Complex Brain Network Analysis and Its Applications to Brain Disorders: A Survey

It is well known that most brain disorders are complex diseases, such as Alzheimer’s disease (AD) and schizophrenia (SCZ). In general, brain regions and their interactions can be modeled as complex brain network, which describe highly efficient information transmission in a brain. Therefore, complex brain network analysis plays an important role in the study of complex brain diseases. With the development of noninvasive neuroimaging and electrophysiological techniques, experimental data can be produced for constructing complex brain networks. In recent years, researchers have found that brain networks constructed by using neuroimaging data and electrophysiological data have many important topological properties, such as small-world property, modularity, and rich club. More importantly, many brain disorders have been found to be associated with the abnormal topological structures of brain networks. These findings provide not only a new perspective to explore the pathological mechanisms of brain disorders, but also guidance for early diagnosis and treatment of brain disorders. The purpose of this survey is to provide a comprehensive overview for complex brain network analysis and its applications to brain disorders.

[1]  Alessandro Vespignani,et al.  Detecting rich-club ordering in complex networks , 2006, physics/0602134.

[2]  Marisa O. Hollinshead,et al.  The organization of the human cerebral cortex estimated by intrinsic functional connectivity. , 2011, Journal of neurophysiology.

[3]  D. Tuch Q‐ball imaging , 2004, Magnetic resonance in medicine.

[4]  Edward T. Bullmore,et al.  Whole-brain anatomical networks: Does the choice of nodes matter? , 2010, NeuroImage.

[5]  Habib Benali,et al.  Relating Structure and Function in the Human Brain: Relative Contributions of Anatomy, Stationary Dynamics, and Non-stationarities , 2014, PLoS Comput. Biol..

[6]  Yong He,et al.  Graph-based network analysis of resting-state functional MRI. , 2010 .

[7]  Brittany N. Dugger,et al.  Graph theory network function in Parkinson’s disease assessed with electroencephalography , 2016, Clinical Neurophysiology.

[8]  Ernesto Pereda,et al.  The variability of EEG functional connectivity of young ADHD subjects in different resting states , 2016, Clinical Neurophysiology.

[9]  Olaf Sporns,et al.  From simple graphs to the connectome: Networks in neuroimaging , 2012, NeuroImage.

[10]  M. V. D. Heuvel,et al.  Brain Networks in Schizophrenia , 2014, Neuropsychology Review.

[11]  P. Basser,et al.  In vivo fiber tractography using DT‐MRI data , 2000, Magnetic resonance in medicine.

[12]  N. Logothetis What we can do and what we cannot do with fMRI , 2008, Nature.

[13]  R Cameron Craddock,et al.  A whole brain fMRI atlas generated via spatially constrained spectral clustering , 2012, Human brain mapping.

[14]  M. Bellgrove,et al.  Altered structural connectivity in ADHD: a network based analysis , 2016, Brain Imaging and Behavior.

[15]  P. V. van Zijl,et al.  Three‐dimensional tracking of axonal projections in the brain by magnetic resonance imaging , 1999, Annals of neurology.

[16]  Yu Zhang,et al.  The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture , 2016, Cerebral cortex.

[17]  O. Sporns,et al.  Rich-Club Organization of the Human Connectome , 2011, The Journal of Neuroscience.

[18]  Cornelis J. Stam,et al.  Declining functional connectivity and changing hub locations in Alzheimer’s disease: an EEG study , 2015, BMC Neurology.

[19]  Yi Pan,et al.  Protein-protein interactions: detection, reliability assessment and applications , 2016, Briefings Bioinform..

[20]  Yong He,et al.  Probabilistic Diffusion Tractography and Graph Theory Analysis Reveal Abnormal White Matter Structural Connectivity Networks in Drug-Naive Boys with Attention Deficit/Hyperactivity Disorder , 2013, The Journal of Neuroscience.

[21]  J. Anthonisse The rush in a directed graph , 1971 .

[22]  Alexander Leemans,et al.  Disruption of cerebral networks and cognitive impairment in Alzheimer disease , 2013, Neurology.

[23]  Timothy E. J. Behrens,et al.  Human connectomics , 2012, Current Opinion in Neurobiology.

[24]  E. Bullmore,et al.  Behavioral / Systems / Cognitive Functional Connectivity and Brain Networks in Schizophrenia , 2010 .

[25]  Karl J. Friston,et al.  Structural and Functional Brain Networks: From Connections to Cognition , 2013, Science.

[26]  Alex Arenas,et al.  Mapping Multiplex Hubs in Human Functional Brain Networks , 2016, Front. Neurosci..

[27]  Kwang-Hyun Cho,et al.  Small-world networks in individuals at ultra-high risk for psychosis and first-episode schizophrenia during a working memory task , 2013, Neuroscience Letters.

[28]  E. Bullmore,et al.  Hierarchical Organization of Human Cortical Networks in Health and Schizophrenia , 2008, The Journal of Neuroscience.

[29]  K. Worsley,et al.  Impaired small-world efficiency in structural cortical networks in multiple sclerosis associated with white matter lesion load. , 2009, Brain : a journal of neurology.

[30]  A. Anwander,et al.  Connectivity-Based Parcellation of Broca's Area. , 2006, Cerebral cortex.

[31]  M. A. Beauchamp AN IMPROVED INDEX OF CENTRALITY. , 1965, Behavioral science.

[32]  Olaf Sporns,et al.  Complex network measures of brain connectivity: Uses and interpretations , 2010, NeuroImage.

[33]  Arijitt Borthakur,et al.  Gender-based analysis of cortical thickness and structural connectivity in Parkinson’s disease , 2016, Journal of Neurology.

[34]  Klaas E. Stephan,et al.  The anatomical basis of functional localization in the cortex , 2002, Nature Reviews Neuroscience.

[35]  Sara Llufriu,et al.  Structural networks involved in attention and executive functions in multiple sclerosis , 2016, NeuroImage: Clinical.

[36]  Yong He,et al.  Diffusion Tensor Tractography Reveals Abnormal Topological Organization in Structural Cortical Networks in Alzheimer's Disease , 2010, The Journal of Neuroscience.

[37]  C. T. Butts,et al.  Revisiting the Foundations of Network Analysis , 2009, Science.

[38]  O. Sporns,et al.  Complex brain networks: graph theoretical analysis of structural and functional systems , 2009, Nature Reviews Neuroscience.

[39]  Jonathan D. Power,et al.  Prediction of Individual Brain Maturity Using fMRI , 2010, Science.

[40]  Chris Rorden,et al.  Individual variability in the anatomical distribution of nodes participating in rich club structural networks , 2015, Front. Neural Circuits.

[41]  Anastasios Bezerianos,et al.  Reduced Hemispheric Asymmetry of Brain Anatomical Networks Is Linked to Schizophrenia: A Connectome Study , 2015, Cerebral cortex.

[42]  Arthur W. Toga,et al.  Construction of a 3D probabilistic atlas of human cortical structures , 2008, NeuroImage.

[43]  Jonathan D. Power,et al.  The Development of Human Functional Brain Networks , 2010, Neuron.

[44]  Gustavo Deco,et al.  Rich club organization supports a diverse set of functional network configurations , 2014, NeuroImage.

[45]  Essa Yacoub,et al.  The WU-Minn Human Connectome Project: An overview , 2013, NeuroImage.

[46]  Anastasios Bezerianos,et al.  Disruption of brain anatomical networks in schizophrenia: A longitudinal, diffusion tensor imaging based study , 2016, Schizophrenia Research.

[47]  Olaf Sporns,et al.  The Human Connectome: A Structural Description of the Human Brain , 2005, PLoS Comput. Biol..

[48]  Yong He,et al.  Functional connectomics from a “big data” perspective , 2017, NeuroImage.

[49]  Defeng Wang,et al.  Altered topological organization of high-level visual networks in Alzheimer’s disease and mild cognitive impairment patients , 2016, Neuroscience Letters.

[50]  Boris C. Bernhardt,et al.  Network analysis for a network disorder: The emerging role of graph theory in the study of epilepsy , 2015, Epilepsy & Behavior.

[51]  Michael Breakspear,et al.  Graph analysis of the human connectome: Promise, progress, and pitfalls , 2013, NeuroImage.

[52]  C. Stam,et al.  Disruption of structural and functional networks in long‐standing multiple sclerosis , 2014, Human brain mapping.

[53]  J. Hogg Magnetic resonance imaging. , 1994, Journal of the Royal Naval Medical Service.

[54]  Jong H. Yoon,et al.  General and Specific Functional Connectivity Disturbances in First-Episode Schizophrenia During Cognitive Control Performance , 2011, Biological Psychiatry.

[55]  Vito Latora,et al.  Multilayer motif analysis of brain networks. , 2016, Chaos.

[56]  He Li,et al.  Disrupted topological organization in white matter structural networks in amnestic mild cognitive impairment: relationship to subtype. , 2012, Radiology.

[57]  S. Bookheimer,et al.  Neural Signatures of Autism Spectrum Disorders: Insights into Brain Network Dynamics , 2015, Neuropsychopharmacology.

[58]  René S. Kahn,et al.  Impaired Rich Club Connectivity in Unaffected Siblings of Schizophrenia Patients , 2013, Schizophrenia bulletin.

[59]  Jonah Lehrer,et al.  Neuroscience: Making connections , 2009, Nature.

[60]  Jin Liu,et al.  Applications of deep learning to MRI images: A survey , 2018, Big Data Min. Anal..

[61]  A. Fagan,et al.  Functional connectivity and graph theory in preclinical Alzheimer's disease , 2014, Neurobiology of Aging.

[62]  Clifford R Jack,et al.  Rich club analysis in the Alzheimer's disease connectome reveals a relatively undisturbed structural core network , 2015, Human brain mapping.

[63]  Alan C. Evans,et al.  Structural Insights into Aberrant Topological Patterns of Large-Scale Cortical Networks in Alzheimer's Disease , 2008, The Journal of Neuroscience.

[64]  J. A. Almendral,et al.  Reorganization of Functional Networks in Mild Cognitive Impairment , 2011, PloS one.

[65]  R. Petersen Mild cognitive impairment as a diagnostic entity , 2004, Journal of internal medicine.

[66]  P. Hagmann,et al.  Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging , 2005, Magnetic resonance in medicine.

[67]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[68]  Edward T. Bullmore,et al.  Efficiency and Cost of Economical Brain Functional Networks , 2007, PLoS Comput. Biol..

[69]  S. Herculano‐Houzel The Human Brain in Numbers: A Linearly Scaled-up Primate Brain , 2009, Front. Hum. Neurosci..

[70]  Daniel L. Rubin,et al.  Network Analysis of Intrinsic Functional Brain Connectivity in Alzheimer's Disease , 2008, PLoS Comput. Biol..

[71]  S. Mori,et al.  Principles of Diffusion Tensor Imaging and Its Applications to Basic Neuroscience Research , 2006, Neuron.

[72]  Cornelis J. Stam,et al.  Brain Network Organization in Focal Epilepsy: A Systematic Review and Meta-Analysis , 2014, PloS one.

[73]  Jesse A. Brown,et al.  Altered functional and structural brain network organization in autism☆ , 2012, NeuroImage: Clinical.

[74]  Mark W. Woolrich,et al.  Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? , 2007, NeuroImage.

[75]  M. Filippi,et al.  Impaired functional integration in multiple sclerosis: a graph theory study , 2014, Brain Structure and Function.

[76]  Leonard M. Freeman,et al.  A set of measures of centrality based upon betweenness , 1977 .

[77]  Olaf Sporns,et al.  THE HUMAN CONNECTOME: A COMPLEX NETWORK , 2011, Schizophrenia Research.

[78]  Nikos Makris,et al.  Understanding Alterations in Brain Connectivity in Attention-Deficit/Hyperactivity Disorder Using Imaging Connectomics , 2014, Biological Psychiatry.

[79]  Shi Zhou,et al.  The rich-club phenomenon in the Internet topology , 2003, IEEE Communications Letters.

[80]  Dinggang Shen,et al.  Multilevel Deficiency of White Matter Connectivity Networks in Alzheimer's Disease: A Diffusion MRI Study with DTI and HARDI Models , 2016, Neural plasticity.

[81]  L. da F. Costa,et al.  Characterization of complex networks: A survey of measurements , 2005, cond-mat/0505185.

[82]  C. Stam,et al.  Functional connectivity changes in multiple sclerosis patients: A graph analytical study of MEG resting state data , 2013, Human brain mapping.

[83]  Timothy O. Laumann,et al.  Functional Network Organization of the Human Brain , 2011, Neuron.

[84]  Ching-Po Lin,et al.  Schizophrenia symptoms and brain network efficiency: A resting-state fMRI study , 2015, Psychiatry Research: Neuroimaging.

[85]  M. Raichle,et al.  Tracking neuronal fiber pathways in the living human brain. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[86]  Karl J. Friston Functional and Effective Connectivity: A Review , 2011, Brain Connect..

[87]  E. Bullmore,et al.  The hubs of the human connectome are generally implicated in the anatomy of brain disorders , 2014, Brain : a journal of neurology.

[88]  O. Sporns,et al.  Organization, development and function of complex brain networks , 2004, Trends in Cognitive Sciences.

[89]  R. Ilmoniemi,et al.  Magnetoencephalography-theory, instrumentation, and applications to noninvasive studies of the working human brain , 1993 .

[90]  Olaf Sporns,et al.  MR connectomics: Principles and challenges , 2010, Journal of Neuroscience Methods.

[91]  Joseph A. Maldjian,et al.  Graph theoretical analysis of resting-state MEG data: Identifying interhemispheric connectivity and the default mode , 2014, NeuroImage.

[92]  Jesper Andersson,et al.  A multi-modal parcellation of human cerebral cortex , 2016, Nature.

[93]  P. Rossini,et al.  Cortical connectivity and memory performance in cognitive decline: A study via graph theory from EEG data , 2016, Neuroscience.

[94]  W. M. van der Flier,et al.  Functional neural network analysis in frontotemporal dementia and Alzheimer's disease using EEG and graph theory , 2009, BMC Neuroscience.

[95]  P. Skudlarski,et al.  Brain Connectivity Is Not Only Lower but Different in Schizophrenia: A Combined Anatomical and Functional Approach , 2010, Biological Psychiatry.

[96]  Lawrence Ver Hoef,et al.  Change in brain network topology as a function of treatment response in schizophrenia: a longitudinal resting-state fMRI study using graph theory , 2016, npj Schizophrenia.

[97]  Clement Hamani,et al.  Disrupted Nodal and Hub Organization Account for Brain Network Abnormalities in Parkinson’s Disease , 2016, Front. Aging Neurosci..

[98]  T. Münte,et al.  Altered Resting State Brain Networks in Parkinson’s Disease , 2013, PloS one.

[99]  Michael Breakspear,et al.  Whole-brain analytic measures of network communication reveal increased structure-function correlation in right temporal lobe epilepsy , 2016, NeuroImage: Clinical.

[100]  N. Tzourio-Mazoyer,et al.  Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain , 2002, NeuroImage.

[101]  Patrick T. Hickey,et al.  Neuroimaging of Parkinson's disease: Expanding views , 2015, Neuroscience & Biobehavioral Reviews.

[102]  Miseon Shim,et al.  Disruptions in small-world cortical functional connectivity network during an auditory oddball paradigm task in patients with schizophrenia , 2014, Schizophrenia Research.

[103]  E. Bullmore,et al.  Disrupted Axonal Fiber Connectivity in Schizophrenia , 2011, Biological Psychiatry.

[104]  Kuncheng Li,et al.  Functional Brain Network Alterations in Clinically Isolated Syndrome and Multiple Sclerosis: A Graph-based Connectome Study. , 2017, Radiology.

[105]  Giovanni Volpe,et al.  Aberrant cerebral network topology and mild cognitive impairment in early Parkinson's disease , 2015, Human brain mapping.

[106]  E. John,et al.  Electroencephalography: Basic Principles and Applications , 2001 .

[107]  Hamid Soltanian-Zadeh,et al.  Measures of the brain functional network that correlate with Alzheimer's neuropsychological test scores: An fMRI and graph analysis study. , 2016, Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference.

[108]  M E J Newman,et al.  Finding and evaluating community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[109]  N. Toschi,et al.  Structural ‘connectomic’ alterations in the limbic system of multiple sclerosis patients with major depression , 2015, Multiple sclerosis.

[110]  L. Passamonti,et al.  Characterizing structural neural networks in de novo Parkinson disease patients using diffusion tensor imaging , 2016, Human brain mapping.

[111]  Yi Pan,et al.  Improving Alzheimer's Disease Classification by Combining Multiple Measures , 2018, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[112]  Bin Hu,et al.  Alzheimer’s Disease Classification Based on Individual Hierarchical Networks Constructed With 3-D Texture Features , 2017, IEEE Transactions on NanoBioscience.

[113]  Dinggang Shen,et al.  Altered Structural Connectivity in Neonates at Genetic Risk for Schizophrenia: a Combined Study Using Morphological and White Matter Networks , 2022 .

[114]  Fang-Xiang Wu,et al.  Double-layer clustering method to predict protein complexes based on power-law distribution and protein sublocalization. , 2016, Journal of theoretical biology.

[115]  Yong He,et al.  Topologically Convergent and Divergent Structural Connectivity Patterns between Patients with Remitted Geriatric Depression and Amnestic Mild Cognitive Impairment , 2012, The Journal of Neuroscience.

[116]  Guido Gerig,et al.  The Emergence of Network Inefficiencies in Infants With Autism Spectrum Disorder , 2017, Biological Psychiatry.

[117]  Arjan Hillebrand,et al.  Disrupted brain network topology in Parkinson's disease: a longitudinal magnetoencephalography study. , 2014, Brain : a journal of neurology.

[118]  Jinhui Wang,et al.  Aberrant Brain Network Efficiency in Parkinson’s Disease Patients with Tremor: A Multi-Modality Study , 2015, Front. Aging Neurosci..

[119]  David K. Yu,et al.  Superficial white matter fiber systems impede detection of long-range cortical connections in diffusion MR tractography , 2015, Proceedings of the National Academy of Sciences.

[120]  Cornelis J. Stam,et al.  Structure out of chaos: Functional brain network analysis with EEG, MEG, and functional MRI , 2013, European Neuropsychopharmacology.

[121]  Ruiwang Huang,et al.  Impaired topological architecture of brain structural networks in idiopathic Parkinson’s disease: a DTI study , 2017, Brain Imaging and Behavior.

[122]  Alfred Anwander,et al.  A hierarchical method for whole‐brain connectivity‐based parcellation , 2014, Human brain mapping.

[123]  Jianxin Wang,et al.  Effective identification of essential proteins based on priori knowledge, network topology and gene expressions. , 2014, Methods.

[124]  V Latora,et al.  Efficient behavior of small-world networks. , 2001, Physical review letters.

[125]  Andrew Zalesky,et al.  Large-Scale Brain Network Dynamics Supporting Adolescent Cognitive Control , 2014, The Journal of Neuroscience.

[126]  Edward T. Bullmore,et al.  Connectivity differences in brain networks , 2012, NeuroImage.

[127]  C. Stam,et al.  Alzheimer's disease: connecting findings from graph theoretical studies of brain networks , 2013, Neurobiology of Aging.

[128]  A. Willis Parkinson disease in the elderly adult. , 2013, Missouri medicine.

[129]  Yi Pan,et al.  Classification of Alzheimer's Disease Using Whole Brain Hierarchical Network. , 2016, IEEE/ACM transactions on computational biology and bioinformatics.

[130]  Nancy Y. Ip,et al.  China Brain Project: Basic Neuroscience, Brain Diseases, and Brain-Inspired Computing , 2016, Neuron.

[131]  Piet Van Mieghem,et al.  Disruption of Functional Brain Networks in Alzheimer's Disease: What Can We Learn from Graph Spectral Analysis of Resting-State Magnetoencephalography? , 2012, Brain Connect..

[132]  O. Sporns,et al.  Identification and Classification of Hubs in Brain Networks , 2007, PloS one.

[133]  A. Zalesky,et al.  Functional brain networks in treatment-resistant schizophrenia , 2017, Schizophrenia Research.

[134]  Anders M. Dale,et al.  An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest , 2006, NeuroImage.

[135]  Yong He,et al.  Diffusion tensor tractography reveals disrupted topological efficiency in white matter structural networks in multiple sclerosis. , 2011, Cerebral cortex.

[136]  Panos M. Pardalos,et al.  Connectivity brain networks based on wavelet correlation analysis in Parkinson fMRI data , 2011, Neuroscience Letters.

[137]  O. Sporns,et al.  High-cost, high-capacity backbone for global brain communication , 2012, Proceedings of the National Academy of Sciences.

[138]  Frederico A. C. Azevedo,et al.  Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled‐up primate brain , 2009, The Journal of comparative neurology.

[139]  Eve C. Johnstone,et al.  Grey matter networks in people at increased familial risk for schizophrenia , 2015, Schizophrenia Research.

[140]  Xiaodong Yan,et al.  Framework to Identify Protein Complexes Based on Similarity Preclustering , 2017 .

[141]  Anders M. Dale,et al.  Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature , 2010, NeuroImage.

[142]  K. Brodmann Vergleichende Lokalisationslehre der Großhirnrinde : in ihren Prinzipien dargestellt auf Grund des Zellenbaues , 1985 .

[143]  T. Prescott,et al.  The brainstem reticular formation is a small-world, not scale-free, network , 2006, Proceedings of the Royal Society B: Biological Sciences.

[144]  U. Ziemann,et al.  Working memory performance of early MS patients correlates inversely with modularity increases in resting state functional connectivity networks , 2014, NeuroImage.

[145]  W. M. van der Flier,et al.  Single-Subject Grey Matter Graphs in Alzheimer's Disease , 2013, PloS one.

[146]  H. Pollard,et al.  Network science and the human brain: Using graph theory to understand the brain and one of its hubs, the amygdala, in health and disease , 2016, Journal of neuroscience research.

[147]  O. Sporns,et al.  Network neuroscience , 2017, Nature Neuroscience.

[148]  Jun Li,et al.  Functional brain network analysis of schizophrenic patients with positive and negative syndrome based on mutual information of EEG time series , 2017, Biomed. Signal Process. Control..

[149]  O. Sporns,et al.  Network hubs in the human brain , 2013, Trends in Cognitive Sciences.

[150]  Yong He,et al.  Disrupted Functional Brain Connectome in Individuals at Risk for Alzheimer's Disease , 2013, Biological Psychiatry.

[151]  Danielle S Bassett,et al.  Brain graphs: graphical models of the human brain connectome. , 2011, Annual review of clinical psychology.

[152]  Vivek Prabhakaran,et al.  Graph theory and cognition: A complementary avenue for examining neuropsychological status in epilepsy , 2016, Epilepsy & Behavior.

[153]  Yuan Zhou,et al.  Abnormal Cortical Networks in Mild Cognitive Impairment and Alzheimer's Disease , 2010, PLoS Comput. Biol..

[154]  Liu Jin,et al.  A survey of MRI-based brain tumor segmentation methods , 2014 .

[155]  Edward T. Bullmore,et al.  Schizophrenia, neuroimaging and connectomics , 2012, NeuroImage.

[156]  Qin Chen,et al.  Functional connectome assessed using graph theory in drug-naive Parkinson’s disease , 2015, Journal of Neurology.

[157]  V. Wedeen,et al.  Diffusion MRI of Complex Neural Architecture , 2003, Neuron.

[158]  Yi Pan,et al.  Classification of Schizophrenia Based on Individual Hierarchical Brain Networks Constructed From Structural MRI Images , 2017, IEEE Transactions on NanoBioscience.

[159]  Cornelis J. Stam,et al.  Small-world and scale-free organization of voxel-based resting-state functional connectivity in the human brain , 2008, NeuroImage.

[160]  Heidi Johansen-Berg,et al.  Tractography: Where Do We Go from Here? , 2011, Brain Connect..

[161]  A. Wheeler,et al.  A review of structural neuroimaging in schizophrenia: from connectivity to connectomics , 2014, Front. Hum. Neurosci..

[162]  Meng Li,et al.  Disrupted brain anatomical connectivity in medication-naïve patients with first-episode schizophrenia , 2015, Brain Structure and Function.

[163]  A. Simmons,et al.  Disrupted Network Topology in Patients with Stable and Progressive Mild Cognitive Impairment and Alzheimer's Disease , 2016, Cerebral cortex.

[164]  T. Su,et al.  Abnormal topological organization of structural brain networks in schizophrenia , 2012, Schizophrenia Research.

[165]  E. Bullmore,et al.  Imaging structural co-variance between human brain regions , 2013, Nature Reviews Neuroscience.

[166]  Jacques-Donald Tournier,et al.  Diffusion tensor imaging and beyond , 2011, Magnetic resonance in medicine.

[167]  Paul J. Laurienti,et al.  An exploration of graph metric reproducibility in complex brain networks , 2013, Front. Neurosci..

[168]  Xenophon Papademetris,et al.  Groupwise whole-brain parcellation from resting-state fMRI data for network node identification , 2013, NeuroImage.

[169]  Nikos Makris,et al.  Automatically parcellating the human cerebral cortex. , 2004, Cerebral cortex.

[170]  B. W. van Dijk,et al.  Opportunities and methodological challenges in EEG and MEG resting state functional brain network research , 2015, Clinical Neurophysiology.

[171]  Yunyun Duan,et al.  Disrupted topological organization of structural and functional brain connectomes in clinically isolated syndrome and multiple sclerosis , 2016, Scientific Reports.

[172]  V. Latora,et al.  Complex networks: Structure and dynamics , 2006 .

[173]  Olaf Sporns,et al.  The human connectome: Origins and challenges , 2013, NeuroImage.