Connectomic Insights into Topologically Centralized Network Edges and Relevant Motifs in the Human Brain

White matter (WM) tracts serve as important material substrates for information transfer across brain regions. However, the topological roles of WM tracts in global brain communications and their underlying microstructural basis remain poorly understood. Here, we employed diffusion magnetic resonance imaging and graph-theoretical approaches to identify the pivotal WM connections in human whole-brain networks and further investigated their wiring substrates (including WM microstructural organization and physical consumption) and topological contributions to the brain's network backbone. We found that the pivotal WM connections with highly topological-edge centrality were primarily distributed in several long-range cortico-cortical connections (including the corpus callosum, cingulum and inferior fronto-occipital fasciculus) and some projection tracts linking subcortical regions. These pivotal WM connections exhibited high levels of microstructural organization indicated by diffusion measures (the fractional anisotropy, the mean diffusivity and the axial diffusivity) and greater physical consumption indicated by streamline lengths, and contributed significantly to the brain's hubs and the rich-club structure. Network motif analysis further revealed their heavy participations in the organization of communication blocks, especially in routes involving inter-hemispheric heterotopic and extremely remote intra-hemispheric systems. Computational simulation models indicated the sharp decrease of global network integrity when attacking these highly centralized edges. Together, our results demonstrated high building-cost consumption and substantial communication capacity contributions for pivotal WM connections, which deepens our understanding of the topological mechanisms that govern the organization of human connectomes.

[1]  Thomas R. Knösche,et al.  White matter integrity, fiber count, and other fallacies: The do's and don'ts of diffusion MRI , 2013, NeuroImage.

[2]  B. Knowlton,et al.  Learning and memory functions of the Basal Ganglia. , 2002, Annual review of neuroscience.

[3]  M. Greicius,et al.  Resting-state functional connectivity reflects structural connectivity in the default mode network. , 2009, Cerebral cortex.

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

[5]  Kevin Zhou Navigation in a small world , 2017 .

[6]  M. Weiner,et al.  A Network Diffusion Model of Disease Progression in Dementia , 2012, Neuron.

[7]  E. Maguire,et al.  The Human Hippocampus and Spatial and Episodic Memory , 2002, Neuron.

[8]  P. Basser,et al.  Axcaliber: A method for measuring axon diameter distribution from diffusion MRI , 2008, Magnetic resonance in medicine.

[9]  B. Pansky,et al.  Review of Neuroscience , 1980 .

[10]  O. Sporns,et al.  Structural and Functional Aspects Relating to Cost and Benefit of Rich Club Organization in the Human Cerebral Cortex , 2013, Cerebral cortex.

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

[12]  G. B. Pike,et al.  Quantitative imaging of magnetization transfer exchange and relaxation properties in vivo using MRI , 2001, Magnetic resonance in medicine.

[13]  Daniel C Alexander,et al.  Optimal acquisition schemes for in vivo quantitative magnetization transfer MRI , 2006, Magnetic resonance in medicine.

[14]  C. Beaulieu,et al.  The basis of anisotropic water diffusion in the nervous system – a technical review , 2002, NMR in biomedicine.

[15]  Yong He,et al.  A connectivity-based test-retest dataset of multi-modal magnetic resonance imaging in young healthy adults , 2015, Scientific Data.

[16]  Alan C. Evans,et al.  Uncovering Intrinsic Modular Organization of Spontaneous Brain Activity in Humans , 2009, PloS one.

[17]  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.

[18]  O Sporns,et al.  Predicting human resting-state functional connectivity from structural connectivity , 2009, Proceedings of the National Academy of Sciences.

[19]  Marcel A de Reus,et al.  An edge-centric perspective on the human connectome: link communities in the brain , 2014, Philosophical Transactions of the Royal Society B: Biological Sciences.

[20]  Keith A. Johnson,et al.  Cortical Hubs Revealed by Intrinsic Functional Connectivity: Mapping, Assessment of Stability, and Relation to Alzheimer's Disease , 2009, The Journal of Neuroscience.

[21]  Peter Andras,et al.  Simulation of robustness against lesions of cortical networks , 2007, The European journal of neuroscience.

[22]  M. Gazzaniga Cerebral specialization and interhemispheric communication: does the corpus callosum enable the human condition? , 2000, Brain : a journal of neurology.

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

[24]  Ravi S. Menon,et al.  Identification of Optimal Structural Connectivity Using Functional Connectivity and Neural Modeling , 2014, The Journal of Neuroscience.

[25]  Andrei G. Vlassenko,et al.  Regional aerobic glycolysis in the human brain , 2010, Proceedings of the National Academy of Sciences.

[26]  Tim B. Dyrby,et al.  Orientationally invariant indices of axon diameter and density from diffusion MRI , 2010, NeuroImage.

[27]  Jeremy D. Schmahmann,et al.  Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers , 2008, NeuroImage.

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

[29]  Hao Yan,et al.  [Diffusion spectrum magnetic resonance imaging]. , 2009, Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences.

[30]  P. Basser,et al.  New modeling and experimental framework to characterize hindered and restricted water diffusion in brain white matter , 2004, Magnetic resonance in medicine.

[31]  O. Sporns,et al.  Rich Club Organization of Macaque Cerebral Cortex and Its Role in Network Communication , 2012, PloS one.

[32]  J. Rapoport,et al.  The anatomical distance of functional connections predicts brain network topology in health and schizophrenia. , 2013, Cerebral cortex.

[33]  T. SHALLICE,et al.  Learning and Memory , 1970, Nature.

[34]  Yaniv Assaf,et al.  Composite hindered and restricted model of diffusion (CHARMED) MR imaging of the human brain , 2005, NeuroImage.

[35]  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.

[36]  B. S. Anami,et al.  Identification and Classification of Normal and Affected Agriculture/horticulture Produce Based on Combined Color and Texture Feature Extraction , 2011 .

[37]  Marián Boguñá,et al.  Navigability of Complex Networks , 2007, ArXiv.

[38]  John Russell,et al.  Dysmyelination Revealed through MRI as Increased Radial (but Unchanged Axial) Diffusion of Water , 2002, NeuroImage.

[39]  M. P. van den Heuvel,et al.  Rich Club Organization and Intermodule Communication in the Cat Connectome , 2013, The Journal of Neuroscience.

[40]  S. Shen-Orr,et al.  Network motifs: simple building blocks of complex networks. , 2002, Science.

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

[42]  P. Basser Inferring microstructural features and the physiological state of tissues from diffusion‐weighted images , 1995, NMR in biomedicine.

[43]  J. Matias Palva,et al.  Infra-Slow EEG Fluctuations Are Correlated with Resting-State Network Dynamics in fMRI , 2014, The Journal of Neuroscience.

[44]  Meir Shinitzky,et al.  Structural and functional aspects , 1994 .

[45]  Yong He,et al.  GRETNA: a graph theoretical network analysis toolbox for imaging connectomics , 2015, Front. Hum. Neurosci..

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

[47]  Julia P. Owen,et al.  Edge density imaging: Mapping the anatomic embedding of the structural connectome within the white matter of the human brain , 2015, NeuroImage.

[48]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[49]  Yong He,et al.  Coupling of functional connectivity and regional cerebral blood flow reveals a physiological basis for network hubs of the human brain , 2013, Proceedings of the National Academy of Sciences.

[50]  Martijn P. van den Heuvel,et al.  Estimating false positives and negatives in brain networks , 2013, NeuroImage.

[51]  Jun Kunimatsu,et al.  Roles of the Primate Motor Thalamus in the Generation of Antisaccades , 2010, The Journal of Neuroscience.

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

[53]  Leonardo L. Gollo,et al.  Time-resolved resting-state brain networks , 2014, Proceedings of the National Academy of Sciences.

[54]  C. Honey,et al.  Identification and Classification of Hubs in Brain , 2007 .

[55]  Terrence J Sejnowski,et al.  Communication in Neuronal Networks , 2003, Science.

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

[57]  H. Duvernoy The Human Hippocampus , 1988, J.F. Bergmann-Verlag.

[58]  Emma K. Towlson,et al.  The Rich Club of the C. elegans Neuronal Connectome , 2013, The Journal of Neuroscience.

[59]  B. Biswal Resting-State Functional Connectivity , 2015 .

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

[61]  O. Sporns,et al.  The economy of brain network organization , 2012, Nature Reviews Neuroscience.

[62]  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.

[63]  J. Rapoport,et al.  Simple models of human brain functional networks , 2012, Proceedings of the National Academy of Sciences.

[64]  Yong He,et al.  BrainNet Viewer: A Network Visualization Tool for Human Brain Connectomics , 2013, PloS one.

[65]  Olaf Sporns,et al.  What Is the Human Connectome , 2009 .

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

[67]  Alan C. Evans,et al.  Mapping anatomical connectivity patterns of human cerebral cortex using in vivo diffusion tensor imaging tractography. , 2009, Cerebral cortex.

[68]  Derek K. Jones,et al.  Cingulum Microstructure Predicts Cognitive Control in Older Age and Mild Cognitive Impairment , 2012, The Journal of Neuroscience.

[69]  O. Sporns,et al.  Mapping the Structural Core of Human Cerebral Cortex , 2008, PLoS biology.

[70]  N. Volkow,et al.  Energetic cost of brain functional connectivity , 2013, Proceedings of the National Academy of Sciences.

[71]  Marcus Kaiser,et al.  Nonoptimal Component Placement, but Short Processing Paths, due to Long-Distance Projections in Neural Systems , 2006, PLoS Comput. Biol..

[72]  S. Strogatz Exploring complex networks , 2001, Nature.

[73]  David D. Jensen,et al.  Navigating networks by using homophily and degree , 2008, Proceedings of the National Academy of Sciences.