Structural determinants of dynamical state transitions in disorders of consciousness: a whole-brain modeling approach

Disorders of consciousness (DoC) are associated with large scale alterations in brain dynamics, yet the structural factors that constrain these changes remain unclear. Here, we investigate how the topology of the structural connectome shapes the sensitivity of brain dynamics to perturbation using a whole brain computational model constrained by diffusion MRI derived connectivity. We systematically probed the effects of node removal and targeted modulation of local excitation/inhibition balance on dynamic functional connectivity, quantifying dynamical richness via transitions between recurrent connectivity states and jump length distributions in functional connectivity space. We show that a node's integration within the structural connectome, quantified using a spectral integration measure, strongly predicts its impact on global brain dynamics. Lesions to highly integrative hubs drive the system toward low complexity dynamical regimes resembling those observed in DoC, particularly posterior medial regions such as the precuneus and posterior cingulate cortex. Analogously, increasing excitability in these regions restores healthy like dynamics in silico. In contrast, perturbations to weakly integrated regions have limited global effects. These results demonstrate that generic features of structural connectivity constrain whole brain dynamical stability and help explain why damage to specific hubs disproportionately disrupts conscious brain activity.