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 Heuvel and B. T. Thomas Yeo ()
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Xiaolu Kong: National University of Singapore
Ru Kong: National University of Singapore
Csaba Orban: National University of Singapore
Peng Wang: Max Planck Institute for Human Cognitive and Brain Sciences
Shaoshi Zhang: National University of Singapore
Kevin Anderson: Harvard University
Avram Holmes: Yale University
John D. Murray: Yale University
Gustavo Deco: Universitat Pompeu Fabra
Martijn Heuvel: Amsterdam University Medical Center
B. T. Thomas Yeo: National University of Singapore

Nature Communications, 2021, vol. 12, issue 1, 1-15

Abstract: 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.

Date: 2021
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DOI: 10.1038/s41467-021-26704-y

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