The evolution of whole-brain turbulent dynamics during recovery from traumatic brain injury

Significant advances in non-linear dynamics and computational modeling have opened up the possibility of studying how whole-brain dynamics may be impacted by brain injury. Importantly, by looking at the local level of synchronization, it is possible to obtain a comprehensive characterization of the spatiotemporal patterns affected at different spatial scales. In the current study, we applied the turbulent dynamics framework to investigate the temporal evolution in whole-brain dynamics using an open access resting state fMRI dataset from a cohort of moderate-to-severe traumatic brain injury (TBI) patients and healthy controls (HC). We first examined how several measures related to turbulent dynamics differ between HCs and TBI patients at 3-, 6- and 12-months post-injury. We found a significant reduction in these empirical measures after TBI, with the largest change at 6-months post-injury. Next, we built a Hopf whole-brain model with coupled oscillators and conducted in silico perturbations to investigate the mechanistic principles underlying the reduced turbulent dynamics found in the empirical data. This revealed a shift to lower coupling parameters in the TBI dataset and, critically, decreased susceptibility and information encoding capability. These findings confirm the potential of the turbulent framework to characterize whole-brain dynamics after TBI and suggest a mechanistic link between structural disconnection and impaired information processing. Highlights Whole-brain turbulent dynamics capture longitudinal changes after TBI during one-year recovery period TBI patients show partial recovery of resting state network dynamics at large spatial scales Whole-brain computational modeling provides a mechanistic link between structural disconnection and recovery