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

It has been previously shown that traumatic brain injury (TBI) is associated with reductions in metastability in large-scale networks in resting state fMRI. However, little is known about how TBI affects the local level of synchronization and how this evolves during the recovery trajectory. Here, we applied a novel 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 TBI patients and healthy controls (HCs). 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. A simulated attack was used to account for the effect of focal lesions. 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 validates the use of whole-brain models to monitor longitudinal changes in the reactivity to external perturbations. HighlightsO_LIWhole-brain turbulent dynamics capture longitudinal changes after TBI during one-year recovery period C_LIO_LITBI patients show partial recovery of resting state network dynamics at large spatial scales C_LIO_LIWhole-brain computational models indicate less reactivity to in silico perturbations after TBI C_LI