Why the study?
Previous studies examined brain functional network disruptions in mTBI primarily using static connectivity measures, leaving dynamic neural communication differences between mTBI patients and controls unaddressed.
Dynamic functional network analysis of resting-state fMRI in the acute stage of mild traumatic brain injury reveals unique alterations in global communication that may predispose patients to persistent postconcussive symptoms.
Dynamic connectivity may better detect mTBI network disruptions than static measures; leaves open clinical utility and validation needs.
Mild traumatic brain injury (mTBI) is one of the most common neurological disorders for which a subset of patients develops persistent postconcussive symptoms. Previous studies discovered abnormalities and disruptions in the brain functional networks of mTBI patients principally using static functional connectivity measures which assume that neural communication across the brain is static during resting state conditions. In this study, we examine the differences in dynamic neural communication between mTBI and control participants through the application of a combination of dynamic functional analysis and graph theoretic algorithms. Resting state functional magnetic resonance imaging data was obtained on 47 mTBI patients at the acute stage of injury and 30 demographically matched healthy control participants. Results show unique alterations in both the static and dynamic functional connectivity at the acute stage in mTBI patients who suffer persistent symptoms (≥6 months after injury). In addition, mTBI patients with postconcussion syndrome demonstrated a unique allocation of time in various brain states compared to both control participants and mTBI patients with favorable outcomes. These findings suggest that global damage to the overall communication across the brain in the acute stage may contribute to chronic mTBI symptoms. Dynamic functional analysis is a powerful tool that provides insights into the brain states and the innovative analysis methodology utilized may hold the potential to delineate patients predisposed to poor outcomes upon early presentation following injury.
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Hou et al. (2019) studied this question.
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