SENSORY-MOTOR CORTICES SHAPE FUNCTIONAL CONNECTIVITY DYNAMICS IN THE HUMAN BRAIN

Abstract

Large-scale biophysical circuit models provide mechanistic insights into the micro-scale and macro-scale properties of brain organization. We developed a spatially heterogeneous large-scale dynamical circuit model that allowed for variation in local synaptic properties across the human cortex. We show that parameterizing local circuit properties with both anatomical and functional gradients generates more realistic 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. Moreover, we mathematically analyze the aforementioned large-scale circuit model. We showed that attractors are due to the stable fixed points and the transitions between multiple attractors are due to bifurcation of dynamic system. Finally, we concluded that the sensory-motor regions are the driver of the attractors’ transition. Overall, this thesis provides novel insights into the mechanism of dynamics FC in the human brain.