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 ...
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.
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