Disorders of consciousness are linked to large-scale changes in brain dynamics, but the structural factors behind these changes are unclear. Using a whole-brain computational model constrained by diffusion MRI-derived connectivity, the authors show that a node's integration within the structural connectome, measured by a spectral integration metric, strongly predicts its impact on global brain dynamics. Lesions to highly integrative hubs, especially in posterior medial regions like the precuneus and posterior cingulate cortex, drive the system toward low-complexity dynamical regimes resembling disorders of consciousness. Increasing excitability in these regions restores healthy-like dynamics in silico. Perturbations to weakly integrated regions have limited global effects, explaining why damage to specific hubs disproportionately disrupts conscious brain activity.
A biologically grounded inhibitory homeostatic plasticity rule embedded into the Dynamic Mean Field (DMF) model creates a Homeostatic Dynamic Mean Field (HDMF) model that dynamically tunes local excitation-inhibition balance. The HDMF reproduces statistical observables of brain activity as well as the original DMF, can sustain neuromodulatory perturbations without overhead computations, and generates unprecedented sleep-like slow-wave activity that can coexist with wake-like asynchronous dynamics, permitting modeling of dissociated states of consciousness such as parasomnias. A single homeostatic rule broadens the stability and expressiveness of the DMF, providing a unified platform for studying how local adaptive processes shape the diverse global dynamics of the human brain.