Sensory-motor cortices shape functional connectivity dynamics in the human brain

Xiaolu Kong, Ru Kong, Csaba Orban, Peng Wang, Shaoshi Zhang, Kevin Anderson, Avram Holmes, John D Murray, Gustavo Deco, Martijn van den Heuvel, B T Thomas Yeo

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Large-scale biophysical circuit models provide mechanistic insights into the micro-scale and macro-scale properties of brain organization that shape complex patterns of spontaneous brain activity. We developed a spatially heterogeneous large-scale dynamical circuit model that allowed for variation in local synaptic properties across the human cortex. Here we show that parameterizing local circuit properties with both anatomical and functional gradients generates more realistic static and dynamic resting-state functional connectivity (FC). Furthermore, empirical and simulated FC dynamics demonstrates remarkably similar sharp transitions in FC patterns, suggesting the existence of multiple attractors. Time-varying regional fMRI amplitude may track multi-stability in FC dynamics. Causal manipulation of the large-scale circuit model suggests that sensory-motor regions are a driver of FC dynamics. Finally, the spatial distribution of sensory-motor drivers matches the principal gradient of gene expression that encompasses certain interneuron classes, suggesting that heterogeneity in excitation-inhibition balance might shape multi-stability in FC dynamics.

Original languageEnglish
Article number6373
Pages (from-to)6373
JournalNature Communications
Volume12
Issue number1
DOIs
Publication statusPublished - 4 Nov 2021

Bibliographical note

© 2021. The Author(s).

Funding

This work was supported by the Singapore National Research Foundation (NRF) Fellowship (Class of 2017), the NUS Yong Loo Lin School of Medicine (NUHSRO/2020/ 124/TMR/LOA), the Singapore National Medical Research Council (NMRC) LCG (OFLCG19May-0035), and the United States National Institutes of Health (R01MH120080). Any opinions, findings, and conclusions, or recommendations expressed in this material are those of the authors and do not reflect the views of the Singapore NRF or the Singapore NMRC. Our computational work was partially performed on resources of the National Supercomputing Centre, Singapore (https://www.nscc.sg). Data were in part provided by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University.

FundersFunder number
NUS Yong Loo Lin School of MedicineNUHSRO/2020/ 124/TMR/LOA
National Institutes of Health1U54MH091657
National Institute of Mental HealthR01MH120080
NIH Blueprint for Neuroscience Research
McDonnell Center for Systems Neuroscience
National Medical Research CouncilOFLCG19May-0035
National Research Foundation SingaporeClass of 2017

    Keywords

    • Brain/physiology
    • Brain Mapping/methods
    • Computer Simulation
    • Connectome/methods
    • Databases, Factual
    • Humans
    • Magnetic Resonance Imaging/methods
    • Models, Neurological
    • Neural Pathways/physiology
    • Rest/physiology
    • Sensorimotor Cortex/physiology

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