriminate between stimulus-specific functional connectivity and more general features of the rat brain architecture. Although global connectivity parameters were similar, mapping of local connectivity parameters at high spatial resolution revealed strong neuroanatomical dependence of functional connectivity in the rat brain, with clear differentiation between the neocortex and older brain regions. Localized foci of high functional connectivity independent of drug challenge were found in the sensorimotor cortices, consistent with the high neuronal connectivity in these regions. Conversely, the topological properties and node roles in subcortical regions varied with neurochemical state and were dependent on the specific dynamics of the different functional processes elicited.

  12. MRI Study on the Functional and Spatial Consistency of Resting State-Related Independent Components of the Brain Network

    Energy Technology Data Exchange (ETDEWEB)

    Jeong, Bum Seok [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Choi, Jee Wook [Daejeon St. Mary' s Hospital, The Catholic University of Korea College of Medicine, Daejeon (Korea, Republic of); Kim, Ji Woong [College of Medical Science, Konyang University, Daejeon(Korea, Republic of)

    2012-06-15

    Resting-state networks (RSNs), including the default mode network (DMN), have been considered as markers of brain status such as consciousness, developmental change, and treatment effects. The consistency of functional connectivity among RSNs has not been fully explored, especially among resting-state-related independent components (RSICs). This resting-state fMRI study addressed the consistency of functional connectivity among RSICs as well as their spatial consistency between 'at day 1' and 'after 4 weeks' in 13 healthy volunteers. We found that most RSICs, especially the DMN, are reproducible across time, whereas some RSICs were variable in either their spatial characteristics or their functional connectivity. Relatively low spatial consistency was found in the basal ganglia, a parietal region of left frontoparietal network, and the supplementary motor area. The functional connectivity between two independent components, the bilateral angular/supramarginal gyri/intraparietal lobule and bilateral middle temporal/occipital gyri, was decreased across time regardless of the correlation analysis method employed, (Pearson's or partial correlation). RSICs showing variable consistency are different between spatial characteristics and functional connectivity. To understand the brain as a dynamic network, we recommend further investigation of both changes in the activation of specific regions and the modulation of functional connectivity in the brain network.

  13. MRI Study on the Functional and Spatial Consistency of Resting State-Related Independent Components of the Brain Network

    International Nuclear Information System (INIS)

    Resting-state networks (RSNs), including the default mode network (DMN), have been considered as markers of brain status such as consciousness, developmental change, and treatment effects. The consistency of functional connectivity among RSNs has not been fully explored, especially among resting-state-related independent components (RSICs). This resting-state fMRI study addressed the consistency of functional connectivity among RSICs as well as their spatial consistency between 'at day 1' and 'after 4 weeks' in 13 healthy volunteers. We found that most RSICs, especially the DMN, are reproducible across time, whereas some RSICs were variable in either their spatial characteristics or their functional connectivity. Relatively low spatial consistency was found in the basal ganglia, a parietal region of left frontoparietal network, and the supplementary motor area. The functional connectivity between two independent components, the bilateral angular/supramarginal gyri/intraparietal lobule and bilateral middle temporal/occipital gyri, was decreased across time regardless of the correlation analysis method employed, (Pearson's or partial correlation). RSICs showing variable consistency are different between spatial characteristics and functional connectivity. To understand the brain as a dynamic network, we recommend further investigation of both changes in the activation of specific regions and the modulation of functional connectivity in the brain network.

  14. Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI.

    Science.gov (United States)

    Xu, Tingting; Cullen, Kathryn R; Mueller, Bryon; Schreiner, Mindy W; Lim, Kelvin O; Schulz, S Charles; Parhi, Keshab K

    2016-01-01

    Borderline personality disorder (BPD) is associated with symptoms such as affect dysregulation, impaired sense of self, and self-harm behaviors. Neuroimaging research on BPD has revealed structural and functional abnormalities in specific brain regions and connections. However, little is known about the topological organizations of brain networks in BPD. We collected resting-state functional magnetic resonance imaging (fMRI) data from 20 patients with BPD and 10 healthy controls, and constructed frequency-specific functional brain networks by correlating wavelet-filtered fMRI signals from 82 cortical and subcortical regions. We employed graph-theory based complex network analysis to investigate the topological properties of the brain networks, and employed network-based statistic to identify functional dysconnections in patients. In the 0.03-0.06 Hz frequency band, compared to controls, patients with BPD showed significantly larger measures of global network topology, including the size of largest connected graph component, clustering coefficient, small-worldness, and local efficiency, indicating increased local cliquishness of the functional brain network. Compared to controls, patients showed lower nodal centrality at several hub nodes but greater centrality at several non-hub nodes in the network. Furthermore, an interconnected subnetwork in 0.03-0.06 Hz frequency band was identified that showed significantly lower connectivity in patients. The links in the subnetwork were mainly long-distance connections between regions located at different lobes; and the mean connectivity of this subnetwork was negatively correlated with the increased global topology measures. Lastly, the key network measures showed high correlations with several clinical symptom scores, and classified BPD patients against healthy controls with high accuracy based on linear discriminant analysis. The abnormal topological properties and connectivity found in this study may add new knowledge

  15. Whole-brain analytic measures of network communication reveal increased structure-function correlation in right temporal lobe epilepsy

    Directory of Open Access Journals (Sweden)

    Jonathan Wirsich

    2016-01-01

    In rTLE patients, we found a widespread hypercorrelated functional network. Network communication analysis revealed greater unspecific branching of the shortest path (search information in the structural connectome and a higher global correlation between the structural and functional connectivity for the patient group. We also found evidence for a preserved structural rich-club in the patient group. In sum, global augmentation of structure-function correlation might be linked to a smaller functional repertoire in rTLE patients, while sparing the central core of the brain which may represent a pathway that facilitates the spread of seizures.

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

    Directory of Open Access Journals (Sweden)

    Xia Liang

    Full Text Available 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

  17. Multilayer motif analysis of brain networks

    OpenAIRE

    Battiston, Federico; Nicosia, Vincenzo; Chavez, Mario; Latora, Vito

    2016-01-01

    In the last decade network science has shed new light on the anatomical connectivity and on correlations in the activity of different areas of the human brain. The study of brain networks has made possible in fact to detect the central areas of a neural system, and to identify its building blocks by looking at overabundant small subgraphs, known as motifs. However, network analysis of the brain has so far mainly focused on structural and functional networks as separate entities. The recently ...

  18. Immunity factor contributes to altered brain functional networks in individuals at risk for Alzheimer's disease: Neuroimaging-genetic evidence.

    Science.gov (United States)

    Bai, Feng; Shi, Yongmei; Yuan, Yonggui; Xie, Chunming; Zhang, Zhijun

    2016-08-01

    Clusterin (CLU) is recognized as a secreted protein that is related to the processes of inflammation and immunity in the pathogenesis of Alzheimer's disease (AD). The effects of the risk variant of the C allele at the rs11136000 locus of the CLU gene are associated with variations in the brain structure and function. However, the relationship of the CLU-C allele to architectural disruptions in resting-state networks in amnestic mild cognitive impairment (aMCI) subjects (i.e., individuals with elevated risk of AD) remains relatively unknown. Using resting-state functional magnetic resonance imaging and an imaging genetic approach, this study investigated whether individual brain functional networks, i.e., the default mode network (DMN) and the task-positive network, were modulated by the CLU-C allele (rs11136000) in 50 elderly participants, including 26 aMCI subjects and 24 healthy controls. CLU-by-aMCI interactions were associated with the information-bridging regions between resting-state networks rather than with the DMN itself, especially in cortical midline regions. Interestingly, the complex communications between resting-state networks were enhanced in aMCI subjects with the CLU rs11136000 CC genotype and were modulated by the degree of memory impairment, suggesting a reconstructed balance of the resting-state networks in these individuals with an elevated risk of AD. The neuroimaging-genetic evidence indicates that immunity factors may contribute to alterations in brain functional networks in aMCI. These findings add to the evidence that the CLU gene may represent a potential therapeutic target for slowing disease progression in AD. PMID:26899953

  19. Creating probabilistic maps of the face network in the adolescent brain: A multi-centre functional MRI study

    International Nuclear Information System (INIS)

    Large-scale magnetic resonance (MR) studies of the human brain offer unique opportunities for identifying genetic and environmental factors shaping the human brain. Here, we describe a dataset collected in the context of a multi-centre study of the adolescent brain, namely the IMAGEN Study. We focus on one of the functional paradigms included in the project to probe the brain network underlying processing of ambiguous and angry faces. Using functional MR (fMRI) data collected in 1,110 adolescents, we constructed probabilistic maps of the neural network engaged consistently while viewing the ambiguous or angry faces; 21 brain regions responding to faces with high probability were identified. We were also able to address several methodological issues, including the minimal sample size yielding a stable location of a test region, namely the fusiform face area (FFA), as well as the effect of acquisition site (eight sites) and scanner (four manufacturers) on the location and magnitude of the fMRI response to faces in the FFA. Finally, we provided a comparison between male and female adolescents in terms of the effect sizes of sex differences in brain response to the ambiguous and angry faces in the 21 regions of interest. Overall, we found a stronger neural response to the ambiguous faces in several cortical regions, including the fusiform face area, in female (vs. male) adolescents, and a slightly stronger response to the angry faces in the amygdala of male (vs. female) adolescents. (authors)

  20. Three Large-Scale Functional Brain Networks from Resting-State Functional MRI in Subjects with Different Levels of Cognitive Impairment.

    Science.gov (United States)

    Joo, Soo Hyun; Lim, Hyun Kook; Lee, Chang Uk

    2016-01-01

    Normal aging and to a greater degree degenerative brain diseases such as Alzheimer's disease (AD), cause changes in the brain's structure and function. Degenerative changes in brain structure and decline in its function are associated with declines in cognitive ability. Early detection of AD is a key priority in dementia services and research. However, depending on the disease progression, neurodegenerative manifestations, such as cerebral atrophy, are detected late in course of AD. Functional changes in the brain may be an indirect indicator of trans-synaptic activity and they usually appear prior to structural changes in AD. Resting-state functional magnetic resonance imaging (RS-fMRI) has recently been highlighted as a new technique for interrogating intrinsic functional connectivity networks. Among the majority of RS-fMRI studies, the default mode network (DMN), salience network (SN), and central executive network (CEN) gained particular focus because alterations to their functional connectivity were observed in subjects who had AD, who had mild cognitive impairment (MCI), or who were at high risk for AD. Herein, we present a review of the current research on changes in functional connectivity, as measured by RS-fMRI. We focus on the DMN, SN, and CEN to describe RS-fMRI results from three groups: normal healthy aging, MCI and AD. PMID:26766941

  1. The brain functional networks associated to human and animal suffering differ among omnivores, vegetarians and vegans

    OpenAIRE

    Filippi, Massimo; Riccitelli, Gianna; Falini, Andrea; Di Salle, Francesco; Vuilleumier, Patrik; Comi, Giancarlo; Rocca, M. A.

    2010-01-01

    Empathy and affective appraisals for conspecifics are among the hallmarks of social interaction. Using functional MRI, we hypothesized that vegetarians and vegans, who made their feeding choice for ethical reasons, might show brain responses to conditions of suffering involving humans or animals different from omnivores. We recruited 20 omnivore subjects, 19 vegetarians, and 21 vegans. The groups were matched for sex and age. Brain activation was investigated using fMRI and an event-related d...

  2. Linking human brain local activity fluctuations to structural and functional network architectures

    OpenAIRE

    Baria, A.T.; Mansour, A; Huang, L.; Baliki, M. N.; Cecchi, G. A.; Mesulam, M M; A. V. Apkarian

    2013-01-01

    Activity of cortical local neuronal populations fluctuates continuously, and a large proportion of these fluctuations are shared across populations of neurons. Here we seek organizational rules that link these two phenomena. Using neuronal activity, as identified by functional MRI (fMRI) and for a given voxel or brain region, we derive a single measure of full bandwidth brain-oxygenation-level-dependent (BOLD) fluctuations by calculating the slope, α, for the log-linear power spectrum. For th...

  3. Motor Network Plasticity and Low-Frequency Oscillations Abnormalities in Patients with Brain Gliomas: A Functional MRI Study

    Science.gov (United States)

    Niu, Chen; Zhang, Ming; Min, Zhigang; Rana, Netra; Zhang, Qiuli; Liu, Xin; Li, Min; Lin, Pan

    2014-01-01

    Brain plasticity is often associated with the process of slow-growing tumor formation, which remodels neural organization and optimizes brain network function. In this study, we aimed to investigate whether motor function plasticity would display deficits in patients with slow-growing brain tumors located in or near motor areas, but who were without motor neurological deficits. We used resting-state functional magnetic resonance imaging to probe motor networks in 15 patients with histopathologically confirmed brain gliomas and 15 age-matched healthy controls. All subjects performed a motor task to help identify individual motor activity in the bilateral primary motor cortex (PMC) and supplementary motor area (SMA). Frequency-based analysis at three different frequencies was then used to investigate possible alterations in the power spectral density (PSD) of low-frequency oscillations. For each group, the average PSD was determined for each brain region and a nonparametric test was performed to determine the difference in power between the two groups. Significantly reduced inter-hemispheric functional connectivity between the left and right PMC was observed in patients compared with controls (P<0.05). We also found significantly decreased PSD in patients compared to that in controls, in all three frequency bands (low: 0.01–0.02 Hz; middle: 0.02–0.06 Hz; and high: 0.06–0.1 Hz), at three key motor regions. These findings suggest that in asymptomatic patients with brain tumors located in eloquent regions, inter-hemispheric connection may be more vulnerable. A comparison of the two approaches indicated that power spectral analysis is more sensitive than functional connectivity analysis for identifying the neurological abnormalities underlying motor function plasticity induced by slow-growing tumors. PMID:24806463

  4. Motor network plasticity and low-frequency oscillations abnormalities in patients with brain gliomas: a functional MRI study.

    Directory of Open Access Journals (Sweden)

    Chen Niu

    Full Text Available Brain plasticity is often associated with the process of slow-growing tumor formation, which remodels neural organization and optimizes brain network function. In this study, we aimed to investigate whether motor function plasticity would display deficits in patients with slow-growing brain tumors located in or near motor areas, but who were without motor neurological deficits. We used resting-state functional magnetic resonance imaging to probe motor networks in 15 patients with histopathologically confirmed brain gliomas and 15 age-matched healthy controls. All subjects performed a motor task to help identify individual motor activity in the bilateral primary motor cortex (PMC and supplementary motor area (SMA. Frequency-based analysis at three different frequencies was then used to investigate possible alterations in the power spectral density (PSD of low-frequency oscillations. For each group, the average PSD was determined for each brain region and a nonparametric test was performed to determine the difference in power between the two groups. Significantly reduced inter-hemispheric functional connectivity between the left and right PMC was observed in patients compared with controls (P<0.05. We also found significantly decreased PSD in patients compared to that in controls, in all three frequency bands (low: 0.01-0.02 Hz; middle: 0.02-0.06 Hz; and high: 0.06-0.1 Hz, at three key motor regions. These findings suggest that in asymptomatic patients with brain tumors located in eloquent regions, inter-hemispheric connection may be more vulnerable. A comparison of the two approaches indicated that power spectral analysis is more sensitive than functional connectivity analysis for identifying the neurological abnormalities underlying motor function plasticity induced by slow-growing tumors.

  5. Effects of meditation experience on functional connectivity of distributed brain networks

    OpenAIRE

    Wendy eHasenkamp; Barsalou, Lawrence W.

    2012-01-01

    This study sought to examine the effect of meditation experience on brain networks underlying cognitive actions employed during contemplative practice. In a previous study, we proposed a basic model of naturalistic cognitive fluctuations that occur during the practice of focused attention meditation. This model specifies four intervals in a cognitive cycle: mind wandering, awareness of mind wandering, shifting of attention, and sustained attention. Using subjective input from experienced pr...

  6. Effects of Meditation Experience on Functional Connectivity of Distributed Brain Networks

    OpenAIRE

    Hasenkamp, Wendy; Barsalou, Lawrence W.

    2012-01-01

    This study sought to examine the effect of meditation experience on brain networks underlying cognitive actions employed during contemplative practice. In a previous study, we proposed a basic model of naturalistic cognitive fluctuations that occur during the practice of focused attention meditation. This model specifies four intervals in a cognitive cycle: mind wandering (MW), awareness of MW, shifting of attention, and sustained attention. Using subjective input from experienced practitione...

  7. Brain imaging and brain function

    International Nuclear Information System (INIS)

    This book is a survey of the applications of imaging studies of regional cerebral blood flow and metabolism to the investigation of neurological and psychiatric disorders. Contributors review imaging techniques and strategies for measuring regional cerebral blood flow and metabolism, for mapping functional neural systems, and for imaging normal brain functions. They then examine the applications of brain imaging techniques to the study of such neurological and psychiatric disorders as: cerebral ischemia; convulsive disorders; cerebral tumors; Huntington's disease; Alzheimer's disease; depression and other mood disorders. A state-of-the-art report on magnetic resonance imaging of the brain and central nervous system rounds out the book's coverage

  8. Large-scale functional brain networks in human non-rapid eye movement sleep: insights from combined electroencephalographic/functional magnetic resonance imaging studies.

    Science.gov (United States)

    Spoormaker, Victor I; Czisch, Michael; Maquet, Pierre; Jäncke, Lutz

    2011-10-13

    This paper reviews the existing body of knowledge on the neural correlates of spontaneous oscillations, functional connectivity and brain plasticity in human non-rapid eye movement (NREM) sleep. The first section reviews the evidence that specific sleep events as slow waves and spindles are associated with transient increases in regional brain activity. The second section describes the changes in functional connectivity during NREM sleep, with a particular focus on changes within a low-frequency, large-scale functional brain network. The third section will discuss the possibility that spontaneous oscillations and differential functional connectivity are related to brain plasticity and systems consolidation, with a particular focus on motor skill acquisition. Implications for the mode of information processing per sleep stage and future experimental studies are discussed. PMID:21893524

  9. SPARK: Sparsity-based analysis of reliable k-hubness and overlapping network structure in brain functional connectivity.

    Science.gov (United States)

    Lee, Kangjoo; Lina, Jean-Marc; Gotman, Jean; Grova, Christophe

    2016-07-01

    Functional hubs are defined as the specific brain regions with dense connections to other regions in a functional brain network. Among them, connector hubs are of great interests, as they are assumed to promote global and hierarchical communications between functionally specialized networks. Damage to connector hubs may have a more crucial effect on the system than does damage to other hubs. Hubs in graph theory are often identified from a correlation matrix, and classified as connector hubs when the hubs are more connected to regions in other networks than within the networks to which they belong. However, the identification of hubs from functional data is more complex than that from structural data, notably because of the inherent problem of multicollinearity between temporal dynamics within a functional network. In this context, we developed and validated a method to reliably identify connectors and corresponding overlapping network structure from resting-state fMRI. This new method is actually handling the multicollinearity issue, since it does not rely on counting the number of connections from a thresholded correlation matrix. The novelty of the proposed method is that besides counting the number of networks involved in each voxel, it allows us to identify which networks are actually involved in each voxel, using a data-driven sparse general linear model in order to identify brain regions involved in more than one network. Moreover, we added a bootstrap resampling strategy to assess statistically the reproducibility of our results at the single subject level. The unified framework is called SPARK, i.e. SParsity-based Analysis of Reliable k-hubness, where k-hubness denotes the number of networks overlapping in each voxel. The accuracy and robustness of SPARK were evaluated using two dimensional box simulations and realistic simulations that examined detection of artificial hubs generated on real data. Then, test/retest reliability of the method was assessed

  10. Markov models for fMRI correlation structure: Is brain functional connectivity small world, or decomposable into networks?

    International Nuclear Information System (INIS)

    Correlations in the signal observed via functional Magnetic Resonance Imaging (fMRI), are expected to reveal the interactions in the underlying neural populations through hemodynamic response. In particular, they highlight distributed set of mutually correlated regions that correspond to brain networks related to different cognitive functions. Yet graph-theoretical studies of neural connections give a different picture: that of a highly integrated system with small-world properties: local clustering but with short pathways across the complete structure. We examine the conditional independence properties of the fMRI signal, i.e. its Markov structure, to find realistic assumptions on the connectivity structure that are required to explain the observed functional connectivity. In particular we seek a decomposition of the Markov structure into segregated functional networks using decomposable graphs: a set of strongly-connected and partially overlapping cliques. We introduce a new method to efficiently extract such cliques on a large, strongly-connected graph. We compare methods learning different graph structures from functional connectivity by testing the goodness of fit of the model they learn on new data. We find that summarizing the structure as strongly-connected networks can give a good description only for very large and overlapping networks. These results highlight that Markov models are good tools to identify the structure of brain connectivity from fMRI signals, but for this purpose they must reflect the small world properties of the underlying neural systems. (authors)

  11. FROM BRAIN DRAIN TO BRAIN NETWORKING

    OpenAIRE

    Irina BONCEA

    2015-01-01

    Scientific networking is the most accessible way a country can turn the brain drain into brain gain. Diaspora’s members offer valuable information, advice or financial support from the destination country, without being necessary to return. This article aims to investigate Romania’s potential of turning brain drain into brain networking, using evidence from the medical sector. The main factors influencing the collaboration with the country of origin are investigated. The co...

  12. Is Traumatic Brain Injury Associated with Reduced Inter-Hemispheric Functional Connectivity? A Study of Large-Scale Resting State Networks following Traumatic Brain Injury.

    Science.gov (United States)

    Rigon, Arianna; Duff, Melissa C; McAuley, Edward; Kramer, Arthur F; Voss, Michelle W

    2016-06-01

    Traumatic brain injury (TBI) often has long-term debilitating sequelae in cognitive and behavioral domains. Understanding how TBI impacts functional integrity of brain networks that underlie these domains is key to guiding future approaches to TBI rehabilitation. In the current study, we investigated the differences in inter-hemispheric functional connectivity (FC) of resting state networks (RSNs) between chronic mild-to-severe TBI patients and normal comparisons (NC), focusing on two externally oriented networks (i.e., the fronto-parietal network [FPN] and the executive control network [ECN]), one internally oriented network (i.e., the default mode network [DMN]), and one somato-motor network (SMN). Seed voxel correlation analysis revealed that TBI patients displayed significantly less FC between lateralized seeds and both homologous and non-homologous regions in the opposite hemisphere for externally oriented networks but not for DMN or SMN; conversely, TBI patients showed increased FC within regions of the DMN, especially precuneus and parahippocampal gyrus. Region of interest correlation analyses confirmed the presence of significantly higher inter-hemispheric FC in NC for the FPN (p  0.05) or SMN (p > 0.05). Further analysis revealed that performance on a neuropsychological test measuring organizational skills and visuo-spatial abilities administered to the TBI group, the Rey-Osterrieth Complex Figure Test, positively correlated with FC between the right FPN and homologous regions. Our findings suggest that distinct RSNs display specific patterns of aberrant FC following TBI; this represents a step forward in the search for biomarkers useful for early diagnosis and treatment of TBI-related cognitive impairment. PMID:25719433

  13. Functional reorganization of the large-scale brain networks that support high-level cognition following brain damage in aphasia

    Directory of Open Access Journals (Sweden)

    Idan Asher Blank

    2015-05-01

    Full Text Available Over the last decade, a number of large-scale networks in the human cortex that support high-level cognition have been identified. Here, we focus on two of these networks: the fronto-temporal language network (e.g., Fedorenko et al., 2010, and the fronto-parietal “multiple demand (MD” network (e.g., Duncan, 2010. These two networks are clearly distinct from one another: first, their respective regions show distinct functional profiles, with language regions showing selective responses to language stimuli (Fedorenko et al., 2011; Monti et al., 2012 and MD regions showing domain-general responses to cognitive effort across a wide range of tasks (Duncan & Owen, 2001; Fedorenko et al., 2013. Second, during “rest” and cognitive processing, each network shows strong activity synchronization among its constituent regions, whereas regions across the two networks are not synchronized (Blank et al., 2014; Lee et al., 2012; Mantini et al., 2013. In the current study, we examined how these functional characteristics of the two networks were affected following aphasia-inducing strokes. In particular, we asked whether damage to the language network would alter the involvement of the MD network in linguistic processing, and whether such damage would alter the patterns of synchronization across the two networks. Four male individuals with aphasia (age: M=53, having suffered a single left MCA CVA, were scanned in fMRI on two paradigms that enable basic functional characterization of language and MD regions: (i a language localizer task, where they passively read sentences and sequences of pseudowords (Fedorenko et al., 2010; and (ii a spatial working memory task, where they had to remember fewer (easy or more (hard locations in a grid (Fedorenko et al., 2013. Language and MD regions were defined in each individual using the sentences > pseudowords contrast and the hard > easy contrast, respectively. Subjects were also scanned while listening to

  14. Disrupted topological organization in the whole-brain functional network of trauma-exposed firefighters: A preliminary study.

    Science.gov (United States)

    Jung, Wi Hoon; Chang, Ki Jung; Kim, Nam Hee

    2016-04-30

    Given that partial posttraumatic stress disorder (pPTSD) may be a specific risk factor for the development of posttraumatic stress disorder (PTSD), it is important to understand the neurobiology of pPTSD. However, there are few extant studies in this domain. Using resting-state functional magnetic resonance imaging (rs-fMRI) and a graph theoretical approach, we compared the topological organization of the whole-brain functional network in trauma-exposed firefighters with pPTSD (pPTSD group, n=9) with those without pPTSD (PC group, n=8) and non-traumatized healthy controls (HC group, n=11). We also examined changes in the network topology of five individuals with pPTSD before and after eye movement desensitization and reprocessing (EMDR) therapy. Individuals with pPTSD exhibited altered global properties, including a reduction in values of a normalized clustering coefficient, normalized local efficiency, and small-worldness. We also observed altered local properties, particularly in the association cortex, including the temporal and parietal cortices, across groups. These disruptive global and local network properties presented in pPTSD before treatment were ameliorated after treatment. Our preliminary results suggest that subthreshold manifestation of PTSD may be due to a disruption in the optimal balance in the functional brain networks and that this disruption can be ameliorated by psychotherapy. PMID:27107156

  15. Human intelligence and brain networks.

    Science.gov (United States)

    Colom, Roberto; Karama, Sherif; Jung, Rex E; Haier, Richard J

    2010-01-01

    Intelligence can be defined as a general mental ability for reasoning, problem solving, and learning. Because of its general nature, intelligence integrates cognitive functions such as perception, attention, memory, language, or planning. On the basis of this definition, intelligence can be reliably measured by standardized tests with obtained scores predicting several broad social outcomes such as educational achievement, job performance, health, and longevity. A detailed understanding of the brain mechanisms underlying this general mental ability could provide significant individual and societal benefits. Structural and functional neuroimaging studies have generally supported a frontoparietal network relevant for intelligence. This same network has also been found to underlie cognitive functions related to perception, short-term memory storage, and language. The distributed nature of this network and its involvement in a wide range of cognitive functions fits well with the integrative nature of intelligence. A new key phase of research is beginning to investigate how functional networks relate to structural networks, with emphasis on how distributed brain areas communicate with each other. PMID:21319494

  16. Causal functional contributions and interactions in the attention network of the brain: an objective multi-perturbation analysis.

    Science.gov (United States)

    Zavaglia, Melissa; Hilgetag, Claus C

    2016-06-01

    Spatial attention is a prime example for the distributed network functions of the brain. Lesion studies in animal models have been used to investigate intact attentional mechanisms as well as perspectives for rehabilitation in the injured brain. Here, we systematically analyzed behavioral data from cooling deactivation and permanent lesion experiments in the cat, where unilateral deactivation of the posterior parietal cortex (in the vicinity of the posterior middle suprasylvian cortex, pMS) or the superior colliculus (SC) cause a severe neglect in the contralateral hemifield. Counterintuitively, additional deactivation of structures in the opposite hemisphere reverses the deficit. Using such lesion data, we employed a game-theoretical approach, multi-perturbation Shapley value analysis (MSA), for inferring functional contributions and network interactions of bilateral pMS and SC from behavioral performance in visual attention studies. The approach provides an objective theoretical strategy for lesion inferences and allows a unique quantitative characterization of regional functional contributions and interactions on the basis of multi-perturbations. The quantitative analysis demonstrated that right posterior parietal cortex and superior colliculus made the strongest positive contributions to left-field orienting, while left brain regions had negative contributions, implying that their perturbation may reverse the effects of contralateral lesions or improve normal function. An analysis of functional modulations and interactions among the regions revealed redundant interactions (implying functional overlap) between regions within each hemisphere, and synergistic interactions between bilateral regions. To assess the reliability of the MSA method in the face of variable and incomplete input data, we performed a sensitivity analysis, investigating how much the contribution values of the four regions depended on the performance of specific configurations and on the

  17. Development of a large-scale functional brain network during human non-rapid eye movement sleep.

    Science.gov (United States)

    Spoormaker, Victor I; Schröter, Manuel S; Gleiser, Pablo M; Andrade, Katia C; Dresler, Martin; Wehrle, Renate; Sämann, Philipp G; Czisch, Michael

    2010-08-25

    Graph theoretical analysis of functional magnetic resonance imaging (fMRI) time series has revealed a small-world organization of slow-frequency blood oxygen level-dependent (BOLD) signal fluctuations during wakeful resting. In this study, we used graph theoretical measures to explore how physiological changes during sleep are reflected in functional connectivity and small-world network properties of a large-scale, low-frequency functional brain network. Twenty-five young and healthy participants fell asleep during a 26.7 min fMRI scan with simultaneous polysomnography. A maximum overlap discrete wavelet transformation was applied to fMRI time series extracted from 90 cortical and subcortical regions in normalized space after residualization of the raw signal against unspecific sources of signal fluctuations; functional connectivity analysis focused on the slow-frequency BOLD signal fluctuations between 0.03 and 0.06 Hz. We observed that in the transition from wakefulness to light sleep, thalamocortical connectivity was sharply reduced, whereas corticocortical connectivity increased; corticocortical connectivity subsequently broke down in slow-wave sleep. Local clustering values were closest to random values in light sleep, whereas slow-wave sleep was characterized by the highest clustering ratio (gamma). Our findings support the hypothesis that changes in consciousness in the descent to sleep are subserved by reduced thalamocortical connectivity at sleep onset and a breakdown of general connectivity in slow-wave sleep, with both processes limiting the capacity of the brain to integrate information across functional modules. PMID:20739559

  18. Protecting Neural Structures and Cognitive Function During Prolonged Space Flight by Targeting the Brain Derived Neurotrophic Factor Molecular Network

    Science.gov (United States)

    Schmidt, M. A.; Goodwin, T. J.

    2014-01-01

    Brain derived neurotrophic factor (BDNF) is the main activity-dependent neurotrophin in the human nervous system. BDNF is implicated in production of new neurons from dentate gyrus stem cells (hippocampal neurogenesis), synapse formation, sprouting of new axons, growth of new axons, sprouting of new dendrites, and neuron survival. Alterations in the amount or activity of BDNF can produce significant detrimental changes to cortical function and synaptic transmission in the human brain. This can result in glial and neuronal dysfunction, which may contribute to a range of clinical conditions, spanning a number of learning, behavioral, and neurological disorders. There is an extensive body of work surrounding the BDNF molecular network, including BDNF gene polymorphisms, methylated BDNF gene promoters, multiple gene transcripts, varied BDNF functional proteins, and different BDNF receptors (whose activation differentially drive the neuron to neurogenesis or apoptosis). BDNF is also closely linked to mitochondrial biogenesis through PGC-1alpha, which can influence brain and muscle metabolic efficiency. BDNF AS A HUMAN SPACE FLIGHT COUNTERMEASURE TARGET Earth-based studies reveal that BDNF is negatively impacted by many of the conditions encountered in the space environment, including oxidative stress, radiation, psychological stressors, sleep deprivation, and many others. A growing body of work suggests that the BDNF network is responsive to a range of diet, nutrition, exercise, drug, and other types of influences. This section explores the BDNF network in the context of 1) protecting the brain and nervous system in the space environment, 2) optimizing neurobehavioral performance in space, and 3) reducing the residual effects of space flight on the nervous system on return to Earth

  19. Stress Impact on Resting State Brain Networks

    OpenAIRE

    Soares, José Miguel; Sampaio, Adriana; Ferreira, Luís Miguel, colab.; Santos, Nadine Correia; Marques, Paulo; Marques, Fernanda; Palha, Joana Almeida; Cerqueira, João José; Sousa, Nuno

    2013-01-01

    Resting state brain networks (RSNs) are spatially distributed large-scale networks, evidenced by resting state functional magnetic resonance imaging (fMRI) studies. Importantly, RSNs are implicated in several relevant brain functions and present abnormal functional patterns in many neuropsychiatric disorders, for which stress exposure is an established risk factor. Yet, so far, little is known about the effect of stress in the architecture of RSNs, both in resting state conditions or during s...

  20. The brain's code and its canonical computational motifs. From sensory cortex to the default mode network: A multi-scale model of brain function in health and disease.

    Science.gov (United States)

    Turkheimer, Federico E; Leech, Robert; Expert, Paul; Lord, Louis-David; Vernon, Anthony C

    2015-08-01

    A variety of anatomical and physiological evidence suggests that the brain performs computations using motifs that are repeated across species, brain areas, and modalities. The computational architecture of cortex, for example, is very similar from one area to another and the types, arrangements, and connections of cortical neurons are highly stereotyped. This supports the idea that each cortical area conducts calculations using similarly structured neuronal modules: what we term canonical computational motifs. In addition, the remarkable self-similarity of the brain observables at the micro-, meso- and macro-scale further suggests that these motifs are repeated at increasing spatial and temporal scales supporting brain activity from primary motor and sensory processing to higher-level behaviour and cognition. Here, we briefly review the biological bases of canonical brain circuits and the role of inhibitory interneurons in these computational elements. We then elucidate how canonical computational motifs can be repeated across spatial and temporal scales to build a multiplexing information system able to encode and transmit information of increasing complexity. We point to the similarities between the patterns of activation observed in primary sensory cortices by use of electrophysiology and those observed in large scale networks measured with fMRI. We then employ the canonical model of brain function to unify seemingly disparate evidence on the pathophysiology of schizophrenia in a single explanatory framework. We hypothesise that such a framework may also be extended to cover multiple brain disorders which are grounded in dysfunction of GABA interneurons and/or these computational motifs. PMID:25956253

  1. FROM BRAIN DRAIN TO BRAIN NETWORKING

    Directory of Open Access Journals (Sweden)

    Irina BONCEA

    2015-06-01

    Full Text Available Scientific networking is the most accessible way a country can turn the brain drain into brain gain. Diaspora’s members offer valuable information, advice or financial support from the destination country, without being necessary to return. This article aims to investigate Romania’s potential of turning brain drain into brain networking, using evidence from the medical sector. The main factors influencing the collaboration with the country of origin are investigated. The conclusions suggest that Romania could benefit from the diaspora option, through an active implication at institutional level and the implementation of a strategy in this area.

  2. Disrupted Brain Functional Network in Internet Addiction Disorder: A Resting-State Functional Magnetic Resonance Imaging Study

    OpenAIRE

    Wee, Chong-Yaw; Zhao, Zhimin; Yap, Pew-Thian; Wu, Guorong; Shi, Feng; Price, True; Du, Yasong; Xu, Jianrong; Zhou, Yan; Shen, Dinggang

    2014-01-01

    Internet addiction disorder (IAD) is increasingly recognized as a mental health disorder, particularly among adolescents. The pathogenesis associated with IAD, however, remains unclear. In this study, we aim to explore the encephalic functional characteristics of IAD adolescents at rest using functional magnetic resonance imaging data. We adopted a graph-theoretic approach to investigate possible disruptions of functional connectivity in terms of network properties including small-worldness, ...

  3. Changes in functional connectivity within the fronto-temporal brain network induced by regular and irregular Russian verb production

    Directory of Open Access Journals (Sweden)

    Maxim Kireev

    2015-02-01

    Full Text Available Functional connectivity between brain areas involved in the processing of complex language forms remains largely unexplored. Contributing to the debate about neural mechanisms underlying regular and irregular inflectional morphology processing in the mental lexicon, we conducted an fMRI experiment in which participants generated forms from different types of Russian verbs and nouns as well as from nonce stimuli. The data were subjected to a whole brain voxel-wise analysis of context dependent changes in functional connectivity (the so-called psychophysiological interaction analysis, PPI. Unlike previously reported subtractive results that reveal functional segregation between brain areas, PPI provides complementary information showing how these areas are functionally integrated in a particular task. To date, PPI evidence on inflectional morphology has been scarce and only available for inflectionally impoverished English verbs in a same-different judgment task. Using PPI here in conjunction with a production task in an inflectionally rich language, we found that functional connectivity between the left inferior frontal gyrus (LIFG and bilateral superior temporal gyri (STG was significantly greater for regular real verbs than for irregular ones. Furthermore, we observed a significant positive covariance between the number of mistakes in irregular real verb trials and the increase in functional connectivity between the LIFG and the right anterior cingulate cortex in these trails, as compared to regular ones. Our results therefore allow for dissociation between regularity and processing difficulty effects. These results, on the one hand, shed new light on the functional interplay within the LIFG-bilateral STG language-related network and, on the other hand, call for partial reconsideration of some of the previous findings while stressing the role of functional temporo-frontal connectivity in complex morphological processes.

  4. Functional Disorganization of Small-World Brain Networks in mild Alzheimer’s Disease and amnestic Mild Cognitive Impairment: An EEG Study using Relative Wavelet Entropy (RWE)

    OpenAIRE

    Frantzidis, Christos A.; Vivas, Ana B.; Anthoula eTsolaki; Klados, Manousos A.; Magda eTsolaki; Panagiotis D Bamidis

    2014-01-01

    Previous neuroscientific findings have linked Alzheimer's Disease (AD) with less efficient information processing and brain network disorganization. However, pathological alterations of the brain networks during the preclinical phase of amnestic Mild Cognitive Impairment (aMCI) remain largely unknown. The present study aimed at comparing patterns of the detection of functional disorganization in MCI relative to Mild Dementia (MD). Participants consisted of 23 cognitively healthy adults, 17 aM...

  5. Spatial and Functional Architecture of the Mammalian Brain Stem Respiratory Network: A Hierarchy of Three Oscillatory Mechanisms

    OpenAIRE

    Smith, J C; Abdala, A. P. L.; Koizumi, H.; Rybak, I. A.; Paton, J. F. R.

    2007-01-01

    Mammalian central pattern generators (CPGs) producing rhythmic movements exhibit extremely robust and flexible behavior. Network architectures that enable these features are not well understood. Here we studied organization of the brain stem respiratory CPG. By sequential rostral to caudal transections through the pontine-medullary respiratory network within an in situ perfused rat brain stem–spinal cord preparation, we showed that network dynamics reorganized and new rhythmogenic mechanisms ...

  6. Functional MRI studies of the neural mechanisms of human brain attentional networks

    International Nuclear Information System (INIS)

    Objective: To identify the neural mechanisms of the anterior attention network (AAN) and posterior attention network (PAN) , investigate the possible interaction between them with event-related functional MRI(ER-fMRI). Methods: Eight right-handed healthy volunteers participated in the experiment designed with inhibition of return in visual orienting and Stroop color-word interference effect. The fMRI data were collected on Siemens 1.5 T Sonata MRI systems and analyzed by AFNI to generate the activation map. Results: The data sets from 6 of 8 subjects were used in the study. The functional localizations of the Stroop and IOR, which manifest the function of the AAN and PAN respectively, were consistent with previous imaging researches. On cued locations, left inferior parietal lobule (IPL), area MT/V5, right dorsolateral prefrontal cortex (DLPFC) and left anterior cingulated cortex (ACC) were significantly activated. On uncued locations, right superior parietal lobule (SPL) and bilateral area MT/V5 were significantly activated. Conclusion: The AAN exerts control over the PAN, while its function can be in turn modulated by the PAN. There are interaction between the AAN and PAN. In addition, it is also proved that ER-fMRI is a feasible method to revise preexisting cognitive model and theory. (authors)

  7. Brain Functional Effects of Psychopharmacological Treatments in Schizophrenia: A Network-based Functional Perspective Beyond Neurotransmitter Systems

    OpenAIRE

    De Rossi, Pietro; Chiapponi, Chiara; Spalletta, Gianfranco

    2015-01-01

    Psychopharmacological treatments for schizophrenia have always been a matter of debate and a very important issue in public health given the chronic, relapsing and disabling nature of the disorder. A thorough understanding of the pros and cons of currently available pharmacological treatments for schizophrenia is critical to better capture the features of treatment-refractory clinical pictures and plan the developing of new treatment strategies. This review focuses on brain functional changes...

  8. Disrupted brain functional network in internet addiction disorder: a resting-state functional magnetic resonance imaging study.

    Directory of Open Access Journals (Sweden)

    Chong-Yaw Wee

    Full Text Available Internet addiction disorder (IAD is increasingly recognized as a mental health disorder, particularly among adolescents. The pathogenesis associated with IAD, however, remains unclear. In this study, we aim to explore the encephalic functional characteristics of IAD adolescents at rest using functional magnetic resonance imaging data. We adopted a graph-theoretic approach to investigate possible disruptions of functional connectivity in terms of network properties including small-worldness, efficiency, and nodal centrality on 17 adolescents with IAD and 16 socio-demographically matched healthy controls. False discovery rate-corrected parametric tests were performed to evaluate the statistical significance of group-level network topological differences. In addition, a correlation analysis was performed to assess the relationships between functional connectivity and clinical measures in the IAD group. Our results demonstrate that there is significant disruption in the functional connectome of IAD patients, particularly between regions located in the frontal, occipital, and parietal lobes. The affected connections are long-range and inter-hemispheric connections. Although significant alterations are observed for regional nodal metrics, there is no difference in global network topology between IAD and healthy groups. In addition, correlation analysis demonstrates that the observed regional abnormalities are correlated with the IAD severity and behavioral clinical assessments. Our findings, which are relatively consistent between anatomically and functionally defined atlases, suggest that IAD causes disruptions of functional connectivity and, importantly, that such disruptions might link to behavioral impairments.

  9. Statistical analysis of brain network

    OpenAIRE

    Sala

    2013-01-01

    Recent developments in the complex networks analysis, based largely on graph theory, have been used to study the brain network organization. The brain is a complex system that can be represented by a graph. A graph is a mathematical representation which can be useful to study the connectivity of the brain. Nodes in the brain can be identified dividing its volume in regions of interest and links can be identified calculating a measure of dependence between pairs of regions whose ac...

  10. Violence-related content in video game may lead to functional connectivity changes in brain networks as revealed by fMRI-ICA in young men.

    Science.gov (United States)

    Zvyagintsev, M; Klasen, M; Weber, R; Sarkheil, P; Esposito, F; Mathiak, K A; Schwenzer, M; Mathiak, K

    2016-04-21

    In violent video games, players engage in virtual aggressive behaviors. Exposure to virtual aggressive behavior induces short-term changes in players' behavior. In a previous study, a violence-related version of the racing game "Carmageddon TDR2000" increased aggressive affects, cognitions, and behaviors compared to its non-violence-related version. This study investigates the differences in neural network activity during the playing of both versions of the video game. Functional magnetic resonance imaging (fMRI) recorded ongoing brain activity of 18 young men playing the violence-related and the non-violence-related version of the video game Carmageddon. Image time series were decomposed into functional connectivity (FC) patterns using independent component analysis (ICA) and template-matching yielded a mapping to established functional brain networks. The FC patterns revealed a decrease in connectivity within 6 brain networks during the violence-related compared to the non-violence-related condition: three sensory-motor networks, the reward network, the default mode network (DMN), and the right-lateralized frontoparietal network. Playing violent racing games may change functional brain connectivity, in particular and even after controlling for event frequency, in the reward network and the DMN. These changes may underlie the short-term increase of aggressive affects, cognitions, and behaviors as observed after playing violent video games. PMID:26855192

  11. Functional MRI of the vocalization-processing network in the macaque brain

    Directory of Open Access Journals (Sweden)

    Michael eOrtiz-Rios

    2015-04-01

    Full Text Available Using functional magnetic resonance imaging in awake behaving monkeys we investigated how species-specific vocalizations are represented in auditory and auditory-related regions of the macaque brain. We found clusters of active voxels along the ascending auditory pathway that responded to various types of complex sounds: inferior colliculus (IC, medial geniculate nucleus (MGN, auditory core, belt, and parabelt cortex, and other parts of the superior temporal gyrus (STG and sulcus (STS. Regions sensitive to monkey calls were most prevalent in the anterior STG, but some clusters were also found in frontal and parietal cortex on the basis of comparisons between responses to calls and environmental sounds. Surprisingly, we found that spectrotemporal control sounds derived from the monkey calls (scrambled calls also activated the parietal and frontal regions. Taken together, our results demonstrate that species-specific vocalizations in rhesus monkeys activate preferentially the auditory ventral stream, and in particular areas of the antero-lateral belt and parabelt.

  12. Balancing the Brain: Resting State Networks and Deep Brain Stimulation

    OpenAIRE

    Kringelbach, Morten L.

    2011-01-01

    Over the last three decades, large numbers of patients with otherwise treatment-resistant disorders have been helped by deep brain stimulation, yet a full scientific understanding of the underlying neural mechanisms is still missing. We have previously proposed that efficacious deep brain stimulation works by restoring the balance of the brain’s resting state networks. Here, we extend this proposal by reviewing how detailed investigations of the highly coherent functional and structural brain...

  13. The role of nonlinearity in computing graph-theoretical properties of resting-state functional magnetic resonance imaging brain networks

    Science.gov (United States)

    Hartman, D.; Hlinka, J.; Paluš, M.; Mantini, D.; Corbetta, M.

    2011-03-01

    In recent years, there has been an increasing interest in the study of large-scale brain activity interaction structure from the perspective of complex networks, based on functional magnetic resonance imaging (fMRI) measurements. To assess the strength of interaction (functional connectivity, FC) between two brain regions, the linear (Pearson) correlation coefficient of the respective time series is most commonly used. Since a potential use of nonlinear FC measures has recently been discussed in this and other fields, the question arises whether particular nonlinear FC measures would be more informative for the graph analysis than linear ones. We present a comparison of network analysis results obtained from the brain connectivity graphs capturing either full (both linear and nonlinear) or only linear connectivity using 24 sessions of human resting-state fMRI. For each session, a matrix of full connectivity between 90 anatomical parcel time series is computed using mutual information. For comparison, connectivity matrices obtained for multivariate linear Gaussian surrogate data that preserve the correlations, but remove any nonlinearity are generated. Binarizing these matrices using multiple thresholds, we generate graphs corresponding to linear and full nonlinear interaction structures. The effect of neglecting nonlinearity is then assessed by comparing the values of a range of graph-theoretical measures evaluated for both types of graphs. Statistical comparisons suggest a potential effect of nonlinearity on the local measures—clustering coefficient and betweenness centrality. Nevertheless, subsequent quantitative comparison shows that the nonlinearity effect is practically negligible when compared to the intersubject variability of the graph measures. Further, on the group-average graph level, the nonlinearity effect is unnoticeable.

  14. Multilayer motif analysis of brain networks

    CERN Document Server

    Battiston, Federico; Chavez, Mario; Latora, Vito

    2016-01-01

    In the last decade network science has shed new light on the anatomical connectivity and on correlations in the activity of different areas of the human brain. The study of brain networks has made possible in fact to detect the central areas of a neural system, and to identify its building blocks by looking at overabundant small subgraphs, known as motifs. However, network analysis of the brain has so far mainly focused on structural and functional networks as separate entities. The recently developed mathematical framework of multi-layer networks allows to perform a multiplex analysis of the human brain where the structural and functional layers are considered at the same time. In this work we describe how to classify subgraphs in multiplex networks, and we extend motif analysis to networks with many layers. We then extract multi-layer motifs in brain networks of healthy subjects by considering networks with two layers, respectively obtained from diffusion and functional magnetic resonance imaging. Results i...

  15. Small-world brain networks in schizophrenia

    Institute of Scientific and Technical Information of China (English)

    Mingli LI; Zhuangfei CHEN; Tao LI

    2012-01-01

    Over the last decade the combination of brain neuroimaging techniques and graph theoretical analysis of the complex anatomical and functional networks in the brain have provided an exciting new platform for exploring the etiology of mental disorders such as schizophrenia. This review introduces the current status of this work, focusing on these networks in schizophrenia. The evidence supporting the findings of reduced efficiency of information exchange in schizophrenia both within local brain regions and globally throughout the brain is reviewed and the potential relationship of these changes to cognitive and clinical symptoms is discussed. Finally we propose some suggestions for future research.

  16. The Brain Functional Networks Associated to Human and Animal Suffering Differ among Omnivores, Vegetarians and Vegans

    Science.gov (United States)

    Filippi, Massimo; Riccitelli, Gianna; Falini, Andrea; Di Salle, Francesco; Vuilleumier, Patrik; Comi, Giancarlo; Rocca, Maria A.

    2010-01-01

    Empathy and affective appraisals for conspecifics are among the hallmarks of social interaction. Using functional MRI, we hypothesized that vegetarians and vegans, who made their feeding choice for ethical reasons, might show brain responses to conditions of suffering involving humans or animals different from omnivores. We recruited 20 omnivore subjects, 19 vegetarians, and 21 vegans. The groups were matched for sex and age. Brain activation was investigated using fMRI and an event-related design during observation of negative affective pictures of human beings and animals (showing mutilations, murdered people, human/animal threat, tortures, wounds, etc.). Participants saw negative-valence scenes related to humans and animals, alternating with natural landscapes. During human negative valence scenes, compared with omnivores, vegetarians and vegans had an increased recruitment of the anterior cingulate cortex (ACC) and inferior frontal gyrus (IFG). More critically, during animal negative valence scenes, they had decreased amygdala activation and increased activation of the lingual gyri, the left cuneus, the posterior cingulate cortex and several areas mainly located in the frontal lobes, including the ACC, the IFG and the middle frontal gyrus. Nonetheless, also substantial differences between vegetarians and vegans have been found responding to negative scenes. Vegetarians showed a selective recruitment of the right inferior parietal lobule during human negative scenes, and a prevailing activation of the ACC during animal negative scenes. Conversely, during animal negative scenes an increased activation of the inferior prefrontal cortex was observed in vegans. These results suggest that empathy toward non conspecifics has different neural representation among individuals with different feeding habits, perhaps reflecting different motivational factors and beliefs. PMID:20520767

  17. DWI and complex brain network analysis predicts vascular cognitive impairment in spontaneous hypertensive rats undergoing executive function tests

    Directory of Open Access Journals (Sweden)

    Xavier eLópez-Gil

    2014-07-01

    Full Text Available The identification of biomarkers of vascular cognitive impairment is urgent for its early diagnosis. The aim of this study was to detect and monitor changes in brain structure and connectivity, and to correlate them with the decline in executive function. We examined the feasibility of early diagnostic magnetic resonance imaging to predict cognitive impairment before onset in an animal model of chronic hypertension: Spontaneously Hypertensive Rats. Cognitive performance was tested in an operant conditioning paradigm that evaluated learning, memory and behavioral flexibility skills. Behavioral tests were coupled with longitudinal diffusion weighted imaging acquired with 126 diffusion gradient directions and 0.3 mm3 isometric resolution at 10, 14, 18, 22, 26 and 40 weeks after birth. Diffusion weighted imaging was analyzed in 2 different ways, by regional characterization of diffusion tensor imaging indices, and by assessing changes in structural brain network organization based on Q-Ball tractography. Already at the first evaluated times, diffusion tensor imaging scalar maps revealed significant differences in many regions, suggesting loss of integrity in white and grey matter of spontaneously hypertensive rats when compared to normotensive control rats. In addition, graph theory analysis of the structural brain network demonstrated a significant decrease of hierarchical modularity, global and local efficacy, with predictive value as shown by regional 3-fold cross validation study. Moreover, these decreases were significantly correlated with the behavioral performance deficits observed at subsequent time points, suggesting that the diffusion weighted imaging and connectivity studies can unravel neuroimaging alterations even overt signs of cognitive impairment become apparent.

  18. Identifying modular relations in complex brain networks

    DEFF Research Database (Denmark)

    Andersen, Kasper Winther; Mørup, Morten; Siebner, Hartwig; Madsen, Kristoffer H.; Hansen, Lars Kai

    2012-01-01

    We evaluate the infinite relational model (IRM) against two simpler alternative nonparametric Bayesian models for identifying structures in multi subject brain networks. The models are evaluated for their ability to predict new data and infer reproducible structures. Prediction and reproducibility...... overfit and obtains comparable reproducibility and predictability. For resting state functional magnetic resonance imaging data from 30 healthy controls the IRM model is also superior to the two simpler alternatives, suggesting that brain networks indeed exhibit universal complex relational structure in...

  19. Testing the hypothesis of neurodegeneracy in respiratory network function with a priori transected arterially perfused brain stem preparation of rat.

    Science.gov (United States)

    Jones, Sarah E; Dutschmann, Mathias

    2016-05-01

    Degeneracy of respiratory network function would imply that anatomically discrete aspects of the brain stem are capable of producing respiratory rhythm. To test this theory we a priori transected brain stem preparations before reperfusion and reoxygenation at 4 rostrocaudal levels: 1.5 mm caudal to obex (n = 5), at obex (n = 5), and 1.5 (n = 7) and 3 mm (n = 6) rostral to obex. The respiratory activity of these preparations was assessed via recordings of phrenic and vagal nerves and lumbar spinal expiratory motor output. Preparations with a priori transection at level of the caudal brain stem did not produce stable rhythmic respiratory bursting, even when the arterial chemoreceptors were stimulated with sodium cyanide (NaCN). Reperfusion of brain stems that preserved the pre-Bötzinger complex (pre-BötC) showed spontaneous and sustained rhythmic respiratory bursting at low phrenic nerve activity (PNA) amplitude that occurred simultaneously in all respiratory motor outputs. We refer to this rhythm as the pre-BötC burstlet-type rhythm. Conserving circuitry up to the pontomedullary junction consistently produced robust high-amplitude PNA at lower burst rates, whereas sequential motor patterning across the respiratory motor outputs remained absent. Some of the rostrally transected preparations expressed both burstlet-type and regular PNA amplitude rhythms. Further analysis showed that the burstlet-type rhythm and high-amplitude PNA had 1:2 quantal relation, with burstlets appearing to trigger high-amplitude bursts. We conclude that no degenerate rhythmogenic circuits are located in the caudal medulla oblongata and confirm the pre-BötC as the primary rhythmogenic kernel. The absence of sequential motor patterning in a priori transected preparations suggests that pontine circuits govern respiratory pattern formation. PMID:26888109

  20. The brain network reflecting bodily self-consciousness: a functional connectivity study

    OpenAIRE

    Ionta, Silvio; Martuzzi, Roberto; Salomon, Roy; Blanke, Olaf

    2014-01-01

    Several brain regions are important for processing self-location and first-person perspective, two important aspects of bodily self-consciousness. However, the interplay between these regions has not been clarified. In addition, while self-location and first-person perspective in healthy subjects are associated with bilateral activity in temporoparietal junction (TPJ), disturbed self-location and first-person perspective result from damage of only the right TPJ. Identifying the involved brain...

  1. Graph analysis of spontaneous brain network using EEG source connectivity

    OpenAIRE

    Kabbara, Aya; Falou, Wassim El; Khalil, Mohamad; Wendling, Fabrice; Hassan, Mahmoud

    2016-01-01

    Exploring the human brain networks during rest is a topic of great interest. Several structural and functional studies have previously been conducted to study the intrinsic brain networks. In this paper, we focus on investigating the human brain network topology using dense Electroencephalography (EEG) source connectivity approach. We applied graph theoretical methods on functional networks reconstructed from resting state data acquired using EEG in 14 healthy subjects. Our findings confirmed...

  2. Role of mitochondrial uncoupling protein-2 (UCP2 in higher brain functions, neuronal plasticity and network oscillation

    Directory of Open Access Journals (Sweden)

    Gretchen Hermes

    2016-06-01

    Conclusions: We conclude that disruptions in mitochondrial function may play a critical role in pathophysiology of mental illness. Specifically, we have shown that NMDA driven behavioral, synaptic, and brain oscillatory functions are impaired in UCP2 knockout mice.

  3. Semi-metric analysis of the functional brain network: Relationship with familial risk for psychotic disorder

    Directory of Open Access Journals (Sweden)

    Sanne Peeters

    2015-01-01

    Discussion: The results are suggestive of more dispersed network communication in patients with psychotic disorder, with some evidence for trait-based network alterations in high-schizotypy individuals. Dispersed communication may contribute to the clinical phenotype in psychotic disorder. In addition, higher SMP may contribute to neuro- and social cognition, independent of psychosis risk.

  4. Change in brain network topology as a function of treatment response in schizophrenia: a longitudinal resting-state fMRI study using graph theory.

    Science.gov (United States)

    Hadley, Jennifer Ann; Kraguljac, Nina Vanessa; White, David Matthew; Ver Hoef, Lawrence; Tabora, Janell; Lahti, Adrienne Carol

    2016-01-01

    A number of neuroimaging studies have provided evidence in support of the hypothesis that faulty interactions between spatially disparate brain regions underlie the pathophysiology of schizophrenia, but it remains unclear to what degree antipsychotic medications affect these. We hypothesized that the balance between functional integration and segregation of brain networks is impaired in unmedicated patients with schizophrenia, but that it can be partially restored by antipsychotic medications. We included 32 unmedicated patients with schizophrenia (SZ) and 32 matched healthy controls (HC) in this study. We obtained resting-state scans while unmedicated, and again after 6 weeks of treatment with risperidone to assess functional integration and functional segregation of brain networks using graph theoretical measures. Compared with HC, unmedicated SZ showed reduced global efficiency and increased clustering coefficients. This pattern of aberrant functional network integration and segregation was modulated with antipsychotic medications, but only in those who responded to treatment. Our work lends support to the concept of schizophrenia as a dysconnectivity syndrome, and suggests that faulty brain network topology in schizophrenia is modulated by antipsychotic medication as a function of treatment response. PMID:27336056

  5. Relationship between episodic memory and resting-state brain functional connectivity network in patients with Alzheimer’s disease and mild cognition impairment

    Institute of Scientific and Technical Information of China (English)

    吴钦娟

    2013-01-01

    Objective To explore the relationship between the scores of episodic memory (EM) encoding and retrieving and the resting-state changes of brain functional connectivity (FC) network of Alzheimer’s disease (AD) and mild cognition impairment (MCI) patients.Methods All

  6. Functional Disorganization of Small-World Brain Networks in mild Alzheimer’s Disease and amnestic Mild Cognitive Impairment: An EEG Study using Relative Wavelet Entropy (RWE

    Directory of Open Access Journals (Sweden)

    Christos A. Frantzidis

    2014-08-01

    Full Text Available Previous neuroscientific findings have linked Alzheimer’s disease (AD with less efficient information processing and brain network disorganization. However, pathological alterations of the brain networks during the preclinical phase of amnestic Mild Cognitive Impairment (aMCI remain largely unknown. The present study aimed at comparing patterns of the detection of functional disorganization in MCI relative to Mild Dementia (MD. Participants consisted of 23 cognitively healthy adults, 17 aMCI and 24 mild AD patients who underwent electroencephalographic (EEG data acquisition during a resting-state condition. Synchronization analysis through the Orthogonal Discrete Wavelet Transform (ODWT, and directional brain network analysis were applied on the EEG data. This computational model was performed for networks that have the same number of edges (N=500, 600, 700, 800 edges across all participants and groups (fixed density values. All groups exhibited a small-world (SW brain architecture. However, we found a significant reduction in the SW brain architecture in both aMCI and MD patients relative to the group of Healthy controls. This functional disorganization was also correlated with the participant’s generic cognitive status. The deterioration of the network’s organization was caused mainly by deficient local information processing as quantified by the mean cluster coefficient value. Functional hubs were identified through the normalized betweenness centrality metric. Analysis of the local characteristics showed relative hub preservation even with statistically significant reduced strength. Compensatory phenomena were also evident through the formation of additional hubs on left frontal and parietal regions. Our results indicate a declined functional network organization even during the prodromal phase. Degeneration is evident even in the preclinical phase and coexists with transient network reorganization due to compensation.

  7. Temporal evolution of brain reorganization under cross-modal training: insights into the functional architecture of encoding and retrieval networks

    Science.gov (United States)

    Likova, Lora T.

    2015-03-01

    This study is based on the recent discovery of massive and well-structured cross-modal memory activation generated in the primary visual cortex (V1) of totally blind people as a result of novel training in drawing without any vision (Likova, 2012). This unexpected functional reorganization of primary visual cortex was obtained after undergoing only a week of training by the novel Cognitive-Kinesthetic Method, and was consistent across pilot groups of different categories of visual deprivation: congenitally blind, late-onset blind and blindfolded (Likova, 2014). These findings led us to implicate V1 as the implementation of the theoretical visuo-spatial 'sketchpad' for working memory in the human brain. Since neither the source nor the subsequent 'recipient' of this non-visual memory information in V1 is known, these results raise a number of important questions about the underlying functional organization of the respective encoding and retrieval networks in the brain. To address these questions, an individual totally blind from birth was given a week of Cognitive-Kinesthetic training, accompanied by functional magnetic resonance imaging (fMRI) both before and just after training, and again after a two-month consolidation period. The results revealed a remarkable temporal sequence of training-based response reorganization in both the hippocampal complex and the temporal-lobe object processing hierarchy over the prolonged consolidation period. In particular, a pattern of profound learning-based transformations in the hippocampus was strongly reflected in V1, with the retrieval function showing massive growth as result of the Cognitive-Kinesthetic memory training and consolidation, while the initially strong hippocampal response during tactile exploration and encoding became non-existent. Furthermore, after training, an alternating patch structure in the form of a cascade of discrete ventral regions underwent radical transformations to reach complete functional

  8. Functional Brain Imaging

    Directory of Open Access Journals (Sweden)

    K. Vessal

    2005-08-01

    Full Text Available Introduction & Background: The historical evolution of concepts of the mind has had a tremendous impact on human civilization. Aside from Smith’s surgical papyrus, there exists practically no documentation down to the era of Hippocrates. While in Corpus, the seat of all sensations is put in the brain, there is an amazing regression, for many centuries thereafter notably influenced by Aristotle, to displace it to the heart. This erroneous diversion promulgated in De Anima with minor corrections by Galen, has per-petuated to our time when we say, for example, that we love something with our very hearts or “knowing by heart” when we mean to memorize something. Avicenna challenged many of Aristotle’s ideas in El-monnafs (psychology section of Al Shafa, paving the road for the later European Renaissance. Cartesian choice of pineal body as the seat of soul in the first half of the 7th century was a fundamental departure from brain-soul dichotomy. It was followed by Gall’s pseudo-science, phrenology, as the first attempt of brain mapping in ascribing “mental faculties” to the speculative “organs” of the brain. Brain mapping through Functional Brain Imaging has flourished ex-tensively in the past decades -starting from PET with later substitution by fMRI- as robust tools for interro-gating mysteries of the brain. With a surprising pace of development, Functional Brain Imaging heralds a welcome adjunct to the science of radiology in ex-ploring mind and human behavior. Given the multi-tude of appropriate MRI machines operating across the country, attention to this aspect of imaging can invigorate research in radiology and boost generation of knowledge in this rapidly growing field. Recent advances in MRI fast imaging, fMRI, as well as clini-cal and spectroscopic imaging with present clinical application and future trends are discussed.

  9. Approach of Complex Networks for the Determination of Brain Death

    Institute of Scientific and Technical Information of China (English)

    SUN Wei-Gang; CAO Jian-Ting; WANG Ru-Bin

    2011-01-01

    In clinical practice, brain death is the irreversible end of all brain activity. Compared to current statistical methods for the determination of brain death, we focus on the approach of complex networks for real-world electroencephalography in its determination. Brain functional networks constructed by correlation analysis are derived, and statistical network quantities used for distinguishing the patients in coma or brain death state, such as average strength, clustering coefficient and average path length, are calculated. Numerical results show that the values of network quantities of patients in coma state are larger than those of patients in brain death state. Our Sndings might provide valuable insights on the determination of brain death.%@@ In clinical practice, brain death is the irreversible end of all brain activity.Compared to current statistical methods for the determination of brain death, we focus on the approach of complex networks for real-world electroencephalography in its determination.Brain functional networks constructed by correlation analysis axe derived, and statistical network quantities used for distinguishing the patients in coma or brain death state, such as average strength, clustering coefficient and average path length, are calculated.Numerical results show that the values of network quantities of patients in coma state are larger than those of patients in brain death state.Our findings might provide valuable insights on the determination of brain death.

  10. Task-Based Cohesive Evolution of Dynamic Brain Networks

    Science.gov (United States)

    Davison, Elizabeth

    2014-03-01

    Applications of graph theory to neuroscience have resulted in significant progress towards a mechanistic understanding of the brain. Functional network representation of the brain has linked efficient network structure to psychometric intelligence and altered configurations with disease. Dynamic graphs provide us with tools to further study integral properties of the brain; specifically, the mathematical convention of hyperedges has allowed us to study the brain's cross-linked structure. Hyperedges capture the changes in network structure by identifying groups of brain regions with correlation patterns that change cohesively through time. We performed a hyperedge analysis on functional MRI data from 86 subjects and explored the cohesive evolution properties of their functional brain networks as they performed a series of tasks. Our results establish the hypergraph as a useful measure in understanding functional brain dynamics over tasks and reveal characteristic differences in the co-evolution structure of task-specific networks.

  11. Functional Magnetic Resonance Imaging of Chronic Dysarthric Speech after Childhood Brain Injury: Reliance on a Left-Hemisphere Compensatory Network

    Science.gov (United States)

    Morgan, Angela T.; Masterton, Richard; Pigdon, Lauren; Connelly, Alan; Liegeois, Frederique J.

    2013-01-01

    Severe and persistent speech disorder, dysarthria, may be present for life after brain injury in childhood, yet the neural correlates of this chronic disorder remain elusive. Although abundant literature is available on language reorganization after lesions in childhood, little is known about the capacity of motor speech networks to reorganize…

  12. The Role of Nonlinearity in Computing Graph-Theoretical Properties of Resting-State Functional Magnetic Resonance Imaging Brain Networks

    Czech Academy of Sciences Publication Activity Database

    Hartman, David; Hlinka, Jaroslav; Paluš, Milan; Mantini, D.; Corbetta, M.

    2011-01-01

    Roč. 21, č. 1 (2011), art.no 013119. ISSN 1054-1500 R&D Projects: GA MŠk 7E08027 Institutional research plan: CEZ:AV0Z10300504 Keywords : complex network * fMRI * brain connectivity * nonlinear * mutual information * correlation Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.076, year: 2011

  13. Patterns of Cortical Oscillations Organize Neural Activity into Whole-Brain Functional Networks Evident in the fMRI BOLD Signal.

    Science.gov (United States)

    Whitman, Jennifer C; Ward, Lawrence M; Woodward, Todd S

    2013-01-01

    Recent findings from electrophysiology and multimodal neuroimaging have elucidated the relationship between patterns of cortical oscillations evident in EEG/MEG and the functional brain networks evident in the BOLD signal. Much of the existing literature emphasized how high-frequency cortical oscillations are thought to coordinate neural activity locally, while low-frequency oscillations play a role in coordinating activity between more distant brain regions. However, the assignment of different frequencies to different spatial scales is an oversimplification. A more informative approach is to explore the arrangements by which these low- and high-frequency oscillations work in concert, coordinating neural activity into whole-brain functional networks. When relating such networks to the BOLD signal, we must consider how the patterns of cortical oscillations change at the same speed as cognitive states, which often last less than a second. Consequently, the slower BOLD signal may often reflect the summed neural activity of several transient network configurations. This temporal mismatch can be circumvented if we use spatial maps to assess correspondence between oscillatory networks and BOLD networks. PMID:23504590

  14. Patterns of cortical oscillations organize neural activity into whole-brain functional networks evident in the fMRI BOLD signal

    Directory of Open Access Journals (Sweden)

    Jennifer C Whitman

    2013-03-01

    Full Text Available Recent findings from electrophysiology and multimodal neuroimaging have elucidated the relationship between patterns of cortical oscillations evident in EEG / MEG and the functional brain networks evident in the BOLD signal. Much of the existing literature emphasized how high-frequency cortical oscillations are thought to coordinate neural activity locally, while low-frequency oscillations play a role in coordinating activity between more distant brain regions. However, the assignment of different frequencies to different spatial scales is an oversimplification. A more informative approach is to explore the arrangements by which these low- and high-frequency oscillations work in concert, coordinating neural activity into whole-brain functional networks. When relating such networks to the BOLD signal, we must consider how the patterns of cortical oscillations change at the same speed as cognitive states, which often last less than a second. Consequently, the slower BOLD signal may often reflect the summed neural activity of several transient network configurations. This temporal mismatch can be circumvented if we use spatial maps to assess correspondence between oscillatory networks and BOLD networks.

  15. Brain and Cognitive Reserve: Translation via Network Control Theory

    OpenAIRE

    Medaglia, John D.; Pasqualetti, Fabio; Hamilton, Roy H.; Thompson-Schill, Sharon L.; Bassett, Danielle S.

    2016-01-01

    Traditional approaches to understanding the brain's resilience to neuropathology have identified neurophysiological variables, often described as brain or cognitive 'reserve,' associated with better outcomes. However, mechanisms of function and resilience in large-scale brain networks remain poorly understood. Dynamic network theory may provide a basis for substantive advances in understanding functional resilience in the human brain. In this perspective, we describe recent theoretical approa...

  16. Strengthening connections: functional connectivity and brain plasticity

    OpenAIRE

    Kelly, Clare; Castellanos, F. Xavier

    2014-01-01

    The ascendancy of functional neuroimaging has facilitated the addition of network-based approaches to the neuropsychologist’s toolbox for evaluating the sequelae of brain insult. In particular, intrinsic functional connectivity (iFC) mapping of resting state fMRI (R-fMRI) data constitutes an ideal approach to measuring macro-scale networks in the human brain. Beyond the value of iFC mapping for charting how the functional topography of the brain is altered by insult and injury, iFC analyses c...

  17. Spatial and functional architecture of the mammalian brain stem respiratory network: a hierarchy of three oscillatory mechanisms.

    Science.gov (United States)

    Smith, J C; Abdala, A P L; Koizumi, H; Rybak, I A; Paton, J F R

    2007-12-01

    Mammalian central pattern generators (CPGs) producing rhythmic movements exhibit extremely robust and flexible behavior. Network architectures that enable these features are not well understood. Here we studied organization of the brain stem respiratory CPG. By sequential rostral to caudal transections through the pontine-medullary respiratory network within an in situ perfused rat brain stem-spinal cord preparation, we showed that network dynamics reorganized and new rhythmogenic mechanisms emerged. The normal three-phase respiratory rhythm transformed to a two-phase and then to a one-phase rhythm as the network was reduced. Expression of the three-phase rhythm required the presence of the pons, generation of the two-phase rhythm depended on the integrity of Bötzinger and pre-Bötzinger complexes and interactions between them, and the one-phase rhythm was generated within the pre-Bötzinger complex. Transformation from the three-phase to a two-phase pattern also occurred in intact preparations when chloride-mediated synaptic inhibition was reduced. In contrast to the three-phase and two-phase rhythms, the one-phase rhythm was abolished by blockade of persistent sodium current (I(NaP)). A model of the respiratory network was developed to reproduce and explain these observations. The model incorporated interacting populations of respiratory neurons within spatially organized brain stem compartments. Our simulations reproduced the respiratory patterns recorded from intact and sequentially reduced preparations. Our results suggest that the three-phase and two-phase rhythms involve inhibitory network interactions, whereas the one-phase rhythm depends on I(NaP). We conclude that the respiratory network has rhythmogenic capabilities at multiple levels of network organization, allowing expression of motor patterns specific for various physiological and pathophysiological respiratory behaviors. PMID:17913982

  18. Functional brain imaging

    International Nuclear Information System (INIS)

    Functional magnetic resonance imaging (fMRI) is a non-invasive method that has become one of the major tools for understanding human brain function and in recent years has also been developed for clinical applications. Changes in hemodynamic signals correspond to changes in neuronal activity with good spatial and temporal resolution in fMRI. Using high-field MR systems and increasingly dedicated statistics and postprocessing, activated brain areas can be detected and superimposed on anatomical images. Currently, fMRI data are often combined in multimodal imaging, e. g. with diffusion tensor imaging (DTI) sequences. This method is helping to further understand the physiology of cognitive brain processes and is also being used in a number of clinical applications. In addition to the blood oxygenation level-dependent (BOLD) signals, this article deals with the construction of fMRI investigations, selection of paradigms and evaluation in the clinical routine. Clinically, this method is mainly used in the planning of brain surgery, analyzing the location of brain tumors in relation to eloquent brain areas and the lateralization of language processing. As the BOLD signal is dependent on the strength of the magnetic field as well as other limitations, an overview of recent developments is given. Increases of magnetic field strength (7 T), available head coils and advances in MRI analytical methods have led to constant improvement in fMRI signals and experimental design. Especially the depiction of eloquent brain regions can be done easily and quickly and has become an essential part of presurgical planning. (orig.)

  19. The Effect of Souvenaid on Functional Brain Network Organisation in Patients with Mild Alzheimer’s Disease: A Randomised Controlled Study

    OpenAIRE

    de Waal, Hanneke; Stam, Cornelis J.; Lansbergen, Marieke M.; Wieggers, Rico L; Kamphuis, Patrick J. G. H.; Scheltens, Philip; Maestú, Fernando; van Straaten, Elisabeth C. W.

    2014-01-01

    Background Synaptic loss is a major hallmark of Alzheimer’s disease (AD). Disturbed organisation of large-scale functional brain networks in AD might reflect synaptic loss and disrupted neuronal communication. The medical food Souvenaid, containing the specific nutrient combination Fortasyn Connect, is designed to enhance synapse formation and function and has been shown to improve memory performance in patients with mild AD in two randomised controlled trials. Objective To explore the effect...

  20. Altered brain activation and functional connectivity in working memory related networks in patients with type 2 diabetes: An ICA-based analysis

    OpenAIRE

    Yang Zhang; Shan Lu; Chunlei Liu; Huimei Zhang; Xuanhe Zhou; Changlin Ni; Wen Qin; Quan Zhang

    2016-01-01

    Type 2 diabetes mellitus (T2DM) can cause multidimensional cognitive deficits, among which working memory (WM) is usually involved at an early stage. However, the neural substrates underlying impaired WM in T2DM patients are still unclear. To clarify this issue, we utilized functional magnetic resonance imaging (fMRI) and independent component analysis to evaluate T2DM patients for alterations in brain activation and functional connectivity (FC) in WM networks and to determine their associati...

  1. Brain network adaptability across task states.

    Directory of Open Access Journals (Sweden)

    Elizabeth N Davison

    2015-01-01

    Full Text Available Activity in the human brain moves between diverse functional states to meet the demands of our dynamic environment, but fundamental principles guiding these transitions remain poorly understood. Here, we capitalize on recent advances in network science to analyze patterns of functional interactions between brain regions. We use dynamic network representations to probe the landscape of brain reconfigurations that accompany task performance both within and between four cognitive states: a task-free resting state, an attention-demanding state, and two memory-demanding states. Using the formalism of hypergraphs, we identify the presence of groups of functional interactions that fluctuate coherently in strength over time both within (task-specific and across (task-general brain states. In contrast to prior emphases on the complexity of many dyadic (region-to-region relationships, these results demonstrate that brain adaptability can be described by common processes that drive the dynamic integration of cognitive systems. Moreover, our results establish the hypergraph as an effective measure for understanding functional brain dynamics, which may also prove useful in examining cross-task, cross-age, and cross-cohort functional change.

  2. Aberrant Functional Connectivity in the Default Mode and Central Executive Networks in Subjects with Schizophrenia – A Whole-Brain Resting-State ICA Study

    Science.gov (United States)

    Littow, Harri; Huossa, Ville; Karjalainen, Sami; Jääskeläinen, Erika; Haapea, Marianne; Miettunen, Jouko; Tervonen, Osmo; Isohanni, Matti; Nikkinen, Juha; Veijola, Juha; Murray, Graham; Kiviniemi, Vesa J.

    2015-01-01

    Neurophysiological changes of schizophrenia are currently linked to disturbances in connectivity between functional brain networks. Functional magnetic resonance imaging studies on schizophrenia have focused on a few selected networks. Also previously, it has not been possible to discern whether the functional alterations in schizophrenia originate from spatial shifting or amplitude alterations of functional connectivity. In this study, we aim to discern the differences in schizophrenia patients with respect to spatial shifting vs. signal amplitude changes in functional connectivity in the whole-brain connectome. We used high model order-independent component analysis to study some 40 resting-state networks (RSN) covering the whole cortex. Group differences were analyzed with dual regression coupled with y-concat correction for multiple comparisons. We investigated the RSNs with and without variance normalization in order to discern spatial shifting from signal amplitude changes in 43 schizophrenia patients and matched controls from the Northern Finland 1966 Birth Cohort. Voxel-level correction for multiple comparisons revealed 18 RSNs with altered functional connectivity, 6 of which had both spatial and signal amplitude changes. After adding the multiple comparison, y-concat correction to the analysis for including the 40 RSNs as well, we found that four RSNs showed still changes. These robust changes actually seem encompass parcellations of the default mode network and central executive networks. These networks both have spatially shifted connectivity and abnormal signal amplitudes. Interestingly the networks seem to mix their functional representations in areas like left caudate nucleus and dorsolateral prefrontal cortex. These changes overlapped with areas that have been related to dopaminergic alterations in patients with schizophrenia compared to controls. PMID:25767449

  3. Functional connectivity in the default network during resting state is preserved in a vegetative but not in a brain dead patient.

    Science.gov (United States)

    Boly, M; Tshibanda, L; Vanhaudenhuyse, A; Noirhomme, Q; Schnakers, C; Ledoux, D; Boveroux, P; Garweg, C; Lambermont, B; Phillips, C; Luxen, A; Moonen, G; Bassetti, C; Maquet, P; Laureys, S

    2009-08-01

    Recent studies on spontaneous fluctuations in the functional MRI blood oxygen level-dependent (BOLD) signal in awake healthy subjects showed the presence of coherent fluctuations among functionally defined neuroanatomical networks. However, the functional significance of these spontaneous BOLD fluctuations remains poorly understood. By means of 3 T functional MRI, we demonstrate absent cortico-thalamic BOLD functional connectivity (i.e. between posterior cingulate/precuneal cortex and medial thalamus), but preserved cortico-cortical connectivity within the default network in a case of vegetative state (VS) studied 2.5 years following cardio-respiratory arrest, as documented by extensive behavioral and paraclinical assessments. In the VS patient, as in age-matched controls, anticorrelations could also be observed between posterior cingulate/precuneus and a previously identified task-positive cortical network. Both correlations and anticorrelations were significantly reduced in VS as compared to controls. A similar approach in a brain dead patient did not show any such long-distance functional connectivity. We conclude that some slow coherent BOLD fluctuations previously identified in healthy awake human brain can be found in alive but unaware patients, and are thus unlikely to be uniquely due to ongoing modifications of conscious thoughts. Future studies are needed to give a full characterization of default network connectivity in the VS patients population. PMID:19350563

  4. Mapping brain function to brain anatomy

    International Nuclear Information System (INIS)

    In Imaging the human brain, MRI is commonly used to reveal anatomical structure, while PET is used to reveal tissue function. This paper presents a protocol for correlating data between these two imaging modalities; this correlation can provide in vivo regional measurements of brain function which are essential to our understanding of the human brain. The authors propose a general protocol to standardize the acquisition and analysis of functional image data. First, MR and PET images are collected to form three-dimensional volumes of structural and functional image data. Second, these volumes of image data are corrected for distortions inherent in each imaging modality. Third, the image volumes are correlated to provide correctly aligned structural and functional images. The functional images are then mapped onto the structural images in both two-dimensional and three-dimensional representations. Finally, morphometric techniques can be used to provide statistical measures of the structure and function of the human brain

  5. Spectral properties of the temporal evolution of brain network structure.

    Science.gov (United States)

    Wang, Rong; Zhang, Zhen-Zhen; Ma, Jun; Yang, Yong; Lin, Pan; Wu, Ying

    2015-12-01

    The temporal evolution properties of the brain network are crucial for complex brain processes. In this paper, we investigate the differences in the dynamic brain network during resting and visual stimulation states in a task-positive subnetwork, task-negative subnetwork, and whole-brain network. The dynamic brain network is first constructed from human functional magnetic resonance imaging data based on the sliding window method, and then the eigenvalues corresponding to the network are calculated. We use eigenvalue analysis to analyze the global properties of eigenvalues and the random matrix theory (RMT) method to measure the local properties. For global properties, the shifting of the eigenvalue distribution and the decrease in the largest eigenvalue are linked to visual stimulation in all networks. For local properties, the short-range correlation in eigenvalues as measured by the nearest neighbor spacing distribution is not always sensitive to visual stimulation. However, the long-range correlation in eigenvalues as evaluated by spectral rigidity and number variance not only predicts the universal behavior of the dynamic brain network but also suggests non-consistent changes in different networks. These results demonstrate that the dynamic brain network is more random for the task-positive subnetwork and whole-brain network under visual stimulation but is more regular for the task-negative subnetwork. Our findings provide deeper insight into the importance of spectral properties in the functional brain network, especially the incomparable role of RMT in revealing the intrinsic properties of complex systems. PMID:26723151

  6. Medial Prefrontal and Anterior Insular Connectivity in Early Schizophrenia and Major Depressive Disorder: A Resting Functional MRI Evaluation of Large-Scale Brain Network Models

    OpenAIRE

    Penner, Jacob; Ford, Kristen A.; Taylor, Reggie; Schaefer, Betsy; Théberge, Jean; Neufeld, Richard W. J.; Osuch, Elizabeth A.; Menon, Ravi S.; Rajakumar, Nagalingam; Allman, John M.; Williamson, Peter C.

    2016-01-01

    Anomalies in the medial prefrontal cortex, anterior insulae, and large-scale brain networks associated with them have been proposed to underlie the pathophysiology of schizophrenia and major depressive disorder (MDD). In this study, we examined the connectivity of the medial prefrontal cortices and anterior insulae in 24 healthy controls, 24 patients with schizophrenia, and 24 patients with MDD early in illness with seed-based resting state functional magnetic resonance imaging analysis using...

  7. Resting network plasticity following brain injury.

    Directory of Open Access Journals (Sweden)

    Toru Nakamura

    Full Text Available The purpose of this study was to examine neural network properties at separate time-points during recovery from traumatic brain injury (TBI using graph theory. Whole-brain analyses of the topological properties of the fMRI signal were conducted in 6 participants at 3 months and 6 months following severe TBI. Results revealed alterations of network properties including a change in the degree distribution, reduced overall strength in connectivity, and increased "small-worldness" from 3 months to 6 months post injury. The findings here indicate that, during recovery from injury, the strength but not the number of network connections diminishes, so that over the course of recovery, the network begins to approximate what is observed in healthy adults. These are the first data examining functional connectivity in a disrupted neural system during recovery.

  8. Early Brain Response to Low-Dose Radiation Exposure Involves Molecular Networks and Pathways Associated with Cognitive Functions, Advanced Aging and Alzheimer's Disease

    Energy Technology Data Exchange (ETDEWEB)

    Lowe, Xiu R; Bhattacharya, Sanchita; Marchetti, Francesco; Wyrobek, Andrew J.

    2008-06-06

    Understanding the cognitive and behavioral consequences of brain exposures to low-dose ionizing radiation has broad relevance for health risks from medical radiation diagnostic procedures, radiotherapy, environmental nuclear contamination, as well as earth orbit and space missions. Analyses of transcriptome profiles of murine brain tissue after whole-body radiation showed that low-dose exposures (10 cGy) induced genes not affected by high dose (2 Gy), and low-dose genes were associated with unique pathways and functions. The low-dose response had two major components: pathways that are consistently seen across tissues, and pathways that were brain tissue specific. Low-dose genes clustered into a saturated network (p < 10{sup -53}) containing mostly down-regulated genes involving ion channels, long-term potentiation and depression, vascular damage, etc. We identified 9 neural signaling pathways that showed a high degree of concordance in their transcriptional response in mouse brain tissue after low-dose radiation, in the aging human brain (unirradiated), and in brain tissue from patients with Alzheimer's disease. Mice exposed to high-dose radiation did not show these effects and associations. Our findings indicate that the molecular response of the mouse brain within a few hours after low-dose irradiation involves the down-regulation of neural pathways associated with cognitive dysfunctions that are also down regulated in normal human aging and Alzheimer's disease.

  9. Early Brain Response to Low-Dose Radiation Exposure Involves Molecular Networks and Pathways Associated with Cognitive Functions, Advanced Aging and Alzheimer's Disease

    International Nuclear Information System (INIS)

    Understanding the cognitive and behavioral consequences of brain exposures to low-dose ionizing radiation has broad relevance for health risks from medical radiation diagnostic procedures, radiotherapy, environmental nuclear contamination, as well as earth orbit and space missions. Analyses of transcriptome profiles of murine brain tissue after whole-body radiation showed that low-dose exposures (10 cGy) induced genes not affected by high dose (2 Gy), and low-dose genes were associated with unique pathways and functions. The low-dose response had two major components: pathways that are consistently seen across tissues, and pathways that were brain tissue specific. Low-dose genes clustered into a saturated network (p -53) containing mostly down-regulated genes involving ion channels, long-term potentiation and depression, vascular damage, etc. We identified 9 neural signaling pathways that showed a high degree of concordance in their transcriptional response in mouse brain tissue after low-dose radiation, in the aging human brain (unirradiated), and in brain tissue from patients with Alzheimer's disease. Mice exposed to high-dose radiation did not show these effects and associations. Our findings indicate that the molecular response of the mouse brain within a few hours after low-dose irradiation involves the down-regulation of neural pathways associated with cognitive dysfunctions that are also down regulated in normal human aging and Alzheimer's disease

  10. Dynamic neuroimaging of brain function.

    Science.gov (United States)

    Simpson, G V; Pflieger, M E; Foxe, J J; Ahlfors, S P; Vaughan, H G; Hrabe, J; Ilmoniemi, R J; Lantos, G

    1995-09-01

    To fully characterize the brain processes underlying sensorimotor and cognitive function, the spatial distribution of active regions, their interconnected regions must be measured. We describe methods for imaging brain sources from surface-recorded EEG and magnetoencephalographic data, called electromagnetic source imaging (EMSI). EMSI provides brain source locations within the common framework of magnetic resonance (MR) images of brain anatomy. This allows integration of data from other functional brain imaging methods, like positron emission tomography and functional MR imaging, which can improve the accuracy of EMSI localization. EMSI also provides submillisecond temporal resolution of the dynamic processes within brain systems. Examples are given of applications to visual perceptual and attentional studies. PMID:8576389

  11. Acupuncture Induces Time-Dependent Remodelling Brain Network on the Stable Somatosensory First-Ever Stroke Patients: Combining Diffusion Tensor and Functional MR Imaging

    Directory of Open Access Journals (Sweden)

    Lijun Bai

    2014-01-01

    Full Text Available Different treatment interventions induce distinct remodelling of network architecture of entire motor system. Acupuncture has been proved to be of a promising efficacy in motor recovery. However, it is still unclear whether the reorganization of motor-related brain network underlying acupuncture is related with time since stroke and severity of deficit at baseline. The aim of study was to characterize the relation between motor-related brain organization following acupuncture and white matter microstructural changes at an interval of two weeks. We demonstrated that acupuncture induced differential reorganization of motor-related network for stroke patients as time-lapse since stroke. At the baseline, acupuncture can induce the increased functional connectivity between the left primary motor cortex (M1 and the right M1, premotor cortex, supplementary motor area (SMA, thalamus, and cerebellum. After two-week recovery, the increased functional connectivity of the left M1 was more widely distributed and primarily located in the insula, cerebellum, basal ganglia, and SMA. Furthermore, a significant negative relation existed between the FA value in the left M1 at the baseline scanning and node centrality of this region following acupuncture for both baseline and two-week recovery. Our findings may shed a new insight on understanding the reorganization of motor-related theory underlying motor impairments after brain lesions in stroke patients.

  12. Cognition and brain functional aging

    Directory of Open Access Journals (Sweden)

    Hui-jie LI

    2014-03-01

    Full Text Available China has the largest population of elderly adults. Meanwhile, it is one of the countries showing fastest aging speed in the world. Aging processing is always companied with a series of brain structural and functional changes, which result in the decline of processing speed, working memory, long-term memory and executive function, etc. The studies based on functional magnetic resonance imaging (fMRI found certain aging effects on brain function activation, spontaneous activity and functional connectivity in old people. However, few studies have explored the brain functional curve during the aging process while most previous studies explored the differences in the brain function between young people and old people. Delineation of the human brain functional aging curve will promote the understanding of brain aging mechanisms and support the normal aging monitoring and early detection of abnormal aging changes. doi: 10.3969/j.issn.1672-6731.2014.03.005

  13. Flexible brain network reconfiguration supporting inhibitory control.

    Science.gov (United States)

    Spielberg, Jeffrey M; Miller, Gregory A; Heller, Wendy; Banich, Marie T

    2015-08-11

    The ability to inhibit distracting stimuli from interfering with goal-directed behavior is crucial for success in most spheres of life. Despite an abundance of studies examining regional brain activation, knowledge of the brain networks involved in inhibitory control remains quite limited. To address this critical gap, we applied graph theory tools to functional magnetic resonance imaging data collected while a large sample of adults (n = 101) performed a color-word Stroop task. Higher demand for inhibitory control was associated with restructuring of the global network into a configuration that was more optimized for specialized processing (functional segregation), more efficient at communicating the output of such processing across the network (functional integration), and more resilient to potential interruption (resilience). In addition, there were regional changes with right inferior frontal sulcus and right anterior insula occupying more central positions as network hubs, and dorsal anterior cingulate cortex becoming more tightly coupled with its regional subnetwork. Given the crucial role of inhibitory control in goal-directed behavior, present findings identifying functional network organization supporting inhibitory control have the potential to provide additional insights into how inhibitory control may break down in a wide variety of individuals with neurological or psychiatric difficulties. PMID:26216985

  14. Can you hear me now? Musical training shapes functional brain networks for selective auditory attention and hearing speech in noise

    Directory of Open Access Journals (Sweden)

    Dana L Strait

    2011-06-01

    Full Text Available Even in the quietest of rooms, our senses are perpetually inundated by a barrage of sounds, requiring the auditory system to adapt to a variety of listening conditions in order to extract signals of interest (e.g., one speaker’s voice amidst others. Brain networks that promote selective attention are thought to sharpen the neural encoding of a target signal, suppressing competing sounds and enhancing perceptual performance. Here, we ask: does musical training benefit cortical mechanisms that underlie selective attention to speech? To answer this question, we assessed the impact of selective auditory attention on cortical auditory-evoked response variability in musicians and nonmusicians. Outcomes indicate strengthened brain networks for selective auditory attention in musicians in that musicians but not nonmusicians demonstrate decreased prefrontal response variability with auditory attention. Results are interpreted in the context of previous work from our laboratory documenting perceptual and subcortical advantages in musicians for the hearing and neural encoding of speech in background noise. Musicians’ neural proficiency for selectively engaging and sustaining auditory attention to language indicates a potential benefit of music for auditory training. Given the importance of auditory attention for the development of language-related skills, musical training may aid in the prevention, habilitation and remediation of children with a wide range of attention-based language and learning impairments.

  15. Multi-scale brain networks

    CERN Document Server

    Betzel, Richard F

    2016-01-01

    The network architecture of the human brain has become a feature of increasing interest to the neuroscientific community, largely because of its potential to illuminate human cognition, its variation over development and aging, and its alteration in disease or injury. Traditional tools and approaches to study this architecture have largely focused on single scales -- of topology, time, and space. Expanding beyond this narrow view, we focus this review on pertinent questions and novel methodological advances for the multi-scale brain. We separate our exposition into content related to multi-scale topological structure, multi-scale temporal structure, and multi-scale spatial structure. In each case, we recount empirical evidence for such structures, survey network-based methodological approaches to reveal these structures, and outline current frontiers and open questions. Although predominantly peppered with examples from human neuroimaging, we hope that this account will offer an accessible guide to any neuros...

  16. Network effects of deep brain stimulation.

    Science.gov (United States)

    Alhourani, Ahmad; McDowell, Michael M; Randazzo, Michael J; Wozny, Thomas A; Kondylis, Efstathios D; Lipski, Witold J; Beck, Sarah; Karp, Jordan F; Ghuman, Avniel S; Richardson, R Mark

    2015-10-01

    The ability to differentially alter specific brain functions via deep brain stimulation (DBS) represents a monumental advance in clinical neuroscience, as well as within medicine as a whole. Despite the efficacy of DBS in the treatment of movement disorders, for which it is often the gold-standard therapy when medical management becomes inadequate, the mechanisms through which DBS in various brain targets produces therapeutic effects is still not well understood. This limited knowledge is a barrier to improving efficacy and reducing side effects in clinical brain stimulation. A field of study related to assessing the network effects of DBS is gradually emerging that promises to reveal aspects of the underlying pathophysiology of various brain disorders and their response to DBS that will be critical to advancing the field. This review summarizes the nascent literature related to network effects of DBS measured by cerebral blood flow and metabolic imaging, functional imaging, and electrophysiology (scalp and intracranial electroencephalography and magnetoencephalography) in order to establish a framework for future studies. PMID:26269552

  17. Macroscopic networks in the human brain: mapping connectivity in healthy and damaged brains

    NARCIS (Netherlands)

    Nijhuis, E.H.J.

    2013-01-01

    The human brain contains a network of interconnected neurons. Recent advances in functional and structural in-vivo magnetic resonance neuroimaging (MRI) techniques have provided opportunities to model the networks of the human brain on a macroscopic scale. This dissertation investigates the possibil

  18. Altered brain activation and functional connectivity in working memory related networks in patients with type 2 diabetes: An ICA-based analysis.

    Science.gov (United States)

    Zhang, Yang; Lu, Shan; Liu, Chunlei; Zhang, Huimei; Zhou, Xuanhe; Ni, Changlin; Qin, Wen; Zhang, Quan

    2016-01-01

    Type 2 diabetes mellitus (T2DM) can cause multidimensional cognitive deficits, among which working memory (WM) is usually involved at an early stage. However, the neural substrates underlying impaired WM in T2DM patients are still unclear. To clarify this issue, we utilized functional magnetic resonance imaging (fMRI) and independent component analysis to evaluate T2DM patients for alterations in brain activation and functional connectivity (FC) in WM networks and to determine their associations with cognitive and clinical variables. Twenty complication-free T2DM patients and 19 matched healthy controls (HCs) were enrolled, and fMRI data were acquired during a block-designed 1-back WM task. The WM metrics of the T2DM patients showed no differences compared with those of the HCs, except for a slightly lower accuracy rate in the T2DM patients. Compared with the HCs, the T2DM patients demonstrated increased activation within their WM fronto-parietal networks, and activation strength was significantly correlated with WM performance. The T2DM patients also showed decreased FC within and between their WM networks. Our results indicate that the functional integration of WM sub-networks was disrupted in the complication-free T2DM patients and that strengthened regional activity in fronto-parietal networks may compensate for the WM impairment caused by T2DM. PMID:27021340

  19. 基于脑电和磁刺激的脑功能网络研究%Study of Brain Functional Network Based on Electroencephalogram and Magnetic Stimulation

    Institute of Scientific and Technical Information of China (English)

    付灵弟; 徐桂芝; 郭苗苗; 尹宁; 于洪丽

    2015-01-01

    大脑的结构和功能具有高度复杂性,其功能执行需要依赖于脑功能区之间的相互作用所构成的网络实现。脑电( EEG)作为一种无创医学检测技术因包含了大量的生理、病理信息且能够反映大脑的功能活动状态,被广泛应用于脑科学以及认知神经科学的研究中。经颅磁刺激( TMS)技术作为一种新型的刺激方式,因具有众多显著优势被应用于临床研究并在人体神经功能调控、疾病治疗以及康复理疗等方面表现出很好的应用前景。鉴于此,本文首先分析了脑网络研究的必要性及迫切性,回顾了近年来国内外基于EEG、功能磁共振成像( fMRI)等技术的脑功能网络研究成果,重点介绍了基于EEG和TMS技术的脑功能网络的构建与分析,最后对脑网络研究中存在的问题及该领域面临的挑战进行了讨论。%The structure and function of the brain are highly complex, and the implementation of brain function depends on the regional connections.Electroencephalogram ( EEG) , a noninvasive medical de-tection technique, contains a large number of physiological and pathological information, and thus can be used to map functional activities of the brain, which is widely used in brain science and cognitive neuro-science research.Transcranial magnetic stimulation ( TMS) as a novel stimulus, demonstrates a promis-ing application prospect in clinical research including regulation of human neural function, disease treat-ment and rehabilitation therapy.In this paper, we analyze the necessity and urgency of brain network re-search, review the studies of brain functional network based on EEG and functional magnetic resonance imaging ( fMRI) , and highlight the construction and analysis of brain functional network based on EEG and TMS technology.Finally, this paper discusses key questions and the challenges in the field of brain network research.

  20. Atomoxetine Treatment Strengthens an Anti-Correlated Relationship between Functional Brain Networks in Medication-Naïve Adults with Attention-Deficit Hyperactivity Disorder: A Randomized Double-Blind Placebo-Controlled Clinical Trial

    OpenAIRE

    Lin, Hsiang-Yuan; Gau, Susan Shur-Fen

    2015-01-01

    Background: Although atomoxetine demonstrates efficacy in individuals with attention-deficit hyperactivity disorder, its treatment effects on brain resting-state functional connectivity remain unknown. Therefore, we aimed to investigate major brain functional networks in medication-naïve adults with attention-deficit hyperactivity disorder and the efficacy of atomoxetine treatment on resting-state functional connectivity. Methods: After collecting baseline resting-state functional MRI scans f...

  1. RIDT/Malta Neuroscience Network (MNN) Brain Campaign 2016

    OpenAIRE

    Kenely, Wilfred; Malta Neuroscience Network (MNN); University of Malta Research Trust (RIDT)

    2015-01-01

    The University of Malta Research Trust (RIDT), in collaboration with the Malta Neuroscience Network (MNN), has chosen The Brain as its main campaign for 2016. The campaign will have two parallel strands - one strand promoting brain awareness and the other a fund-raising campaign for research in brain disorders. The main objective of the fi rst strand is for the public to understand the brain and its functions and is intended to bring together scientists and the communi...

  2. Generalized Network Externality Function

    OpenAIRE

    A. Paothong; G.S. Ladde

    2012-01-01

    In this work, we focus on the development of mathematical modeling of network externality processes. The introduction of the generalized network externality function provides a unified source of a tool for developing and analyzing the planning, policy and performance of the network externality process and network goods/services in a systematic way. This leads to fulfill all existing network externality assumptions as special cases. We study its properties and applications. This study provides...

  3. Complex brain networks: From topological communities to clustered dynamics

    Indian Academy of Sciences (India)

    Lucia Zemanová; Gorka Zamora-López; Changsong Zhou; Jürgen Kurths

    2008-06-01

    Recent research has revealed a rich and complicated network topology in the cortical connectivity of mammalian brains. A challenging task is to understand the implications of such network structures on the functional organisation of the brain activities. We investigate synchronisation dynamics on the corticocortical network of the cat by modelling each node of the network (cortical area) with a subnetwork of interacting excitable neurons. We find that this network of networks displays clustered synchronisation behaviour and the dynamical clusters closely coincide with the topological community structures observed in the anatomical network. The correlation between the firing rate of the areas and the areal intensity is additionally examined. Our results provide insights into the relationship between the global organisation and the functional specialisation of the brain cortex.

  4. Scaling in topological properties of brain networks.

    Science.gov (United States)

    Singh, Soibam Shyamchand; Khundrakpam, Budhachandra; Reid, Andrew T; Lewis, John D; Evans, Alan C; Ishrat, Romana; Sharma, B Indrajit; Singh, R K Brojen

    2016-01-01

    The organization in brain networks shows highly modular features with weak inter-modular interaction. The topology of the networks involves emergence of modules and sub-modules at different levels of constitution governed by fractal laws that are signatures of self-organization in complex networks. The modular organization, in terms of modular mass, inter-modular, and intra-modular interaction, also obeys fractal nature. The parameters which characterize topological properties of brain networks follow one parameter scaling theory in all levels of network structure, which reveals the self-similar rules governing the network structure. Further, the calculated fractal dimensions of brain networks of different species are found to decrease when one goes from lower to higher level species which implicates the more ordered and self-organized topography at higher level species. The sparsely distributed hubs in brain networks may be most influencing nodes but their absence may not cause network breakdown, and centrality parameters characterizing them also follow one parameter scaling law indicating self-similar roles of these hubs at different levels of organization in brain networks. The local-community-paradigm decomposition plot and calculated local-community-paradigm-correlation co-efficient of brain networks also shows the evidence for self-organization in these networks. PMID:27112129

  5. Cocaine addiction related reproducible brain regions of abnormal default-mode network functional connectivity: a group ICA study with different model orders.

    Science.gov (United States)

    Ding, Xiaoyu; Lee, Seong-Whan

    2013-08-26

    Model order selection in group independent component analysis (ICA) has a significant effect on the obtained components. This study investigated the reproducible brain regions of abnormal default-mode network (DMN) functional connectivity related with cocaine addiction through different model order settings in group ICA. Resting-state fMRI data from 24 cocaine addicts and 24 healthy controls were temporally concatenated and processed by group ICA using model orders of 10, 20, 30, 40, and 50, respectively. For each model order, the group ICA approach was repeated 100 times using the ICASSO toolbox and after clustering the obtained components, centrotype-based anterior and posterior DMN components were selected for further analysis. Individual DMN components were obtained through back-reconstruction and converted to z-score maps. A whole brain mixed effects factorial ANOVA was performed to explore the differences in resting-state DMN functional connectivity between cocaine addicts and healthy controls. The hippocampus, which showed decreased functional connectivity in cocaine addicts for all the tested model orders, might be considered as a reproducible abnormal region in DMN associated with cocaine addiction. This finding suggests that using group ICA to examine the functional connectivity of the hippocampus in the resting-state DMN may provide an additional insight potentially relevant for cocaine-related diagnoses and treatments. PMID:23707901

  6. Resolving structural variability in network models and the brain.

    Directory of Open Access Journals (Sweden)

    Florian Klimm

    2014-03-01

    Full Text Available Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known in general about mechanistic drivers of structured networks. Here we contrast network properties derived from diffusion spectrum imaging data of the human brain with 13 synthetic network models chosen to probe the roles of physical network embedding and temporal network growth. We characterize both the empirical and synthetic networks using familiar graph metrics, but presented here in a more complete statistical form, as scatter plots and distributions, to reveal the full range of variability of each measure across scales in the network. We focus specifically on the degree distribution, degree assortativity, hierarchy, topological Rentian scaling, and topological fractal scaling--in addition to several summary statistics, including the mean clustering coefficient, the shortest path-length, and the network diameter. The models are investigated in a progressive, branching sequence, aimed at capturing different elements thought to be important in the brain, and range from simple random and regular networks, to models that incorporate specific growth rules and constraints. We find that synthetic models that constrain the network nodes to be physically embedded in anatomical brain regions tend to produce distributions that are most similar to the corresponding measurements for the brain. We also find that network models hardcoded to display one network property (e.g., assortativity do not in general simultaneously display a second (e.g., hierarchy. This relative independence of network properties suggests that multiple neurobiological mechanisms might be at play in the development of human brain network architecture. Together, the network models that we develop and employ provide a potentially useful

  7. The modular and integrative functional architecture of the human brain.

    Science.gov (United States)

    Bertolero, Maxwell A; Yeo, B T Thomas; D'Esposito, Mark

    2015-12-01

    Network-based analyses of brain imaging data consistently reveal distinct modules and connector nodes with diverse global connectivity across the modules. How discrete the functions of modules are, how dependent the computational load of each module is to the other modules' processing, and what the precise role of connector nodes is for between-module communication remains underspecified. Here, we use a network model of the brain derived from resting-state functional MRI (rs-fMRI) data and investigate the modular functional architecture of the human brain by analyzing activity at different types of nodes in the network across 9,208 experiments of 77 cognitive tasks in the BrainMap database. Using an author-topic model of cognitive functions, we find a strong spatial correspondence between the cognitive functions and the network's modules, suggesting that each module performs a discrete cognitive function. Crucially, activity at local nodes within the modules does not increase in tasks that require more cognitive functions, demonstrating the autonomy of modules' functions. However, connector nodes do exhibit increased activity when more cognitive functions are engaged in a task. Moreover, connector nodes are located where brain activity is associated with many different cognitive functions. Connector nodes potentially play a role in between-module communication that maintains the modular function of the brain. Together, these findings provide a network account of the brain's modular yet integrated implementation of cognitive functions. PMID:26598686

  8. Three-dimensional network of Drosophila brain hemisphere

    CERN Document Server

    Mizutani, Ryuta; Takeuchi, Akihisa; Uesugi, Kentaro; Suzuki, Yoshio

    2016-01-01

    The first step to understanding brain function is to determine the brain's network structure. We report a three-dimensional analysis of the brain network of the fruit fly Drosophila melanogaster by synchrotron-radiation tomographic microscopy. A skeletonized wire model of the left half of the brain network was built by tracing the three-dimensional distribution of X-ray absorption coefficients. The obtained models of neuronal processes were classified into groups on the basis of their three-dimensional structures. These classified groups correspond to neuronal tracts that send long-range projections or repeated structures of the optic lobe. The skeletonized model is also composed of neuronal processes that could not be classified into the groups. The distribution of these unclassified structures correlates with the distribution of contacts between neuronal processes. This suggests that neurons that cannot be classified into typical structures should play important roles in brain functions. The quantitative de...

  9. Generative models of rich clubs in Hebbian neuronal networks and large-scale human brain networks

    OpenAIRE

    Vértes, Petra E.; Alexander-Bloch, Aaron; Bullmore, Edward T

    2014-01-01

    Rich clubs arise when nodes that are ‘rich’ in connections also form an elite, densely connected ‘club’. In brain networks, rich clubs incur high physical connection costs but also appear to be especially valuable to brain function. However, little is known about the selection pressures that drive their formation. Here, we take two complementary approaches to this question: firstly we show, using generative modelling, that the emergence of rich clubs in large-scale human brain networks can be...

  10. Brain network modules of meaningful and meaningless objects

    OpenAIRE

    Rizkallah, J.; Benquet, P.; Wendling, F; Khalil, M; Mheich, A; Dufor, O.; Hassan, M

    2016-01-01

    Network modularity is a key feature for efficient information processing in the human brain. This information processing is however dynamic and networks can reconfigure at very short time period, few hundreds of millisecond. This requires neuroimaging techniques with sufficient time resolution. Here we use the dense electroencephalography, EEG, source connectivity methods to identify cortical networks with excellent time resolution, in the order of millisecond. We identify functional networks...

  11. Support Network Responses to Acquired Brain Injury

    Science.gov (United States)

    Chleboun, Steffany; Hux, Karen

    2011-01-01

    Acquired brain injury (ABI) affects social relationships; however, the ways social and support networks change and evolve as a result of brain injury is not well understood. This study explored ways in which survivors of ABI and members of their support networks perceive relationship changes as recovery extends into the long-term stage. Two…

  12. Decoding the Encoding of Functional Brain Networks: an fMRI Classification Comparison of Non-negative Matrix Factorization (NMF), Independent Component Analysis (ICA), and Sparse Coding Algorithms

    OpenAIRE

    Xie, Jianwen; Douglas, Pamela K.; Wu, Ying Nian; Brody, Arthur L.; Anderson, Ariana E.

    2016-01-01

    Brain networks in fMRI are typically identified using spatial independent component analysis (ICA), yet mathematical constraints such as sparse coding and positivity both provide alternate biologically-plausible frameworks for generating brain networks. Non-negative Matrix Factorization (NMF) would suppress negative BOLD signal by enforcing positivity. Spatial sparse coding algorithms ($L1$ Regularized Learning and K-SVD) would impose local specialization and a discouragement of multitasking,...

  13. A permutation testing framework to compare groups of brain networks

    Directory of Open Access Journals (Sweden)

    Sean L Simpson

    2013-11-01

    Full Text Available Brain network analyses have moved to the forefront of neuroimaging research over the last decade. However, methods for statistically comparing groups of networks have lagged behind. These comparisons have great appeal for researchers interested in gaining further insight into complex brain function and how it changes across different mental states and disease conditions. Current comparison approaches generally either rely on a summary metric or on mass-univariate nodal or edge-based comparisons that ignore the inherent topological properties of the network, yielding little power and failing to make network level comparisons. Gleaning deeper insights into normal and abnormal changes in complex brain function demands methods that take advantage of the wealth of data present in an entire brain network. Here we propose a permutation testing framework that allows comparing groups of networks while incorporating topological features inherent in each individual network. We validate our approach using simulated data with known group differences. We then apply the method to functional brain networks derived from fMRI data.

  14. Altered resting state brain networks in Parkinson's disease.

    Directory of Open Access Journals (Sweden)

    Martin Göttlich

    Full Text Available Parkinson's disease (PD is a neurodegenerative disorder affecting dopaminergic neurons in the substantia nigra leading to dysfunctional cortico-striato-thalamic-cortical loops. In addition to the characteristic motor symptoms, PD patients often show cognitive impairments, affective changes and other non-motor symptoms, suggesting system-wide effects on brain function. Here, we used functional magnetic resonance imaging and graph-theory based analysis methods to investigate altered whole-brain intrinsic functional connectivity in PD patients (n = 37 compared to healthy controls (n = 20. Global network properties indicated less efficient processing in PD. Analysis of brain network modules pointed to increased connectivity within the sensorimotor network, but decreased interaction of the visual network with other brain modules. We found lower connectivity mainly between the cuneus and the ventral caudate, medial orbitofrontal cortex and the temporal lobe. To identify regions of altered connectivity, we mapped the degree of intrinsic functional connectivity both on ROI- and on voxel-level across the brain. Compared to healthy controls, PD patients showed lower connectedness in the medial and middle orbitofrontal cortex. The degree of connectivity was also decreased in the occipital lobe (cuneus and calcarine, but increased in the superior parietal cortex, posterior cingulate gyrus, supramarginal gyrus and supplementary motor area. Our results on global network and module properties indicated that PD manifests as a disconnection syndrome. This was most apparent in the visual network module. The higher connectedness within the sensorimotor module in PD patients may be related to compensation mechanism in order to overcome the functional deficit of the striato-cortical motor loops or to loss of mutual inhibition between brain networks. Abnormal connectivity in the visual network may be related to adaptation and compensation processes as a consequence

  15. Predicting errors from reconfiguration patterns in human brain networks

    OpenAIRE

    Ekman, Matthias; Derrfuss, Jan; Tittgemeyer, Marc; Fiebach, Christian J.

    2012-01-01

    Task preparation is a complex cognitive process that implements anticipatory adjustments to facilitate future task performance. Little is known about quantitative network parameters governing this process in humans. Using functional magnetic resonance imaging (fMRI) and functional connectivity measurements, we show that the large-scale topology of the brain network involved in task preparation shows a pattern of dynamic reconfigurations that guides optimal behavior. This network could be deco...

  16. Estimating brain's functional graph from the structural graph's Laplacian

    Science.gov (United States)

    Abdelnour, F.; Dayan, M.; Devinsky, O.; Thesen, T.; Raj, A.

    2015-09-01

    The interplay between the brain's function and structure has been of immense interest to the neuroscience and connectomics communities. In this work we develop a simple linear model relating the structural network and the functional network. We propose that the two networks are related by the structural network's Laplacian up to a shift. The model is simple to implement and gives accurate prediction of function's eigenvalues at the subject level and its eigenvectors at group level.

  17. Mutated Genes in Schizophrenia Map to Brain Networks

    Science.gov (United States)

    ... 2013 Mutated Genes in Schizophrenia Map to Brain Networks Schizophrenia networks in the prefrontal cortex area of the brain. ... of spontaneous mutations in genes that form a network in the front region of the brain. The ...

  18. Network-dependent modulation of brain activity during sleep

    OpenAIRE

    Watanabe, T.; Kan, S.; Koike, T.; Misaki, M; Konishi, S.; Miyauchi, S; Miyahsita, Y.; Masuda, N.

    2014-01-01

    Brain activity dynamically changes even during sleep. A line of neuroimaging studies has reported changes in functional connectivity and regional activity across different sleep stages such as slow-wave sleep (SWS) and rapid-eye-movement (REM) sleep. However, it remains unclear whether and how the large-scale network activity of human brains changes within a given sleep stage. Here, we investigated modulation of network activity within sleep stages by applying the pairwise maximum entropy mod...

  19. Lead poisoning and brain cell function

    Energy Technology Data Exchange (ETDEWEB)

    Goldstein, G.W. (Johns Hopkins School of Medicine, Baltimore, MD (USA) Kennedy Institute, Baltimore, MD (USA))

    1990-11-01

    Exposure to excessive amounts of inorganic lead during the toddler years may produce lasting adverse effects upon brain function. Maximal ingestion of lead occurs at an age when major changes are occurring in the density of brain synaptic connections. The developmental reorganization of synapses is, in part, mediated by protein kinases, and these enzymes are particularly sensitive to stimulation by lead. By inappropriately activating specific protein kinases, lead poisoning may disrupt the development of neural networks without producing overt pathological alterations. The blood-brain barrier is another potential vulnerable site for the neurotoxic action of lead. protein kinases appear to regulate the development of brain capillaries and the expression of the blood-brain barrier properties. Stimulation of protein kinase by lead may disrupt barrier development and alter the precise regulation of the neuronal environment that is required for normal brain function. Together, these findings suggest that the sensitivity of protein kinases to lead may in part underlie the brain dysfunction observed in children poisoned by this toxicant.

  20. The Virtual Brain: a simulator of primate brain network dynamics.

    Science.gov (United States)

    Sanz Leon, Paula; Knock, Stuart A; Woodman, M Marmaduke; Domide, Lia; Mersmann, Jochen; McIntosh, Anthony R; Jirsa, Viktor

    2013-01-01

    We present The Virtual Brain (TVB), a neuroinformatics platform for full brain network simulations using biologically realistic connectivity. This simulation environment enables the model-based inference of neurophysiological mechanisms across different brain scales that underlie the generation of macroscopic neuroimaging signals including functional MRI (fMRI), EEG and MEG. Researchers from different backgrounds can benefit from an integrative software platform including a supporting framework for data management (generation, organization, storage, integration and sharing) and a simulation core written in Python. TVB allows the reproduction and evaluation of personalized configurations of the brain by using individual subject data. This personalization facilitates an exploration of the consequences of pathological changes in the system, permitting to investigate potential ways to counteract such unfavorable processes. The architecture of TVB supports interaction with MATLAB packages, for example, the well known Brain Connectivity Toolbox. TVB can be used in a client-server configuration, such that it can be remotely accessed through the Internet thanks to its web-based HTML5, JS, and WebGL graphical user interface. TVB is also accessible as a standalone cross-platform Python library and application, and users can interact with the scientific core through the scripting interface IDLE, enabling easy modeling, development and debugging of the scientific kernel. This second interface makes TVB extensible by combining it with other libraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to the development of TVB, the architecture and features of its major software components as well as potential neuroscience applications. PMID:23781198

  1. Scaling in topological properties of brain networks

    OpenAIRE

    Soibam Shyamchand Singh; Budhachandra Khundrakpam; Andrew T. Reid; Lewis, John D.; Evans, Alan C.; Romana Ishrat; B. Indrajit Sharma; R K Brojen Singh

    2016-01-01

    The organization in brain networks shows highly modular features with weak inter-modular interaction. The topology of the networks involves emergence of modules and sub-modules at different levels of constitution governed by fractal laws that are signatures of self-organization in complex networks. The modular organization, in terms of modular mass, inter-modular, and intra-modular interaction, also obeys fractal nature. The parameters which characterize topological properties of brain networ...

  2. Scaling in topological properties of brain networks

    OpenAIRE

    Singh, Soibam Shyamchand; Singh, Khundrakpam Budhachandra; Ishrat, Romana; Sharma, B. Indrajit; Singh, R. K. Brojen

    2015-01-01

    The organization in brain networks shows highly modular features with weak inter-modular interaction. The topology of the networks involves emergence of modules and sub-modules at different levels of constitution governed by fractal laws. The modular organization, in terms of modular mass, inter-modular, and intra-modular interaction, also obeys fractal nature. The parameters which characterize topological properties of brain networks follow one parameter scaling theory in all levels of netwo...

  3. Role of physical and mental training in brain network configuration

    Directory of Open Access Journals (Sweden)

    Philip P. Foster

    2015-06-01

    Full Text Available Continuous remodeling of proteins of excitatory neurons is fine-tuning the scaling and strength of excitatory synapses up or down via regulation of intra-cellular metabolic and regulatory networks of the genome-transcriptome-proteome interface. Alzheimer's disease is a model of energy cost-driven small-world network disorder as the network global efficiency is impaired by the deposition of an informed agent, the amyloid-β, selectively targeting high-degree nodes. In schizophrenia, the interconnectivity and density of rich-club networks are significantly reduced. Training-induced homeostatic synaptogenesis-enhancement produces a reconfiguration of brain networks into greater small-worldness. Creation of synaptic connections in a macro-network, and, at the intra-cellular scale, micro-networks regulate the physiological mechanisms for the preferential attachment of synapses. The strongest molecular relationship of exercise and functional connectivity was identified for brain-derived neurotrophic factor (BDNF. The allele variant, rs7294919, also shows a powerful relationship with the hippocampal volume. How the brain achieves this unique quest of reconfiguration remains a puzzle. What are the underlying mechanisms of synaptogenesis promoting communications brain ↔ muscle and brainbrain in such trainings? What is the respective role of independent mental, physical or combined-mental-physical trainings? Physical practice seems to be playing an instrumental role in the cognitive enhancement (brain ↔ muscle com.. However, mental training, meditation or virtual reality (films, games require only minimal motor activity and cardio-respiratory stimulation. Therefore, other potential paths (brainbrain com. molding brain networks are nonetheless essential. Patients with motor neuron disease/injury (e.g. amyotrophic lateral sclerosis, traumatism also achieve successful cognitive enhancement albeit they may only elicit mental practice

  4. Small-World Propensity and Weighted Brain Networks

    Science.gov (United States)

    Muldoon, Sarah Feldt; Bridgeford, Eric W.; Bassett, Danielle S.

    2016-02-01

    Quantitative descriptions of network structure can provide fundamental insights into the function of interconnected complex systems. Small-world structure, diagnosed by high local clustering yet short average path length between any two nodes, promotes information flow in coupled systems, a key function that can differ across conditions or between groups. However, current techniques to quantify small-worldness are density dependent and neglect important features such as the strength of network connections, limiting their application in real-world systems. Here, we address both limitations with a novel metric called the Small-World Propensity (SWP). In its binary instantiation, the SWP provides an unbiased assessment of small-world structure in networks of varying densities. We extend this concept to the case of weighted brain networks by developing (i) a standardized procedure for generating weighted small-world networks, (ii) a weighted extension of the SWP, and (iii) a method for mapping observed brain network data onto the theoretical model. In applying these techniques to compare real-world brain networks, we uncover the surprising fact that the canonical biological small-world network, the C. elegans neuronal network, has strikingly low SWP. These metrics, models, and maps form a coherent toolbox for the assessment and comparison of architectural properties in brain networks.

  5. Research progress of brain connectivity network on functional magnetic resonance imaging in epilepsy%fMRI在癫大脑网络中的研究进展

    Institute of Scientific and Technical Information of China (English)

    陈彤; 郭亮

    2015-01-01

    Epilepsy is a chronic paroxysmal neurological disorder that caused by abnormal discharge of neurons. Because of its repetitive seizures, complex and various clinical manifestation, the structure and function of the brain both have been severely damaged. In recent years, with the rapid development of functional imaging technology, functional magnetic resonance imaging (fMRI) has been widely used in the evaluation of epilepsy. Particularly the resting-state fMRI alone or combining with EEG plays an important role in revealing the characteristics of the changes in complex network, structure network and functional network. It helps us to understand deeply about the pathogenesis of epilepsy.%癫日是神经元异常放电所致的慢性发作性神经功能障碍性疾病,因其发作的反复性、复杂性和多样性,大脑的结构和功能均受到严重损害。近年来,随着功能成像技术的不断发展,功能MR成像(fMRI)在癫日中的应用越来越广泛,尤其是静息态 fMRI(rs-fMRI)和同步联合脑电图 fMRI(EEG-fMRI)的应用揭示了癫日复杂网络、结构网络及功能网络改变的特点,为理解癫日发病机制提供了重要的帮助。

  6. Bioprinting: Functional droplet networks

    Science.gov (United States)

    Durmus, Naside Gozde; Tasoglu, Savas; Demirci, Utkan

    2013-06-01

    Tissue-mimicking printed networks of droplets separated by lipid bilayers that can be functionalized with membrane proteins are able to spontaneously fold and transmit electrical currents along predefined paths.

  7. Scaling in topological properties of brain networks

    NARCIS (Netherlands)

    Singh, S.S.; Khundrakpam, B.; Reid, A.T.; Lewis, J.D.; Evans, A.C.; Ishrat, R.; Sharma, B.I.; Singh, R.K.B.

    2016-01-01

    The organization in brain networks shows highly modular features with weak inter-modular interaction. The topology of the networks involves emergence of modules and sub-modules at different levels of constitution governed by fractal laws that are signatures of self-organization in complex networks.

  8. Does IQ affect the functional brain network involved in pseudoword reading in students with reading disability? A magnetoencephalography study

    OpenAIRE

    Simos, Panagiotis G.; Fletcher, Jack M.; Andrew C. Papanicolaou

    2014-01-01

    The study examined whether individual differences in performance and verbal IQ affect the profiles of reading-related regional brain activation in 127 students experiencing reading difficulties and typical readers. Using magnetoencephalography in a pseudoword read-aloud task, we compared brain activation profiles of students experiencing word-level reading difficulties who did (n=29) or did not (n=36) meet the IQ-reading achievement discrepancy criterion. Typical readers assigned to a lower-I...

  9. Virtual network functions orchestration in wireless networks

    OpenAIRE

    Riggio, Roberto; Bradai, Abbas; Rasheed, Tinku; Schulz-Zander, Julius; Kuklinski, Slawomir; Ahmed, Toufik

    2015-01-01

    Network Function Virtualization (NFV) is emerging as one of the most innovative concepts in the networking landscape. By migrating network functions from dedicated mid-dleboxes to general purpose computing platforms, NFV can effectively reduce the cost to deploy and to operate large networks. However, in order to achieve its full potential, NFV needs to encompass also the radio access network allowing Mobile Virtual Network Operators to deploy custom resource allocation solutions within their...

  10. Pain: a distributed brain information network?

    Directory of Open Access Journals (Sweden)

    Hiroaki Mano

    2015-01-01

    Full Text Available Understanding how pain is processed in the brain has been an enduring puzzle, because there doesn't appear to be a single "pain cortex" that directly codes the subjective perception of pain. An emerging concept is that, instead, pain might emerge from the coordinated activity of an integrated brain network. In support of this view, Woo and colleagues present evidence that distinct brain networks support the subjective changes in pain that result from nociceptive input and self-directed cognitive modulation. This evidence for the sensitivity of distinct neural subsystems to different aspects of pain opens up the way to more formal computational network theories of pain.

  11. Scale-Free Brain Networks Based on the Event-Related Potential during Visual Spatial Attention

    Institute of Scientific and Technical Information of China (English)

    LI Ling; JIN Zhen-Lan

    2011-01-01

    @@ The human brain is thought of as one of the most complex dynamical systems in the universe.The network view of the dynamical system has emerged since the discovery of scale-free networks.Brain functional networks, which represent functional associations among brain regions, are extracted by measuring the temporal correlations from electroencephalogram data.We measure the topological properties of the brain functional network, including degree distribution, average degree, clustering coefficient and the shortest path length, to compare the networks of multi-channel event-related potential activity between visual spatial attention and unattention conditions.It is found that the degree distribution of the brain functional networks under both the conditions is a power law distribution, which reflects a scale-free property.Moreover, the scaling exponent of the attention condition is significantly smaller than that of the unattention condition.However, the degree distribution of equivalent random networks does not follow the power law distribution.In addition, the clustering coefficient of these random networks is smaller than those of brain networks, and the shortest path length of these random networks is large and comparable with those of brain networks.Our results, typical of scale-free networks, indicate that the scaling exponent of brain activity could reflect different cognitive processes.%The human brain is thought of as one of the most complex dynamical systems in the universe. The network view of the dynamical system has emerged since the discovery of scale-free networks. Brain functional networks, which represent functional associations among brain regions, are extracted by measuring the temporal correlations from electroencephalogram data. We measure the topological properties of the brain functional network, including degree distribution, average degree, clustering coefficient and the shortest path length, to compare the networks of multi-channel event

  12. Future of functional brain imaging

    International Nuclear Information System (INIS)

    To examine the living human brain's sensory, motor and cognitive interactions and to understand how activities in anatomically distinct neural processing regions are orchestrated to perform complex tasks represents a future challenge to neuroscientists. Until recently, functional brain imaging data have been constrained by the severely limited spatial (5-15 mm) and temporal resolution (from a few seconds to minutes) of the nuclear medicine methods, single-photon emission tomography (SPET) and positron emission tomography (PET). The advent of new non-invasive, fast imaging methods - functional magnetic resonance imaging (fMRI), serial X-ray computed tomography ('cine' CT) and magnetoencephalography (MEG) - has created a need for a survey to compare these techniques with conventional SPET and PET. Each technique has unique advantages and simultaneously serious limitations. No method has achieved a clear supremacy in functional brain imaging. (orig.)

  13. Functional Brain Imaging: A Comprehensive Survey

    CERN Document Server

    Sarraf, Saman

    2016-01-01

    Functional brain imaging allows measuring dynamic functionality in all brain regions. It is broadly used in clinical cognitive neuroscience as, well as in research. It will allow the observation of neural activities in the brain simultaneously. From the beginning when functional brain imaging was initiated by the mapping of brain functions proposed by phrenologists, many scientists were asking why we need to image brain functionality since we have already structural information. Simply, their important question was including a great answer. Functional information of the human brain would definitely complement structural information, helping to have a better understanding of what is happening in the brain. This paper, which could be useful to those who have an interest in functional brain imaging, such as engineers, will present a quick review of modalities used in functional brain imaging. We will concentrate on the most used techniques in functional imaging which are functional magnetic resonance imaging (fM...

  14. A magnetoencephalography study of functional brain connectivity in childhood, adolescence and adulthood

    OpenAIRE

    Smith, Helen Joanna Fabienne

    2015-01-01

    Functional brain networks are interconnected brain regions that flexibly coordinate their activity to support cognitive demands (Fair et al., 2009). Functional brain connectivity describes a statistical dependency between the activities recorded at spatially distinct brain regions (Friston, 2009). Changes in the pattern of connections and level of activation in functional brain networks are thought to occur across development (Taylor, Donner, & Pang, 2012) but the nature of these changes and ...

  15. Resting Network Plasticity Following Brain Injury

    OpenAIRE

    Toru Nakamura; Hillary, Frank G.; Biswal, Bharat B.

    2009-01-01

    The purpose of this study was to examine neural network properties at separate time-points during recovery from traumatic brain injury (TBI) using graph theory. Whole-brain analyses of the topological properties of the fMRI signal were conducted in 6 participants at 3 months and 6 months following severe TBI. Results revealed alterations of network properties including a change in the degree distribution, reduced overall strength in connectivity, and increased "small-worldness" from 3 months ...

  16. Medial Prefrontal and Anterior Insular Connectivity in Early Schizophrenia and Major Depressive Disorder: A Resting Functional MRI Evaluation of Large-Scale Brain Network Models.

    Science.gov (United States)

    Penner, Jacob; Ford, Kristen A; Taylor, Reggie; Schaefer, Betsy; Théberge, Jean; Neufeld, Richard W J; Osuch, Elizabeth A; Menon, Ravi S; Rajakumar, Nagalingam; Allman, John M; Williamson, Peter C

    2016-01-01

    Anomalies in the medial prefrontal cortex, anterior insulae, and large-scale brain networks associated with them have been proposed to underlie the pathophysiology of schizophrenia and major depressive disorder (MDD). In this study, we examined the connectivity of the medial prefrontal cortices and anterior insulae in 24 healthy controls, 24 patients with schizophrenia, and 24 patients with MDD early in illness with seed-based resting state functional magnetic resonance imaging analysis using Statistical Probability Mapping. As hypothesized, reduced connectivity was found between the medial prefrontal cortex and the dorsal anterior cingulate cortex and other nodes associated with directed effort in patients with schizophrenia compared to controls while patients with MDD had reduced connectivity between the medial prefrontal cortex and ventral prefrontal emotional encoding regions compared to controls. Reduced connectivity was found between the anterior insulae and the medial prefrontal cortex in schizophrenia compared to controls, but contrary to some models emotion processing regions failed to demonstrate increased connectivity with the medial prefrontal cortex in MDD compared to controls. Although, not statistically significant after correction for multiple comparisons, patients with schizophrenia tended to demonstrate decreased connectivity between basal ganglia-thalamocortical regions and the medial prefrontal cortex compared to patients with MDD, which might be expected as these regions effect action. Results were interpreted to support anomalies in nodes associated with directed effort in schizophrenia and nodes associated with emotional encoding network in MDD compared to healthy controls. PMID:27064387

  17. Medial Prefrontal and Anterior Insular Connectivity in Early Schizophrenia and Major Depressive Disorder: A Resting Functional MRI Evaluation of Large-Scale Brain Network Models

    Science.gov (United States)

    Penner, Jacob; Ford, Kristen A.; Taylor, Reggie; Schaefer, Betsy; Théberge, Jean; Neufeld, Richard W. J.; Osuch, Elizabeth A.; Menon, Ravi S.; Rajakumar, Nagalingam; Allman, John M.; Williamson, Peter C.

    2016-01-01

    Anomalies in the medial prefrontal cortex, anterior insulae, and large-scale brain networks associated with them have been proposed to underlie the pathophysiology of schizophrenia and major depressive disorder (MDD). In this study, we examined the connectivity of the medial prefrontal cortices and anterior insulae in 24 healthy controls, 24 patients with schizophrenia, and 24 patients with MDD early in illness with seed-based resting state functional magnetic resonance imaging analysis using Statistical Probability Mapping. As hypothesized, reduced connectivity was found between the medial prefrontal cortex and the dorsal anterior cingulate cortex and other nodes associated with directed effort in patients with schizophrenia compared to controls while patients with MDD had reduced connectivity between the medial prefrontal cortex and ventral prefrontal emotional encoding regions compared to controls. Reduced connectivity was found between the anterior insulae and the medial prefrontal cortex in schizophrenia compared to controls, but contrary to some models emotion processing regions failed to demonstrate increased connectivity with the medial prefrontal cortex in MDD compared to controls. Although, not statistically significant after correction for multiple comparisons, patients with schizophrenia tended to demonstrate decreased connectivity between basal ganglia-thalamocortical regions and the medial prefrontal cortex compared to patients with MDD, which might be expected as these regions effect action. Results were interpreted to support anomalies in nodes associated with directed effort in schizophrenia and nodes associated with emotional encoding network in MDD compared to healthy controls. PMID:27064387

  18. Functional brain mapping of psychopathology

    OpenAIRE

    Honey, G.; Fletcher, P.; BULLMORE, E.

    2002-01-01

    In this paper, we consider the impact that the novel functional neuroimaging techniques may have upon psychiatric illness. Functional neuroimaging has rapidly developed as a powerful tool in cognitive neuroscience and, in recent years, has seen widespread application in psychiatry. Although such studies have produced evidence for abnormal patterns of brain response in association with some pathological conditions, the core pathophysiologies remain unresolved. Although imaging techniques provi...

  19. Frequency-specific network topologies in the resting human brain.

    Science.gov (United States)

    Sasai, Shuntaro; Homae, Fumitaka; Watanabe, Hama; Sasaki, Akihiro T; Tanabe, Hiroki C; Sadato, Norihiro; Taga, Gentaro

    2014-01-01

    A community is a set of nodes with dense inter-connections, while there are sparse connections between different communities. A hub is a highly connected node with high centrality. It has been shown that both "communities" and "hubs" exist simultaneously in the brain's functional connectivity network (FCN), as estimated by correlations among low-frequency spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signal changes (0.01-0.10 Hz). This indicates that the brain has a spatial organization that promotes both segregation and integration of information. Here, we demonstrate that frequency-specific network topologies that characterize segregation and integration also exist within this frequency range. In investigating the coherence spectrum among 87 brain regions, we found that two frequency bands, 0.01-0.03 Hz (very low frequency [VLF] band) and 0.07-0.09 Hz (low frequency [LF] band), mainly contributed to functional connectivity. Comparing graph theoretical indices for the VLF and LF bands revealed that the network in the former had a higher capacity for information segregation between identified communities than the latter. Hubs in the VLF band were mainly located within the anterior cingulate cortices, whereas those in the LF band were located in the posterior cingulate cortices and thalamus. Thus, depending on the timescale of brain activity, at least two distinct network topologies contributed to information segregation and integration. This suggests that the brain intrinsically has timescale-dependent functional organizations. PMID:25566037

  20. Does IQ affect the functional brain network involved in pseudoword reading in students with reading disability? A magnetoencephalography study.

    Science.gov (United States)

    Simos, Panagiotis G; Rezaie, Roozbeh; Papanicolaou, Andrew C; Fletcher, Jack M

    2014-01-01

    The study examined whether individual differences in performance and verbal IQ affect the profiles of reading-related regional brain activation in 127 students experiencing reading difficulties and typical readers. Using magnetoencephalography in a pseudoword read-aloud task, we compared brain activation profiles of students experiencing word-level reading difficulties who did (n = 29) or did not (n = 36) meet the IQ-reading achievement discrepancy criterion. Typical readers assigned to a lower-IQ (n = 18) or a higher IQ (n = 44) subgroup served as controls. Minimum norm estimates of regional cortical activity revealed that the degree of hypoactivation in the left superior temporal and supramarginal gyri in both RD subgroups was not affected by IQ. Moreover, IQ did not moderate the positive association between degree of activation in the left fusiform gyrus and phonological decoding ability. We did find, however, that the hypoactivation of the left pars opercularis in RD was restricted to lower-IQ participants. In accordance with previous morphometric and fMRI studies, degree of activity in inferior frontal, and inferior parietal regions correlated with IQ across reading ability subgroups. Results are consistent with current views questioning the relevance of IQ-discrepancy criteria in the diagnosis of dyslexia. PMID:24409136

  1. Does IQ affect the functional brain network involved in pseudoword reading in students with reading disability? A magnetoencephalography study

    Directory of Open Access Journals (Sweden)

    Panagiotis G Simos

    2014-01-01

    Full Text Available The study examined whether individual differences in performance and verbal IQ affect the profiles of reading-related regional brain activation in 127 students experiencing reading difficulties and typical readers. Using magnetoencephalography in a pseudoword read-aloud task, we compared brain activation profiles of students experiencing word-level reading difficulties who did (n=29 or did not (n=36 meet the IQ-reading achievement discrepancy criterion. Typical readers assigned to a lower-IQ (n=18 or a higher IQ (n=44 subgroup served as controls. Minimum norm estimates of regional cortical activity revealed that the degree of hypoactivation in the left superior temporal and supramarginal gyri in both RD subgroups was not affected by IQ. Moreover, IQ did not moderate the positive association between degree of activation in the left fusiform gyrus and phonological decoding ability. We did find, however, that the hypoactivation of the left pars opercularis in RD was restricted to lower-IQ participants. In accordance with previous morphometric and fMRI studies, degree of activity in inferior frontal and inferior parietal regions correlated with IQ across reading ability subgroups. Results are consistent with current views questioning the relevance of IQ measures and IQ-discrepancy criteria in the diagnosis of dyslexia.

  2. Does IQ affect the functional brain network involved in pseudoword reading in students with reading disability? A magnetoencephalography study

    Science.gov (United States)

    Simos, Panagiotis G.; Rezaie, Roozbeh; Papanicolaou, Andrew C.; Fletcher, Jack M.

    2014-01-01

    The study examined whether individual differences in performance and verbal IQ affect the profiles of reading-related regional brain activation in 127 students experiencing reading difficulties and typical readers. Using magnetoencephalography in a pseudoword read-aloud task, we compared brain activation profiles of students experiencing word-level reading difficulties who did (n = 29) or did not (n = 36) meet the IQ-reading achievement discrepancy criterion. Typical readers assigned to a lower-IQ (n = 18) or a higher IQ (n = 44) subgroup served as controls. Minimum norm estimates of regional cortical activity revealed that the degree of hypoactivation in the left superior temporal and supramarginal gyri in both RD subgroups was not affected by IQ. Moreover, IQ did not moderate the positive association between degree of activation in the left fusiform gyrus and phonological decoding ability. We did find, however, that the hypoactivation of the left pars opercularis in RD was restricted to lower-IQ participants. In accordance with previous morphometric and fMRI studies, degree of activity in inferior frontal, and inferior parietal regions correlated with IQ across reading ability subgroups. Results are consistent with current views questioning the relevance of IQ-discrepancy criteria in the diagnosis of dyslexia. PMID:24409136

  3. High-order interactions observed in multi-task intrinsic networks are dominant indicators of aberrant brain function in schizophrenia

    OpenAIRE

    Plis, Sergey M.; Sui, Jing; Lane, Terran; Roy, Sushmita; Clark, Vincent P.; Potluru, Vamsi K.; Huster, Rene J.; Michael, Andrew; Sponheim, Scott R.; Weisend, Michael P.; Calhoun, Vince D.

    2013-01-01

    Identifying the complex activity relationships present in rich, modern neuroimaging data sets remains a key challenge for neuroscience. The problem is hard because (a) the underlying spatial and temporal networks may be nonlinear and multivariate and (b) the observed data may be driven by numerous latent factors. Further, modern experiments often produce data sets containing multiple stimulus contexts or tasks processed by the same subjects. Fusing such multi-session data sets may reveal addi...

  4. Mapping Functional Brain Development: Building a Social Brain through Interactive Specialization

    Science.gov (United States)

    Johnson, Mark H.; Grossmann, Tobias; Kadosh, Kathrin Cohen

    2009-01-01

    The authors review a viewpoint on human functional brain development, interactive specialization (IS), and its application to the emerging network of cortical regions referred to as the "social brain." They advance the IS view in 2 new ways. First, they extend IS into a domain to which it has not previously been applied--the emergence of social…

  5. Online Social Networks and the Consumer Brain

    OpenAIRE

    Adina Zara

    2011-01-01

    Online social networks have moved from being seen as trends or communication channels to becoming an effective tool for business. They play a large role in consumer’s life. The online purchase decisions are not as rational as we consider them to be. This paper shows why it is important the study of the human brain for social networks website. By researching how they react to different online marketing stimuli is a key factor in having success on an online social network.

  6. Mapping Individual Brain Networks Using Statistical Similarity in Regional Morphology from MRI.

    Directory of Open Access Journals (Sweden)

    Xiang-zhen Kong

    Full Text Available Representing brain morphology as a network has the advantage that the regional morphology of 'isolated' structures can be described statistically based on graph theory. However, very few studies have investigated brain morphology from the holistic perspective of complex networks, particularly in individual brains. We proposed a new network framework for individual brain morphology. Technically, in the new network, nodes are defined as regions based on a brain atlas, and edges are estimated using our newly-developed inter-regional relation measure based on regional morphological distributions. This implementation allows nodes in the brain network to be functionally/anatomically homogeneous but different with respect to shape and size. We first demonstrated the new network framework in a healthy sample. Thereafter, we studied the graph-theoretical properties of the networks obtained and compared the results with previous morphological, anatomical, and functional networks. The robustness of the method was assessed via measurement of the reliability of the network metrics using a test-retest dataset. Finally, to illustrate potential applications, the networks were used to measure age-related changes in commonly used network metrics. Results suggest that the proposed method could provide a concise description of brain organization at a network level and be used to investigate interindividual variability in brain morphology from the perspective of complex networks. Furthermore, the method could open a new window into modeling the complexly distributed brain and facilitate the emerging field of human connectomics.

  7. Spatial Neural Networks and their Functional Samples: Similarities and Differences

    OpenAIRE

    Antiqueira, Lucas; Zhao, Liang

    2014-01-01

    Models of neural networks have proven their utility in the development of learning algorithms in computer science and in the theoretical study of brain dynamics in computational neuroscience. We propose in this paper a spatial neural network model to analyze the important class of functional networks, which are commonly employed in computational studies of clinical brain imaging time series. We developed a simulation framework inspired by multichannel brain surface recordings (more specifical...

  8. Modeling of Large-Scale Functional Brain Networks Based on Structural Connectivity from DTI: Comparison with EEG Derived Phase Coupling Networks and Evaluation of Alternative Methods along the Modeling Path

    Science.gov (United States)

    Cheng, Bastian; Messé, Arnaud; Thomalla, Götz; Gerloff, Christian; König, Peter

    2016-01-01

    In this study, we investigate if phase-locking of fast oscillatory activity relies on the anatomical skeleton and if simple computational models informed by structural connectivity can help further to explain missing links in the structure-function relationship. We use diffusion tensor imaging data and alpha band-limited EEG signal recorded in a group of healthy individuals. Our results show that about 23.4% of the variance in empirical networks of resting-state functional connectivity is explained by the underlying white matter architecture. Simulating functional connectivity using a simple computational model based on the structural connectivity can increase the match to 45.4%. In a second step, we use our modeling framework to explore several technical alternatives along the modeling path. First, we find that an augmentation of homotopic connections in the structural connectivity matrix improves the link to functional connectivity while a correction for fiber distance slightly decreases the performance of the model. Second, a more complex computational model based on Kuramoto oscillators leads to a slight improvement of the model fit. Third, we show that the comparison of modeled and empirical functional connectivity at source level is much more specific for the underlying structural connectivity. However, different source reconstruction algorithms gave comparable results. Of note, as the fourth finding, the model fit was much better if zero-phase lag components were preserved in the empirical functional connectome, indicating a considerable amount of functionally relevant synchrony taking place with near zero or zero-phase lag. The combination of the best performing alternatives at each stage in the pipeline results in a model that explains 54.4% of the variance in the empirical EEG functional connectivity. Our study shows that large-scale brain circuits of fast neural network synchrony strongly rely upon the structural connectome and simple computational

  9. Modeling of Large-Scale Functional Brain Networks Based on Structural Connectivity from DTI: Comparison with EEG Derived Phase Coupling Networks and Evaluation of Alternative Methods along the Modeling Path.

    Science.gov (United States)

    Finger, Holger; Bönstrup, Marlene; Cheng, Bastian; Messé, Arnaud; Hilgetag, Claus; Thomalla, Götz; Gerloff, Christian; König, Peter

    2016-08-01

    In this study, we investigate if phase-locking of fast oscillatory activity relies on the anatomical skeleton and if simple computational models informed by structural connectivity can help further to explain missing links in the structure-function relationship. We use diffusion tensor imaging data and alpha band-limited EEG signal recorded in a group of healthy individuals. Our results show that about 23.4% of the variance in empirical networks of resting-state functional connectivity is explained by the underlying white matter architecture. Simulating functional connectivity using a simple computational model based on the structural connectivity can increase the match to 45.4%. In a second step, we use our modeling framework to explore several technical alternatives along the modeling path. First, we find that an augmentation of homotopic connections in the structural connectivity matrix improves the link to functional connectivity while a correction for fiber distance slightly decreases the performance of the model. Second, a more complex computational model based on Kuramoto oscillators leads to a slight improvement of the model fit. Third, we show that the comparison of modeled and empirical functional connectivity at source level is much more specific for the underlying structural connectivity. However, different source reconstruction algorithms gave comparable results. Of note, as the fourth finding, the model fit was much better if zero-phase lag components were preserved in the empirical functional connectome, indicating a considerable amount of functionally relevant synchrony taking place with near zero or zero-phase lag. The combination of the best performing alternatives at each stage in the pipeline results in a model that explains 54.4% of the variance in the empirical EEG functional connectivity. Our study shows that large-scale brain circuits of fast neural network synchrony strongly rely upon the structural connectome and simple computational

  10. Brain plasticity and hand function

    OpenAIRE

    Björkman, Anders

    2005-01-01

    The aim of this thesis was to investigate the effects of cortical reorganisational changes following experimental deafferentation and peripheral nerve injury and apply the concept of brain plasticity to enhance sensory re-education following peripheral nerve injury and repair in the hand. In the first two papers the effects on hand function of contralateral deafferentation was investigated. Tourniquet induced anaesthesia (paper I) resulted in significant improvement in perception of to...

  11. Complex networks in brain electrical activity

    CERN Document Server

    Ruffini, G; Grau, C; Marco, J; Ray, C

    2005-01-01

    We analyze the complex networks associated with brain electrical activity. Multichannel EEG measurements are first processed to obtain 3D voxel activations using the tomographic algorithm LORETA. Then, the correlation of the current intensity activation between voxel pairs is computed to produce a voxel cross-correlation coefficient matrix. Using several correlation thresholds, the cross-correlation matrix is then transformed into a network connectivity matrix and analyzed. To study a specific example, we selected data from an earlier experiment focusing on the MMN brain wave. The resulting analysis highlights significant differences between the spatial activations associated with Standard and Deviant tones, with interesting physiological implications. When compared to random data networks, physiological networks are more connected, with longer links and shorter path lengths. Furthermore, as compared to the Deviant case, Standard data networks are more connected, with longer links and shorter path lengths--i....

  12. Creative Cognition and Brain Network Dynamics.

    Science.gov (United States)

    Beaty, Roger E; Benedek, Mathias; Silvia, Paul J; Schacter, Daniel L

    2016-02-01

    Creative thinking is central to the arts, sciences, and everyday life. How does the brain produce creative thought? A series of recently published papers has begun to provide insight into this question, reporting a strikingly similar pattern of brain activity and connectivity across a range of creative tasks and domains, from divergent thinking to poetry composition to musical improvisation. This research suggests that creative thought involves dynamic interactions of large-scale brain systems, with the most compelling finding being that the default and executive control networks, which can show an antagonistic relation, tend to cooperate during creative cognition and artistic performance. These findings have implications for understanding how brain networks interact to support complex cognitive processes, particularly those involving goal-directed, self-generated thought. PMID:26553223

  13. Language networks in children: Evidence from functional MRI studies

    OpenAIRE

    Vannest, Jennifer; Karunanayaka, Prasanna R.; Schmithorst, Vincent J.; Szaflarski, Jerzy P; Holland, Scott K.

    2009-01-01

    We review functional MRI and other neuroimaging studies of language skills in children from infancy to adulthood. These studies show developmental changes in the networks of brain regions supporting language, which can be affected by brain injuries or neurological disorders. Particular aspects of language rely on networks that lateralize to the dominant hemisphere; others rely on bilateral or non-dominant mechanisms. Multiple fMRI tasks for pediatric patients characterize functional brain reo...

  14. Decreased functional brain connectivity in adolescents with internet addiction.

    Directory of Open Access Journals (Sweden)

    Soon-Beom Hong

    Full Text Available BACKGROUND: Internet addiction has become increasingly recognized as a mental disorder, though its neurobiological basis is unknown. This study used functional neuroimaging to investigate whole-brain functional connectivity in adolescents diagnosed with internet addiction. Based on neurobiological changes seen in other addiction related disorders, it was predicted that connectivity disruptions in adolescents with internet addiction would be most prominent in cortico-striatal circuitry. METHODS: Participants were 12 adolescents diagnosed with internet addiction and 11 healthy comparison subjects. Resting-state functional magnetic resonance images were acquired, and group differences in brain functional connectivity were analyzed using the network-based statistic. We also analyzed network topology, testing for between-group differences in key graph-based network measures. RESULTS: Adolescents with internet addiction showed reduced functional connectivity spanning a distributed network. The majority of impaired connections involved cortico-subcortical circuits (∼24% with prefrontal and ∼27% with parietal cortex. Bilateral putamen was the most extensively involved subcortical brain region. No between-group difference was observed in network topological measures, including the clustering coefficient, characteristic path length, or the small-worldness ratio. CONCLUSIONS: Internet addiction is associated with a widespread and significant decrease of functional connectivity in cortico-striatal circuits, in the absence of global changes in brain functional network topology.

  15. Analysing Local Sparseness in the Macaque Brain Network.

    Science.gov (United States)

    Singh, Raghavendra; Nagar, Seema; Nanavati, Amit A

    2015-01-01

    Understanding the network structure of long distance pathways in the brain is a necessary step towards developing an insight into the brain's function, organization and evolution. Dense global subnetworks of these pathways have often been studied, primarily due to their functional implications. Instead we study sparse local subnetworks of the pathways to establish the role of a brain area in enabling shortest path communication between its non-adjacent topological neighbours. We propose a novel metric to measure the topological communication load on a vertex due to its immediate neighbourhood, and show that in terms of distribution of this local communication load, a network of Macaque long distance pathways is substantially different from other real world networks and random graph models. Macaque network contains the entire range of local subnetworks, from star-like networks to clique-like networks, while other networks tend to contain a relatively small range of subnetworks. Further, sparse local subnetworks in the Macaque network are not only found across topographical super-areas, e.g., lobes, but also within a super-area, arguing that there is conservation of even relatively short-distance pathways. To establish the communication role of a vertex we borrow the concept of brokerage from social science, and present the different types of brokerage roles that brain areas play, highlighting that not only the thalamus, but also cingulate gyrus and insula often act as "relays" for areas in the neocortex. These and other analysis of communication load and roles of the sparse subnetworks of the Macaque brain provide new insights into the organisation of its pathways. PMID:26437077

  16. Neural substrate expansion for the restoration of brain function

    Directory of Open Access Journals (Sweden)

    Han-Chiao Isaac Chen

    2016-01-01

    Full Text Available Restoring neurological and cognitive function in individuals who have suffered brain damage is one of the principal objectives of modern translational neuroscience. Electrical stimulation approaches, such as deep-brain stimulation, have achieved the most clinical success, but they ultimately may be limited by the computational capacity of the residual cerebral circuitry. An alternative strategy is brain substrate expansion, in which the computational capacity of the brain is augmented through the addition of new processing units and the reconstitution of network connectivity. This latter approach has been explored to some degree using both biological and electronic means but thus far has not demonstrated the ability to reestablish the function of large-scale neuronal networks. In this review, we contend that fulfilling the potential of brain substrate expansion will require a significant shift from current methods that emphasize direct manipulations of the brain (e.g., injections of cellular suspensions and the implantation of multi-electrode arrays to the generation of more sophisticated neural tissues and neural-electric hybrids in vitro that are subsequently transplanted into the brain. Drawing from neural tissue engineering, stem cell biology, and neural interface technologies, this strategy makes greater use of the manifold techniques available in the laboratory to create biocompatible constructs that recapitulate brain architecture and thus are more easily recognized and utilized by brain networks.

  17. Neural Substrate Expansion for the Restoration of Brain Function.

    Science.gov (United States)

    Chen, H Isaac; Jgamadze, Dennis; Serruya, Mijail D; Cullen, D Kacy; Wolf, John A; Smith, Douglas H

    2016-01-01

    Restoring neurological and cognitive function in individuals who have suffered brain damage is one of the principal objectives of modern translational neuroscience. Electrical stimulation approaches, such as deep-brain stimulation, have achieved the most clinical success, but they ultimately may be limited by the computational capacity of the residual cerebral circuitry. An alternative strategy is brain substrate expansion, in which the computational capacity of the brain is augmented through the addition of new processing units and the reconstitution of network connectivity. This latter approach has been explored to some degree using both biological and electronic means but thus far has not demonstrated the ability to reestablish the function of large-scale neuronal networks. In this review, we contend that fulfilling the potential of brain substrate expansion will require a significant shift from current methods that emphasize direct manipulations of the brain (e.g., injections of cellular suspensions and the implantation of multi-electrode arrays) to the generation of more sophisticated neural tissues and neural-electric hybrids in vitro that are subsequently transplanted into the brain. Drawing from neural tissue engineering, stem cell biology, and neural interface technologies, this strategy makes greater use of the manifold techniques available in the laboratory to create biocompatible constructs that recapitulate brain architecture and thus are more easily recognized and utilized by brain networks. PMID:26834579

  18. Default network connectivity decodes brain states with simulated microgravity.

    Science.gov (United States)

    Zeng, Ling-Li; Liao, Yang; Zhou, Zongtan; Shen, Hui; Liu, Yadong; Liu, Xufeng; Hu, Dewen

    2016-04-01

    With great progress of space navigation technology, it becomes possible to travel beyond Earth's gravity. So far, it remains unclear whether the human brain can function normally within an environment of microgravity and confinement. Particularly, it is a challenge to figure out some neuroimaging-based markers for rapid screening diagnosis of disrupted brain function in microgravity environment. In this study, a 7-day -6° head down tilt bed rest experiment was used to simulate the microgravity, and twenty healthy male participants underwent resting-state functional magnetic resonance imaging scans at baseline and after the simulated microgravity experiment. We used a multivariate pattern analysis approach to distinguish the brain states with simulated microgravity from normal gravity based on the functional connectivity within the default network, resulting in an accuracy of no less than 85 % via cross-validation. Moreover, most discriminative functional connections were mainly located between the limbic system and cortical areas and were enhanced after simulated microgravity, implying a self-adaption or compensatory enhancement to fulfill the need of complex demand in spatial navigation and motor control functions in microgravity environment. Overall, the findings suggest that the brain states in microgravity are likely different from those in normal gravity and that brain connectome could act as a biomarker to indicate the brain state in microgravity. PMID:27066149

  19. Community detection in weighted brain connectivity networks beyond the resolution limit

    CERN Document Server

    Nicolini, Carlo; Bifone, Angelo

    2016-01-01

    Graph theory provides a powerful framework to investigate brain functional connectivity networks and their modular organization. However, most graph-based methods suffer from a fundamental resolution limit that may have affected previous studies and prevented detection of modules, or communities, that are smaller than a specific scale. Surprise, a resolution-limit-free function rooted in discrete probability theory, has been recently introduced and applied to brain networks, revealing a wide size-distribution of functional modules, in contrast with many previous reports. However, the use of Surprise is limited to binary networks, while brain networks are intrinsically weighted, reflecting a continuous distribution of connectivity strengths between different brain regions. Here, we propose Asymptotical Surprise, a continuous version of Surprise, for the study of weighted brain connectivity networks, and validate this approach in synthetic networks endowed with a ground-truth modular structure. We compare Asymp...

  20. Identification and Classification of Hubs in Brain Networks

    Science.gov (United States)

    Sporns, Olaf; Honey, Christopher J.; Kötter, Rolf

    2007-01-01

    Brain regions in the mammalian cerebral cortex are linked by a complex network of fiber bundles. These inter-regional networks have previously been analyzed in terms of their node degree, structural motif, path length and clustering coefficient distributions. In this paper we focus on the identification and classification of hub regions, which are thought to play pivotal roles in the coordination of information flow. We identify hubs and characterize their network contributions by examining motif fingerprints and centrality indices for all regions within the cerebral cortices of both the cat and the macaque. Motif fingerprints capture the statistics of local connection patterns, while measures of centrality identify regions that lie on many of the shortest paths between parts of the network. Within both cat and macaque networks, we find that a combination of degree, motif participation, betweenness centrality and closeness centrality allows for reliable identification of hub regions, many of which have previously been functionally classified as polysensory or multimodal. We then classify hubs as either provincial (intra-cluster) hubs or connector (inter-cluster) hubs, and proceed to show that lesioning hubs of each type from the network produces opposite effects on the small-world index. Our study presents an approach to the identification and classification of putative hub regions in brain networks on the basis of multiple network attributes and charts potential links between the structural embedding of such regions and their functional roles. PMID:17940613

  1. Brain foods: the effects of nutrients on brain function

    OpenAIRE

    Gómez-Pinilla, Fernando

    2008-01-01

    It has long been suspected that the relative abundance of specific nutrients can affect cognitive processes and emotions. Newly described influences of dietary factors on neuronal function and synaptic plasticity have revealed some of the vital mechanisms that are responsible for the action of diet on brain health and mental function. Several gut hormones that can enter the brain, or that are produced in the brain itself, influence cognitive ability. In addition, well-established regulators o...

  2. Whole brain and brain regional coexpression network interactions associated with predisposition to alcohol consumption.

    Directory of Open Access Journals (Sweden)

    Lauren A Vanderlinden

    Full Text Available To identify brain transcriptional networks that may predispose an animal to consume alcohol, we used weighted gene coexpression network analysis (WGCNA. Candidate coexpression modules are those with an eigengene expression level that correlates significantly with the level of alcohol consumption across a panel of BXD recombinant inbred mouse strains, and that share a genomic region that regulates the module transcript expression levels (mQTL with a genomic region that regulates alcohol consumption (bQTL. To address a controversy regarding utility of gene expression profiles from whole brain, vs specific brain regions, as indicators of the relationship of gene expression to phenotype, we compared candidate coexpression modules from whole brain gene expression data (gathered with Affymetrix 430 v2 arrays in the Colorado laboratories and from gene expression data from 6 brain regions (nucleus accumbens (NA; prefrontal cortex (PFC; ventral tegmental area (VTA; striatum (ST; hippocampus (HP; cerebellum (CB available from GeneNetwork. The candidate modules were used to construct candidate eigengene networks across brain regions, resulting in three "meta-modules", composed of candidate modules from two or more brain regions (NA, PFC, ST, VTA and whole brain. To mitigate the potential influence of chromosomal location of transcripts and cis-eQTLs in linkage disequilibrium, we calculated a semi-partial correlation of the transcripts in the meta-modules with alcohol consumption conditional on the transcripts' cis-eQTLs. The function of transcripts that retained the correlation with the phenotype after correction for the strong genetic influence, implicates processes of protein metabolism in the ER and Golgi as influencing susceptibility to variation in alcohol consumption. Integration of these data with human GWAS provides further information on the function of polymorphisms associated with alcohol-related traits.

  3. The functional brain connectome of the child and autism spectrum disorders.

    Science.gov (United States)

    Mevel, Katell; Fransson, Peter

    2016-09-01

    Brain connectomics is a relatively new field of research that maps the brain's large-scale structural and functional networks at rest. The connectome of the human brain develops progressively from early infancy to late adolescence, and this review describes the theory behind the concept and its applicability to studying the development and dynamics of brain networks through graph theoretical metrics. We also describe how the brain connectome concept could further our understanding of autism spectrum disorders (ASD) CONCLUSION: Further research into the functional child brain connectome concept could enhance our understanding of atypical brain connectivity patterns presumed to be linked to ASD. PMID:27228241

  4. Functional brain imaging; Funktionelle Hirnbildgebung

    Energy Technology Data Exchange (ETDEWEB)

    Gizewski, E.R. [Medizinische Universitaet Innsbruck, Universitaetsklinik fuer Neuroradiologie, Innsbruck (Austria)

    2016-02-15

    Functional magnetic resonance imaging (fMRI) is a non-invasive method that has become one of the major tools for understanding human brain function and in recent years has also been developed for clinical applications. Changes in hemodynamic signals correspond to changes in neuronal activity with good spatial and temporal resolution in fMRI. Using high-field MR systems and increasingly dedicated statistics and postprocessing, activated brain areas can be detected and superimposed on anatomical images. Currently, fMRI data are often combined in multimodal imaging, e. g. with diffusion tensor imaging (DTI) sequences. This method is helping to further understand the physiology of cognitive brain processes and is also being used in a number of clinical applications. In addition to the blood oxygenation level-dependent (BOLD) signals, this article deals with the construction of fMRI investigations, selection of paradigms and evaluation in the clinical routine. Clinically, this method is mainly used in the planning of brain surgery, analyzing the location of brain tumors in relation to eloquent brain areas and the lateralization of language processing. As the BOLD signal is dependent on the strength of the magnetic field as well as other limitations, an overview of recent developments is given. Increases of magnetic field strength (7 T), available head coils and advances in MRI analytical methods have led to constant improvement in fMRI signals and experimental design. Especially the depiction of eloquent brain regions can be done easily and quickly and has become an essential part of presurgical planning. (orig.) [German] Mittlerweile ist die funktionelle MRT (fMRT) eine Methode, die nicht mehr nur in der neurowissenschaftlichen Routine verwendet wird. Die fMRT ermoeglicht die nichtinvasive Darstellung der Hirnaktivitaet in guter raeumlicher und zeitlicher Aufloesung unter Ausnutzung der Durchblutungsaenderung aufgrund der erhoehten Nervenzellaktivitaet. Unter

  5. A study of brain networks associated with swallowing using graph-theoretical approaches.

    Directory of Open Access Journals (Sweden)

    Bo Luan

    Full Text Available Functional connectivity between brain regions during swallowing tasks is still not well understood. Understanding these complex interactions is of great interest from both a scientific and a clinical perspective. In this study, functional magnetic resonance imaging (fMRI was utilized to study brain functional networks during voluntary saliva swallowing in twenty-two adult healthy subjects (all females, [Formula: see text] years of age. To construct these functional connections, we computed mean partial correlation matrices over ninety brain regions for each participant. Two regions were determined to be functionally connected if their correlation was above a certain threshold. These correlation matrices were then analyzed using graph-theoretical approaches. In particular, we considered several network measures for the whole brain and for swallowing-related brain regions. The results have shown that significant pairwise functional connections were, mostly, either local and intra-hemispheric or symmetrically inter-hemispheric. Furthermore, we showed that all human brain functional network, although varying in some degree, had typical small-world properties as compared to regular networks and random networks. These properties allow information transfer within the network at a relatively high efficiency. Swallowing-related brain regions also had higher values for some of the network measures in comparison to when these measures were calculated for the whole brain. The current results warrant further investigation of graph-theoretical approaches as a potential tool for understanding the neural basis of dysphagia.

  6. Resting state brain activity and functional brain mapping

    Institute of Scientific and Technical Information of China (English)

    Zhao Xiaohu; Wang Peijun; Tang Xiaowei

    2007-01-01

    Functional brain imaging studies commonly use either resting or passive task states as their control conditions, and typically identify the activation brain region associated with a specific task by subtracting the resting from the active task conditions. Numerous studies now suggest, however, that the resting state may not reflect true mental "rest" conditions. The mental activity that occurs during"rest" might therefore greatly influence the functional neuroimaging observations that are collected through the usual subtracting analysis strategies. Exploring the ongoing mental processes that occur during resting conditions is thus of particular importance for deciphering functional brain mapping results and obtaining a more comprehensive understanding of human brain functions. In this review article, we will mainly focus on the discussion of the current research background of functional brain mapping at resting state and the physiological significance of the available neuroimaging data.

  7. Behavioral and Brain Functions. A new journal

    Directory of Open Access Journals (Sweden)

    Sagvolden Terje

    2005-04-01

    Full Text Available Abstract Behavioral and Brain Functions (BBF is an Open Access, peer-reviewed, online journal considering original research, review, and modeling articles in all aspects of neurobiology or behavior, favoring research that relates to both domains. Behavioral and Brain Functions is published by BioMed Central. The greatest challenge for empirical science is to understand human behavior; how human behavior arises from the myriad functions such as attention, language, memory and emotion; how these functions are reflected in brain structures and functions; and how the brain and behavior are altered in disease. Behavioral and Brain Functions covers the entire area of behavioral and cognitive neuroscience – an area where animal studies traditionally play a prominent role. Behavioral and Brain Functions is published online, allowing unlimited space for figures, extensive datasets to allow readers to study the data for themselves, and moving pictures, which are important qualities assisting communication in modern science.

  8. Plasticity of brain wave network interactions and evolution across physiologic states

    Directory of Open Access Journals (Sweden)

    Kang K. L. Liu

    2015-10-01

    Full Text Available Neural plasticity transcends a range of spatio-temporal scales and serves as the basis of various brain activities and physiologic functions. At the microscopic level, it enables the emergence of brain waves with complex temporal dynamics. At the macroscopic level, presence and dominance of specific brain waves is associated with important brain functions. The role of neural plasticity at different levels in generating distinct brain rhythms and how brain rhythms communicate with each other across brain areas to generate physiologic states and functions remains not understood. Here we perform an empirical exploration of neural plasticity at the level of brain wave network interactions representing dynamical communications within and between different brain areas in the frequency domain. We introduce the concept of time delay stability to quantify coordinated bursts in the activity of brain waves, and we employ a system-wide Network Physiology integrative approach to probe the network of coordinated brain wave activations and its evolution across physiologic states. We find an association between network structure and physiologic states. We uncover a hierarchical reorganization in the brain wave networks in response to changes in physiologic state, indicating new aspects of neural plasticity at the integrated level. Globally, we find that the entire brain network undergoes a pronounced transition from low connectivity in Deep Sleep and REM to high connectivity in Light Sleep and Wake. In contrast, we find that locally, different brain areas exhibit different network dynamics of brain wave interactions to achieve differentiation in function during different sleep stages. Moreover, our analyses indicate that plasticity also emerges in frequency-specific networks, which represent interactions across brain locations mediated through a specific frequency band. Comparing frequency-specific networks within the same physiologic state we find very

  9. Plasticity of brain wave network interactions and evolution across physiologic states

    Science.gov (United States)

    Liu, Kang K. L.; Bartsch, Ronny P.; Lin, Aijing; Mantegna, Rosario N.; Ivanov, Plamen Ch.

    2015-01-01

    Neural plasticity transcends a range of spatio-temporal scales and serves as the basis of various brain activities and physiologic functions. At the microscopic level, it enables the emergence of brain waves with complex temporal dynamics. At the macroscopic level, presence and dominance of specific brain waves is associated with important brain functions. The role of neural plasticity at different levels in generating distinct brain rhythms and how brain rhythms communicate with each other across brain areas to generate physiologic states and functions remains not understood. Here we perform an empirical exploration of neural plasticity at the level of brain wave network interactions representing dynamical communications within and between different brain areas in the frequency domain. We introduce the concept of time delay stability (TDS) to quantify coordinated bursts in the activity of brain waves, and we employ a system-wide Network Physiology integrative approach to probe the network of coordinated brain wave activations and its evolution across physiologic states. We find an association between network structure and physiologic states. We uncover a hierarchical reorganization in the brain wave networks in response to changes in physiologic state, indicating new aspects of neural plasticity at the integrated level. Globally, we find that the entire brain network undergoes a pronounced transition from low connectivity in Deep Sleep and REM to high connectivity in Light Sleep and Wake. In contrast, we find that locally, different brain areas exhibit different network dynamics of brain wave interactions to achieve differentiation in function during different sleep stages. Moreover, our analyses indicate that plasticity also emerges in frequency-specific networks, which represent interactions across brain locations mediated through a specific frequency band. Comparing frequency-specific networks within the same physiologic state we find very different degree of

  10. Reorganization of Functional Connectivity as a Correlate of Cognitive Recovery in Acquired Brain Injury

    Science.gov (United States)

    Castellanos, Nazareth P.; Paul, Nuria; Ordonez, Victoria E.; Demuynck, Olivier; Bajo, Ricardo; Campo, Pablo; Bilbao, Alvaro; Ortiz, Tomas; del-Pozo, Francisco; Maestu, Fernando

    2010-01-01

    Cognitive processes require a functional interaction between specialized multiple, local and remote brain regions. Although these interactions can be strongly altered by an acquired brain injury, brain plasticity allows network reorganization to be principally responsible for recovery. The present work evaluates the impact of brain injury on…

  11. 5-HTTLPR differentially predicts brain network responses to emotional faces

    DEFF Research Database (Denmark)

    Fisher, Patrick M; Grady, Cheryl L; Madsen, Martin K;

    2015-01-01

    The effects of the 5-HTTLPR polymorphism on neural responses to emotionally salient faces have been studied extensively, focusing on amygdala reactivity and amygdala-prefrontal interactions. Despite compelling evidence that emotional face paradigms engage a distributed network of brain regions...... involved in emotion, cognitive and visual processing, less is known about 5-HTTLPR effects on broader network responses. To address this, we evaluated 5-HTTLPR differences in the whole-brain response to an emotional faces paradigm including neutral, angry and fearful faces using functional magnetic...... to fearful faces was significantly greater in S' carriers compared to LA LA individuals. These findings provide novel evidence for emotion-specific 5-HTTLPR effects on the response of a distributed set of brain regions including areas responsive to emotionally salient stimuli and critical components...

  12. Dynamic reconfiguration of frontal brain networks during executive cognition in humans

    OpenAIRE

    Braun, Urs; Schäfer, Axel; Walter, Henrik; Erk, Susanne; Romanczuk-Seiferth, Nina; Haddad, Leila; Schweiger, Janina I.; Grimm, Oliver; Heinz, Andreas; Tost, Heike; Meyer-Lindenberg, Andreas; Bassett, Danielle S

    2015-01-01

    Cognitive flexibility is hypothesized to require dynamic integration between brain areas. However, the time-dependent nature and distributed complexity of this integration remains poorly understood. Using recent advances in network science, we examine the functional integration between brain areas during a quintessential task that requires executive function. By linking brain regions (nodes) by their interactions (time-dependent edges), we uncover nontrivial modular structure: groups of brain...

  13. Dolichol alters brain membrane functions

    International Nuclear Information System (INIS)

    It has been well demonstrated that there is a direct correlation between increase in dolichol level in brain and aging. An abnormally high level of dolichol was found in brain tissue of patients with pathological aging disorders. The aim of this study is to examine the physiological significance of dolichol affecting membrane transport activity and phospholipid acyl group turnover. Dolichol added to synaptic plasma membranes resulted in a biphasic effect on (Na+, K+)-ATPase, i.e., an enhancement of activity at low concentrations (5 μg/125 mg protein) and an inhibition of activity at high concentrations (40-100 μg). To probe the membrane acyl group turnover, the incorporation of [14C]-arachidonate into plasma membrane phospholipids was examined in the presence and absence of dolichol. Dolichol elicited an increase in the incorporation of label into phospholipids. However, the effects varied depending on whether BSA is present. In the absence of BSA, the increase in labeling of phosphatidylinositols is higher than that of phosphatidylcholines. These results suggest that dolichols, when inserted into membranes, may alter membrane functions

  14. Dolichol alters brain membrane functions

    Energy Technology Data Exchange (ETDEWEB)

    Sun, G.Y.; Sun, A.Y.; Schroeder, F.; Wood, G.; Strong, R.

    1986-03-05

    It has been well demonstrated that there is a direct correlation between increase in dolichol level in brain and aging. An abnormally high level of dolichol was found in brain tissue of patients with pathological aging disorders. The aim of this study is to examine the physiological significance of dolichol affecting membrane transport activity and phospholipid acyl group turnover. Dolichol added to synaptic plasma membranes resulted in a biphasic effect on (Na/sup +/, K/sup +/)-ATPase, i.e., an enhancement of activity at low concentrations (5 ..mu..g/125 mg protein) and an inhibition of activity at high concentrations (40-100 ..mu..g). To probe the membrane acyl group turnover, the incorporation of (/sup 14/C)-arachidonate into plasma membrane phospholipids was examined in the presence and absence of dolichol. Dolichol elicited an increase in the incorporation of label into phospholipids. However, the effects varied depending on whether BSA is present. In the absence of BSA, the increase in labeling of phosphatidylinositols is higher than that of phosphatidylcholines. These results suggest that dolichols, when inserted into membranes, may alter membrane functions.

  15. Fast optical imaging of human brain function

    Directory of Open Access Journals (Sweden)

    Gabriele Gratton

    2010-06-01

    Full Text Available Great advancements in brain imaging during the last few decades have opened a large number of new possibilities for neuroscientists. The most dominant methodologies (electrophysiological and magnetic resonance-based methods emphasize temporal and spatial information, respectively. However, theorizing about brain function has recently emphasized the importance of rapid (within 100 ms or so interactions between different elements of complex neuronal networks. Fast optical imaging, and in particular the event-related optical signal (EROS, a technology that has emerged over the last 15 years may provide descriptions of localized (to sub-cm level brain activity with a temporal resolution of less than 100 ms. The main limitations of EROS are its limited penetration, which allows us to image cortical structures not deeper than 3 cm from the surface of the head, and its low signal-to-noise ratio. Advantages include the fact that EROS is compatible with most other imaging methods, including electrophysiological, magnetic resonance, and trans-cranial magnetic stimulation techniques, with which can be recorded concurrently. In this paper we present a summary of the research that has been conducted so far on fast optical imaging, including evidence for the possibility of recording neuronal signals with this method, the properties of the signals, and various examples of applications to the study of human cognitive neuroscience. Extant issues, controversies, and possible future developments are also discussed.

  16. The application of graph theoretical analysis to complex networks in the brain.

    Science.gov (United States)

    Reijneveld, Jaap C; Ponten, Sophie C; Berendse, Henk W; Stam, Cornelis J

    2007-11-01

    Considering the brain as a complex network of interacting dynamical systems offers new insights into higher level brain processes such as memory, planning, and abstract reasoning as well as various types of brain pathophysiology. This viewpoint provides the opportunity to apply new insights in network sciences, such as the discovery of small world and scale free networks, to data on anatomical and functional connectivity in the brain. In this review we start with some background knowledge on the history and recent advances in network theories in general. We emphasize the correlation between the structural properties of networks and the dynamics of these networks. We subsequently demonstrate through evidence from computational studies, in vivo experiments, and functional MRI, EEG and MEG studies in humans, that both the functional and anatomical connectivity of the healthy brain have many features of a small world network, but only to a limited extent of a scale free network. The small world structure of neural networks is hypothesized to reflect an optimal configuration associated with rapid synchronization and information transfer, minimal wiring costs, resilience to certain types of damage, as well as a balance between local processing and global integration. Eventually, we review the current knowledge on the effects of focal and diffuse brain disease on neural network characteristics, and demonstrate increasing evidence that both cognitive and psychiatric disturbances, as well as risk of epileptic seizures, are correlated with (changes in) functional network architectural features. PMID:17900977

  17. INFORMATION BASED METAPHORS: FROM BRAIN TO NETWORK

    Directory of Open Access Journals (Sweden)

    Marcos Cortez Campomar

    2009-10-01

    Full Text Available Metaphoric language has grown in popularity over the last years. Once simple figure of speech, metaphors were transformed into a respectable approach for organizational analysis. The brain metaphor constitutes an attractive system of ideas for studying organizational phenomena. In this paper, it is used the brain metaphor as a point of departure in developing another informational metaphor: the network metaphor. It is suggested that the latter might provide a better perspective for studying contemporary organizations in this age of information and telecommunications.

  18. Plasticity of resting state brain networks in recovery from stress

    Directory of Open Access Journals (Sweden)

    Jose Miguel Soares

    2013-12-01

    Full Text Available Chronic stress has been widely reported to have deleterious impact in multiple biological systems. Specifically, structural and functional remodelling of several brain regions following prolonged stress exposure have been described; importantly, some of these changes are eventually reversible. Recently, we showed the impact of stress on resting state networks (RSNs, but nothing is known about the plasticity of RSNs after recovery from stress. Herein, we examined the plasticity of RSNs, both at functional and structural levels, by comparing the same individuals before and after recovery from the exposure to chronic stress; results were also contrasted with a control group. Here we show that the stressed individuals after recovery displayed a decreased resting functional connectivity in the default mode network (DMN, ventral attention network (VAN and sensorimotor network (SMN when compared to themselves immediately after stress; however, this functional plastic recovery was only partial as when compared with the control group, as there were still areas of increased connectivity in dorsal attention network (DAN, SMN and primary visual network (VN in participants recovered from stress. Data also shows that participants after recovery from stress displayed increased deactivations in DMN, SMN and auditory network (AN, to levels similar to those of controls, showing a normalization of the deactivation pattern in RSNs after recovery from stress. In contrast, structural changes (volumetry of the brain areas involving these networks are absent after the recovery period. These results reveal plastic phenomena in specific RSNs and a functional remodeling of the activation-deactivation pattern following recovery from chronic-stress, which is not accompanied by significant structural plasticity.

  19. Differential synchronization in default and task-specific networks of the human brain

    Directory of Open Access Journals (Sweden)

    Aaron Kirschner

    2012-05-01

    Full Text Available On a regional scale the brain is organized into dynamic functional networks. The activity within one of these, the default network, can be dissociated from that in other task-specific networks. All brain networks are connected structurally, but evidently are only transiently connected functionally. One hypothesis as to how such transient functional coupling occurs is that network formation and dissolution is mediated, or at least accompanied, by increases and decreases in oscillatory synchronization between constituent brain regions. If so, then we should be able to find transient differences in intra-network synchronization between the default network and a task-specific network. In order to investigate this hypothesis we conducted two experiments in which subjects engaged in a Sustained Attention to Response Task (SART while having brain activity recorded via high-density electroencephalography (EEG. We found that during periods when attention was focused internally (mind-wandering there was significantly more neural phase synchronization between brain regions associated with the default network, whereas during periods when subjects were focused on performing the visual task there was significantly more neural phase synchrony within a task-specific brain network that shared some of the same brain regions. These differences in network synchrony occurred in each of theta, alpha, and gamma frequency bands. A similar pattern of differential oscillatory power changes, indicating modulation of local synchronization by attention state, was also found. These results provide further evidence that the human brain is intrinsically organized into default and task-specific brain networks, and confirm that oscillatory synchronization is a potential mechanism for functional coupling within these networks.

  20. Aberrant functional brain connectome in people with antisocial personality disorder

    Science.gov (United States)

    Tang, Yan; Long, Jun; Wang, Wei; Liao, Jian; Xie, Hua; Zhao, Guihu; Zhang, Hao

    2016-01-01

    Antisocial personality disorder (ASPD) is characterised by a disregard for social obligations and callous unconcern for the feelings of others. Studies have demonstrated that ASPD is associated with abnormalities in brain regions and aberrant functional connectivity. In this paper, topological organisation was examined in resting-state fMRI data obtained from 32 ASPD patients and 32 non-ASPD controls. The frequency-dependent functional networks were constructed using wavelet-based correlations over 90 brain regions. The topology of the functional networks of ASPD subjects was analysed via graph theoretical analysis. Furthermore, the abnormal functional connectivity was determined with a network-based statistic (NBS) approach. Our results revealed that, compared with the controls, the ASPD patients exhibited altered topological configuration of the functional connectome in the frequency interval of 0.016–0.031 Hz, as indicated by the increased clustering coefficient and decreased betweenness centrality in the medial superior frontal gyrus, precentral gyrus, Rolandic operculum, superior parietal gyrus, angular gyrus, and middle temporal pole. In addition, the ASPD patients showed increased functional connectivity mainly located in the default-mode network. The present study reveals an aberrant topological organisation of the functional brain network in individuals with ASPD. Our findings provide novel insight into the neuropathological mechanisms of ASPD. PMID:27257047

  1. Aberrant functional brain connectome in people with antisocial personality disorder.

    Science.gov (United States)

    Tang, Yan; Long, Jun; Wang, Wei; Liao, Jian; Xie, Hua; Zhao, Guihu; Zhang, Hao

    2016-01-01

    Antisocial personality disorder (ASPD) is characterised by a disregard for social obligations and callous unconcern for the feelings of others. Studies have demonstrated that ASPD is associated with abnormalities in brain regions and aberrant functional connectivity. In this paper, topological organisation was examined in resting-state fMRI data obtained from 32 ASPD patients and 32 non-ASPD controls. The frequency-dependent functional networks were constructed using wavelet-based correlations over 90 brain regions. The topology of the functional networks of ASPD subjects was analysed via graph theoretical analysis. Furthermore, the abnormal functional connectivity was determined with a network-based statistic (NBS) approach. Our results revealed that, compared with the controls, the ASPD patients exhibited altered topological configuration of the functional connectome in the frequency interval of 0.016-0.031 Hz, as indicated by the increased clustering coefficient and decreased betweenness centrality in the medial superior frontal gyrus, precentral gyrus, Rolandic operculum, superior parietal gyrus, angular gyrus, and middle temporal pole. In addition, the ASPD patients showed increased functional connectivity mainly located in the default-mode network. The present study reveals an aberrant topological organisation of the functional brain network in individuals with ASPD. Our findings provide novel insight into the neuropathological mechanisms of ASPD. PMID:27257047

  2. Rounding of abrupt phase transitions in brain networks

    International Nuclear Information System (INIS)

    The observation of critical-like behavior in cortical networks represents a major step forward in elucidating how the brain manages information. Understanding the origin and functionality of critical-like dynamics, as well as its robustness, is a major challenge in contemporary neuroscience. Here, we present an extensive numerical study of a family of simple dynamical models, which describe activity propagation in brain networks through the integration of different neighboring spiking potentials, mimicking basic neural interactions. The requirement of signal integration may lead to discontinuous phase transitions in networks that are well described by the mean-field approximation, thus preventing the emergence of critical points in such systems. Brain networks, however, are finite dimensional and exhibit a heterogeneous hierarchical structure that cannot be encoded in mean-field models. Here we propose that, as a consequence of the presence of such a heterogeneous substrate with its concomitant structural disorder, critical-like features may emerge even in the presence of integration. These conclusions may prove significant in explaining the observation of traits of critical behavior in large-scale measurements of brain activity. (paper)

  3. Promoting Motor Function by Exercising the Brain

    OpenAIRE

    Stephane Perrey

    2013-01-01

    Exercise represents a behavioral intervention that enhances brain health and motor function. The increase in cerebral blood volume in response to physical activity may be responsible for improving brain function. Among the various neuroimaging techniques used to monitor brain hemodynamic response during exercise, functional near-infrared spectroscopy could facilitate the measurement of task-related cortical responses noninvasively and is relatively robust with regard to the subjects’ motion. ...

  4. Human intelligence and brain networks

    OpenAIRE

    Colom, Roberto; Karama, Sherif; Jung, Rex E.; Haier, Richard J.

    2010-01-01

    Intelligence can be defined as a general mental ability for reasoning, problem solving, and learning. Because of its general nature, intelligence integrates cognitive functions such as perception, attention, memory, language, or planning. On the basis of this definition, intelligence can be reliably measured by standardized tests with obtained scores predicting several broad social outcomes such as educational achievement, job performance, health, and longevity. A detailed understanding of th...

  5. Sinc-function based Network

    DEFF Research Database (Denmark)

    Madsen, Per Printz

    1998-01-01

    The purpose of this paper is to describe a neural network (SNN), that is based on Shannons ideas of reconstruction of a real continuous function from its samples. The basic function, used in this network, is the Sinc-function. Two learning algorithms are described. A simple one called IM...

  6. Sinc-function based Network

    DEFF Research Database (Denmark)

    Madsen, Per Printz

    1999-01-01

    The purpose of this paper is to describe a neural network (SNN), that is based on Shannons ideas of reconstruction of a real continuous function from its samples. The basic function, used in this network, is the Sinc-function. Two learning algorithms are described. A simple one called IM...

  7. scMRI reveals large-scale brain network abnormalities in autism.

    Directory of Open Access Journals (Sweden)

    Brandon A Zielinski

    Full Text Available Autism is a complex neurological condition characterized by childhood onset of dysfunction in multiple cognitive domains including socio-emotional function, speech and language, and processing of internally versus externally directed stimuli. Although gross brain anatomic differences in autism are well established, recent studies investigating regional differences in brain structure and function have yielded divergent and seemingly contradictory results. How regional abnormalities relate to the autistic phenotype remains unclear. We hypothesized that autism exhibits distinct perturbations in network-level brain architecture, and that cognitive dysfunction may be reflected by abnormal network structure. Network-level anatomic abnormalities in autism have not been previously described. We used structural covariance MRI to investigate network-level differences in gray matter structure within two large-scale networks strongly implicated in autism, the salience network and the default mode network, in autistic subjects and age-, gender-, and IQ-matched controls. We report specific perturbations in brain network architecture in the salience and default-mode networks consistent with clinical manifestations of autism. Extent and distribution of the salience network, involved in social-emotional regulation of environmental stimuli, is restricted in autism. In contrast, posterior elements of the default mode network have increased spatial distribution, suggesting a 'posteriorization' of this network. These findings are consistent with a network-based model of autism, and suggest a unifying interpretation of previous work. Moreover, we provide evidence of specific abnormalities in brain network architecture underlying autism that are quantifiable using standard clinical MRI.

  8. A Signal-Processing-Based Approach to Time-Varying Graph Analysis for Dynamic Brain Network Identification

    OpenAIRE

    Ali Yener Mutlu; Edward Bernat; Selin Aviyente

    2012-01-01

    In recent years, there has been a growing need to analyze the functional connectivity of the human brain. Previous studies have focused on extracting static or time-independent functional networks to describe the long-term behavior of brain activity. However, a static network is generally not sufficient to represent the long term communication patterns of the brain and is considered as an unreliable snapshot of functional connectivity. In this paper, we propose a dynamic network summarization...

  9. Promoting motor function by exercising the brain.

    Science.gov (United States)

    Perrey, Stephane

    2013-01-01

    Exercise represents a behavioral intervention that enhances brain health and motor function. The increase in cerebral blood volume in response to physical activity may be responsible for improving brain function. Among the various neuroimaging techniques used to monitor brain hemodynamic response during exercise, functional near-infrared spectroscopy could facilitate the measurement of task-related cortical responses noninvasively and is relatively robust with regard to the subjects' motion. Although the components of optimal exercise interventions have not been determined, evidence from animal and human studies suggests that aerobic exercise with sufficiently high intensity has neuroprotective properties and promotes motor function. This review provides an insight into the effect of physical activity (based on endurance and resistance exercises) on brain function for producing movement. Since most progress in the study of brain function has come from patients with neurological disorders (e.g., stroke and Parkinson's patients), this review presents some findings emphasizing training paradigms for restoring motor function. PMID:24961309

  10. Investigating a Novel Measure of Brain Networking Following Sports Concussion.

    Science.gov (United States)

    Broglio, S P; Rettmann, A; Greer, J; Brimacombe, S; Moore, B; Narisetty, N; He, X; Eckner, J

    2016-08-01

    Clinicians managing sports-related concussions are left to their clinical judgment in making diagnoses and return-to-play decisions. This study was designed to evaluate the utility of a novel measure of functional brain networking for concussion management. 24 athletes with acutely diagnosed concussion and 21 control participants were evaluated in a research laboratory. At each of the 4 post-injury time points, participants completed the Axon assessment of neurocognitive function, a self-report symptom inventory, and the auditory oddball and go/no-go tasks while electroencephalogram (EEG) readings were recorded. Brain Network Activation (BNA) scores were calculated from EEG data related to the auditory oddball and go/no-go tasks. BNA scores were unable to differentiate between the concussed and control groups or by self-report symptom severity. These findings conflict with previous work implementing electrophysiological assessments in concussed athletes, suggesting that BNA requires additional investigation and refinement before clinical implementation. PMID:27286176

  11. Connectivity and functional profiling of abnormal brain structures in pedophilia

    Science.gov (United States)

    Poeppl, Timm B.; Eickhoff, Simon B.; Fox, Peter T.; Laird, Angela R.; Rupprecht, Rainer; Langguth, Berthold; Bzdok, Danilo

    2015-01-01

    Despite its 0.5–1% lifetime prevalence in men and its general societal relevance, neuroimaging investigations in pedophilia are scarce. Preliminary findings indicate abnormal brain structure and function. However, no study has yet linked structural alterations in pedophiles to both connectional and functional properties of the aberrant hotspots. The relationship between morphological alterations and brain function in pedophilia as well as their contribution to its psychopathology thus remain unclear. First, we assessed bimodal connectivity of structurally altered candidate regions using meta-analytic connectivity modeling (MACM) and resting-state correlations employing openly accessible data. We compared the ensuing connectivity maps to the activation likelihood estimation (ALE) maps of a recent quantitative meta-analysis of brain activity during processing of sexual stimuli. Second, we functionally characterized the structurally altered regions employing meta-data of a large-scale neuroimaging database. Candidate regions were functionally connected to key areas for processing of sexual stimuli. Moreover, we found that the functional role of structurally altered brain regions in pedophilia relates to nonsexual emotional as well as neurocognitive and executive functions, previously reported to be impaired in pedophiles. Our results suggest that structural brain alterations affect neural networks for sexual processing by way of disrupted functional connectivity, which may entail abnormal sexual arousal patterns. The findings moreover indicate that structural alterations account for common affective and neurocognitive impairments in pedophilia. The present multi-modal integration of brain structure and function analyses links sexual and nonsexual psychopathology in pedophilia. PMID:25733379

  12. Connectivity and functional profiling of abnormal brain structures in pedophilia.

    Science.gov (United States)

    Poeppl, Timm B; Eickhoff, Simon B; Fox, Peter T; Laird, Angela R; Rupprecht, Rainer; Langguth, Berthold; Bzdok, Danilo

    2015-06-01

    Despite its 0.5-1% lifetime prevalence in men and its general societal relevance, neuroimaging investigations in pedophilia are scarce. Preliminary findings indicate abnormal brain structure and function. However, no study has yet linked structural alterations in pedophiles to both connectional and functional properties of the aberrant hotspots. The relationship between morphological alterations and brain function in pedophilia as well as their contribution to its psychopathology thus remain unclear. First, we assessed bimodal connectivity of structurally altered candidate regions using meta-analytic connectivity modeling (MACM) and resting-state correlations employing openly accessible data. We compared the ensuing connectivity maps to the activation likelihood estimation (ALE) maps of a recent quantitative meta-analysis of brain activity during processing of sexual stimuli. Second, we functionally characterized the structurally altered regions employing meta-data of a large-scale neuroimaging database. Candidate regions were functionally connected to key areas for processing of sexual stimuli. Moreover, we found that the functional role of structurally altered brain regions in pedophilia relates to nonsexual emotional as well as neurocognitive and executive functions, previously reported to be impaired in pedophiles. Our results suggest that structural brain alterations affect neural networks for sexual processing by way of disrupted functional connectivity, which may entail abnormal sexual arousal patterns. The findings moreover indicate that structural alterations account for common affective and neurocognitive impairments in pedophilia. The present multimodal integration of brain structure and function analyses links sexual and nonsexual psychopathology in pedophilia. PMID:25733379

  13. Brain networks underlying bistable perception.

    Science.gov (United States)

    Baker, Daniel H; Karapanagiotidis, Theodoros; Coggan, David D; Wailes-Newson, Kirstie; Smallwood, Jonathan

    2015-10-01

    Bistable stimuli, such as the Necker Cube, demonstrate that experience can change in the absence of changes in the environment. Such phenomena can be used to assess stimulus-independent aspects of conscious experience. The current study used resting state functional magnetic resonance imaging (rs-fMRI) to index stimulus-independent changes in neural activity to understand the neural architecture that determines dominance durations during bistable perception (using binocular rivalry and Necker cube stimuli). Anterior regions of the Superior Parietal Lobule (SPL) exhibited robust connectivity with regions of primary sensorimotor cortex. The strength of this region's connectivity with the striatum predicted shorter dominance durations during binocular rivalry, whereas its connectivity to pre-motor cortex predicted longer dominance durations for the Necker Cube. Posterior regions of the SPL, on the other hand, were coupled to associative cortex in the temporal and frontal lobes. The posterior SPL's connectivity to the temporal lobe predicted longer dominance during binocular rivalry. In conjunction with prior work, these data suggest that the anterior SPL contributes to perceptual rivalry through the inhibition of incongruent bottom up information, whereas the posterior SPL influences rivalry by supporting the current interpretation of a bistable stimulus. Our data suggests that the functional connectivity of the SPL with regions of sensory, motor, and associative cortex allows it to regulate the interpretation of the environment that forms the focus of conscious attention at a specific moment in time. PMID:26123379

  14. Frequency-specific network topologies in the resting human brain

    Directory of Open Access Journals (Sweden)

    Shuntaro Sasai

    2014-12-01

    Full Text Available A community is a set of nodes with dense inter-connections, while there are sparse connections between different communities. A hub is a highly connected node with high centrality. It has been shown that both “communities” and “hubs” exist simultaneously in the brain’s functional connectivity network, as estimated by correlations among low-frequency spontaneous fluctuations in functional magnetic resonance imaging (fMRI signal changes (0.01–0.10 Hz. This indicates that the brain has a spatial organization that promotes both segregation and integration of information. Here, we demonstrate that frequency-specific network topologies that characterize segregation and integration also exist within this frequency range. In investigating the coherence spectrum among 87 brain regions, we found that two frequency bands, 0.01–0.03 Hz (very low frequency [VLF] band and 0.07–0.09 Hz (low frequency [LF] band, mainly contributed to functional connectivity. Comparing graph theoretical indices for the VLF and LF bands revealed that the network in the former had a higher capacity for information segregation between identified communities than the latter. Hubs in the VLF band were mainly located within the anterior cingulate cortices, whereas those in the LF band were located in the posterior cingulate cortices and thalamus. Thus, depending on the timescale of brain activity, at least two distinct network topologies contributed to information segregation and integration. This suggests that the brain intrinsically has timescale-dependent functional organizations.

  15. Extraversion and Neuroticism relate to topological properties of resting-state brain networks

    OpenAIRE

    Qing Gao; Qiang Xu; Zhiqiang Zhang; Yuan Li

    2013-01-01

    With the advent and development of modern neuroimaging techniques, there is an increasing interest in linking extraversion and neuroticism to anatomical and functional brain markers. Here we aimed to test the theoretically derived biological personality model as proposed by Eysenck using graph theoretical analyses. Specifically, the association between the topological organization of whole-brain functional networks and extraversion/neuroticism was explored. To construct functional brain netwo...

  16. Extraversion and neuroticism relate to topological properties of resting-state brain networks

    OpenAIRE

    Gao, Qing; Xu, Qiang; Duan, Xujun; Liao, Wei(Institute of Modern Physics, School of Science, East China University of Science and Technology, Shanghai, China); Ding, Jurong; Zhang, Zhiqiang; Li, Yuan; Lu, Guangming; Chen, Huafu

    2013-01-01

    With the advent and development of modern neuroimaging techniques, there is an increasing interest in linking extraversion and neuroticism to anatomical and functional brain markers. Here, we aimed to test the theoretically derived biological personality model as proposed by Eysenck using graph theoretical analyses. Specifically, the association between the topological organization of whole-brain functional networks and extraversion/neuroticism was explored. To construct functional brain netw...

  17. Optogenetic approaches for functional mouse brain mapping

    OpenAIRE

    Diana H Lim; LeDue, Jeffrey; Mohajerani, Majid H.; Vanni, Matthieu P.; Murphy, Timothy H.

    2013-01-01

    To better understand the connectivity of the brain, it is important to map both structural and functional connections between neurons and cortical regions. In recent years, a set of optogenetic tools have been developed that permit selective manipulation and investigation of neural systems. These tools have enabled the mapping of functional connections between stimulated cortical targets and other brain regions. Advantages of the approach include the ability to arbitrarily stimulate brain reg...

  18. Meeting the memory challenges of brain-scale network simulation

    Directory of Open Access Journals (Sweden)

    Susanne eKunkel

    2012-01-01

    Full Text Available The development of high-performance simulation software is crucial for studying the brain connectome. Using connectome data to generate neurocomputational models requires software capable of coping with models on a variety of scales: from the microscale, investigating plasticity and dynamics of circuits in local networks, to the macroscale, investigating the interactions between distinct brain regions. Prior to any serious dynamical investigation, the first task of network simulations is to check the consistency of data integrated in the connectome and constrain ranges for yet unknown parameters. Thanks to distributed computing techniques, it is possible today to routinely simulate local cortical networks of around 10^5 neurons with up to 10^9 synapses on clusters and multi-processor shared-memory machines. However, brain-scale networks are one or two orders of magnitude larger than such local networks, in terms of numbers of neurons and synapses as well as in terms of computational load. Such networks have been studied in individual studies, but the underlying simulation technologies have neither been described in sufficient detail to be reproducible nor made publicly available. Here, we discover that as the network model sizes approach the regime of meso- and macroscale simulations, memory consumption on individual compute nodes becomes a critical bottleneck. This is especially relevant on modern supercomputers such as the Bluegene/P architecture where the available working memory per CPU core is rather limited. We develop a simple linear model to analyze the memory consumption of the constituent components of a neuronal simulator as a function of network size and the number of cores used. This approach has multiple benefits. The model enables identification of key contributing components to memory saturation and prediction of the effects of potential improvements to code before any implementation takes place.

  19. Plasticity of brain networks in a randomized intervention trial of exercise training in older adults

    Directory of Open Access Journals (Sweden)

    Michelle W Voss

    2010-08-01

    Full Text Available Research has shown the human brain is organized into separable functional networks during rest and varied states of cognition, and that aging is associated with specific network dysfunctions. The present study used functional magnetic resonance imaging (fMRI to examine low-frequency (.008<.08 Hz coherence of cognitively relevant and sensory brain networks in older adults who participated in a one-year intervention trial, comparing the effects of aerobic and non-aerobic fitness training on brain function and cognition. Results showed that aerobic training improved the aging brain’s resting functional efficiency in higher-level cognitive networks. One year of walking increased functional connectivity between aspects of the frontal, posterior, and temporal cortices within the Default Mode Network and a Frontal Executive Network, two brain networks central to brain dysfunction in aging. Length of training was also an important factor. Effects in favor of the walking group were observed only after 12 months of training, compared to non-significant trends after six months. A non-aerobic stretching and toning group also showed increased functional connectivity in the DMN after six months and in a Frontal Parietal Network after 12 months, possibly reflecting experience-dependent plasticity. Finally, we found that changes in functional connectivity were behaviorally relevant. Increased functional connectivity was associated with greater improvement in executive function. Therefore the study provides the first evidence for exercise-induced functional plasticity in large-scale brain systems in the aging brain, using functional connectivity techniques, and offers new insight into the role of aerobic fitness in attenuating age-related brain dysfunction.

  20. Disrupted functional brain connectome in unilateral sudden sensorineural hearing loss.

    Science.gov (United States)

    Xu, Haibo; Fan, Wenliang; Zhao, Xueyan; Li, Jing; Zhang, Wenjuan; Lei, Ping; Liu, Yuan; Wang, Haha; Cheng, Huamao; Shi, Hong

    2016-05-01

    Sudden sensorineural hearing loss (SSNHL) is generally defined as sensorineural hearing loss of 30 dB or greater over at least three contiguous audiometric frequencies and within a three-day period. This hearing loss is usually unilateral and can be associated with tinnitus and vertigo. The pathogenesis of unilateral sudden sensorineural hearing loss is still unknown, and the alterations in the functional connectivity are suspected to involve one possible pathogenesis. Despite scarce findings with respect to alterations in brain functional networks in unilateral sudden sensorineural hearing loss, the alterations of the whole brain functional connectome and whether these alterations were already in existence in the acute period remains unknown. The aim of this study was to investigate the alterations of brain functional connectome in two large samples of unilateral sudden sensorineural hearing loss patients and to investigate the correlation between unilateral sudden sensorineural hearing loss characteristics and changes in the functional network properties. Pure tone audiometry was performed to assess hearing ability. Abnormal changes in the peripheral auditory system were examined using conventional magnetic resonance imaging. The graph theoretical network analysis method was used to detect brain connectome alterations in unilateral sudden sensorineural hearing loss. Compared with the control groups, both groups of unilateral SSNHL patients exhibited a significantly increased clustering coefficient, global efficiency, and local efficiency but a significantly decreased characteristic path length. In addition, the primary increased nodal strength (e.g., nodal betweenness, hubs) was observed in several regions primarily, including the limbic and paralimbic systems, and in the auditory network brain areas. These findings suggest that the alteration of network organization already exists in unilateral sudden sensorineural hearing loss patients within the acute period

  1. Dynamic functional network connectivity using distance correlation

    Science.gov (United States)

    Rudas, Jorge; Guaje, Javier; Demertzi, Athena; Heine, Lizette; Tshibanda, Luaba; Soddu, Andrea; Laureys, Steven; Gómez, Francisco

    2015-01-01

    Investigations about the intrinsic brain organization in resting-state are critical for the understanding of healthy, pathological and pharmacological cerebral states. Recent studies on fMRI suggest that resting state activity is organized on large scale networks of coordinated activity, in the so called, Resting State Networks (RSNs). The assessment of the interactions among these functional networks plays an important role for the understanding of different brain pathologies. Current methods to quantify these interactions commonly assume that the underlying coordination mechanisms are stationary and linear through the whole recording of the resting state phenomena. Nevertheless, recent evidence suggests that rather than stationary, these mechanisms may exhibit a rich set of time-varying repertoires. In addition, these approaches do not consider possible non-linear relationships maybe linked to feed-back communication mechanisms between RSNs. In this work, we introduce a novel approach for dynamical functional network connectivity for functional magnetic resonance imaging (fMRI) resting activity, which accounts for non-linear dynamic relationships between RSNs. The proposed method is based on a windowed distance correlations computed on resting state time-courses extracted at single subject level. We showed that this strategy is complementary to the current approaches for dynamic functional connectivity and will help to enhance the discrimination capacity of patients with disorder of consciousness.

  2. The restless brain: how intrinsic activity organizes brain function.

    Science.gov (United States)

    Raichle, Marcus E

    2015-05-19

    Traditionally studies of brain function have focused on task-evoked responses. By their very nature such experiments tacitly encourage a reflexive view of brain function. While such an approach has been remarkably productive at all levels of neuroscience, it ignores the alternative possibility that brain functions are mainly intrinsic and ongoing, involving information processing for interpreting, responding to and predicting environmental demands. I suggest that the latter view best captures the essence of brain function, a position that accords well with the allocation of the brain's energy resources, its limited access to sensory information and a dynamic, intrinsic functional organization. The nature of this intrinsic activity, which exhibits a surprising level of organization with dimensions of both space and time, is revealed in the ongoing activity of the brain and its metabolism. As we look to the future, understanding the nature of this intrinsic activity will require integrating knowledge from cognitive and systems neuroscience with cellular and molecular neuroscience where ion channels, receptors, components of signal transduction and metabolic pathways are all in a constant state of flux. The reward for doing so will be a much better understanding of human behaviour in health and disease. PMID:25823869

  3. Kauffman networks with threshold functions

    OpenAIRE

    Greil, Florian; Drossel, Barbara

    2007-01-01

    We investigate Threshold Random Boolean Networks with $K = 2$ inputs per node, which are equivalent to Kauffman networks, with only part of the canalyzing functions as update functions. According to the simplest consideration these networks should be critical but it turns out that they show a rich variety of behaviors, including periodic and chaotic oscillations. The results are supported by analytical calculations and computer simulations.

  4. Network-based functional enrichment

    Directory of Open Access Journals (Sweden)

    Poirel Christopher L

    2011-11-01

    Full Text Available Abstract Background Many methods have been developed to infer and reason about molecular interaction networks. These approaches often yield networks with hundreds or thousands of nodes and up to an order of magnitude more edges. It is often desirable to summarize the biological information in such networks. A very common approach is to use gene function enrichment analysis for this task. A major drawback of this method is that it ignores information about the edges in the network being analyzed, i.e., it treats the network simply as a set of genes. In this paper, we introduce a novel method for functional enrichment that explicitly takes network interactions into account. Results Our approach naturally generalizes Fisher’s exact test, a gene set-based technique. Given a function of interest, we compute the subgraph of the network induced by genes annotated to this function. We use the sequence of sizes of the connected components of this sub-network to estimate its connectivity. We estimate the statistical significance of the connectivity empirically by a permutation test. We present three applications of our method: i determine which functions are enriched in a given network, ii given a network and an interesting sub-network of genes within that network, determine which functions are enriched in the sub-network, and iii given two networks, determine the functions for which the connectivity improves when we merge the second network into the first. Through these applications, we show that our approach is a natural alternative to network clustering algorithms. Conclusions We presented a novel approach to functional enrichment that takes into account the pairwise relationships among genes annotated by a particular function. Each of the three applications discovers highly relevant functions. We used our methods to study biological data from three different organisms. Our results demonstrate the wide applicability of our methods. Our algorithms are

  5. ABCD: a functional database for the avian brain.

    Science.gov (United States)

    Schrott, Aniko; Kabai, Peter

    2008-01-30

    Here we present the first database developed for storing, retrieving and cross-referencing neuroscience information about the connectivity of the avian brain. The Avian Brain Circuitry Database (ABCD) contains entries about the new and old terminology of the areas and their hierarchy, data on connections between brain regions, as well as a functional keyword system linked to brain regions and connections. Data were collected from the primary literature and textbooks, and an online submission system was developed to facilitate further data collection directly from researchers. The database aims to help spread the results of avian connectivity studies, the recently revised nomenclature and also to provide data for brain network research. ABCD is freely available at http://www.behav.org/abcd. PMID:17889371

  6. Functional constraints in the evolution of brain circuits

    Science.gov (United States)

    Bosman, Conrado A.; Aboitiz, Francisco

    2015-01-01

    Regardless of major anatomical and neurodevelopmental differences, the vertebrate isocortex shows a remarkably well-conserved organization. In the isocortex, reciprocal connections between excitatory and inhibitory neurons are distributed across multiple layers, encompassing modular, dynamical and recurrent functional networks during information processing. These dynamical brain networks are often organized in neuronal assemblies interacting through rhythmic phase relationships. Accordingly, these oscillatory interactions are observed across multiple brain scale levels, and they are associated with several sensory, motor, and cognitive processes. Most notably, oscillatory interactions are also found in the complete spectrum of vertebrates. Yet, it is unknown why this functional organization is so well conserved in evolution. In this perspective, we propose some ideas about how functional requirements of the isocortex can account for the evolutionary stability observed in microcircuits across vertebrates. We argue that isocortex architectures represent canonical microcircuits resulting from: (i) the early selection of neuronal architectures based on the oscillatory excitatory-inhibitory balance, which lead to the implementation of compartmentalized oscillations and (ii) the subsequent emergence of inferential coding strategies (predictive coding), which are able to expand computational capacities. We also argue that these functional constraints may be the result of several advantages that oscillatory activity contributes to brain network processes, such as information transmission and code reliability. In this manner, similarities in mesoscale brain circuitry and input-output organization between different vertebrate groups may reflect evolutionary constraints imposed by these functional requirements, which may or may not be traceable to a common ancestor. PMID:26388716

  7. Spatial dependencies between large-scale brain networks.

    Directory of Open Access Journals (Sweden)

    Robert Leech

    Full Text Available Functional neuroimaging reveals both increases (task-positive and decreases (task-negative in neural activation with many tasks. Many studies show a temporal relationship between task positive and task negative networks that is important for efficient cognitive functioning. Here we provide evidence for a spatial relationship between task positive and negative networks. There are strong spatial similarities between many reported task negative brain networks, termed the default mode network, which is typically assumed to be a spatially fixed network. However, this is not the case. The spatial structure of the DMN varies depending on what specific task is being performed. We test whether there is a fundamental spatial relationship between task positive and negative networks. Specifically, we hypothesize that the distance between task positive and negative voxels is consistent despite different spatial patterns of activation and deactivation evoked by different cognitive tasks. We show significantly reduced variability in the distance between within-condition task positive and task negative voxels than across-condition distances for four different sensory, motor and cognitive tasks--implying that deactivation patterns are spatially dependent on activation patterns (and vice versa, and that both are modulated by specific task demands. We also show a similar relationship between positively and negatively correlated networks from a third 'rest' dataset, in the absence of a specific task. We propose that this spatial relationship may be the macroscopic analogue of microscopic neuronal organization reported in sensory cortical systems, and that this organization may reflect homeostatic plasticity necessary for efficient brain function.

  8. The brain stem function in patients with brain bladder

    International Nuclear Information System (INIS)

    A syndrome of detrusor-sphincter dyssynergia (DSD) is occasionally found in patients with brain bladder. To evaluate the brain stem function in cases of brain bladder, urodynamic study, dynamic CT scan of the brain stem (DCT) and auditory brainstem response (ABR) were performed. The region of interest of DCT aimed at the posterolateral portion of the pons. The results were analysed in contrast with the presense of DSD in urodynamic study. DCT studies were performed in 13 cases with various brain diseases and 5 control cases without neurological diseases. Abnormal patterns of the time-density curve consisted of low peak value, prolongation of filling time and low rapid washout ratio (low clearance ratio) of the contrast medium. Four of 6 cases with DSD showed at least one of the abnormal patterns of the time-density curve bilaterally. In 7 cases without DSD none showed bilateral abnormality of the curve and in 2 of 7 cases only unilateral abnormality was found. ABR was performed in 8 patients with brain diseases. The interpeak latency of the wave I-V (I-V IPL) was considered to be prolonged in 2 cases with DSD compared to that of 4 without DSD. In 2 cases with DSD who had normal DCT findings, measurement of the I-V IPL was impossible due to abnormal pattern of the ABR wave. Above mentioned results suggests the presence of functional disturbance at the posterolateral portion of the pons in cases of brain bladder with DSD. (author)

  9. Network Dynamics with BrainX3: A Large-Scale Simulation of the Human Brain Network with Real-Time Interaction

    Directory of Open Access Journals (Sweden)

    Xerxes D. Arsiwalla

    2015-02-01

    Full Text Available BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimulations to observe reverberating network activity, simulate lesion dynamics or implement network analysis functions from a library of graph theoretic measures. BrainX3 can thus be used as a novel immersive platform for real-time exploration and analysis of dynamical activity patterns in brain networks, both at rest or in a task-related state, for discovery of signaling pathways associated to brain function and/or dysfunction and as a tool for virtual neurosurgery. Our results demonstrate these functionalities and shed insight on the dynamics of the resting-state attractor. Specifically, we found that a noisy network seems to favor a low firing attractor state. We also found that the dynamics of a noisy network is less resilient to lesions. Our simulations on TMS perturbations show that even though TMS inhibits most of the network, it also sparsely excites a few regions. This is presumably, due to anti-correlations in the dynamics and suggests that even a lesioned network can show sparsely distributed increased activity compared to healthy resting-state, over specific brain areas.

  10. Schizophrenia classification using functional network features

    Science.gov (United States)

    Rish, Irina; Cecchi, Guillermo A.; Heuton, Kyle

    2012-03-01

    This paper focuses on discovering statistical biomarkers (features) that are predictive of schizophrenia, with a particular focus on topological properties of fMRI functional networks. We consider several network properties, such as node (voxel) strength, clustering coefficients, local efficiency, as well as just a subset of pairwise correlations. While all types of features demonstrate highly significant statistical differences in several brain areas, and close to 80% classification accuracy, the most remarkable results of 93% accuracy are achieved by using a small subset of only a dozen of most-informative (lowest p-value) correlation features. Our results suggest that voxel-level correlations and functional network features derived from them are highly informative about schizophrenia and can be used as statistical biomarkers for the disease.

  11. Clinical impact of anatomo-functional evaluation of brain function during brain tumor surgery

    International Nuclear Information System (INIS)

    To attempt to improve surgical outcome of brain surgery, clinical significance of anatomo-functional evaluation of brain function during resection of brain tumors was assessed. Seventy four patients with glioma located near eloquent areas underwent surgery while awake. Intraoperative tractography-integrated functional neuronavigation and cortical/subcortical electrical stimulation were correlated with clinical symptoms during and after resection of tumors. Cortical functional areas were safely removed with negative electric stimulation and eloquent cortices could be removed in some circumstances. Subcortical functional mapping was difficult except for motor function. Studying cortical functional compensation allows more extensive removal of brain tumors located in the eloquent areas. (author)

  12. Brain function assessment in different conscious states

    OpenAIRE

    Ozgoren, Murat; Bayazit, Onur; Kocaaslan, Sibel; Gokmen, Necati; Oniz, Adile

    2010-01-01

    Background The study of brain functioning is a major challenge in neuroscience fields as human brain has a dynamic and ever changing information processing. Case is worsened with conditions where brain undergoes major changes in so-called different conscious states. Even though the exact definition of consciousness is a hard one, there are certain conditions where the descriptions have reached a consensus. The sleep and the anesthesia are different conditions which are separable from each oth...

  13. Behavioral and Brain Functions. A new journal

    OpenAIRE

    Sagvolden Terje

    2005-01-01

    Abstract Behavioral and Brain Functions (BBF) is an Open Access, peer-reviewed, online journal considering original research, review, and modeling articles in all aspects of neurobiology or behavior, favoring research that relates to both domains. Behavioral and Brain Functions is published by BioMed Central. The greatest challenge for empirical science is to understand human behavior; how human behavior arises from the myriad functions such as attention, language, memory and emotion; how the...

  14. Neuroticism and Functional Connectomics of the Resting Adolescent Brain - Insights from a Danish Child Cohort

    DEFF Research Database (Denmark)

    Baruël Johansen, Louise

    The personality trait neuroticism is a well-known risk factor for anxiety and mood disorders that typically have their onset in childhood and adolescence. This period is characterized by ongoing structural and functional maturation of the brain, which can be traced with magnetic resonance imaging...... (MRI). Resting-state functional MRI is a widely used technique for studies of brain development due to the task-free condition. Furthermore, this imaging modality can be used to study the functional network of the brain that subserves communication between regions of the brain. Properties of this...... network can be quantified with graph theory. By using this analytical approach one can assess e.g. how efficiently information is exchanged throughout the brain. Functional network analyses of the adult brain at rest suggest that higher neuroticism scores are associated with a less efficient functional...

  15. Brain structural and functional correlates of resilience to Bipolar Disorder

    Directory of Open Access Journals (Sweden)

    Sophia Frangou

    2012-01-01

    Results: Resilient relatives of BD patients expressed structural, functional and connectivity changes reflecting the effect of genetic risk on the brain. These included increased insular volume, decreased activation within the posterior and inferior parietal regions involved in selective attention during the SCWT, and reduced fronto-insular and fronto-cingulate connectivity.Resilience was associated with increased cerebellar vermal volume and enhanced functional coupling between the dorsal and the ventral prefrontal cortex. Conclusions: Our findings suggests the presence of biological mechanisms associated with resilient adaptation of brain networks and pave the way for the identification of outcome-specific trajectories given a particular genotype.

  16. Identification of Resting State Networks Involved in Executive Function.

    Science.gov (United States)

    Connolly, Joanna; McNulty, Jonathan P; Boran, Lorraine; Roche, Richard A P; Delany, David; Bokde, Arun L W

    2016-06-01

    The structural networks in the human brain are consistent across subjects, and this is reflected also in that functional networks across subjects are relatively consistent. These findings are not only present during performance of a goal oriented task but there are also consistent functional networks during resting state. It suggests that goal oriented activation patterns may be a function of component networks identified using resting state. The current study examines the relationship between resting state networks measured and patterns of neural activation elicited during a Stroop task. The association between the Stroop-activated networks and the resting state networks was quantified using spatial linear regression. In addition, we investigated if the degree of spatial association of resting state networks with the Stroop task may predict performance on the Stroop task. The results of this investigation demonstrated that the Stroop activated network can be decomposed into a number of resting state networks, which were primarily associated with attention, executive function, visual perception, and the default mode network. The close spatial correspondence between the functional organization of the resting brain and task-evoked patterns supports the relevance of resting state networks in cognitive function. PMID:26935902

  17. The Trees and the Forest: Characterization of complex brain networks with minimum spanning trees

    NARCIS (Netherlands)

    Stam, C.J.; Tewarie, P.; Van Dellen, E.; Van Straaten, E.C.W.; Hillebrand, A.; Van Mieghem, P.

    2014-01-01

    In recent years there has been a shift in focus from the study of local, mostly task-related activation to the exploration of the organization and functioning of large-scale structural and functional complex brain networks. Progress in the interdisciplinary field of modern network science has introd

  18. Brain networks: small-worlds, after all?

    International Nuclear Information System (INIS)

    Since its introduction, the ‘small-world’ effect has played a central role in network science, particularly in the analysis of the complex networks of the nervous system. From the cellular level to that of interconnected cortical regions, many analyses have revealed small-world properties in the networks of the brain. In this work, we revisit the quantification of small-worldness in neural graphs. We find that neural graphs fall into the ‘borderline’ regime of small-worldness, residing close to that of a random graph, especially when the degree sequence of the network is taken into account. We then apply recently introducted analytical expressions for clustering and distance measures, to study this borderline small-worldness regime. We derive theoretical bounds for the minimal and maximal small-worldness index for a given graph, and by semi-analytical means, study the small-worldness index itself. With this approach, we find that graphs with small-worldness equivalent to that observed in experimental data are dominated by their random component. These results provide the first thorough analysis suggesting that neural graphs may reside far away from the maximally small-world regime. (paper)

  19. Aberrant functional brain connectome in people with antisocial personality disorder

    OpenAIRE

    Yan Tang; Jun Long; Wei Wang(College of William and Mary); Jian Liao; Hua Xie; Guihu Zhao; Hao Zhang

    2016-01-01

    Antisocial personality disorder (ASPD) is characterised by a disregard for social obligations and callous unconcern for the feelings of others. Studies have demonstrated that ASPD is associated with abnormalities in brain regions and aberrant functional connectivity. In this paper, topological organisation was examined in resting-state fMRI data obtained from 32 ASPD patients and 32 non-ASPD controls. The frequency-dependent functional networks were constructed using wavelet-based correlation...

  20. 一种基于先验信息的脑功能网络提取方法%Method for brain functional network extraction based on prior information

    Institute of Scientific and Technical Information of China (English)

    杜宇慧; 桂志国; 隋婧

    2016-01-01

    提出一种基于先验信息的脑功能网络提取方法。该方法基于先验信息得到初始的目标和背景种子点,然后基于图论将整个脑图像构建图,最后利用半监督聚类技术提取脑功能网络。基于不同信噪比的模拟数据,对提出方法、基于种子点的方法、独立成分分析方法以及两种聚类方法(归一化最小化割和K-均值方法)进行比较。基于真实脑静息态功能核磁共振数据,使用提出方法对默认模式网络进行提取。基于模拟数据的实验结果表明,提出的算法相对于传统的方法可以得到更为准确且鲁棒的脑功能网络。基于静息态功能核磁共振数据得到的默认模式网络在一些重要脑区具有高的稳定性,且不同地点采集数据得到的结果具有较强的一致性。提出的方法是一种有效的脑功能网络提取方法。%This paper proposed a prior information based method to identify brain functional networks.The method firstly ob-tained objective and background seeds based on prior information,and then constructed a graph for the brain image using graph theory,finally extracted the brain functional network using a semi-supervised clustering technique.Based on the simulated data with different signal to noise ratios,it compared the proposed method,the seed based method,independent component analysis, and two clustering methods (normalized cuts and K-means).Based on the real resting-state functional magnetic resonance ima-ging (fMRI)data,it extracted default mode network using the proposed method.Simulation based experimental results show that compared to the traditional methods,the proposed method can obtain more accurate and robust brain functional network.Real fM-RI based experimental results illustrate that the default mode network has high stability in important regions as well as great con-sistency among data from different sites.The proposed method is an effective method for brain

  1. Neuroenergetics: How energy constraints shape brain function

    CERN Document Server

    CERN. Geneva

    2016-01-01

    The nervous system consumes a disproportionate fraction of the resting body’s energy production. In humans, the brain represents 2% of the body’s mass, yet it accounts for ~20% of the total oxygen consumption. Expansion in the size of the brain relative to the body and an increase in the number of connections between neurons during evolution underpin our cognitive powers and are responsible for our brains’ high metabolic rate. The molecules at the center of cellular energy metabolism also act as intercellular signals and constitute an important communication pathway, coordinating for instance the immune surveillance of the brain. Despite the significance of energy consumption in the nervous system, how energy constrains and shapes brain function is often under appreciated. I will illustrate the importance of brain energetics and metabolism with two examples from my recent work. First, I will show how the brain trades information for energy savings in the visual pathway. Indeed, a significant fraction ...

  2. Cell cycle networks link gene expression dysregulation, mutation, and brain maldevelopment in autistic toddlers.

    Science.gov (United States)

    Pramparo, Tiziano; Lombardo, Michael V; Campbell, Kathleen; Barnes, Cynthia Carter; Marinero, Steven; Solso, Stephanie; Young, Julia; Mayo, Maisi; Dale, Anders; Ahrens-Barbeau, Clelia; Murray, Sarah S; Lopez, Linda; Lewis, Nathan; Pierce, Karen; Courchesne, Eric

    2015-12-01

    Genetic mechanisms underlying abnormal early neural development in toddlers with Autism Spectrum Disorder (ASD) remain uncertain due to the impossibility of direct brain gene expression measurement during critical periods of early development. Recent findings from a multi-tissue study demonstrated high expression of many of the same gene networks between blood and brain tissues, in particular with cell cycle functions. We explored relationships between blood gene expression and total brain volume (TBV) in 142 ASD and control male toddlers. In control toddlers, TBV variation significantly correlated with cell cycle and protein folding gene networks, potentially impacting neuron number and synapse development. In ASD toddlers, their correlations with brain size were lost as a result of considerable changes in network organization, while cell adhesion gene networks significantly correlated with TBV variation. Cell cycle networks detected in blood are highly preserved in the human brain and are upregulated during prenatal states of development. Overall, alterations were more pronounced in bigger brains. We identified 23 candidate genes for brain maldevelopment linked to 32 genes frequently mutated in ASD. The integrated network includes genes that are dysregulated in leukocyte and/or postmortem brain tissue of ASD subjects and belong to signaling pathways regulating cell cycle G1/S and G2/M phase transition. Finally, analyses of the CHD8 subnetwork and altered transcript levels from an independent study of CHD8 suppression further confirmed the central role of genes regulating neurogenesis and cell adhesion processes in ASD brain maldevelopment. PMID:26668231

  3. Spectral signatures of reorganised brain networks in disorders of consciousness.

    Directory of Open Access Journals (Sweden)

    Srivas Chennu

    2014-10-01

    Full Text Available Theoretical advances in the science of consciousness have proposed that it is concomitant with balanced cortical integration and differentiation, enabled by efficient networks of information transfer across multiple scales. Here, we apply graph theory to compare key signatures of such networks in high-density electroencephalographic data from 32 patients with chronic disorders of consciousness, against normative data from healthy controls. Based on connectivity within canonical frequency bands, we found that patient networks had reduced local and global efficiency, and fewer hubs in the alpha band. We devised a novel topographical metric, termed modular span, which showed that the alpha network modules in patients were also spatially circumscribed, lacking the structured long-distance interactions commonly observed in the healthy controls. Importantly however, these differences between graph-theoretic metrics were partially reversed in delta and theta band networks, which were also significantly more similar to each other in patients than controls. Going further, we found that metrics of alpha network efficiency also correlated with the degree of behavioural awareness. Intriguingly, some patients in behaviourally unresponsive vegetative states who demonstrated evidence of covert awareness with functional neuroimaging stood out from this trend: they had alpha networks that were remarkably well preserved and similar to those observed in the controls. Taken together, our findings inform current understanding of disorders of consciousness by highlighting the distinctive brain networks that characterise them. In the significant minority of vegetative patients who follow commands in neuroimaging tests, they point to putative network mechanisms that could support cognitive function and consciousness despite profound behavioural impairment.

  4. Structural Brain Network: What is the Effect of LiFE Optimization of Whole Brain Tractography?

    OpenAIRE

    Qi, Shouliang; Meesters, Stephan; Nicolay, Klaas; ter Haar Romeny, Bart M.; Ossenblok, Pauly

    2016-01-01

    Structural brain networks constructed based on diffusion-weighted MRI (dMRI) have provided a systems perspective to explore the organization of the human brain. Some redundant and nonexistent fibers, however, are inevitably generated in whole brain tractography. We propose to add one critical step while constructing the networks to remove these fibers using the linear fascicle evaluation (LiFE) method, and study the differences between the networks with and without LiFE optimization. For a co...

  5. A brain network processing the age of faces.

    Directory of Open Access Journals (Sweden)

    György A Homola

    Full Text Available Age is one of the most salient aspects in faces and of fundamental cognitive and social relevance. Although face processing has been studied extensively, brain regions responsive to age have yet to be localized. Using evocative face morphs and fMRI, we segregate two areas extending beyond the previously established face-sensitive core network, centered on the inferior temporal sulci and angular gyri bilaterally, both of which process changes of facial age. By means of probabilistic tractography, we compare their patterns of functional activation and structural connectivity. The ventral portion of Wernicke's understudied perpendicular association fasciculus is shown to interconnect the two areas, and activation within these clusters is related to the probability of fiber connectivity between them. In addition, post-hoc age-rating competence is found to be associated with high response magnitudes in the left angular gyrus. Our results provide the first evidence that facial age has a distinct representation pattern in the posterior human brain. We propose that particular face-sensitive nodes interact with additional object-unselective quantification modules to obtain individual estimates of facial age. This brain network processing the age of faces differs from the cortical areas that have previously been linked to less developmental but instantly changeable face aspects. Our probabilistic method of associating activations with connectivity patterns reveals an exemplary link that can be used to further study, assess and quantify structure-function relationships.

  6. An Evaluation of the Left-Brain vs. Right-Brain Hypothesis with Resting State Functional Connectivity Magnetic Resonance Imaging

    OpenAIRE

    Nielsen, Jared A; Zielinski, Brandon A.; Ferguson, Michael A.; Janet E. Lainhart; Anderson, Jeffrey S.

    2013-01-01

    Lateralized brain regions subserve functions such as language and visuospatial processing. It has been conjectured that individuals may be left-brain dominant or right-brain dominant based on personality and cognitive style, but neuroimaging data has not provided clear evidence whether such phenotypic differences in the strength of left-dominant or right-dominant networks exist. We evaluated whether strongly lateralized connections covaried within the same individuals. Data were analyzed from...

  7. Aberrant Global and Regional Topological Organization of the Fractional Anisotropy-weighted Brain Structural Networks in Major Depressive Disorder

    Institute of Scientific and Technical Information of China (English)

    Jian-Huai Chen; Zhi-Jian Yao; Jiao-Long Qin; Rui Yan; Ling-Ling Hua; Qing Lu

    2016-01-01

    Background:Most previous neuroimaging studies have focused on the structural and functional abnormalities of local brain regions in major depressive disorder (MDD).Moreover,the exactly topological organization of networks underlying MDD remains unclear.This study examined the aberrant global and regional topological patterns of the brain white matter networks in MDD patients.Methods:The diffusion tensor imaging data were obtained from 27 patients with MDD and 40 healthy controls.The brain fractional anisotropy-weighted structural networks were constructed,and the global network and regional nodal metrics of the networks were explored by the complex network theory.Results:Compared with the healthy controls,the brain structural network of MDD patients showed an intact small-world topology,but significantly abnormal global network topological organization and regional nodal characteristic of the network in MDD were found.Our findings also indicated that the brain structural networks in MDD patients become a less strongly integrated network with a reduced central role of some key brain regions.Conclusions:All these resulted in a less optimal topological organization of networks underlying MDD patients,including an impaired capability of local information processing,reduced centrality of some brain regions and limited capacity to integrate information across different regions.Thus,these global network and regional node-level aberrations might contribute to understanding the pathogenesis of MDD from the view of the brain network.

  8. Promoting Motor Function by Exercising the Brain

    Directory of Open Access Journals (Sweden)

    Stephane Perrey

    2013-01-01

    Full Text Available Exercise represents a behavioral intervention that enhances brain health and motor function. The increase in cerebral blood volume in response to physical activity may be responsible for improving brain function. Among the various neuroimaging techniques used to monitor brain hemodynamic response during exercise, functional near-infrared spectroscopy could facilitate the measurement of task-related cortical responses noninvasively and is relatively robust with regard to the subjects’ motion. Although the components of optimal exercise interventions have not been determined, evidence from animal and human studies suggests that aerobic exercise with sufficiently high intensity has neuroprotective properties and promotes motor function. This review provides an insight into the effect of physical activity (based on endurance and resistance exercises on brain function for producing movement. Since most progress in the study of brain function has come from patients with neurological disorders (e.g., stroke and Parkinson’s patients, this review presents some findings emphasizing training paradigms for restoring motor function.

  9. Functional Aspects of Biological Networks

    Science.gov (United States)

    Sneppen, Kim

    2007-03-01

    We discuss biological networks with respect to 1) relative positioning and importance of high degree nodes, 2) function and signaling, 3) logic and dynamics of regulation. Visually the soft modularity of many real world networks can be characterized in terms of number of high and low degrees nodes positioned relative to each other in a landscape analogue with mountains (high-degree nodes) and valleys (low-degree nodes). In these terms biological networks looks like rugged landscapes with separated peaks, hub proteins, which each are roughly as essential as any of the individual proteins on the periphery of the hub. Within each sup-domain of a molecular network one can often identify dynamical feedback mechanisms that falls into combinations of positive and negative feedback circuits. We will illustrate this with examples taken from phage regulation and bacterial uptake and regulation of small molecules. In particular we find that a double negative regulation often are replaced by a single positive link in unrelated organisms with same functional requirements. Overall we argue that network topology primarily reflects functional constraints. References: S. Maslov and K. Sneppen. ``Computational architecture of the yeast regulatory network." Phys. Biol. 2:94 (2005) A. Trusina et al. ``Functional alignment of regulatory networks: A study of temerate phages". Plos Computational Biology 1:7 (2005). J.B. Axelsen et al. ``Degree Landscapes in Scale-Free Networks" physics/0512075 (2005). A. Trusina et al. ``Hierarchy and Anti-Hierarchy in Real and Scale Free networks." PRL 92:178702 (2004) S. Semsey et al. ``Genetic Regulation of Fluxes: Iron Homeostasis of Escherichia coli". (2006) q-bio.MN/0609042

  10. Cross-Frequency Coupling in Real and Virtual Brain Networks

    Directory of Open Access Journals (Sweden)

    Viktor Jirsa

    2013-07-01

    Full Text Available Information processing in the brain is thought to rely on the convergence and divergence of oscillatory behaviors of widely distributed brain areas. This information flow is captured in its simplest form via the concepts of synchronization and desynchronization and related metrics. More complex forms of information flow are transient synchronizations and multi-frequency behaviors with metrics related to cross-frequency coupling (CFC. It is supposed that CFC plays a crucial role in the organization of large-scale networks and functional integration across large distances. In this study we describe different CFC measures and test their applicability in simulated and real electroencephalographic (EEG data obtained during resting state. For these purposes, we derive generic oscillator equations from full brain network models. We systematically model and simulate the various scenarios of cross-frequency coupling under the influence of noise to obtain biologically realistic oscillator dynamics. We find that (i specific CFC-measures detect correctly in most cases the nature of CFC under noise conditions, (ii bispectrum and bicoherence correctly detect the CFCs in simulated data, (iii empirical resting state EEG show a prominent delta-alpha CFC as identified by specific CFC measures and the more classic bispectrum and bicoherence. This coupling was mostly asymmetric (directed and generally higher in the eyes-closed than in the eyes-open condition. In conjunction, these two sets of measures provide a powerful toolbox to reveal the nature of couplings from experimental data and as such allow inference on the brain state dependent information processing. Methodological advantages of using CFC measures and theoretical significance of delta and alpha interactions during resting and other brain states are discussed.

  11. Combining EEG source connectivity and network similarity: Application to object categorization in the human brain

    OpenAIRE

    Mheich, Ahmad; Hassan, Mahmoud; Dufor, Olivier; Khalil, Mohamad; Wendling, Fabrice

    2016-01-01

    A major challenge in cognitive neuroscience is to evaluate the ability of the human brain to categorize or group visual stimuli based on common features. This categorization process is very fast and occurs in few hundreds of millisecond time scale. However, an accurate tracking of the spatiotemporal dynamics of large-scale brain networks is still an unsolved issue. Here, we show the combination of recently developed method called dense-EEG source connectivity to identify functional brain netw...

  12. Disentangling Brain Graphs: A Note on the Conflation of Network and Connectivity Analyses.

    Science.gov (United States)

    Simpson, Sean L; Laurienti, Paul J

    2016-03-01

    Understanding the human brain remains the holy grail in biomedical science, and arguably in all of the sciences. Our brains represent the most complex systems in the world (and some contend the universe) comprising nearly 100 billion neurons with septillions of possible connections between them. The structure of these connections engenders an efficient hierarchical system capable of consciousness, as well as complex thoughts, feelings, and behaviors. Brain connectivity and network analyses have exploded over the last decade due to their potential in helping us understand both normal and abnormal brain function. Functional connectivity (FC) analysis examines functional associations between time series pairs in specified brain voxels or regions. Brain network analysis serves as a distinct subfield of connectivity analysis, in which associations are quantified for all time series pairs to create an interconnected representation of the brain (a brain network), which allows studying its systemic properties. While connectivity analyses underlie network analyses, the subtle distinction between the two research areas has generally been overlooked in the literature, with them often being referred to synonymously. However, developing more useful analytic methods and allowing for more precise biological interpretations require distinguishing these two complementary domains. PMID:26414952

  13. DHA effects in brain development and function

    DEFF Research Database (Denmark)

    Lauritzen, Lotte; Brambilla, Paola; Mazzocchi, Allesandra;

    2016-01-01

    the endogenous formation of DHA seems to be relatively low, DHA intake may contribute to optimal conditions for brain development. We performed a narrative review on research on the associations between DHA levels and brain development and function throughout the lifespan. Data from cell and animal studies...... justify the indication of DHA in relation to brain function for neuronal cell growth and differentiation as well as in relation to neuronal signaling. Most data from human studies concern the contribution of DHA to optimal visual acuity development. Accumulating data indicate that DHA may have effects......Docosahexaenoic acid (DHA) is a structural constituent of membranes specifically in the central nervous system. Its accumulation in the fetal brain takes place mainly during the last trimester of pregnancy and continues at very high rates up to the end of the second year of life. Since...

  14. A Novel Human Body Area Network for Brain Diseases Analysis.

    Science.gov (United States)

    Lin, Kai; Xu, Tianlang

    2016-10-01

    Development of wireless sensor and mobile communication technology provide an unprecedented opportunity for realizing smart and interactive healthcare systems. Designing such systems aims to remotely monitor the health and diagnose the diseases for users. In this paper, we design a novel human body area network for brain diseases analysis, which is named BABDA. Considering the brain is one of the most complex organs in the human body, the BABDA system provides four function modules to ensure the high quality of the analysis result, which includes initial data collection, data correction, data transmission and comprehensive data analysis. The performance evaluation conducted in a realistic environment with several criteria shows the availability and practicability of the BABDA system. PMID:27526187

  15. Genetic variants in Alzheimer disease - molecular and brain network approaches.

    Science.gov (United States)

    Gaiteri, Chris; Mostafavi, Sara; Honey, Christopher J; De Jager, Philip L; Bennett, David A

    2016-07-01

    Genetic studies in late-onset Alzheimer disease (LOAD) are aimed at identifying core disease mechanisms and providing potential biomarkers and drug candidates to improve clinical care of AD. However, owing to the complexity of LOAD, including pathological heterogeneity and disease polygenicity, extraction of actionable guidance from LOAD genetics has been challenging. Past attempts to summarize the effects of LOAD-associated genetic variants have used pathway analysis and collections of small-scale experiments to hypothesize functional convergence across several variants. In this Review, we discuss how the study of molecular, cellular and brain networks provides additional information on the effects of LOAD-associated genetic variants. We then discuss emerging combinations of these omic data sets into multiscale models, which provide a more comprehensive representation of the effects of LOAD-associated genetic variants at multiple biophysical scales. Furthermore, we highlight the clinical potential of mechanistically coupling genetic variants and disease phenotypes with multiscale brain models. PMID:27282653

  16. Functional level after Traumatic Brain Injury

    OpenAIRE

    Sandhaug, Maria

    2012-01-01

    Objectives: The objectives of the thesis were to describe the functional level (papers I and II) and self awareness of functional deficits (paper III) after moderate and severe Traumatic Brain Injury (TBI), and to evaluate the predictive impact of pre-injury and injury-related factors on functional level (papers I, II) and awareness of functional deficits (paper III). Material and methods: Papers I-II were cohort studies of 55 TBI patients (moderate = 21, severe = 34) and 65...

  17. Exercise Benefits Brain Function: The Monoamine Connection

    OpenAIRE

    Tzu-Wei Lin; Yu-Min Kuo

    2013-01-01

    The beneficial effects of exercise on brain function have been demonstrated in animal models and in a growing number of clinical studies on humans. There are multiple mechanisms that account for the brain-enhancing effects of exercise, including neuroinflammation, vascularization, antioxidation, energy adaptation, and regulations on neurotrophic factors and neurotransmitters. Dopamine (DA), noradrenaline (NE), and serotonin (5-HT) are the three major monoamine neurotransmitters that are known...

  18. Function approximation in inhibitory networks.

    Science.gov (United States)

    Tripp, Bryan; Eliasmith, Chris

    2016-05-01

    In performance-optimized artificial neural networks, such as convolutional networks, each neuron makes excitatory connections with some of its targets and inhibitory connections with others. In contrast, physiological neurons are typically either excitatory or inhibitory, not both. This is a puzzle, because it seems to constrain computation, and because there are several counter-examples that suggest that it may not be a physiological necessity. Parisien et al. (2008) showed that any mixture of excitatory and inhibitory functional connections could be realized by a purely excitatory projection in parallel with a two-synapse projection through an inhibitory population. They showed that this works well with ratios of excitatory and inhibitory neurons that are realistic for the neocortex, suggesting that perhaps the cortex efficiently works around this apparent computational constraint. Extending this work, we show here that mixed excitatory and inhibitory functional connections can also be realized in networks that are dominated by inhibition, such as those of the basal ganglia. Further, we show that the function-approximation capacity of such connections is comparable to that of idealized mixed-weight connections. We also study whether such connections are viable in recurrent networks, and find that such recurrent networks can flexibly exhibit a wide range of dynamics. These results offer a new perspective on computation in the basal ganglia, and also perhaps on inhibitory networks within the cortex. PMID:26963256

  19. Cluster imaging of multi-brain networks (CIMBN): a general framework for hyperscanning and modeling a group of interacting brains.

    Science.gov (United States)

    Duan, Lian; Dai, Rui-Na; Xiao, Xiang; Sun, Pei-Pei; Li, Zheng; Zhu, Chao-Zhe

    2015-01-01

    Studying the neural basis of human social interactions is a key topic in the field of social neuroscience. Brain imaging studies in this field usually focus on the neural correlates of the social interactions between two participants. However, as the participant number further increases, even by a small amount, great difficulties raise. One challenge is how to concurrently scan all the interacting brains with high ecological validity, especially for a large number of participants. The other challenge is how to effectively model the complex group interaction behaviors emerging from the intricate neural information exchange among a group of socially organized people. Confronting these challenges, we propose a new approach called "Cluster Imaging of Multi-brain Networks" (CIMBN). CIMBN consists of two parts. The first part is a cluster imaging technique with high ecological validity based on multiple functional near-infrared spectroscopy (fNIRS) systems. Using this technique, we can easily extend the simultaneous imaging capacity of social neuroscience studies up to dozens of participants. The second part of CIMBN is a multi-brain network (MBN) modeling method based on graph theory. By taking each brain as a network node and the relationship between any two brains as a network edge, one can construct a network model for a group of interacting brains. The emergent group social behaviors can then be studied using the network's properties, such as its topological structure and information exchange efficiency. Although there is still much work to do, as a general framework for hyperscanning and modeling a group of interacting brains, CIMBN can provide new insights into the neural correlates of group social interactions, and advance social neuroscience and social psychology. PMID:26283906

  20. Prospects for optogenetic augmentation of brain function

    Directory of Open Access Journals (Sweden)

    Sarah eJarvis

    2015-11-01

    Full Text Available The ability to optically control neural activity opens up possibilities for the restoration of normal function following neurological disorders. The temporal precision, spatial resolution and neuronal specificity that optogenetics offers is unequalled by other available methods, so will it be suitable for not only restoring but also extending brain function? As the first demonstrations of optically ``implanted'' novel memories emerge, we examine the suitability of optogenetics as a technique for extending neural function. While optogenetics is an effective tool for altering neural activity, the largest impediment for optogenetics in neural augmentation is our systems level understanding of brain function. Furthermore, a number of clinical limitations currently remain as substantial hurdles for the applications proposed. While neurotechnologies for treating brain disorders and interfacing with prosthetics have advanced rapidly in the past few years, partially addressing some of these critical problems, optogenetics is not yet suitable for use in humans. Instead we conclude that for the immediate future, optogenetics is the neurological equivalent of the 3D printer: its flexibility providing an ideal tool for testing and prototyping solutions for treating brain disorders and augmenting brain function.

  1. Imaging visual function of the human brain

    International Nuclear Information System (INIS)

    Imaging of human brain structure and activity with particular reference to visual function is reviewed along with methods of obtaining the data including computed tomographic (CT) scan, magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), and positron emission tomography (PET). The literature is reviewed and the potential for a new understanding of brain visual function is discussed. PET is reviewed from basic physical principles to the most recent visual brain findings with oxygen-15. It is shown that there is a potential for submillimeter localization of visual functions with sequentially different visual stimuli designed for the temporal separation of the responses. Single photon emission computed tomography (SPECT), a less expensive substitute for PET, is also discussed. MRS is covered from basic physical principles to the current state of the art of in vivo biochemical analysis. Future possible clinical applications are discussed. Improved understanding of the functional neural organization of vision and brain will open a window to maps and circuits of human brain function.119 references

  2. Neurolinguistics: Structure, Function, and Connectivity in the Bilingual Brain

    Science.gov (United States)

    Wong, Becky; Yin, Bin; O'Brien, Beth

    2016-01-01

    Advances in neuroimaging techniques and analytic methods have led to a proliferation of studies investigating the impact of bilingualism on the cognitive and brain systems in humans. Lately, these findings have attracted much interest and debate in the field, leading to a number of recent commentaries and reviews. Here, we contribute to the ongoing discussion by compiling and interpreting the plethora of findings that relate to the structural, functional, and connective changes in the brain that ensue from bilingualism. In doing so, we integrate theoretical models and empirical findings from linguistics, cognitive/developmental psychology, and neuroscience to examine the following issues: (1) whether the language neural network is different for first (dominant) versus second (nondominant) language processing; (2) the effects of bilinguals' executive functioning on the structure and function of the “universal” language neural network; (3) the differential effects of bilingualism on phonological, lexical-semantic, and syntactic aspects of language processing on the brain; and (4) the effects of age of acquisition and proficiency of the user's second language in the bilingual brain, and how these have implications for future research in neurolinguistics. PMID:26881224

  3. Neurolinguistics: Structure, Function, and Connectivity in the Bilingual Brain.

    Science.gov (United States)

    Wong, Becky; Yin, Bin; O'Brien, Beth

    2016-01-01

    Advances in neuroimaging techniques and analytic methods have led to a proliferation of studies investigating the impact of bilingualism on the cognitive and brain systems in humans. Lately, these findings have attracted much interest and debate in the field, leading to a number of recent commentaries and reviews. Here, we contribute to the ongoing discussion by compiling and interpreting the plethora of findings that relate to the structural, functional, and connective changes in the brain that ensue from bilingualism. In doing so, we integrate theoretical models and empirical findings from linguistics, cognitive/developmental psychology, and neuroscience to examine the following issues: (1) whether the language neural network is different for first (dominant) versus second (nondominant) language processing; (2) the effects of bilinguals' executive functioning on the structure and function of the "universal" language neural network; (3) the differential effects of bilingualism on phonological, lexical-semantic, and syntactic aspects of language processing on the brain; and (4) the effects of age of acquisition and proficiency of the user's second language in the bilingual brain, and how these have implications for future research in neurolinguistics. PMID:26881224

  4. FMRI connectivity analysis of acupuncture effects on an amygdala-associated brain network

    Directory of Open Access Journals (Sweden)

    Zhao Baixiao

    2008-11-01

    Full Text Available Abstract Background Recently, increasing evidence has indicated that the primary acupuncture effects are mediated by the central nervous system. However, specific brain networks underpinning these effects remain unclear. Results In the present study using fMRI, we employed a within-condition interregional covariance analysis method to investigate functional connectivity of brain networks involved in acupuncture. The fMRI experiment was performed before, during and after acupuncture manipulations on healthy volunteers at an acupuncture point, which was previously implicated in a neural pathway for pain modulation. We first identified significant fMRI signal changes during acupuncture stimulation in the left amygdala, which was subsequently selected as a functional reference for connectivity analyses. Our results have demonstrated that there is a brain network associated with the amygdala during a resting condition. This network encompasses the brain structures that are implicated in both pain sensation and pain modulation. We also found that such a pain-related network could be modulated by both verum acupuncture and sham acupuncture. Furthermore, compared with a sham acupuncture, the verum acupuncture induced a higher level of correlations among the amygdala-associated network. Conclusion Our findings indicate that acupuncture may change this amygdala-specific brain network into a functional state that underlies pain perception and pain modulation.

  5. Advantages in functional imaging of the brain

    Directory of Open Access Journals (Sweden)

    Walter Mier

    2015-05-01

    Full Text Available As neuronal pathologies cause only minor morphological alterations, molecular imaging techniques are a prerequisite for the study of diseases of the brain. The development of molecular probes that specifically bind biochemical markers and the advances of instrumentation have revolutionized the possibilities to gain insight into the human brain organization and beyond this visualize structure-function and brain-behavior relationships. The review describes the development and current applications of functional brain imaging techniques with a focus on applications in psychiatry. A historical overview of the development of functional imaging is followed by the portrayal of the principles and applications of positron emission tomography (PET and functional magnetic resonance imaging (fMRI, two key molecular imaging techniques that have revolutionized the ability to image molecular processes in the brain. In the juxtaposition of PET and fMRI in hybrid PET/MRI scanners enhances the significance of both modalities for research in neurology and psychiatry and might pave the way for a new area of personalized medicine.

  6. A Framework for the Evaluation of Complete Weighted Network Topology in EEG Functional Connectivity

    OpenAIRE

    Smith, Keith; Escudero, Javier

    2016-01-01

    Graph theory provides an analytical framework for brain functional connectivity. The complete weighted networks (CWNs) derived from functional connectivity analyses are fundamentally different to the sparse binary networks studied in other research areas. Nonetheless, CWNs are typically analysed using sparse network methodology. This creates problems with reproducibility and negates important information of the CWNs. We offer an alternative framework for brain networks designed specifically f...

  7. Topological organization of the human brain functional connectome across the lifespan

    Directory of Open Access Journals (Sweden)

    Miao Cao

    2014-01-01

    Full Text Available Human brain function undergoes complex transformations across the lifespan. We employed resting-state functional MRI and graph-theory approaches to systematically chart the lifespan trajectory of the topological organization of human whole-brain functional networks in 126 healthy individuals ranging in age from 7 to 85 years. Brain networks were constructed by computing Pearson's correlations in blood-oxygenation-level-dependent temporal fluctuations among 1024 parcellation units followed by graph-based network analyses. We observed that the human brain functional connectome exhibited highly preserved non-random modular and rich club organization over the entire age range studied. Further quantitative analyses revealed linear decreases in modularity and inverted-U shaped trajectories of local efficiency and rich club architecture. Regionally heterogeneous age effects were mainly located in several hubs (e.g., default network, dorsal attention regions. Finally, we observed inverse trajectories of long- and short-distance functional connections, indicating that the reorganization of connectivity concentrates and distributes the brain's functional networks. Our results demonstrate topological changes in the whole-brain functional connectome across nearly the entire human lifespan, providing insights into the neural substrates underlying individual variations in behavior and cognition. These results have important implications for disease connectomics because they provide a baseline for evaluating network impairments in age-related neuropsychiatric disorders.

  8. Dismissing Attachment Characteristics Dynamically Modulate Brain Networks Subserving Social Aversion

    Science.gov (United States)

    Krause, Anna Linda; Borchardt, Viola; Li, Meng; van Tol, Marie-José; Demenescu, Liliana Ramona; Strauss, Bernhard; Kirchmann, Helmut; Buchheim, Anna; Metzger, Coraline D.; Nolte, Tobias; Walter, Martin

    2016-01-01

    Attachment patterns influence actions, thoughts and feeling through a person’s “inner working model”. Speech charged with attachment-dependent content was proposed to modulate the activation of cognitive-emotional schemata in listeners. We performed a 7 Tesla rest-task-rest functional magnetic resonance imaging (fMRI)-experiment, presenting auditory narratives prototypical of dismissing attachment representations to investigate their effect on 23 healthy males. We then examined effects of participants’ attachment style and childhood trauma on brain state changes using seed-based functional connectivity (FC) analyses, and finally tested whether subjective differences in responsivity to narratives could be predicted by baseline network states. In comparison to a baseline state, we observed increased FC in a previously described “social aversion network” including dorsal anterior cingulated cortex (dACC) and left anterior middle temporal gyrus (aMTG) specifically after exposure to insecure-dismissing attachment narratives. Increased dACC-seeded FC within the social aversion network was positively related to the participants’ avoidant attachment style and presence of a history of childhood trauma. Anxious attachment style on the other hand was positively correlated with FC between the dACC and a region outside of the “social aversion network”, namely the dorsolateral prefrontal cortex, which suggests decreased network segregation as a function of anxious attachment. Finally, the extent of subjective experience of friendliness towards the dismissing narrative was predicted by low baseline FC-values between hippocampus and inferior parietal lobule (IPL). Taken together, our study demonstrates an activation of networks related to social aversion in terms of increased connectivity after listening to insecure-dismissing attachment narratives. A causal interrelation of brain state changes and subsequent changes in social reactivity was further supported by

  9. Functional brain imaging - baric and clinical questions

    International Nuclear Information System (INIS)

    The advancing biological knowledge of disease processes plays a central part in the progress of modern psychiatry. An essential contribution comes from the functional and structural brain imaging techniques (CT, MRI, SPECT, PET). Their application is important for biological oriented research in psychiatry and there is also a growing relevance in clinical aspects. This development is taken into account by recent diagnostic classification systems in psychiatry. The capabilities and limitations of functional brain imaging in the context of research and clinic will be presented and discussed by examples and own investigations. (orig.)

  10. Personality and complex brain networks: The role of openness to experience in default network efficiency.

    Science.gov (United States)

    Beaty, Roger E; Kaufman, Scott Barry; Benedek, Mathias; Jung, Rex E; Kenett, Yoed N; Jauk, Emanuel; Neubauer, Aljoscha C; Silvia, Paul J

    2016-02-01

    The brain's default network (DN) has been a topic of considerable empirical interest. In fMRI research, DN activity is associated with spontaneous and self-generated cognition, such as mind-wandering, episodic memory retrieval, future thinking, mental simulation, theory of mind reasoning, and creative cognition. Despite large literatures on developmental and disease-related influences on the DN, surprisingly little is known about the factors that impact normal variation in DN functioning. Using structural equation modeling and graph theoretical analysis of resting-state fMRI data, we provide evidence that Openness to Experience-a normally distributed personality trait reflecting a tendency to engage in imaginative, creative, and abstract cognitive processes-underlies efficiency of information processing within the DN. Across two studies, Openness predicted the global efficiency of a functional network comprised of DN nodes and corresponding edges. In Study 2, Openness remained a robust predictor-even after controlling for intelligence, age, gender, and other personality variables-explaining 18% of the variance in DN functioning. These findings point to a biological basis of Openness to Experience, and suggest that normally distributed personality traits affect the intrinsic architecture of large-scale brain systems. Hum Brain Mapp 37:773-779, 2016. © 2015 Wiley Periodicals, Inc. PMID:26610181

  11. Cluster imaging of multi-brain networks (CIMBN: a general framework for hyperscanning and modeling a group of interacting brains

    Directory of Open Access Journals (Sweden)

    Lian eDuan

    2015-07-01

    Full Text Available Studying the neural basis of human social interactions is a key topic in the field of social neuroscience. Brain imaging studies in this field usually focus on the neural correlates of the social interactions between two participants. However, as the participant number further increases, even by a small amount, great difficulties raise. One challenge is how to concurrently scan all the interacting brains with high ecological validity, especially for a large number of participants. The other challenge is how to effectively model the complex group interaction behaviors emerging from the intricate neural information exchange among a group of socially organized people. Confronting these challenges, we propose a new approach called Cluster Imaging of Multi-brain Networks (CIMBN. CIMBN consists of two parts. The first part is a cluster imaging technique with high ecological validity based on multiple functional near-infrared spectroscopy (fNIRS systems. Using this technique, we can easily extend the simultaneous imaging capacity of social neuroscience studies up to dozens of participants. The second part of CIMBN is a multi-brain network (MBN modeling method based on graph theory. By taking each brain as a network node and the relationship between any two brains as a network edge, one can construct a network model for a group of interacting brains. The emergent group social behaviors can then be studied using the network’s properties, such as its topological structure and information exchange efficiency. Although there is still much work to do, as a general framework for hyperscanning and modeling a group of interacting brains, CIMBN can provide new insights into the neural correlates of group social interactions, and advance social neuroscience and social psychology.

  12. Caffeine Modulates Attention Network Function

    Science.gov (United States)

    Brunye, Tad T.; Mahoney, Caroline R.; Lieberman, Harris R.; Taylor, Holly A.

    2010-01-01

    The present work investigated the effects of caffeine (0 mg, 100 mg, 200 mg, 400 mg) on a flanker task designed to test Posner's three visual attention network functions: alerting, orienting, and executive control [Posner, M. I. (2004). "Cognitive neuroscience of attention". New York, NY: Guilford Press]. In a placebo-controlled, double-blind…

  13. Structural and Functional Plasticity in the Maternal Brain Circuitry.

    Science.gov (United States)

    Pereira, Mariana

    2016-09-01

    Parenting recruits a distributed network of brain structures (and neuromodulators) that coordinates caregiving responses attuned to the young's affect, needs, and developmental stage. Many of these structures and connections undergo significant structural and functional plasticity, mediated by the interplay between maternal hormones and social experience while the reciprocal relationship between the mother and her infant forms and develops. These alterations account for the remarkable behavioral plasticity of mothers. This review will examine the molecular and neurobiological modulation and plasticity through which parenting develops and adjusts in new mothers, primarily discussing recent findings in nonhuman animals. A better understanding of how parenting impacts the brain at the molecular, cellular, systems/network, and behavioral levels is likely to significantly contribute to novel strategies for treating postpartum neuropsychiatric disorders in new mothers, and critical for both the mother's physiological and mental health and the development and well-being of her young. PMID:27589496

  14. Functional community analysis of brain: a new approach for EEG-based investigation of the brain pathology.

    Science.gov (United States)

    Ahmadlou, Mehran; Adeli, Hojjat

    2011-09-15

    Analysis of structure of the brain functional connectivity (SBFC) is a fundamental issue for understanding of the brain cognition as well as the pathology of brain disorders. Analysis of communities among sub-parts of a system is increasingly used for social, ecological, and other networks. This paper presents a new methodology for investigation of the SBFC and understanding of the brain based on graph theory and community pattern analysis of functional connectivity graph of the brain obtained from encephalograms (EEGs). The methodology consists of three main parts: fuzzy synchronization likelihood (FSL), community partitioning, and decisions based on partitions. As an example application, the methodology is applied to analysis of brain of patients with attention deficit/hyperactivity disorder (ADHD) and the problem of discrimination of ADHD EEGs from healthy (non-ADHD) EEGs. PMID:21586331

  15. Brain networks and their origins. Comment on “Understanding brain networks and brain organization” by Luiz Pessoa

    Science.gov (United States)

    Cisek, Paul

    2014-09-01

    Nearly every textbook on psychology or neuroscience contains theories of function described with box and arrow diagrams. Sometimes, the boxes stand for purely theoretical constructs, such as attention or working memory, and sometimes they also correspond to specific brain regions or systems, such as parietal or prefrontal cortex, and the arrows between them to known anatomical pathways. It is common for scientists (present company included) to summarize their theories in this way and to think of the brain as a set of interacting modules with clearly distinguishable functions.

  16. Dismissing attachment characteristics dynamically modulate brain networks subserving social aversion.

    Directory of Open Access Journals (Sweden)

    Anna Linda eKrause

    2016-03-01

    Full Text Available Attachment patterns influence actions, thoughts and feeling through a person’s ‘Inner Working Model’. Speech charged with attachment-dependent content was proposed to modulate the activation of cognitive-emotional schemata in listeners. We performed a 7 Tesla rest-task-rest fMRI-experiment, presenting auditory narratives prototypical of dismissing attachment representations to investigate their effect on 23 healthy males. We then examined effects of participants’ attachment style and childhood trauma on brain state changes using seed-based functional connectivity (FC analyses, and finally tested whether subjective differences in responsivity to narratives could be predicted by baseline network states. In comparison to a baseline state, we observed increased FC in a previously described ‘social aversion network’ including dorsal anterior cingulated cortex (dACC and left anterior middle temporal gyrus (aMTG specifically after exposure to insecure-dismissing attachment narratives. Increased dACC-seeded FC within the social aversion network was positively related to the participants’ avoidant attachment style and presence of a history of childhood trauma. Anxious attachment style on the other hand was positively correlated with FC between the dACC and a region outside of the ‘social aversion network’, namely the dorsolateral prefrontal cortex, which suggests decreased network segregation as a function of anxious attachment. Finally, the extent of subjective experience of friendliness towards the dismissing narrative was predicted by low baseline FC-values between hippocampus and inferior parietal lobule. Taken together, our study demonstrates an activation of networks related to social aversion in terms of increased connectivity after listening to insecure-dismissing attachment narratives. A causal interrelation of brain state changes and subsequent changes in social reactivity was further supported by our observation of direct

  17. Neural Signatures of Autism Spectrum Disorders: Insights into Brain Network Dynamics

    OpenAIRE

    Hernandez, Leanna M.; Rudie, Jeffrey D.; Green, Shulamite A.; Bookheimer, Susan; Dapretto, Mirella

    2014-01-01

    Neuroimaging investigations of autism spectrum disorders (ASDs) have advanced our understanding of atypical brain function and structure, and have recently converged on a model of altered network-level connectivity. Traditional task-based functional magnetic resonance imaging (MRI) and volume-based structural MRI studies have identified widespread atypicalities in brain regions involved in social behavior and other core ASD-related behavioral deficits. More recent advances in MR-neuroimaging ...

  18. Circuit-wide Transcriptional Profiling Reveals Brain Region-Specific Gene Networks Regulating Depression Susceptibility.

    Science.gov (United States)

    Bagot, Rosemary C; Cates, Hannah M; Purushothaman, Immanuel; Lorsch, Zachary S; Walker, Deena M; Wang, Junshi; Huang, Xiaojie; Schlüter, Oliver M; Maze, Ian; Peña, Catherine J; Heller, Elizabeth A; Issler, Orna; Wang, Minghui; Song, Won-Min; Stein, Jason L; Liu, Xiaochuan; Doyle, Marie A; Scobie, Kimberly N; Sun, Hao Sheng; Neve, Rachael L; Geschwind, Daniel; Dong, Yan; Shen, Li; Zhang, Bin; Nestler, Eric J

    2016-06-01

    Depression is a complex, heterogeneous disorder and a leading contributor to the global burden of disease. Most previous research has focused on individual brain regions and genes contributing to depression. However, emerging evidence in humans and animal models suggests that dysregulated circuit function and gene expression across multiple brain regions drive depressive phenotypes. Here, we performed RNA sequencing on four brain regions from control animals and those susceptible or resilient to chronic social defeat stress at multiple time points. We employed an integrative network biology approach to identify transcriptional networks and key driver genes that regulate susceptibility to depressive-like symptoms. Further, we validated in vivo several key drivers and their associated transcriptional networks that regulate depression susceptibility and confirmed their functional significance at the levels of gene transcription, synaptic regulation, and behavior. Our study reveals novel transcriptional networks that control stress susceptibility and offers fundamentally new leads for antidepressant drug discovery. PMID:27181059

  19. Exploring brain function from anatomical connectivity

    Directory of Open Access Journals (Sweden)

    Gorka Zamora-López

    2011-06-01

    Full Text Available The intrinsic relationship between the architecture of the brain and the range of sensory and behavioral phenomena it produces is a relevant question in neuroscience. Here, we review recent knowledge gained on the architecture of the anatomical connectivity by means of complex network analysis. It has been found that corticocortical networks display a few prominent characteristics: (i modular organization, (ii abundant alternative processing paths and (iii the presence of highly connected hubs. Additionally, we present a novel classification of cortical areas of the cat according to the role they play in multisensory connectivity. All these properties represent an ideal anatomical substrate supporting rich dynamical behaviors, as-well-as facilitating the capacity of the brain to process sensory information of different modalities segregated and to integrate them towards a comprehensive perception of the real world. The result here exposed are mainly based in anatomical data of cats’ brain, but we show how further observations suggest that, from worms to humans, the nervous system of all animals might share fundamental principles of organization.

  20. Integrating Retinoic Acid Signaling with Brain Function

    Science.gov (United States)

    Luo, Tuanlian; Wagner, Elisabeth; Drager, Ursula C.

    2009-01-01

    The vitamin A derivative retinoic acid (RA) regulates the transcription of about a 6th of the human genome. Compelling evidence indicates a role of RA in cognitive activities, but its integration with the molecular mechanisms of higher brain functions is not known. Here we describe the properties of RA signaling in the mouse, which point to…

  1. Platelet Serotonin Transporter Function Predicts Default-Mode Network Activity

    OpenAIRE

    Christian Scharinger; Ulrich Rabl; Christian H. Kasess; Meyer, Bernhard M.; Tina Hofmaier; Kersten Diers; Lucie Bartova; Gerald Pail; Wolfgang Huf; Zeljko Uzelac; Beate Hartinger; Klaudius Kalcher; Thomas Perkmann; Helmuth Haslacher; Andreas Meyer-Lindenberg

    2014-01-01

    Background The serotonin transporter (5-HTT) is abundantly expressed in humans by the serotonin transporter gene SLC6A4 and removes serotonin (5-HT) from extracellular space. A blood-brain relationship between platelet and synaptosomal 5-HT reuptake has been suggested, but it is unknown today, if platelet 5-HT uptake can predict neural activation of human brain networks that are known to be under serotonergic influence. Methods A functional magnetic resonance study was performed in 48 healthy...

  2. The functional connectivity landscape of the human brain.

    Directory of Open Access Journals (Sweden)

    Bratislav Mišić

    Full Text Available Functional brain networks emerge and dissipate over a primarily static anatomical foundation. The dynamic basis of these networks is inter-regional communication involving local and distal regions. It is assumed that inter-regional distances play a pivotal role in modulating network dynamics. Using three different neuroimaging modalities, 6 datasets were evaluated to determine whether experimental manipulations asymmetrically affect functional relationships based on the distance between brain regions in human participants. Contrary to previous assumptions, here we show that short- and long-range connections are equally likely to strengthen or weaken in response to task demands. Additionally, connections between homotopic areas are the most stable and less likely to change compared to any other type of connection. Our results point to a functional connectivity landscape characterized by fluid transitions between local specialization and global integration. This ability to mediate functional properties irrespective of spatial distance may engender a diverse repertoire of cognitive processes when faced with a dynamic environment.

  3. DHA Effects in Brain Development and Function

    Directory of Open Access Journals (Sweden)

    Lotte Lauritzen

    2016-01-01

    Full Text Available Docosahexaenoic acid (DHA is a structural constituent of membranes specifically in the central nervous system. Its accumulation in the fetal brain takes place mainly during the last trimester of pregnancy and continues at very high rates up to the end of the second year of life. Since the endogenous formation of DHA seems to be relatively low, DHA intake may contribute to optimal conditions for brain development. We performed a narrative review on research on the associations between DHA levels and brain development and function throughout the lifespan. Data from cell and animal studies justify the indication of DHA in relation to brain function for neuronal cell growth and differentiation as well as in relation to neuronal signaling. Most data from human studies concern the contribution of DHA to optimal visual acuity development. Accumulating data indicate that DHA may have effects on the brain in infancy, and recent studies indicate that the effect of DHA may depend on gender and genotype of genes involved in the endogenous synthesis of DHA. While DHA levels may affect early development, potential effects are also increasingly recognized during childhood and adult life, suggesting a role of DHA in cognitive decline and in relation to major psychiatric disorders.

  4. Detection of dynamic brain networks modulated by acupuncture using a graph theory model

    Institute of Scientific and Technical Information of China (English)

    Lijun Bai; Wei Qin; Jie Tian; Jianping Dai; Wanhai Yang

    2009-01-01

    Neuroimaging studies involving acute acupuncture manipulation have already demonstrated significant modulatory effects on wide limbic/paralimbic nuclei, subcortical gray structures and the neocortical system of the brain. Due to the sustained effect of acupuncture, however, knowledge on the organization of such large-scale cortical networks behind the active needle stimulation phase is lacking. In this study, we originally adopted a network model analysis from graph theory to evaluate the functional connectivity among multiple brain regions during the post-stimulus phase. Evidence from our findings clearly supported the existence of a large organized functional connectivity network related to acupuncture function in the resting brain. More importantly, acupuncture can change such a network into a functional state underlying both pain perception and modulation, which is exhibited by significant changes in the functional con-nectivity of some brain regions. This analysis may help us to better understand the long-lasting effects of acupuncture on brain function, as well as the potential benefits of clinical treatments.

  5. Dietary boron, brain function, and cognitive performance.

    OpenAIRE

    Penland, J G

    1994-01-01

    Although the trace element boron has yet to be recognized as an essential nutrient for humans, recent data from animal and human studies suggest that boron may be important for mineral metabolism and membrane function. To investigate further the functional role of boron, brain electrophysiology and cognitive performance were assessed in response to dietary manipulation of boron (approximately 0.25 versus approximately 3.25 mg boron/2000 kcal/day) in three studies with healthy older men and wo...

  6. Gender Differences in Brain Functional Connectivity Density

    OpenAIRE

    Tomasi, Dardo; Volkow, Nora D

    2011-01-01

    The neural bases of gender differences in emotional, cognitive, and socials behaviors are largely unknown. Here, magnetic resonance imaging data from 336 women and 225 men revealed a gender dimorphism in the functional organization of the brain. Consistently across five research sites, women had 14% higher local functional connectivity density (lFCD) and up to 5% higher gray matter density than men in cortical and subcortical regions. The negative power scaling of the lFCD was steeper for men...

  7. Compensation through Functional Hyperconnectivity: A Longitudinal Connectome Assessment of Mild Traumatic Brain Injury

    OpenAIRE

    Armin Iraji; Hanbo Chen; Natalie Wiseman; Welch, Robert D.; Brian J. O’Neil; E. Mark Haacke; Tianming Liu; Zhifeng Kou

    2016-01-01

    Mild traumatic brain injury (mTBI) is a major public health concern. Functional MRI has reported alterations in several brain networks following mTBI. However, the connectome-scale brain network changes are still unknown. In this study, sixteen mTBI patients were prospectively recruited from an emergency department and followed up at 4–6 weeks after injury. Twenty-four healthy controls were also scanned twice with the same time interval. Three hundred fifty-eight brain landmarks that preserve...

  8. Violent Video Games Alter Brain Function in Young Men

    Science.gov (United States)

    ... Updates News from the RSNA Annual Meeting Violent Video Games Alter Brain Function in Young Men At A ... functional MRI, researchers have found that playing violent video games for one week causes changes in brain function. ...

  9. Aging brain from a network science perspective: something to be positive about?

    Directory of Open Access Journals (Sweden)

    Michelle W Voss

    Full Text Available To better understand age differences in brain function and behavior, the current study applied network science to model functional interactions between brain regions. We observed a shift in network topology whereby for older adults subcortical and cerebellar structures overlapping with the Salience network had more connectivity to the rest of the brain, coupled with fragmentation of large-scale cortical networks such as the Default and Fronto-Parietal networks. Additionally, greater integration of the dorsal medial thalamus and red nucleus in the Salience network was associated with greater satisfaction with life for older adults, which is consistent with theoretical predictions of age-related increases in emotion regulation that are thought to help maintain well-being and life satisfaction in late adulthood. In regard to cognitive abilities, greater ventral medial prefrontal cortex coherence with its topological neighbors in the Default Network was associated with faster processing speed. Results suggest that large-scale organizing properties of the brain differ with normal aging, and this perspective may offer novel insight into understanding age-related differences in cognitive function and well-being.

  10. Using network science to evaluate exercise-associated brain changes in older adults

    Directory of Open Access Journals (Sweden)

    Jonathan H Burdette

    2010-06-01

    Full Text Available Literature has shown that exercise is beneficial for cognitive function in older adults and that aerobic fitness is associated with increased hippocampal tissue and blood volumes. The current study used novel network science methods to shed light on the neurophysiological implications of exercise-induced changes in the hippocampus of older adults. Participants represented a volunteer subgroup of older adults that were part of either the exercise training (ET or healthy aging educational control (HAC treatment arms from the Seniors Health and Activity Research Program Pilot (SHARP-P trial. Following the four-month interventions, MRI measures of resting brain blood flow and connectivity were performed. The ET group’s hippocampal CBF exhibited statistically significant increases compared to the HAC group. Novel whole-brain network connectivity analyses showed greater connectivity in the hippocampi of the ET participants compared to HAC. Furthermore, the hippocampus was consistently shown to be within the same network neighborhood (module as the anterior cingulate cortex only within the ET group. Thus, within the ET group, the hippocampus and anterior cingulate were highly interconnected and localized to the same network neighborhood. This project shows the power of network science to investigate potential mechanisms for exercise-induced benefits to the brain in older adults. We show a link between neurological network features and cerebral blood flow, and it is possible that this alteration of functional brain networks may lead to the known improvement in cognitive function among older adults following exercise.

  11. Multifractal analysis of resting state networks in functional MRI

    International Nuclear Information System (INIS)

    It has been know for at least one decade that functional MRI time series display long-memory properties, such as power-law scaling in the frequency spectrum. Concomitantly, multivariate model free analysis of spatial patterns, such as spatial Independent Component Analysis (sICA), has been successfully used to segment from spontaneous activity Resting-State Networks (RSN) that correspond to known brain function. As recent neuro-scientific studies suggest a link between spectral properties of brain activity and cognitive processes, a burning question emerges: can temporal scaling properties offer new markers of brain states encoded in these large scale networks? In this paper, we combine two recent methodologies: group-level canonical ICA for multi-subject segmentation of brain network, and wavelet leader-based multifractal formalism for the analysis of RSN scaling properties. We identify the brain networks that elicit self-similarity or multi-fractality and explore which spectral properties correspond specifically to known functionally relevant processes in spontaneous activity. (authors)

  12. Hierarchical brain networks active in approach and avoidance goal pursuit

    Directory of Open Access Journals (Sweden)

    Jeffrey Martin Spielberg

    2013-06-01

    Full Text Available Effective approach/avoidance goal pursuit is critical for attaining long-term health and well-being. Research on the neural correlates of key goal pursuit processes (e.g., motivation has long been of interest, with lateralization in prefrontal cortex being a particularly fruitful target of investigation. However, this literature has often been limited by a lack of spatial specificity and has not delineated the precise aspects of approach/avoidance motivation involved. Additionally, the relationships among brain regions (i.e., network connectivity vital to goal pursuit remain largely unexplored. Specificity in location, process, and network relationship is vital for moving beyond gross characterizations of function and identifying the precise cortical mechanisms involved in motivation. The present paper integrates research using more spatially specific methodologies (e.g., functional magnetic resonance imaging with the rich psychological literature on approach/avoidance to propose an integrative network model that takes advantage of the strengths of each of these literatures.

  13. Intrinsic connectivity in the human brain does not reveal networks for 'basic' emotions.

    Science.gov (United States)

    Touroutoglou, Alexandra; Lindquist, Kristen A; Dickerson, Bradford C; Barrett, Lisa Feldman

    2015-09-01

    We tested two competing models for the brain basis of emotion, the basic emotion theory and the conceptual act theory of emotion, using resting-state functional connectivity magnetic resonance imaging (rs-fcMRI). The basic emotion view hypothesizes that anger, sadness, fear, disgust and happiness each arise from a brain network that is innate, anatomically constrained and homologous in other animals. The conceptual act theory of emotion hypothesizes that an instance of emotion is a brain state constructed from the interaction of domain-general, core systems within the brain such as the salience, default mode and frontoparietal control networks. Using peak coordinates derived from a meta-analysis of task-evoked emotion fMRI studies, we generated a set of whole-brain rs-fcMRI 'discovery' maps for each emotion category and examined the spatial overlap in their conjunctions. Instead of discovering a specific network for each emotion category, variance in the discovery maps was accounted for by the known domain-general network. Furthermore, the salience network is observed as part of every emotion category. These results indicate that specific networks for each emotion do not exist within the intrinsic architecture of the human brain and instead support the conceptual act theory of emotion. PMID:25680990

  14. Meal replacement: calming the hot-state brain network of appetite

    OpenAIRE

    Brielle M Paolini; Laurienti, Paul J.; Norris, James; Rejeski, W. Jack

    2014-01-01

    There is a growing awareness in the field of neuroscience that the self-regulation of eating behavior is driven by complex networks within the brain. These networks may be vulnerable to “hot states” which people can move into and out of dynamically throughout the course of a day as a function of changes in affect or visceral cues. The goal of the current study was to identify and determine differences in the Hot-state Brain Network of Appetite (HBN-A) that exists after a brief period of food ...

  15. Meal Replacement: Calming the Hot-State Brain Network of Appetite

    OpenAIRE

    Brielle ePaolini; Laurienti, Paul J.; James eNorris; W. Jack eRejeski

    2014-01-01

    There is a growing awareness in the field of neuroscience that the self-regulation of eating behavior is driven by complex networks within the brain. These networks may be vulnerable to hot states which people can move into and out of dynamically throughout the course of a day as a function of changes in affect or visceral cues. The goal of the current study was to identify and determine differences in the Hot-state Brain Network of Appetite (HBN-A) that exists after a brief period of food re...

  16. Motif-Synchronization: A new method for analysis of dynamic brain networks with EEG

    Science.gov (United States)

    Rosário, R. S.; Cardoso, P. T.; Muñoz, M. A.; Montoya, P.; Miranda, J. G. V.

    2015-12-01

    The major aim of this work was to propose a new association method known as Motif-Synchronization. This method was developed to provide information about the synchronization degree and direction between two nodes of a network by counting the number of occurrences of some patterns between any two time series. The second objective of this work was to present a new methodology for the analysis of dynamic brain networks, by combining the Time-Varying Graph (TVG) method with a directional association method. We further applied the new algorithms to a set of human electroencephalogram (EEG) signals to perform a dynamic analysis of the brain functional networks (BFN).

  17. BRAIN TUMOR CLASSIFICATION USING NEURAL NETWORK BASED METHODS

    OpenAIRE

    Kalyani A. Bhawar*, Prof. Nitin K. Bhil

    2016-01-01

    MRI (Magnetic resonance Imaging) brain neoplasm pictures Classification may be a troublesome tasks due to the variance and complexity of tumors. This paper presents two Neural Network techniques for the classification of the magnetic resonance human brain images. The proposed Neural Network technique consists of 3 stages, namely, feature extraction, dimensionality reduction, and classification. In the first stage, we have obtained the options connected with tomography pictures victimization d...

  18. Network Organization of the Huntingtin Proteomic Interactome in Mammalian Brain

    OpenAIRE

    Shirasaki, Dyna I; Greiner, Erin R.; Al-Ramahi, Ismael; Gray, Michelle; Boontheung, Pinmanee; Geschwind, Daniel H.; Botas, Juan; Coppola, Giovanni; Horvath, Steve; Loo, Joseph A.; Yang, X. William

    2012-01-01

    We used affinity-purification mass spectrometry to identify 747 candidate proteins that are complexed with Huntingtin (Htt) in distinct brain regions and ages in Huntington’s disease (HD) and wildtype mouse brains. To gain a systems-level view of the Htt interactome, we applied Weighted Gene Correlation Network Analysis (WGCNA) to the entire proteomic dataset to unveil a verifiable rank of Htt-correlated proteins and a network of Htt-interacting protein modules, with each module highlighting ...

  19. Estimation of brain network ictogenicity predicts outcome from epilepsy surgery

    OpenAIRE

    Goodfellow, M.; Rummel, C.; Abela, E.; M. P. Richardson; Schindler, K.; Terry, J.R.

    2016-01-01

    Surgery is a valuable option for pharmacologically intractable epilepsy. However, significant post-operative improvements are not always attained. This is due in part to our incomplete understanding of the seizure generating (ictogenic) capabilities of brain networks. Here we introduce an in silico, model-based framework to study the effects of surgery within ictogenic brain networks. We find that factors conventionally determining the region of tissue to resect, such as the location of focal...

  20. Nodal centrality of functional network in the differentiation of schizophrenia.

    Science.gov (United States)

    Cheng, Hu; Newman, Sharlene; Goñi, Joaquín; Kent, Jerillyn S; Howell, Josselyn; Bolbecker, Amanda; Puce, Aina; O'Donnell, Brian F; Hetrick, William P

    2015-10-01

    A disturbance in the integration of information during mental processing has been implicated in schizophrenia, possibly due to faulty communication within and between brain regions. Graph theoretic measures allow quantification of functional brain networks. Functional networks are derived from correlations between time courses of brain regions. Group differences between SZ and control groups have been reported for functional network properties, but the potential of such measures to classify individual cases has been little explored. We tested whether the network measure of betweenness centrality could classify persons with schizophrenia and normal controls. Functional networks were constructed for 19 schizophrenic patients and 29 non-psychiatric controls based on resting state functional MRI scans. The betweenness centrality of each node, or fraction of shortest-paths that pass through it, was calculated in order to characterize the centrality of the different regions. The nodes with high betweenness centrality agreed well with hub nodes reported in previous studies of structural and functional networks. Using a linear support vector machine algorithm, the schizophrenia group was differentiated from non-psychiatric controls using the ten nodes with the highest betweenness centrality. The classification accuracy was around 80%, and stable against connectivity thresholding. Better performance was achieved when using the ranks as feature space as opposed to the actual values of betweenness centrality. Overall, our findings suggest that changes in functional hubs are associated with schizophrenia, reflecting a variation of the underlying functional network and neuronal communications. In addition, a specific network property, betweenness centrality, can classify persons with SZ with a high level of accuracy. PMID:26299706

  1. Overlapping communities reveal rich structure in large-scale brain networks during rest and task conditions.

    Science.gov (United States)

    Najafi, Mahshid; McMenamin, Brenton W; Simon, Jonathan Z; Pessoa, Luiz

    2016-07-15

    Large-scale analysis of functional MRI data has revealed that brain regions can be grouped into stable "networks" or communities. In many instances, the communities are characterized as relatively disjoint. Although recent work indicates that brain regions may participate in multiple communities (for example, hub regions), the extent of community overlap is poorly understood. To address these issues, here we investigated large-scale brain networks based on "rest" and task human functional MRI data by employing a mixed-membership Bayesian model that allows each brain region to belong to all communities simultaneously with varying membership strengths. The approach allowed us to 1) compare the structure of disjoint and overlapping communities; 2) determine the relationship between functional diversity (how diverse is a region's functional activation repertoire) and membership diversity (how diverse is a region's affiliation to communities); 3) characterize overlapping community structure; 4) characterize the degree of non-modularity in brain networks; 5) study the distribution of "bridges", including bottleneck and hub bridges. Our findings revealed the existence of dense community overlap that was not limited to "special" hubs. Furthermore, the findings revealed important differences between community organization during rest and during specific task states. Overall, we suggest that dense overlapping communities are well suited to capture the flexible and task dependent mapping between brain regions and their functions. PMID:27129758

  2. Network science and the human brain: Using graph theory to understand the brain and one of its hubs, the amygdala, in health and disease.

    Science.gov (United States)

    Mears, David; Pollard, Harvey B

    2016-06-01

    Over the past 15 years, the emerging field of network science has revealed the key features of brain networks, which include small-world topology, the presence of highly connected hubs, and hierarchical modularity. The value of network studies of the brain is underscored by the range of network alterations that have been identified in neurological and psychiatric disorders, including epilepsy, depression, Alzheimer's disease, schizophrenia, and many others. Here we briefly summarize the concepts of graph theory that are used to quantify network properties and describe common experimental approaches for analysis of brain networks of structural and functional connectivity. These range from tract tracing to functional magnetic resonance imaging, diffusion tensor imaging, electroencephalography, and magnetoencephalography. We then summarize the major findings from the application of graph theory to nervous systems ranging from Caenorhabditis elegans to more complex primate brains, including man. Focusing, then, on studies involving the amygdala, a brain region that has attracted intense interest as a center for emotional processing, fear, and motivation, we discuss the features of the amygdala in brain networks for fear conditioning and emotional perception. Finally, to highlight the utility of graph theory for studying dysfunction of the amygdala in mental illness, we review data with regard to changes in the hub properties of the amygdala in brain networks of patients with depression. We suggest that network studies of the human brain may serve to focus attention on regions and connections that act as principal drivers and controllers of brain function in health and disease.(†) Published 2016. PMID:26771046

  3. Dependency Network Analysis (DEPNA) Reveals Context Related Influence of Brain Network Nodes

    Science.gov (United States)

    Jacob, Yael; Winetraub, Yonatan; Raz, Gal; Ben-Simon, Eti; Okon-Singer, Hadas; Rosenberg-Katz, Keren; Hendler, Talma; Ben-Jacob, Eshel

    2016-01-01

    Communication between and within brain regions is essential for information processing within functional networks. The current methods to determine the influence of one region on another are either based on temporal resolution, or require a predefined model for the connectivity direction. However these requirements are not always achieved, especially in fMRI studies, which have poor temporal resolution. We thus propose a new graph theory approach that focuses on the correlation influence between selected brain regions, entitled Dependency Network Analysis (DEPNA). Partial correlations are used to quantify the level of influence of each node during task performance. As a proof of concept, we conducted the DEPNA on simulated datasets and on two empirical motor and working memory fMRI tasks. The simulations revealed that the DEPNA correctly captures the network’s hierarchy of influence. Applying DEPNA to the functional tasks reveals the dynamics between specific nodes as would be expected from prior knowledge. To conclude, we demonstrate that DEPNA can capture the most influencing nodes in the network, as they emerge during specific cognitive processes. This ability opens a new horizon for example in delineating critical nodes for specific clinical interventions. PMID:27271458

  4. The Effect of Aging on Resting-State Brain Function: An fMRI Study

    Directory of Open Access Journals (Sweden)

    A. H. Batouli

    2009-11-01

    Full Text Available Background/Objective: Healthy aging may be accompanied by some types of cognitive impairment; moreover, normal aging may cause natural atrophy in the healthy human brain. The hypothesis of the healthy aging brain is the structural changes together with the functional impairment happening. The brain struggles to over-compensate for those functional age-related impairments to continue as a healthy brain in its functions. Our goal in this study was to evaluate the effects of aging on the resting-state activation network of the brain using the multi-session probabilistic independent component analysis algorithm (PICA. "nPatients and Methods: We compared the resting-state brain activities between two groups of healthy aged and young subjects, so we examined 30 right-handed subjects and finally 12 healthy aging and 11 controls were enrolled in the study. "nResults: Our results showed that during the resting-state, older brains benefit from larger areas of activation, while in young competent brains, higher activation occurs in terms of greater intensity. These results were obtained in prefrontal areas as regions with regard to memory function as well as the posterior cingulate cortex (PCC as parts of the default mode network. Meanwhile, we reached the same results after normalization of activation size with total brain volume. "nConclusion: The difference in activation patterns between the two groups shows the brain's endeavor to compensate the functional impairment.

  5. Functional connectivity of reward processing in the brain

    Directory of Open Access Journals (Sweden)

    2009-01-01

    Full Text Available Controversial results have been reported concerning the neural mechanisms involved in the processing of rewards and punishments. On the one hand, there is evidence suggesting that monetary gains and losses activate a similar fronto-subcortical network. On the other hand, results of recent studies imply that reward and punishment may engage distinct neural mechanisms. Using functional magnetic resonance imaging we investigated both regional and interregional functional connectivity patterns while participants performed a gambling task featuring unexpectedly high monetary gains and losses. Classical univariate statistical analysis showed that monetary gains and losses activated a similar fronto-striatal-limbic network, in which main activation peaks were observed bilaterally in the ventral striatum. Functional connectivity analysis showed similar responses for gain and loss conditions in the insular cortex, the amygdala, and the hippocampus that correlated with the activity observed in the seed region ventral striatum, with the connectivity to the amygdale appearing more pronounced after losses. Larger functional connectivity was found to the medial OFC for negative outcomes. The fact that different functional patterns were obtained with both analyses suggests that the brain activations observed in the classical univariate approach identifies the involvement of different functional networks in a current task. These results stress the importance of studying functional connectivity in addition to standard fMRI analysis in reward-related studies.

  6. Asymmetric development of dorsal and ventral attention networks in the human brain

    Directory of Open Access Journals (Sweden)

    Kristafor Farrant

    2015-04-01

    Full Text Available Two neural systems for goal-directed and stimulus-driven attention have been described in the adult human brain; the dorsal attention network (DAN centered in the frontal eye fields (FEF and intraparietal sulcus (IPS, and the ventral attention network (VAN anchored in the temporoparietal junction (TPJ and ventral frontal cortex (VFC. Little is known regarding the processes governing typical development of these attention networks in the brain. Here we use resting state functional MRI data collected from thirty 7 to 12 year-old children and thirty 18 to 31 year-old adults to examine two key regions of interest from the dorsal and ventral attention networks. We found that for the DAN nodes (IPS and FEF, children showed greater functional connectivity with regions within the network compared with adults, whereas adults showed greater functional connectivity between the FEF and extra-network regions including the posterior cingulate cortex. For the VAN nodes (TPJ and VFC, adults showed greater functional connectivity with regions within the network compared with children. Children showed greater functional connectivity between VFC and nodes of the salience network. This asymmetric pattern of development of attention networks may be a neural signature of the shift from over-representation of bottom-up attention mechanisms to greater top-down attentional capacities with development.

  7. Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia.

    Science.gov (United States)

    Kim, Junghoe; Calhoun, Vince D; Shim, Eunsoo; Lee, Jong-Hwan

    2016-01-01

    Functional connectivity (FC) patterns obtained from resting-state functional magnetic resonance imaging data are commonly employed to study neuropsychiatric conditions by using pattern classifiers such as the support vector machine (SVM). Meanwhile, a deep neural network (DNN) with multiple hidden layers has shown its ability to systematically extract lower-to-higher level information of image and speech data from lower-to-higher hidden layers, markedly enhancing classification accuracy. The objective of this study was to adopt the DNN for whole-brain resting-state FC pattern classification of schizophrenia (SZ) patients vs. healthy controls (HCs) and identification of aberrant FC patterns associated with SZ. We hypothesized that the lower-to-higher level features learned via the DNN would significantly enhance the classification accuracy, and proposed an adaptive learning algorithm to explicitly control the weight sparsity in each hidden layer via L1-norm regularization. Furthermore, the weights were initialized via stacked autoencoder based pre-training to further improve the classification performance. Classification accuracy was systematically evaluated as a function of (1) the number of hidden layers/nodes, (2) the use of L1-norm regularization, (3) the use of the pre-training, (4) the use of framewise displacement (FD) removal, and (5) the use of anatomical/functional parcellation. Using FC patterns from anatomically parcellated regions without FD removal, an error rate of 14.2% was achieved by employing three hidden layers and 50 hidden nodes with both L1-norm regularization and pre-training, which was substantially lower than the error rate from the SVM (22.3%). Moreover, the trained DNN weights (i.e., the learned features) were found to represent the hierarchical organization of aberrant FC patterns in SZ compared with HC. Specifically, pairs of nodes extracted from the lower hidden layer represented sparse FC patterns implicated in SZ, which was

  8. Robust transient dynamics and brain functions

    Directory of Open Access Journals (Sweden)

    Mikhail I Rabinovich

    2011-06-01

    Full Text Available In the last few decades several concepts of Dynamical Systems Theory (DST have guided psychologists, cognitive scientists, and neuroscientists to rethink about sensory motor behavior and embodied cognition. A critical step in the progress of DST application to the brain (supported by modern methods of brain imaging and multi-electrode recording techniques has been the transfer of its initial success in motor behavior to mental function, i.e., perception, emotion, and cognition. Open questions from research in genetics, ecology, brain sciences, etc. have changed DST itself and lead to the discovery of a new dynamical phenomenon, i.e., reproducible and robust transients that are at the same time sensitive to informational signals. The goal of this review is to describe a new mathematical framework -heteroclinic sequential dynamics- to understand self-organized activity in the brain that can explain certain aspects of robust itinerant behavior. Specifically, we discuss a hierarchy of coarse-grain models of mental dynamics in the form of kinetic equations of modes. These modes compete for resources at three levels: (i within the same modality, (ii among different modalities from the same family (like perception, and (iii among modalities from different families (like emotion and cognition. The analysis of the conditions for robustness, i.e., the structural stability of transient (sequential dynamics, give us the possibility to explain phenomena like the finite capacity of our sequential working memory -a vital cognitive function-, and to find specific dynamical signatures -different kinds of instabilities- of several brain functions and mental diseases.

  9. Optimal Brain Surgeon on Artificial Neural Networks in

    DEFF Research Database (Denmark)

    Christiansen, Niels Hørbye; Job, Jonas Hultmann; Klyver, Katrine; Høgsberg, Jan Becker

    2012-01-01

    It is shown how the procedure know as optimal brain surgeon can be used to trim and optimize artificial neural networks in nonlinear structural dynamics. Beside optimizing the neural network, and thereby minimizing computational cost in simulation, the surgery procedure can also serve as a quick...

  10. Identification and classification of hubs in brain networks

    NARCIS (Netherlands)

    Sporns, O.; Honey, C.J.; Kotter, R.

    2007-01-01

    Brain regions in the mammalian cerebral cortex are linked by a complex network of fiber bundles. These inter-regional networks have previously been analyzed in terms of their node degree, structural motif, path length and clustering coefficient distributions. In this paper we focus on the identifica

  11. Dynamic reconfiguration of frontal brain networks during executive cognition in humans.

    Science.gov (United States)

    Braun, Urs; Schäfer, Axel; Walter, Henrik; Erk, Susanne; Romanczuk-Seiferth, Nina; Haddad, Leila; Schweiger, Janina I; Grimm, Oliver; Heinz, Andreas; Tost, Heike; Meyer-Lindenberg, Andreas; Bassett, Danielle S

    2015-09-15

    The brain is an inherently dynamic system, and executive cognition requires dynamically reconfiguring, highly evolving networks of brain regions that interact in complex and transient communication patterns. However, a precise characterization of these reconfiguration processes during cognitive function in humans remains elusive. Here, we use a series of techniques developed in the field of "dynamic network neuroscience" to investigate the dynamics of functional brain networks in 344 healthy subjects during a working-memory challenge (the "n-back" task). In contrast to a control condition, in which dynamic changes in cortical networks were spread evenly across systems, the effortful working-memory condition was characterized by a reconfiguration of frontoparietal and frontotemporal networks. This reconfiguration, which characterizes "network flexibility," employs transient and heterogeneous connectivity between frontal systems, which we refer to as "integration." Frontal integration predicted neuropsychological measures requiring working memory and executive cognition, suggesting that dynamic network reconfiguration between frontal systems supports those functions. Our results characterize dynamic reconfiguration of large-scale distributed neural circuits during executive cognition in humans and have implications for understanding impaired cognitive function in disorders affecting connectivity, such as schizophrenia or dementia. PMID:26324898

  12. Predicting healthy older adult's brain age based on structural connectivity networks using artificial neural networks.

    Science.gov (United States)

    Lin, Lan; Jin, Cong; Fu, Zhenrong; Zhang, Baiwen; Bin, Guangyu; Wu, Shuicai

    2016-03-01

    Brain ageing is followed by changes of the connectivity of white matter (WM) and changes of the grey matter (GM) concentration. Neurodegenerative disease is more vulnerable to an accelerated brain ageing, which is associated with prospective cognitive decline and disease severity. Accurate detection of accelerated ageing based on brain network analysis has a great potential for early interventions designed to hinder atypical brain changes. To capture the brain ageing, we proposed a novel computational approach for modeling the 112 normal older subjects (aged 50-79 years) brain age by connectivity analyses of networks of the brain. Our proposed method applied principal component analysis (PCA) to reduce the redundancy in network topological parameters. Back propagation artificial neural network (BPANN) improved by hybrid genetic algorithm (GA) and Levenberg-Marquardt (LM) algorithm is established to model the relation among principal components (PCs) and brain age. The predicted brain age is strongly correlated with chronological age (r=0.8). The model has mean absolute error (MAE) of 4.29 years. Therefore, we believe the method can provide a possible way to quantitatively describe the typical and atypical network organization of human brain and serve as a biomarker for presymptomatic detection of neurodegenerative diseases in the future. PMID:26718834

  13. THE IMPACT OF POVERTY ON THE DEVELOPMENT OF BRAIN NETWORKS

    Directory of Open Access Journals (Sweden)

    Sebastian J Lipina

    2012-08-01

    Full Text Available Although the study of brain development in non-human animals is an old one, recent imaging methods have allowed non-invasive studies of the grey and white matter of the human brain over the lifespan. Classic animal studies show clearly that impoverished environments reduce cortical grey matter in relation to complex environments and cognitive and imaging studies in humans suggest which networks may be most influenced by poverty. Studies have been clear in showing the plasticity of many brain systems, but whether sensitivity to learning differs over the lifespan and for which networks is still unclear. A major task for current research is a successful integration of these methods to understand how development and learning shape the neural networks underlying achievements in literacy, numeracy, and attention. This paper seeks to foster further integration by reviewing the currents state of knowledge relating brain changes to behavior and indicating possible future directions.

  14. Stimulation-Based Control of Dynamic Brain Networks.

    Science.gov (United States)

    Muldoon, Sarah Feldt; Pasqualetti, Fabio; Gu, Shi; Cieslak, Matthew; Grafton, Scott T; Vettel, Jean M; Bassett, Danielle S

    2016-09-01

    The ability to modulate brain states using targeted stimulation is increasingly being employed to treat neurological disorders and to enhance human performance. Despite the growing interest in brain stimulation as a form of neuromodulation, much remains unknown about the network-level impact of these focal perturbations. To study the system wide impact of regional stimulation, we employ a data-driven computational model of nonlinear brain dynamics to systematically explore the effects of targeted stimulation. Validating predictions from network control theory, we uncover the relationship between regional controllability and the focal versus global impact of stimulation, and we relate these findings to differences in the underlying network architecture. Finally, by mapping brain regions to cognitive systems, we observe that the default mode system imparts large global change despite being highly constrained by structural connectivity. This work forms an important step towards the development of personalized stimulation protocols for medical treatment or performance enhancement. PMID:27611328

  15. Cognitive functioning of the aging brain

    OpenAIRE

    Tam, Man-kin, Helena; 譚敏堅

    2013-01-01

    This thesis contains two studies which examined the cognitive functioning of the aging brain. Specifically, age-related changes in processing speed and its remediation via cognitive training were studied. In study 1, younger adults (n = 34) and older adults (n = 39) were recruited to investigate the age-related differences in the relationships between processing speed and general cognitive status (GCS). Their performance in GCS (as measured by The Montreal Cognitive Assessment, Hong Kong Vers...

  16. The network of brain areas involved in the motion aftereffect

    OpenAIRE

    Taylor, J. G.; Schmitz, N.; Ziemons, K.; Grosse-Ruyken, M. L.; Gruber, O; Müller-Gärtner, H. W.; Shah, J. N.

    2000-01-01

    A network of brain areas is expected to be involved in supporting the motion aftereffect. The most active components of this network were determined by means of an fMRI study of nine subjects exposed to a visual stimulus of moving bars producing the effect. Across the subjects, common areas were identified during various stages of the effect, as well as networks of areas specific to a single stage. In addition to the well-known motion-sensitive area MT the prefrontal brain areas BA44 and 47 a...

  17. Intrinsic network activity in tinnitus investigated using functional MRI.

    Science.gov (United States)

    Leaver, Amber M; Turesky, Ted K; Seydell-Greenwald, Anna; Morgan, Susan; Kim, Hung J; Rauschecker, Josef P

    2016-08-01

    Tinnitus is an increasingly common disorder in which patients experience phantom auditory sensations, usually ringing or buzzing in the ear. Tinnitus pathophysiology has been repeatedly shown to involve both auditory and non-auditory brain structures, making network-level studies of tinnitus critical. In this magnetic resonance imaging (MRI) study, two resting-state functional connectivity (RSFC) approaches were used to better understand functional network disturbances in tinnitus. First, we demonstrated tinnitus-related reductions in RSFC between specific brain regions and resting-state networks (RSNs), defined by independent components analysis (ICA) and chosen for their overlap with structures known to be affected in tinnitus. Then, we restricted ICA to data from tinnitus patients, and identified one RSN not apparent in control data. This tinnitus RSN included auditory-sensory regions like inferior colliculus and medial Heschl's gyrus, as well as classically non-auditory regions like the mediodorsal nucleus of the thalamus, striatum, lateral prefrontal, and orbitofrontal cortex. Notably, patients' reported tinnitus loudness was positively correlated with RSFC between the mediodorsal nucleus and the tinnitus RSN, indicating that this network may underlie the auditory-sensory experience of tinnitus. These data support the idea that tinnitus involves network dysfunction, and further stress the importance of communication between auditory-sensory and fronto-striatal circuits in tinnitus pathophysiology. Hum Brain Mapp 37:2717-2735, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. PMID:27091485

  18. Disrupted small-world brain networks in moderate Alzheimer's disease: a resting-state FMRI study.

    Directory of Open Access Journals (Sweden)

    Xiaohu Zhao

    Full Text Available The small-world organization has been hypothesized to reflect a balance between local processing and global integration in the human brain. Previous multimodal imaging studies have consistently demonstrated that the topological architecture of the brain network is disrupted in Alzheimer's disease (AD. However, these studies have reported inconsistent results regarding the topological properties of brain alterations in AD. One potential explanation for these inconsistent results lies with the diverse homogeneity and distinct progressive stages of the AD involved in these studies, which are thought to be critical factors that might affect the results. We investigated the topological properties of brain functional networks derived from resting functional magnetic resonance imaging (fMRI of carefully selected moderate AD patients and normal controls (NCs. Our results showed that the topological properties were found to be disrupted in AD patients, which showing increased local efficiency but decreased global efficiency. We found that the altered brain regions are mainly located in the default mode network, the temporal lobe and certain subcortical regions that are closely associated with the neuropathological changes in AD. Of note, our exploratory study revealed that the ApoE genotype modulates brain network properties, especially in AD patients.

  19. Attentional Performance is Correlated with the Local Regional Efficiency of Intrinsic Brain Networks

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    Junhai eXu

    2015-07-01

    Full Text Available Attention is a crucial brain function for human beings. Using neuropsychological paradigms and task-based functional brain imaging, previous studies have indicated that widely distributed brain regions are engaged in three distinct attention subsystems: alerting, orienting and executive control (EC. Here, we explored the potential contribution of spontaneous brain activity to attention by examining whether resting-state activity could account for individual differences of the attentional performance in normal individuals. The resting-state functional images and behavioral data from attention network test (ANT task were collected in 59 healthy subjects. Graph analysis was conducted to obtain the characteristics of functional brain networks and linear regression analyses were used to explore their relationships with behavioral performances of the three attentional components. We found that there was no significant relationship between the attentional performance and the global measures, while the attentional performance was associated with specific local regional efficiency. These regions related to the scores of alerting, orienting and EC largely overlapped with the regions activated in previous task-related functional imaging studies, and were consistent with the intrinsic dorsal and ventral attention networks (DAN/VAN. In addition, the strong associations between the attentional performance and specific regional efficiency suggested that there was a possible relationship between the DAN/VAN and task performances in the ANT. We concluded that the intrinsic activity of the human brain could reflect the processing efficiency of the attention system. Our findings revealed a robust evidence for the functional significance of the efficiently organized intrinsic brain network for highly productive cognitions and the hypothesized role of the DAN/ VAN at rest.

  20. Brain Function Lateralization and Language Acquisition: the Evidence from Japanese.

    Science.gov (United States)

    Sanches, Mary

    1979-01-01

    Presents evidence of differences in brain function lateralization between Japanese-speakers and speakers of Indo-European languages, and suggests that current conceptualizations of brain function specialization are not adequate. (AM)

  1. Differential Recruitment of Brain Networks following Route and Cartographic Map Learning of Spatial Environments

    OpenAIRE

    Hui ZHANG; Copara, Milagros; Ekstrom, Arne D.

    2012-01-01

    An extensive neuroimaging literature has helped characterize the brain regions involved in navigating a spatial environment. Far less is known, however, about the brain networks involved when learning a spatial layout from a cartographic map. To compare the two means of acquiring a spatial representation, participants learned spatial environments either by directly navigating them or learning them from an aerial-view map. While undergoing functional magnetic resonance imaging (fMRI), particip...

  2. Sleep, Plasticity and Memory from Molecules to Whole-Brain Networks

    OpenAIRE

    Abel, Ted; Havekes, Robbert; Saletin, Jared M.; Walker, Matthew P.

    2013-01-01

    Despite the ubiquity of sleep across phylogeny, its function remains elusive. In this review, we consider one compelling candidate: brain plasticity associated with memory processing. Focusing largely on hippocampus-dependent memory in rodents and humans, we describe molecular, cellular, network, whole-brain and behavioral evidence establishing a role for sleep both in preparation for initial memory encoding, and in the subsequent offline consolidation ofmemory. Sleep and sleep deprivation bi...

  3. Non-invasive brain-to-brain interface (BBI: establishing functional links between two brains.

    Directory of Open Access Journals (Sweden)

    Seung-Schik Yoo

    Full Text Available Transcranial focused ultrasound (FUS is capable of modulating the neural activity of specific brain regions, with a potential role as a non-invasive computer-to-brain interface (CBI. In conjunction with the use of brain-to-computer interface (BCI techniques that translate brain function to generate computer commands, we investigated the feasibility of using the FUS-based CBI to non-invasively establish a functional link between the brains of different species (i.e. human and Sprague-Dawley rat, thus creating a brain-to-brain interface (BBI. The implementation was aimed to non-invasively translate the human volunteer's intention to stimulate a rat's brain motor area that is responsible for the tail movement. The volunteer initiated the intention by looking at a strobe light flicker on a computer display, and the degree of synchronization in the electroencephalographic steady-state-visual-evoked-potentials (SSVEP with respect to the strobe frequency was analyzed using a computer. Increased signal amplitude in the SSVEP, indicating the volunteer's intention, triggered the delivery of a burst-mode FUS (350 kHz ultrasound frequency, tone burst duration of 0.5 ms, pulse repetition frequency of 1 kHz, given for 300 msec duration to excite the motor area of an anesthetized rat transcranially. The successful excitation subsequently elicited the tail movement, which was detected by a motion sensor. The interface was achieved at 94.0±3.0% accuracy, with a time delay of 1.59±1.07 sec from the thought-initiation to the creation of the tail movement. Our results demonstrate the feasibility of a computer-mediated BBI that links central neural functions between two biological entities, which may confer unexplored opportunities in the study of neuroscience with potential implications for therapeutic applications.

  4. Bottom up modeling of the connectome: Linking structure and function in the resting brain and their changes in aging.

    OpenAIRE

    Nakagawa, Tristan T.; Jirsa, Viktor K.; Spiegler, Andreas; McIntosh, Anthony R.; Deco, Gustavo

    2013-01-01

    With the increasing availability of advanced imaging technologies, we are entering a new era of neuroscience. Detailed descriptions of the complex brain network enable us to map out a structural connectome, characterize it with graph theoretical methods, and compare it to the functional networks with increasing detail. To link these two aspects and understand how dynamics and structure interact to form functional brain networks in task and in the resting state, we use theore...

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

    Science.gov (United States)

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

    2016-04-01

    Abnormal brain connectivity or network dysfunction has been suggested as a paradigm to understand several psychiatric disorders. We here review the use of novel meta-analytic approaches in neuroscience that go beyond a summary description of existing results by applying network analysis methods to previously published studies and/or publicly accessible databases. We define this strategy of combining connectivity with other brain characteristics as 'meta-connectomics'. For example, we show how network analysis of task-based neuroimaging studies has been used to infer functional co-activation from primary data on regional activations. This approach has been able to relate cognition to functional network topology, demonstrating that the brain is composed of cognitively specialized functional subnetworks or modules, linked by a rich club of cognitively generalized regions that mediate many inter-modular connections. Another major application of meta-connectomics has been efforts to link meta-analytic maps of disorder-related abnormalities or MRI 'lesions' to the complex topology of the normative connectome. This work has highlighted the general importance of network hubs as hotspots for concentration of cortical grey-matter deficits in schizophrenia, Alzheimer's disease and other disorders. Finally, we show how by incorporating cellular and transcriptional data on individual nodes with network models of the connectome, studies have begun to elucidate the microscopic mechanisms underpinning the macroscopic organization of whole-brain networks. We argue that meta-connectomics is an exciting field, providing robust and integrative insights into brain organization that will likely play an important future role in consolidating network models of psychiatric disorders. PMID:26809184

  6. Stability of whole brain and regional network topology within and between resting and cognitive states.

    Directory of Open Access Journals (Sweden)

    Justyna K Rzucidlo

    Full Text Available BACKGROUND: Graph-theory based analyses of resting state functional Magnetic Resonance Imaging (fMRI data have been used to map the network organization of the brain. While numerous analyses of resting state brain organization exist, many questions remain unexplored. The present study examines the stability of findings based on this approach over repeated resting state and working memory state sessions within the same individuals. This allows assessment of stability of network topology within the same state for both rest and working memory, and between rest and working memory as well. METHODOLOGY/PRINCIPAL FINDINGS: fMRI scans were performed on five participants while at rest and while performing the 2-back working memory task five times each, with task state alternating while they were in the scanner. Voxel-based whole brain network analyses were performed on the resulting data along with analyses of functional connectivity in regions associated with resting state and working memory. Network topology was fairly stable across repeated sessions of the same task, but varied significantly between rest and working memory. In the whole brain analysis, local efficiency, Eloc, differed significantly between rest and working memory. Analyses of network statistics for the precuneus and dorsolateral prefrontal cortex revealed significant differences in degree as a function of task state for both regions and in local efficiency for the precuneus. Conversely, no significant differences were observed across repeated sessions of the same state. CONCLUSIONS/SIGNIFICANCE: These findings suggest that network topology is fairly stable within individuals across time for the same state, but also fluid between states. Whole brain voxel-based network analyses may prove to be a valuable tool for exploring how functional connectivity changes in response to task demands.

  7. Extraversion and Neuroticism relate to topological properties of resting-state brain networks

    Directory of Open Access Journals (Sweden)

    Qing Gao

    2013-06-01

    Full Text Available With the advent and development of modern neuroimaging techniques, there is an increasing interest in linking extraversion and neuroticism to anatomical and functional brain markers. Here we aimed to test the theoretically derived biological personality model as proposed by Eysenck using graph theoretical analyses. Specifically, the association between the topological organization of whole-brain functional networks and extraversion/neuroticism was explored. To construct functional brain networks, functional connectivity among 90 brain regions was measured by temporal correlation using resting-state functional magnetic resonance imaging (fMRI data of 71 healthy subjects. Graph theoretical analysis revealed a positive association of extraversion scores and normalized clustering coefficient values. These results suggested a more clustered configuration in brain networks of individuals high in extraversion, which could imply a higher arousal threshold and higher levels of arousal tolerance in the cortex of extraverts. On a local network level, we observed that a specific nodal measure, i.e. betweenness centrality (BC, was positively associated with neuroticism scores in the right precentral gyrus, right caudate nucleus, right olfactory cortex and bilateral amygdala. For individuals high in neuroticism, these results suggested a more frequent participation of these specific regions in information transition within the brain network and, in turn, may partly explain greater regional activation levels and lower arousal thresholds in these regions. In contrast, extraversion scores were positively correlated with BC in the right insula, while negatively correlated with BC in the bilateral middle temporal gyrus, indicating that the relationship between extraversion and regional arousal is not as simple as proposed by Eysenck.

  8. Statistical characterization of an ensemble of functional neural networks

    Science.gov (United States)

    Silva, B. B. M.; Miranda, J. G. V.; Corso, G.; Copelli, M.; Vasconcelos, N.; Ribeiro, S.; Andrade, R. F. S.

    2012-10-01

    This work uses a complex network approach to analyze temporal sequences of electrophysiological signals of brain activity from freely behaving rats. A network node represents a neuron and a network link is included between a pair of nodes whenever their firing rates are correlated. The framework of time varying graph (TVG) is used to deal with a very large number (>30 000) of time dependent networks, which are set up by taking into account correlations between neuron firing rates in a moving time lag window of suitable width. Statistical distributions for the following network measures are obtained: size of the largest connected cluster, number of edges, average node degree, and average minimal path. We find that the number of networks with highly correlated activity in distinct brain areas has a fat-tailed distribution, irrespective of the behavioral state of the animal. This contrasts with short-tailed distributions for surrogates obtained by shuffling the original data, and reflects the fact that neurons in the neocortex and hippocampus often act in precise temporal coordination. Our results also suggest that functional neuronal networks at the millimeter scale undergo statistically nontrivial rearrangements over time, thus delimitating an empirical constraint for models of brain activity.

  9. Influence of Acupuncture of Zusanli(ST 36)on Connectivity of Brain Functional Network in Healthy Subjects%针刺对脑功能性网络连接的影响

    Institute of Scientific and Technical Information of China (English)

    李诺; 王江; 邓斌; 魏熙乐; 车艳秋; 贾晨辉; 郭义; 王超

    2011-01-01

    目的:通过研究脑功能性网络的连接特性探讨针刺对脑部的作用.方法:首先设计了针刘足三里采集脑电(EEG)信号的实验;然后采用相干估计法分析9位志愿者((6位男性,3位女性)针刺前、针利中和针刺后各阶段EEG信号的同步特性并建立相应的脑同步性矩阵和脑功能性网络.结果:通过针刺中、针刺后与针刺前的状态相比观察到,针刺足三里会显著提高EEG信号的S频段和Y频段的同步性.通过对脑功能性网络的节点度分析发现,针刺足三里会增加脑部区域的度;进一步分析发现针刺会大量增加己频段内脑部远端区域间长距离连接的数目,从而增强脑功能性网络的聚类系数,降低其平均路径长度.结论:针刘足三里能够协调脑部不同区域间的电活动,具有提高脑部远端区域间信息交流的效果,并且这种效果是对脑部有益的.%Objective To observe the effect of acupuncture of Zusanli (ST 36) on electroencephalogram (EEG) so as to probe into its law in regulating the interconnectvity of brain functional network. Methods A total of 9 healthy young volunteer students (6 male, 3 female) participated in the present study. They were asked to take a dorsal position on a test-bed. EEG signals were acquired from 22 surface scalp electrodes (Fp1, Fp2, F7. F3, Fz, F4, F8, A1, T3, C3, C2, C4, T4, A2, T5. P3, P2, P4, T6, Oz, O1and O2) fixed on the subject's head. Acupuncture stimulation was applied to the right Zusanli (ST 36) by manipulating the filiform needle with uniform reducing-reinforcing method and at a frequency of about 50 cycles/min for 2 min. Then the stimulation was stopped for 10 min, and repeated once again (needle-twirling frequency ; 150 and 200 cycles/min). 3 times altogether. The acquired EEG data were analyzed by using coherence estimation method, average path length, average clustering coefficient, and the average degree of the articulation points (nodes) for analyzing the

  10. Control channels in the brain and their influence on brain executive functions

    Science.gov (United States)

    Meng, Qinglei; Choa, Fow-Sen; Hong, Elliot; Wang, Zhiguang; Islam, Mohammad

    2014-05-01

    In a computer network there are distinct data channels and control channels where massive amount of visual information are transported through data channels but the information streams are routed and controlled by intelligent algorithm through "control channels". Recent studies on cognition and consciousness have shown that the brain control channels are closely related to the brainwave beta (14-40 Hz) and alpha (7-13 Hz) oscillations. The high-beta wave is used by brain to synchronize local neural activities and the alpha oscillation is for desynchronization. When two sensory inputs are simultaneously presented to a person, the high-beta is used to select one of the inputs and the alpha is used to deselect the other so that only one input will get the attention. In this work we demonstrated that we can scan a person's brain using binaural beats technique and identify the individual's preferred control channels. The identified control channels can then be used to influence the subject's brain executive functions. In the experiment, an EEG measurement system was used to record and identify a subject's control channels. After these channels were identified, the subject was asked to do Stroop tests. Binaural beats was again used to produce these control-channel frequencies on the subject's brain when we recorded the completion time of each test. We found that the high-beta signal indeed speeded up the subject's executive function performance and reduced the time to complete incongruent tests, while the alpha signal didn't seem to be able to slow down the executive function performance.

  11. [Contribution of brain function analysis to the evolution of neurorehabilitation].

    Science.gov (United States)

    Miyai, Ichiro; Mihara, Masahito; Hattori, Noriaki; Hatakenaka, Megumi; Kawano, Teiji; Yagura, Hajime

    2012-01-01

    Recent studies of functional neuroimaging and clinical neurophysiology have implied that functional recovery after stroke is associated with use-dependent plasticity of the damaged brain. However the property of the reorganized neural network depends on site and size of the lesion, which makes it difficult to assess what the adaptive plasticity is. From clinical point of view there is accumulating randomized controlled trials for the benefit of task-oriented rehabilitative intervention including constraint-induced movement therapy, robotics, and body-weight supported treadmill training. However dose-matched control intervention is usually as effective as a specific intervention. This raises a question regarding the specificity of a task-oriented intervention. Second question is whether such intervention goes beyond the biological destiny of human. Specifically there is no known strategy enhancing recovery of severely impaired hand. To augment functional gain, several methods of neuro-modulation may bring break-through on the assumption that they induce greater adaptive plasticity. Such neuro-modulative methods include neuropharmacological modulation, brain stimulation using transcranial magnetic stimulation and direct current stimulation, peripheral nerve stimulation, neurofeedback using real-time fMRI and real-time fNIRS, and brain-machine interface. A preliminary randomized controlled trial regarding real-time feedback of premotor activities revealed promising results for recovery of paretic hand in patients with stroke. PMID:23196554

  12. Democratic reinforcement: A principle for brain function

    International Nuclear Information System (INIS)

    We introduce a simple ''toy'' brain model. The model consists of a set of randomly connected, or layered integrate-and-fire neurons. Inputs to and outputs from the environment are connected randomly to subsets of neurons. The connections between firing neurons are strengthened or weakened according to whether the action was successful or not. Unlike previous reinforcement learning algorithms, the feedback from the environment is democratic: it affects all neurons in the same way, irrespective of their position in the network and independent of the output signal. Thus no unrealistic back propagation or other external computation is needed. This is accomplished by a global threshold regulation which allows the system to self-organize into a highly susceptible, possibly ''critical'' state with low activity and sparse connections between firing neurons. The low activity permits memory in quiescent areas to be conserved since only firing neurons are modified when new information is being taught

  13. Brain functional integration decreases during propofol-induced loss of consciousness.

    Science.gov (United States)

    Schrouff, Jessica; Perlbarg, Vincent; Boly, Mélanie; Marrelec, Guillaume; Boveroux, Pierre; Vanhaudenhuyse, Audrey; Bruno, Marie-Aurélie; Laureys, Steven; Phillips, Christophe; Pélégrini-Issac, Mélanie; Maquet, Pierre; Benali, Habib

    2011-07-01

    Consciousness has been related to the amount of integrated information that the brain is able to generate. In this paper, we tested the hypothesis that the loss of consciousness caused by propofol anesthesia is associated with a significant reduction in the capacity of the brain to integrate information. To assess the functional structure of the whole brain, functional integration and partial correlations were computed from fMRI data acquired from 18 healthy volunteers during resting wakefulness and propofol-induced deep sedation. Total integration was significantly reduced from wakefulness to deep sedation in the whole brain as well as within and between its constituent networks (or systems). Integration was systematically reduced within each system (i.e., brain or networks), as well as between networks. However, the ventral attentional network maintained interactions with most other networks during deep sedation. Partial correlations further suggested that functional connectivity was particularly affected between parietal areas and frontal or temporal regions during deep sedation. Our findings suggest that the breakdown in brain integration is the neural correlate of the loss of consciousness induced by propofol. They stress the important role played by parietal and frontal areas in the generation of consciousness. PMID:21524704

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

    Science.gov (United States)

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

    2015-06-01

    Traumatic brain injury affects brain connectivity by producing traumatic axonal injury. This disrupts the function of large-scale networks that support cognition. The best way to describe this relationship is unclear, but one elegant approach is to view networks as graphs. Brain regions become nodes in the graph, and white matter tracts the connections. The overall effect of an injury can then be estimated by calculating graph metrics of network structure and function. Here we test which graph metrics best predict the presence of traumatic axonal injury, as well as which are most highly associated with cognitive impairment. A comprehensive range of graph metrics was calculated from structural connectivity measures for 52 patients with traumatic brain injury, 21 of whom had microbleed evidence of traumatic axonal injury, and 25 age-matched controls. White matter connections between 165 grey matter brain regions were defined using tractography, and structural connectivity matrices calculated from skeletonized diffusion tensor imaging data. This technique estimates injury at the centre of tract, but is insensitive to damage at tract edges. Graph metrics were calculated from the resulting connectivity matrices and machine-learning techniques used to select the metrics that best predicted the presence of traumatic brain injury. In addition, we used regularization and variable selection via the elastic net to predict patient behaviour on tests of information processing speed, executive function and associative memory. Support vector machines trained with graph metrics of white matter connectivity matrices from the microbleed group were able to identify patients with a history of traumatic brain injury with 93.4% accuracy, a result robust to different ways of sampling the data. Graph metrics were significantly associated with cognitive performance: information processing speed (R(2) = 0.64), executive function (R(2) = 0.56) and associative memory (R(2) = 0.25). These

  15. Resting-state networks link invasive and noninvasive brain stimulation across diverse psychiatric and neurological diseases.

    Science.gov (United States)

    Fox, Michael D; Buckner, Randy L; Liu, Hesheng; Chakravarty, M Mallar; Lozano, Andres M; Pascual-Leone, Alvaro

    2014-10-14

    Brain stimulation, a therapy increasingly used for neurological and psychiatric disease, traditionally is divided into invasive approaches, such as deep brain stimulation (DBS), and noninvasive approaches, such as transcranial magnetic stimulation. The relationship between these approaches is unknown, therapeutic mechanisms remain unclear, and the ideal stimulation site for a given technique is often ambiguous, limiting optimization of the stimulation and its application in further disorders. In this article, we identify diseases treated with both types of stimulation, list the stimulation sites thought to be most effective in each disease, and test the hypothesis that these sites are different nodes within the same brain network as defined by resting-state functional-connectivity MRI. Sites where DBS was effective were functionally connected to sites where noninvasive brain stimulation was effective across diseases including depression, Parkinson's disease, obsessive-compulsive disorder, essential tremor, addiction, pain, minimally conscious states, and Alzheimer's disease. A lack of functional connectivity identified sites where stimulation was ineffective, and the sign of the correlation related to whether excitatory or inhibitory noninvasive stimulation was found clinically effective. These results suggest that resting-state functional connectivity may be useful for translating therapy between stimulation modalities, optimizing treatment, and identifying new stimulation targets. More broadly, this work supports a network perspective toward understanding and treating neuropsychiatric disease, highlighting the therapeutic potential of targeted brain network modulation. PMID:25267639

  16. Frontoparietal Connectivity and Hierarchical Structure of the Brain’s Functional Network during Sleep

    OpenAIRE

    Spoormaker, Victor I.; PABLO M. GLEISER; Czisch, Michael

    2012-01-01

    Frontal and parietal regions are associated with some of the most complex cognitive functions, and several frontoparietal resting-state networks can be observed in wakefulness. We used functional magnetic resonance imaging data acquired in polysomnographically validated wakefulness, light sleep, and slow-wave sleep to examine the hierarchical structure of a low-frequency functional brain network, and to examine whether frontoparietal connectivity would disintegrate in sleep. Whole-brain analy...

  17. The application of a mathematical model linking structural and functional connectomes in severe brain injury

    Directory of Open Access Journals (Sweden)

    A. Kuceyeski

    2016-01-01

    Full Text Available Following severe injuries that result in disorders of consciousness, recovery can occur over many months or years post-injury. While post-injury synaptogenesis, axonal sprouting and functional reorganization are known to occur, the network-level processes underlying recovery are poorly understood. Here, we test a network-level functional rerouting hypothesis in recovery of patients with disorders of consciousness following severe brain injury. This hypothesis states that the brain recovers from injury by restoring normal functional connections via alternate structural pathways that circumvent impaired white matter connections. The so-called network diffusion model, which relates an individual's structural and functional connectomes by assuming that functional activation diffuses along structural pathways, is used here to capture this functional rerouting. We jointly examined functional and structural connectomes extracted from MRIs of 12 healthy and 16 brain-injured subjects. Connectome properties were quantified via graph theoretic measures and network diffusion model parameters. While a few graph metrics showed groupwise differences, they did not correlate with patients' level of consciousness as measured by the Coma Recovery Scale — Revised. There was, however, a strong and significant partial Pearson's correlation (accounting for age and years post-injury between level of consciousness and network diffusion model propagation time (r = 0.76, p < 0.05, corrected, i.e. the time functional activation spends traversing the structural network. We concluded that functional rerouting via alternate (and less efficient pathways leads to increases in network diffusion model propagation time. Simulations of injury and recovery in healthy connectomes confirmed these results. This work establishes the feasibility for using the network diffusion model to capture network-level mechanisms in recovery of consciousness after severe brain injury.

  18. Stochastic causality, criticality, and non-locality in brain networks. Comment on "Foundational perspectives on causality in large-scale brain networks" by M. Mannino and S.L. Bressler

    Science.gov (United States)

    Kozma, Robert; Hu, Sanqing

    2015-12-01

    For millennia, causality served as a powerful guiding principle to our understanding of natural processes, including the functioning of our body, mind, and brain. The target paper presents an impressive vista of the field of causality in brain networks, starting from philosophical issues, expanding on neuroscience effects, and addressing broad engineering and societal aspects as well. The authors conclude that the concept of stochastic causality is more suited to characterize the experimentally observed complex dynamical processes in large-scale brain networks, rather than the more traditional view of deterministic causality. We strongly support this conclusion and provide two additional examples that may enhance and complement this review: (i) a generalization of the Wiener-Granger Causality (WGC) to fit better the complexity of brain networks; (ii) employment of criticality as a key concept highly relevant to interpreting causality and non-locality in large-scale brain networks.

  19. Modelling Human Cortical Network in Real Brain Space

    Institute of Scientific and Technical Information of China (English)

    ZHAO Qing-Bai; FENG Hong-Bo; TANG Yi-Yuan

    2007-01-01

    Highly specific structural organization is of great significance in the topology of cortical networks.We introduce a human cortical network model.taking the specific cortical structure into account,in which nodes are brain sites placed in the actual positions of cerebral cortex and the establishment of edges depends on the spatial path length rather than the linear distance.The resulting network exhibits the essential features of cortical connectivity,properties of small-world networks and multiple clusters structure.Additionally.assortative mixing is also found in this roodel.All of these findings may be attributed to the spedtic cortical architecture.

  20. Hyper-Brain Networks Support Romantic Kissing in Humans

    OpenAIRE

    Müller, Viktor; Lindenberger, Ulman

    2014-01-01

    Coordinated social interaction is associated with, and presumably dependent on, oscillatory couplings within and between brains, which, in turn, consist of an interplay across different frequencies. Here, we introduce a method of network construction based on the cross-frequency coupling (CFC) and examine whether coordinated social interaction is associated with CFC within and between brains. Specifically, we compare the electroencephalograms (EEG) of 15 heterosexual couples during romantic k...

  1. Sleeping of a Complex Brain Networks with Hierarchical Organization

    Institute of Scientific and Technical Information of China (English)

    ZHANG Ying-Yue; YANG Qiu-Ying; CHEN Tian-Lun

    2009-01-01

    The dynamical behavior in the cortical brain network of macaque is studied by modeling each cortical area with a subnetwork of interacting excitable neurons. We characterize the system by studying how to perform the transition, which is now topology-dependent, from the active state to that with no activity. This could be a naive model for the wakening and sleeping of a brain-like system, i.e., a multi-component system with two different dynamical behavior.

  2. Rehabilitation of People with a Brain Injury Through the Lens of Networked Learning

    DEFF Research Database (Denmark)

    Konnerup, Ulla; Castro Rojas, Maria Dolores; Bygholm, Ann

    2016-01-01

    This paper will demonstrate how avatar-mediated interactions and learning in networks might lead to identity formation and rehabilitation of language after a brain injury. With references to Vygotsky's notion of the social origins of higher mental functions (1978) and Hutchins claims that cognition...

  3. The brain as a system of nested but partially overlapping networks. Heuristic relevance of the model for brain physiology and pathology.

    Science.gov (United States)

    Agnati, L F; Guidolin, D; Fuxe, K

    2007-01-01

    A new model of the brain organization is proposed. The model is based on the assumption that a global molecular network enmeshes the entire central nervous system. Thus, brain extra-cellular and intra-cellular molecular networks are proposed to communicate at the level of special plasma membrane regions (e.g., the lipid rafts) where horizontal molecular networks can represent input/output regions allowing the cell to have informational exchanges with the extracellular environment. Furthermore, some "pervasive signals" such as field potentials, pressure waves and thermal gradients that affect large parts of the brain cellular and molecular networks are discussed. Finally, at least two learning paradigms are analyzed taking into account the possible role of Volume Transmission: the so-called model of "temporal difference learning" and the "Turing B-unorganised machine". The relevance of this new view of brain organization for a deeper understanding of some neurophysiological and neuropathological aspects of its function is briefly discussed. PMID:16906353

  4. The function of histamine receptor H4R in the brain revealed by interaction partners.

    Science.gov (United States)

    Moya-Garcia, Aurelio A; Rodriguez, Carlos E; Morilla, Ian; Sanchez-Jimenez, Francisca; Ranea, Juan A G

    2011-01-01

    The histamine H4 receptor is mainly expressed in haematopoietic cells, hence is linked to inflammatory and immune system conditions. It has been recently discovered that the receptor is expressed also in the mammalian central nervous system (CNS), but its role in the brain remains unclear. We address the potential functions of the histamine H4 receptor in the human brain using a 'guilty by association' logic, by close examination of protein-protein functional associations networks in the human proteome. PMID:21622255

  5. Toward discovery science of human brain function

    DEFF Research Database (Denmark)

    Biswal, Bharat B; Mennes, Maarten; Zuo, Xi-Nian;

    2010-01-01

    priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally...... require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter......-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the...

  6. Motor deficits correlate with resting state motor network connectivity in patients with brain tumours

    OpenAIRE

    Otten, Marc L.; Mikell, Charles B; Youngerman, Brett E.; Liston, Conor; Sisti, Michael B.; Bruce, Jeffrey N.; Small, Scott A.; McKhann, Guy M.

    2012-01-01

    While a tumour in or abutting primary motor cortex leads to motor weakness, how tumours elsewhere in the frontal or parietal lobes affect functional connectivity in a weak patient is less clear. We hypothesized that diminished functional connectivity in a distributed network of motor centres would correlate with motor weakness in subjects with brain masses. Furthermore, we hypothesized that interhemispheric connections would be most vulnerable to subtle disruptions in functional connectivity....

  7. Stimulating brain tissue with bright light alters functional connectivity in brain at the resting state

    OpenAIRE

    Timo Takala; Markku Timonen; Juha Nikkinen; Jukka Remes; Antti Aunio; Ahmed Abou-Elseoud; Juuso Nissilä; Tuomo Starck; Osmo Tervonen; Vesa Kiviniemi

    2012-01-01

    Light is considered to modulate human brain function only via the retinal pathway, a way of thinking that we aimed to challenge in the present study. Literature provides evidence of inherent phototransduction for instance in the rat brain and there are potentially photosensitive opsin proteins like melanopsin and panopsin in the human brain too. In order to investigate a short term response, functional connectivity changes of the brain were studied in the resting state with functional magneti...

  8. Network stratification analysis for identifying function-specific network layers.

    Science.gov (United States)

    Zhang, Chuanchao; Wang, Jiguang; Zhang, Chao; Liu, Juan; Xu, Dong; Chen, Luonan

    2016-04-22

    A major challenge of systems biology is to capture the rewiring of biological functions (e.g. signaling pathways) in a molecular network. To address this problem, we proposed a novel computational framework, namely network stratification analysis (NetSA), to stratify the whole biological network into various function-specific network layers corresponding to particular functions (e.g. KEGG pathways), which transform the network analysis from the gene level to the functional level by integrating expression data, the gene/protein network and gene ontology information altogether. The application of NetSA in yeast and its comparison with a traditional network-partition both suggest that NetSA can more effectively reveal functional implications of network rewiring and extract significant phenotype-related biological processes. Furthermore, for time-series or stage-wise data, the function-specific network layer obtained by NetSA is also shown to be able to characterize the disease progression in a dynamic manner. In particular, when applying NetSA to hepatocellular carcinoma and type 1 diabetes, we can derive functional spectra regarding the progression of the disease, and capture active biological functions (i.e. active pathways) in different disease stages. The additional comparison between NetSA and SPIA illustrates again that NetSA could discover more complete biological functions during disease progression. Overall, NetSA provides a general framework to stratify a network into various layers of function-specific sub-networks, which can not only analyze a biological network on the functional level but also investigate gene rewiring patterns in biological processes. PMID:26879865

  9. Small-World Brain Networks Revisited

    OpenAIRE

    Bassett, Danielle S.; Bullmore, Edward T.

    2016-01-01

    It is nearly 20 years since the concept of a small-world network was first quantitatively defined, by a combination of high clustering and short path length; and about 10 years since this metric of complex network topology began to be widely applied to analysis of neuroimaging and other neuroscience data as part of the rapid growth of the new field of connectomics. Here we review briefly the foundational concepts of graph theoretical estimation and generation of small-world networks. We take ...

  10. Localisation of brain functions : stimuling brain activity and source reconstruction for classification/

    OpenAIRE

    Noirhomme, Quentin

    2006-01-01

    A key issue in understanding how the brain functions is the ability to correlate functional information with anatomical localisation. Functional information can be provided by a variety of techniques like positron emission tomography (PET), functional MRI (fMRI), electroencephalography (EEG), magnetoencephalography (MEG) or transcranial magnetic stimulation (TMS). All these methods provide different, but complementary, information about the functional areas of the brain. ...

  11. In vivo Visuotopic Brain Mapping with Manganese-Enhanced MRI and Resting-State Functional Connectivity MRI

    OpenAIRE

    Chan, Kevin C.; Fan, Shu-Juan; Chan, Russell W.; Cheng, Joe S.; Zhou, Iris Y.; Wu, Ed X.

    2014-01-01

    The rodents are an increasingly important model for understanding the mechanisms of development, plasticity, functional specialization and disease in the visual system. However, limited tools have been available for assessing the structural and functional connectivity of the visual brain network globally, in vivo and longitudinally. There are also ongoing debates on whether functional brain connectivity directly reflects structural brain connectivity. In this study, we explored the feasibilit...

  12. Changes of the directional brain networks related with brain plasticity in patients with long-term unilateral sensorineural hearing loss.

    Science.gov (United States)

    Zhang, G-Y; Yang, M; Liu, B; Huang, Z-C; Li, J; Chen, J-Y; Chen, H; Zhang, P-P; Liu, L-J; Wang, J; Teng, G-J

    2016-01-28

    Previous studies often report that early auditory deprivation or congenital deafness contributes to cross-modal reorganization in the auditory-deprived cortex, and this cross-modal reorganization limits clinical benefit from cochlear prosthetics. However, there are inconsistencies among study results on cortical reorganization in those subjects with long-term unilateral sensorineural hearing loss (USNHL). It is also unclear whether there exists a similar cross-modal plasticity of the auditory cortex for acquired monaural deafness and early or congenital deafness. To address this issue, we constructed the directional brain functional networks based on entropy connectivity of resting-state functional MRI and researched changes of the networks. Thirty-four long-term USNHL individuals and seventeen normally hearing individuals participated in the test, and all USNHL patients had acquired deafness. We found that certain brain regions of the sensorimotor and visual networks presented enhanced synchronous output entropy connectivity with the left primary auditory cortex in the left long-term USNHL individuals as compared with normally hearing individuals. Especially, the left USNHL showed more significant changes of entropy connectivity than the right USNHL. No significant plastic changes were observed in the right USNHL. Our results indicate that the left primary auditory cortex (non-auditory-deprived cortex) in patients with left USNHL has been reorganized by visual and sensorimotor modalities through cross-modal plasticity. Furthermore, the cross-modal reorganization also alters the directional brain functional networks. The auditory deprivation from the left or right side generates different influences on the human brain. PMID:26621123

  13. Self-organized Criticality in Hierarchical Brain Network

    Institute of Scientific and Technical Information of China (English)

    YANG Qiu-Ying; ZHANG Ying-Yue; CHEN Tian-Lun

    2008-01-01

    It is shown that the cortical brain network of the macaque displays a hierarchically clustered organization and the neuron network shows small-world properties. Now the two factors will be considered in our model and the dynamical behavior of the model will be studied. We study the characters of the model and find that the distribution of avalanche size of the model follows power-law behavior.

  14. Foundational perspectives on causality in large-scale brain networks

    Science.gov (United States)

    Mannino, Michael; Bressler, Steven L.

    2015-12-01

    A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical

  15. Network Physiology reveals relations between network topology and physiological function

    CERN Document Server

    Bashan, Amir; Kantelhardt, Jan W; Havlin, Shlomo; Ivanov, Plamen Ch; 10.1038/ncomms1705

    2012-01-01

    The human organism is an integrated network where complex physiologic systems, each with its own regulatory mechanisms, continuously interact, and where failure of one system can trigger a breakdown of the entire network. Identifying and quantifying dynamical networks of diverse systems with different types of interactions is a challenge. Here, we develop a framework to probe interactions among diverse systems, and we identify a physiologic network. We find that each physiologic state is characterized by a specific network structure, demonstrating a robust interplay between network topology and function. Across physiologic states the network undergoes topological transitions associated with fast reorganization of physiologic interactions on time scales of a few minutes, indicating high network flexibility in response to perturbations. The proposed system-wide integrative approach may facilitate the development of a new field, Network Physiology.

  16. Estimating Large-Scale Network Convergence in the Human Functional Connectome.

    Science.gov (United States)

    Bell, Peter T; Shine, James M

    2015-11-01

    The study of resting-state networks provides an informative paradigm for understanding the functional architecture of the human brain. Although investigating specialized resting-state networks has led to significant advances in our understanding of brain organization, the manner in which information is integrated across these networks remains unclear. Here, we have developed and validated a data-driven methodology for describing the topography of resting-state network convergence in the human brain. Our results demonstrate the importance of an ensemble of cortical and subcortical regions in supporting the convergence of multiple resting-state networks, including the rostral anterior cingulate, precuneus, posterior cingulate cortex, posterior parietal cortex, dorsal prefrontal cortex, along with the caudate head, anterior claustrum, and posterior thalamus. In addition, we have demonstrated a significant correlation between voxel-wise network convergence and global brain connectivity, emphasizing the importance of resting-state network convergence in facilitating global brain communication. Finally, we examined the convergence of systems within each of the individual resting-state networks in the brain, revealing the heterogeneity by which individual resting-state networks balance the competing demands of specialized processing against the integration of information. Together, our results suggest that the convergence of resting-state networks represents an important organizational principle underpinning systems-level integration in the human brain. PMID:26005099

  17. Abnormal functional global and local brain connectivity in female patients with anorexia nervosa

    Science.gov (United States)

    Geisler, Daniel; Borchardt, Viola; Lord, Anton R.; Boehm, Ilka; Ritschel, Franziska; Zwipp, Johannes; Clas, Sabine; King, Joseph A.; Wolff-Stephan, Silvia; Roessner, Veit; Walter, Martin; Ehrlich, Stefan

    2016-01-01

    Background Previous resting-state functional connectivity studies in patients with anorexia nervosa used independent component analysis or seed-based connectivity analysis to probe specific brain networks. Instead, modelling the entire brain as a complex network allows determination of graph-theoretical metrics, which describe global and local properties of how brain networks are organized and how they interact. Methods To determine differences in network properties between female patients with acute anorexia nervosa and pairwise matched healthy controls, we used resting-state fMRI and computed well-established global and local graph metrics across a range of network densities. Results Our analyses included 35 patients and 35 controls. We found that the global functional network structure in patients with anorexia nervosa is characterized by increases in both characteristic path length (longer average routes between nodes) and assortativity (more nodes with a similar connectedness link together). Accordingly, we found locally decreased connectivity strength and increased path length in the posterior insula and thalamus. Limitations The present results may be limited to the methods applied during preprocessing and network construction. Conclusion We demonstrated anorexia nervosa–related changes in the network configuration for, to our knowledge, the first time using resting-state fMRI and graph-theoretical measures. Our findings revealed an altered global brain network architecture accompanied by local degradations indicating wide-scale disturbance in information flow across brain networks in patients with acute anorexia nervosa. Reduced local network efficiency in the thalamus and posterior insula may reflect a mechanism that helps explain the impaired integration of visuospatial and homeostatic signals in patients with this disorder, which is thought to be linked to abnormal representations of body size and hunger. PMID:26252451

  18. Inferring Functional Brain States Using Temporal Evolution of Regularized Classifiers

    OpenAIRE

    Leslie Ungerleider; Nathan Intrator; Andrey Zhdanov; Talma Hendler

    2007-01-01

    We present a framework for inferring functional brain state from electrophysiological (MEG or EEG) brain signals. Our approach is adapted to the needs of functional brain imaging rather than EEG-based brain-computer interface (BCI). This choice leads to a different set of requirements, in particular to the demand for more robust inference methods and more sophisticated model validation techniques. We approach the problem from a machine learning perspective, by constructing a classif...

  19. Brain function in coma, vegetative state, and related disorders

    OpenAIRE

    Laureys, Steven; Owen, Adrian M.; Schiff, Nicholas D.

    2004-01-01

    We review the nosological criteria and functional neuroanatomical basis for brain death, coma, vegetative state, minimally conscious state, and the locked-in state. Functional neuroimaging is providing new insights into cerebral activity in patients with severe brain damage. Measurements of cerebral metabolism and brain activations in response to sensory stimuli with PET, fMRI, and electrophysiological methods can provide information on the presence, degree, and location of any residual brain...

  20. Abdominal Pain, the Adolescent and Altered Brain Structure and Function.

    Science.gov (United States)

    Hubbard, Catherine S; Becerra, Lino; Heinz, Nicole; Ludwick, Allison; Rasooly, Tali; Wu, Rina; Johnson, Adriana; Schechter, Neil L; Borsook, David; Nurko, Samuel

    2016-01-01

    Irritable bowel syndrome (IBS) is a functional gastrointestinal (GI) disorder of unknown etiology. Although relatively common in children, how this condition affects brain structure and function in a pediatric population remains unclear. Here, we investigate brain changes in adolescents with IBS and healthy controls. Imaging was performed with a Siemens 3 Tesla Trio Tim MRI scanner equipped with a 32-channel head coil. A high-resolution T1-weighted anatomical scan was acquired followed by a T2-weighted functional scan. We used a surface-based morphometric approach along with a seed-based resting-state functional connectivity (RS-FC) analysis to determine if groups differed in cortical thickness and whether areas showing structural differences also showed abnormal RS-FC patterns. Patients completed the Abdominal Pain Index and the GI Module of the Pediatric Quality of Life Inventory to assess abdominal pain severity and impact of GI symptoms on health-related quality of life (HRQOL). Disease duration and pain intensity were also assessed. Pediatric IBS patients, relative to controls, showed cortical thickening in the posterior cingulate (PCC), whereas cortical thinning in posterior parietal and prefrontal areas were found, including the dorsolateral prefrontal cortex (DLPFC). In patients, abdominal pain severity was related to cortical thickening in the intra-abdominal area of the primary somatosensory cortex (SI), whereas HRQOL was associated with insular cortical thinning. Disease severity measures correlated with cortical thickness in bilateral DLPFC and orbitofrontal cortex. Patients also showed reduced anti-correlations between PCC and DLPFC compared to controls, a finding that may reflect aberrant connectivity between default mode and cognitive control networks. We are the first to demonstrate concomitant structural and functional brain changes associated with abdominal pain severity, HRQOL related to GI-specific symptoms, and disease-specific measures in

  1. Abdominal Pain, the Adolescent and Altered Brain Structure and Function.

    Directory of Open Access Journals (Sweden)

    Catherine S Hubbard

    Full Text Available Irritable bowel syndrome (IBS is a functional gastrointestinal (GI disorder of unknown etiology. Although relatively common in children, how this condition affects brain structure and function in a pediatric population remains unclear. Here, we investigate brain changes in adolescents with IBS and healthy controls. Imaging was performed with a Siemens 3 Tesla Trio Tim MRI scanner equipped with a 32-channel head coil. A high-resolution T1-weighted anatomical scan was acquired followed by a T2-weighted functional scan. We used a surface-based morphometric approach along with a seed-based resting-state functional connectivity (RS-FC analysis to determine if groups differed in cortical thickness and whether areas showing structural differences also showed abnormal RS-FC patterns. Patients completed the Abdominal Pain Index and the GI Module of the Pediatric Quality of Life Inventory to assess abdominal pain severity and impact of GI symptoms on health-related quality of life (HRQOL. Disease duration and pain intensity were also assessed. Pediatric IBS patients, relative to controls, showed cortical thickening in the posterior cingulate (PCC, whereas cortical thinning in posterior parietal and prefrontal areas were found, including the dorsolateral prefrontal cortex (DLPFC. In patients, abdominal pain severity was related to cortical thickening in the intra-abdominal area of the primary somatosensory cortex (SI, whereas HRQOL was associated with insular cortical thinning. Disease severity measures correlated with cortical thickness in bilateral DLPFC and orbitofrontal cortex. Patients also showed reduced anti-correlations between PCC and DLPFC compared to controls, a finding that may reflect aberrant connectivity between default mode and cognitive control networks. We are the first to demonstrate concomitant structural and functional brain changes associated with abdominal pain severity, HRQOL related to GI-specific symptoms, and disease

  2. Default network connectivity reflects the level of consciousness in non-communicative brain-damaged patients.

    Science.gov (United States)

    Vanhaudenhuyse, Audrey; Noirhomme, Quentin; Tshibanda, Luaba J-F; Bruno, Marie-Aurelie; Boveroux, Pierre; Schnakers, Caroline; Soddu, Andrea; Perlbarg, Vincent; Ledoux, Didier; Brichant, Jean-François; Moonen, Gustave; Maquet, Pierre; Greicius, Michael D; Laureys, Steven; Boly, Melanie

    2010-01-01

    The 'default network' is defined as a set of areas, encompassing posterior-cingulate/precuneus, anterior cingulate/mesiofrontal cortex and temporo-parietal junctions, that show more activity at rest than during attention-demanding tasks. Recent studies have shown that it is possible to reliably identify this network in the absence of any task, by resting state functional magnetic resonance imaging connectivity analyses in healthy volunteers. However, the functional significance of these spontaneous brain activity fluctuations remains unclear. The aim of this study was to test if the integrity of this resting-state connectivity pattern in the default network would differ in different pathological alterations of consciousness. Fourteen non-communicative brain-damaged patients and 14 healthy controls participated in the study. Connectivity was investigated using probabilistic independent component analysis, and an automated template-matching component selection approach. Connectivity in all default network areas was found to be negatively correlated with the degree of clinical consciousness impairment, ranging from healthy controls and locked-in syndrome to minimally conscious, vegetative then coma patients. Furthermore, precuneus connectivity was found to be significantly stronger in minimally conscious patients as compared with unconscious patients. Locked-in syndrome patient's default network connectivity was not significantly different from controls. Our results show that default network connectivity is decreased in severely brain-damaged patients, in proportion to their degree of consciousness impairment. Future prospective studies in a larger patient population are needed in order to evaluate the prognostic value of the presented methodology. PMID:20034928

  3. Scalable Semisupervised Functional Neurocartography Reveals Canonical Neurons in Behavioral Networks.

    Science.gov (United States)

    Frady, E Paxon; Kapoor, Ashish; Horvitz, Eric; Kristan, William B

    2016-08-01

    Large-scale data collection efforts to map the brain are underway at multiple spatial and temporal scales, but all face fundamental problems posed by high-dimensional data and intersubject variability. Even seemingly simple problems, such as identifying a neuron/brain region across animals/subjects, become exponentially more difficult in high dimensions, such as recognizing dozens of neurons/brain regions simultaneously. We present a framework and tools for functional neurocartography-the large-scale mapping of neural activity during behavioral states. Using a voltage-sensitive dye (VSD), we imaged the multifunctional responses of hundreds of leech neurons during several behaviors to identify and functionally map homologous neurons. We extracted simple features from each of these behaviors and combined them with anatomical features to create a rich medium-dimensional feature space. This enabled us to use machine learning techniques and visualizations to characterize and account for intersubject variability, piece together a canonical atlas of neural activity, and identify two behavioral networks. We identified 39 neurons (18 pairs, 3 unpaired) as part of a canonical swim network and 17 neurons (8 pairs, 1 unpaired) involved in a partially overlapping preparatory network. All neurons in the preparatory network rapidly depolarized at the onsets of each behavior, suggesting that it is part of a dedicated rapid-response network. This network is likely mediated by the S cell, and we referenced VSD recordings to an activity atlas to identify multiple cells of interest simultaneously in real time for further experiments. We targeted and electrophysiologically verified several neurons in the swim network and further showed that the S cell is presynaptic to multiple neurons in the preparatory network. This study illustrates the basic framework to map neural activity in high dimensions with large-scale recordings and how to extract the rich information necessary to perform

  4. Naturalistic fMRI mapping reveals superior temporal sulcus as the hub for the distributed brain network for social perception

    OpenAIRE

    Juha Marko Lahnakoski; Enrico eGlerean; Juha eSalmi; Jääskeläinen, Iiro P.; Mikko eSams; Riitta eHari; Lauri eNummenmaa

    2012-01-01

    Despite the abundant data on brain networks processing static social signals, such as pictures of faces, the neural systems supporting social perception in naturalistic conditions are still poorly understood. Here we delineated brain networks subserving social perception under naturalistic conditions in 19 healthy humans who watched, during 3-T functional magnetic resonance imaging (fMRI), a set of 137 short (approximately 16 s each, total 27 min) audiovisual movie clips depicting pre-selecte...

  5. Annual Research Review: Growth connectomics – the organization and reorganization of brain networks during normal and abnormal development

    OpenAIRE

    Vértes, Petra E.; Bullmore, Edward T

    2014-01-01

    Background We first give a brief introduction to graph theoretical analysis and its application to the study of brain network topology or connectomics. Within this framework, we review the existing empirical data on developmental changes in brain network organization across a range of experimental modalities (including structural and functional MRI, diffusion tensor imaging, magnetoencephalography and electroencephalography in humans). Synthesis We discuss preliminary evidence and current hyp...

  6. Functional connectivity of the rodent brain using optical imaging

    Science.gov (United States)

    Guevara Codina, Edgar

    The aim of this thesis is to apply functional connectivity in a variety of animal models, using several optical imaging modalities. Even at rest, the brain shows high metabolic activity: the correlation in slow spontaneous fluctuations identifies remotely connected areas of the brain; hence the term "functional connectivity". Ongoing changes in spontaneous activity may provide insight into the neural processing that takes most of the brain metabolic activity, and so may provide a vast source of disease related changes. Brain hemodynamics may be modified during disease and affect resting-state activity. The thesis aims to better understand these changes in functional connectivity due to disease, using functional optical imaging. The optical imaging techniques explored in the first two contributions of this thesis are Optical Imaging of Intrinsic Signals and Laser Speckle Contrast Imaging, together they can estimate the metabolic rate of oxygen consumption, that closely parallels neural activity. They both have adequate spatial and temporal resolution and are well adapted to image the convexity of the mouse cortex. In the last article, a depth-sensitive modality called photoacoustic tomography was used in the newborn rat. Optical coherence tomography and laminar optical tomography were also part of the array of imaging techniques developed and applied in other collaborations. The first article of this work shows the changes in functional connectivity in an acute murine model of epileptiform activity. Homologous correlations are both increased and decreased with a small dependence on seizure duration. These changes suggest a potential decoupling between the hemodynamic parameters in resting-state networks, underlining the importance to investigate epileptic networks with several independent hemodynamic measures. The second study examines a novel murine model of arterial stiffness: the unilateral calcification of the right carotid. Seed-based connectivity analysis

  7. Brain parcellation choice affects disease-related topology differences increasingly from global to local network levels.

    Science.gov (United States)

    Lord, Anton; Ehrlich, Stefan; Borchardt, Viola; Geisler, Daniel; Seidel, Maria; Huber, Stefanie; Murr, Julia; Walter, Martin

    2016-03-30

    Network-based analyses of deviant brain function have become extremely popular in psychiatric neuroimaging. Underpinning brain network analyses is the selection of appropriate regions of interest (ROIs). Although ROI selection is fundamental in network analysis, its impact on detecting disease effects remains unclear. We investigated the impact of parcellation choice when comparing results from different studies. We investigated the effects of anatomical (AAL) and literature-based (Dosenbach) parcellation schemes on comparability of group differences in 35 female patients with anorexia nervosa and 35 age- and sex-matched healthy controls. Global and local network properties, including network-based statistics (NBS), were assessed on resting state functional magnetic resonance imaging data obtained at 3T. Parcellation schemes were comparably consistent on global network properties, while NBS and local metrics differed in location, but not metric type. Location of local metric alterations varied for AAL (parietal and cingulate cortices) versus Dosenbach (insula, thalamus) parcellation approaches. However, consistency was observed for the occipital cortex. Patient-specific global network properties can be robustly observed using different parcellation schemes, while graph metrics characterizing impairments of individual nodes vary considerably. Therefore, the impact of parcellation choice on specific group differences varies depending on the level of network organization. PMID:27000302

  8. Visible rodent brain-wide networks at single-neuron resolution

    Directory of Open Access Journals (Sweden)

    Jing eYuan

    2015-05-01

    Full Text Available There are some unsolvable fundamental questions, such as cell type classification, neural circuit tracing and neurovascular coupling, though great progresses are being made in neuroscience. Because of the structural features of neurons and neural circuits, the solution of these questions needs us to break through the current technology of neuroanatomy for acquiring the exactly fine morphology of neuron and vessels and tracing long-distant circuit at axonal resolution in the whole brain of mammals. Combined with fast-developing labeling techniques, efficient whole-brain optical imaging technology emerging at the right moment presents a huge potential in the structure and function research of specific-function neuron and neural circuit. In this review, we summarize brain-wide optical tomography techniques, review the progress on visible brain neuronal/vascular networks benefit from these novel techniques, and prospect the future technical development.

  9. Brain microvascular function during cardiopulmonary bypass

    Energy Technology Data Exchange (ETDEWEB)

    Sorensen, H.R.; Husum, B.; Waaben, J.; Andersen, K.; Andersen, L.I.; Gefke, K.; Kaarsen, A.L.; Gjedde, A.

    1987-11-01

    Emboli in the brain microvasculature may inhibit brain activity during cardiopulmonary bypass. Such hypothetical blockade, if confirmed, may be responsible for the reduction of cerebral metabolic rate for glucose observed in animals subjected to cardiopulmonary bypass. In previous studies of cerebral blood flow during bypass, brain microcirculation was not evaluated. In the present study in animals (pigs), reduction of the number of perfused capillaries was estimated by measurements of the capillary diffusion capacity for hydrophilic tracers of low permeability. Capillary diffusion capacity, cerebral blood flow, and cerebral metabolic rate for glucose were measured simultaneously by the integral method, different tracers being used with different circulation times. In eight animals subjected to normothermic cardiopulmonary bypass, and seven subjected to hypothermic bypass, cerebral blood flow, cerebral metabolic rate for glucose, and capillary diffusion capacity decreased significantly: cerebral blood flow from 63 to 43 ml/100 gm/min in normothermia and to 34 ml/100 gm/min in hypothermia and cerebral metabolic rate for glucose from 43.0 to 23.0 mumol/100 gm/min in normothermia and to 14.1 mumol/100 gm/min in hypothermia. The capillary diffusion capacity declined markedly from 0.15 to 0.03 ml/100 gm/min in normothermia but only to 0.08 ml/100 gm/min in hypothermia. We conclude that the decrease of cerebral metabolic rate for glucose during normothermic cardiopulmonary bypass is caused by interruption of blood flow through a part of the capillary bed, possibly by microemboli, and that cerebral blood flow is an inadequate indicator of capillary blood flow. Further studies must clarify why normal microvascular function appears to be preserved during hypothermic cardiopulmonary bypass.

  10. Selectively disrupted functional connectivity networks in type 2 diabetes mellitus

    Directory of Open Access Journals (Sweden)

    Yaojing eChen

    2015-12-01

    Full Text Available Background: The high prevalence of type 2 diabetes mellitus (T2DM in individuals over 65 years old and cognitive deficits caused by T2DM have attracted broad attention. The pathophysiological mechanism of T2DM induced cognitive impairments, however, remains poorly understood. Previous studies have suggested that the cognitive impairments can be attributed not merely to local functional and structural abnormalities but also to specific brain networks. Thus, we aimed to investigate the changes of global networks selectively affected by T2DM. Methods: A resting state functional network analysis was conducted to investigate the intrinsic functional connectivity in 37 patients with diabetes and 40 healthy controls which were recruited from local communities in Beijing, China. Results: We found that patients with T2DM exhibited cognitive function declines and functional connectivity disruptions within the default mode network, left frontal parietal network, and sensorimotor network. More importantly, the fasting glucose level was correlated with abnormal functional connectivity.Conclusions: These findings could help to understand the neural mechanisms of cognitive impairments in T2DM and provide potential neuroimaging biomarkers that may be used for early diagnosis and intervention in cognitive decline.

  11. Different brain networks underlying the acquisition and expression of contextual fear conditioning: a metabolic mapping study.

    Science.gov (United States)

    González-Pardo, H; Conejo, N M; Lana, G; Arias, J L

    2012-01-27

    The specific brain regions and circuits involved in the acquisition and expression of contextual fear conditioning are still a matter of debate. To address this issue, regional changes in brain metabolic capacity were mapped during the acquisition and expression of contextual fear conditioning using cytochrome oxidase (CO) quantitative histochemistry. In comparison with a group briefly exposed to a conditioning chamber, rats that received a series of randomly presented footshocks in the same conditioning chamber (fear acquisition group) showed increased CO activity in anxiety-related brain regions like the ventral periaqueductal gray, the ventral hippocampus, the lateral habenula, the mammillary bodies, and the laterodorsal thalamic nucleus. Another group received randomly presented footshocks, and it was re-exposed to the same conditioning chamber one week later (fear expression group). The conditioned group had significantly higher CO activity as compared with the matched control group in the following brain regions: the ventral periaqueductal gray, the central and lateral nuclei of the amygdala, and the bed nucleus of the stria terminalis. In addition, analysis of functional brain networks using interregional CO activity correlations revealed different patterns of functional connectivity between fear acquisition and fear expression groups. In particular, a network comprising the ventral hippocampus and amygdala nuclei was found in the fear acquisition group, whereas a closed reciprocal dorsal hippocampal network was detected in the fear expression group. These results suggest that contextual fear acquisition and expression differ as regards to the brain networks involved, although they share common brain regions involved in fear, anxiety, and defensive behavior. PMID:22173014

  12. The modulation of brain functional connectivity with manual acupuncture in healthy subjects: An electroencephalograph case study

    International Nuclear Information System (INIS)

    Manual acupuncture is widely used for pain relief and stress control. Previous studies on acupuncture have shown its modulatory effects on the functional connectivity associated with one or a few preselected brain regions. To investigate how manual acupuncture modulates the organization of functional networks at a whole-brain level, we acupuncture at ST36 of a right leg to obtain electroencephalograph (EEG) signals. By coherence estimation, we determine the synchronizations between all pairwise combinations of EEG channels in three acupuncture states. The resulting synchronization matrices are converted into functional networks by applying a threshold, and the clustering coefficients and path lengths are computed as a function of threshold. The results show that acupuncture can increase functional connections and synchronizations between different brain areas. For a wide range of thresholds, the clustering coefficient during acupuncture and post-acupuncture period is higher than that during the pre-acupuncture control period, whereas the characteristic path length is shorter. We provide further support for the presence of “small-world” network characteristics in functional networks by using acupuncture. These preliminary results highlight the beneficial modulations of functional connectivity by manual acupuncture, which could contribute to the understanding of the effects of acupuncture on the entire brain, as well as the neurophysiological mechanisms underlying acupuncture. Moreover, the proposed method may be a useful approach to the further investigation of the complexity of patterns of interrelations between EEG channels. (interdisciplinary physics and related areas of science and technology)

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

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

    2016-07-01

    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