Relating Structure and Function in the Human Brain: Relative Contributions of Anatomy, Stationary Dynamics, and Non-stationarities

Investigating the relationship between brain structure and function is a central endeavor for neuroscience research. Yet, the mechanisms shaping this relationship largely remain to be elucidated and are highly debated. In particular, the existence and relative contributions of anatomical constraints and dynamical physiological mechanisms of different types remain to be established. We addressed this issue by systematically comparing functional connectivity (FC) from resting-state functional magnetic resonance imaging data with simulations from increasingly complex computational models, and by manipulating anatomical connectivity obtained from fiber tractography based on diffusion-weighted imaging. We hypothesized that FC reflects the interplay of at least three types of components: (i) a backbone of anatomical connectivity, (ii) a stationary dynamical regime directly driven by the underlying anatomy, and (iii) other stationary and non-stationary dynamics not directly related to the anatomy. We showed that anatomical connectivity alone accounts for up to 15% of FC variance; that there is a stationary regime accounting for up to an additional 20% of variance and that this regime can be associated to a stationary FC; that a simple stationary model of FC better explains FC than more complex models; and that there is a large remaining variance (around 65%), which must contain the non-stationarities of FC evidenced in the literature. We also show that homotopic connections across cerebral hemispheres, which are typically improperly estimated, play a strong role in shaping all aspects of FC, notably indirect connections and the topographic organization of brain networks.

[1]  G. Deco,et al.  Ongoing Cortical Activity at Rest: Criticality, Multistability, and Ghost Attractors , 2012, The Journal of Neuroscience.

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

[3]  O. Sporns,et al.  Functional connectivity between anatomically unconnected areas is shaped by collective network-level effects in the macaque cortex. , 2012, Cerebral cortex.

[4]  G. Edelman,et al.  A measure for brain complexity: relating functional segregation and integration in the nervous system. , 1994, Proceedings of the National Academy of Sciences of the United States of America.

[5]  D. Schacter,et al.  The Brain's Default Network , 2008, Annals of the New York Academy of Sciences.

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

[7]  Scott T. Grafton,et al.  Structural foundations of resting-state and task-based functional connectivity in the human brain , 2013, Proceedings of the National Academy of Sciences.

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

[9]  S Laureys,et al.  Intrinsic Brain Activity in Altered States of Consciousness , 2008, Annals of the New York Academy of Sciences.

[10]  G. Glover,et al.  Dissociable Intrinsic Connectivity Networks for Salience Processing and Executive Control , 2007, The Journal of Neuroscience.

[11]  Viktor K. Jirsa,et al.  Noise during Rest Enables the Exploration of the Brain's Dynamic Repertoire , 2008, PLoS Comput. Biol..

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

[13]  R. F. Galán,et al.  On How Network Architecture Determines the Dominant Patterns of Spontaneous Neural Activity , 2008, PLoS ONE.

[14]  Stephen M. Smith,et al.  The future of FMRI connectivity , 2012, NeuroImage.

[15]  G. Gratton,et al.  Combining structural and functional neuroimaging data for studying brain connectivity: a review. , 2008, Psychophysiology.

[16]  J. Martinerie,et al.  The brainweb: Phase synchronization and large-scale integration , 2001, Nature Reviews Neuroscience.

[17]  R. Luján Fiber Pathways of the Brain, J.D. Schmahmann, D.N. Pandya (Eds.). Oxford University Press (2006), ISBN: 0-19-510423-4 , 2008 .

[18]  Gustavo Deco,et al.  Resting brains never rest: computational insights into potential cognitive architectures , 2013, Trends in Neurosciences.

[19]  Archana Venkataraman,et al.  Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization. , 2010, Journal of neurophysiology.

[20]  S. Bressler,et al.  Operational principles of neurocognitive networks. , 2006, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

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

[22]  V. Batagelj Generalized Ward and Related Clustering Problems ∗ , 1988 .

[23]  M. Mesulam,et al.  From sensation to cognition. , 1998, Brain : a journal of neurology.

[24]  Mansel Davies,et al.  Time domain methods , 1972 .

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

[26]  Christian Windischberger,et al.  Toward discovery science of human brain function , 2010, Proceedings of the National Academy of Sciences.

[27]  Mark W. Woolrich,et al.  Biophysical network models and the human connectome , 2013, NeuroImage.

[28]  Flavio Dell'Acqua,et al.  Structural human brain networks: hot topics in diffusion tractography. , 2012, Current opinion in neurology.

[29]  J. Duyn,et al.  Time-varying functional network information extracted from brief instances of spontaneous brain activity , 2013, Proceedings of the National Academy of Sciences.

[30]  M. Greicius,et al.  Greater than the sum of its parts: a review of studies combining structural connectivity and resting-state functional connectivity , 2009, Brain Structure and Function.

[31]  Jorge Sepulcre,et al.  Network assemblies in the functional brain. , 2012, Current opinion in neurology.

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

[33]  G. Deco,et al.  Emerging concepts for the dynamical organization of resting-state activity in the brain , 2010, Nature Reviews Neuroscience.

[34]  William M. Rand,et al.  Objective Criteria for the Evaluation of Clustering Methods , 1971 .

[35]  Olaf Sporns,et al.  Can structure predict function in the human brain? , 2010, NeuroImage.

[36]  Heidi Johansen-Berg,et al.  Using diffusion imaging to study human connectional anatomy. , 2009, Annual review of neuroscience.

[37]  Hans-Hermann Bock,et al.  Classification and Related Methods of Data Analysis , 1988 .

[38]  Gustavo Deco,et al.  Computational models of the brain: From structure to function , 2010, NeuroImage.

[39]  R I Kitney,et al.  Biomedical signal processing (in four parts) , 1990, Medical and Biological Engineering and Computing.

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

[41]  B. Biswal,et al.  The resting brain: unconstrained yet reliable. , 2009, Cerebral cortex.

[42]  O. Sporns,et al.  Key role of coupling, delay, and noise in resting brain fluctuations , 2009, Proceedings of the National Academy of Sciences.

[43]  R. Kahn,et al.  Functionally linked resting‐state networks reflect the underlying structural connectivity architecture of the human brain , 2009, Human brain mapping.

[44]  R. Larter,et al.  A coupled ordinary differential equation lattice model for the simulation of epileptic seizures. , 1999, Chaos.

[45]  Olaf Sporns,et al.  Network attributes for segregation and integration in the human brain , 2013, Current Opinion in Neurobiology.

[46]  Stephen M Smith,et al.  Correspondence of the brain's functional architecture during activation and rest , 2009, Proceedings of the National Academy of Sciences.

[47]  M. Fox,et al.  Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging , 2007, Nature Reviews Neuroscience.

[48]  S. Rombouts,et al.  Consistent resting-state networks across healthy subjects , 2006, Proceedings of the National Academy of Sciences.

[49]  Xiaoping Hu,et al.  Quantitative assessment of a framework for creating anatomical brain networks via global tractography , 2012, NeuroImage.

[50]  Karl J. Friston,et al.  Dynamic causal modelling , 2003, NeuroImage.

[51]  M. Cugmas,et al.  On comparing partitions , 2015 .

[52]  Eswar Damaraju,et al.  Tracking whole-brain connectivity dynamics in the resting state. , 2014, Cerebral cortex.

[53]  Morten L. Kringelbach,et al.  Modeling the outcome of structural disconnection on resting-state functional connectivity , 2012, NeuroImage.

[54]  Gustavo Deco,et al.  Role of local network oscillations in resting-state functional connectivity , 2011, NeuroImage.

[55]  Marsel Mesulam,et al.  Defining Neurocognitive Networks in the BOLD New World of Computed Connectivity , 2009, Neuron.

[56]  Justin L. Vincent,et al.  Precuneus shares intrinsic functional architecture in humans and monkeys , 2009, Proceedings of the National Academy of Sciences.

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

[58]  Justin L. Vincent,et al.  Intrinsic functional architecture in the anaesthetized monkey brain , 2007, Nature.