Structural determinants of dynamical state transitions in disorders of consciousness: a whole-brain modeling approach
Fernando Lehue, Iván Mindlin, Carlos Coronel-Oliveros, Jacobo Sitt, Patricio Orio, Jacobo D. Sitt
bioRxiv (Cold Spring Harbor Laboratory) July 1, 2026 DOI: 10.64898/2026.06.26.734644 via OpenAlex
Summary
AI-generated from the abstractDisorders 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.
Study at a glance
| Characteristics | Computational modeling study Peer reviewed |
|---|---|
| Interventions | node removal targeted modulation of local excitation–inhibition balance |
| Keywords | Connectome Dynamical systems theory Precuneus Perturbation astronomy Posterior cingulate |
| Key finding | A node's integration within the structural connectome, quantified by a spectral integration measure, strongly predicts its impact on global brain dynamics, with lesions to highly integrative hubs driving the system toward low-complexity dynamical regimes resembling disorders of consciousness. |
Abstract
Abstract 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.