Summary: | Mild traumatic brain injury (mTBI) poses a considerable burden on healthcare systems. Whilst most patients
recover quickly, a significant number suffer from sequelae that are not accompanied by measurable
structural damage. Understanding the neural underpinnings of these debilitating effects and developing a
means to detect injury, would address an important unmet clinical need. It could inform interventions and
help predict prognosis. Magnetoencephalography (MEG) affords excellent sensitivity in probing neural
function and presents significant promise for assessing mTBI, with abnormal neural oscillations being a
potential specific biomarker. However, growing evidence suggests that neural dynamics are (at least in part)
driven by transient, pan-spectral bursting and in this paper, we employ this model to investigate mTBI. We
applied a Hidden Markov Model to MEG data recorded during resting state and a motor task and show that
previous findings of diminished intrinsic beta amplitude in individuals with mTBI are largely due to the
reduced beta band spectral content of bursts, and that diminished beta connectivity results from a loss in
the temporal coincidence of burst states. In a motor task, mTBI results in diminished burst amplitude, altered
modulation of burst probability during movement, and a loss in connectivity in motor networks. These results
suggest that, mechanistically, mTBI disrupts the structural framework underlying neural synchrony, which
impairs network function. Whilst the damage may be too subtle for structural imaging to see, the functional
consequences are detectable and persist after injury. Our work shows that mTBI impairs the dynamic
coordination of neural network activity and proposes a potent new method for understanding mTBI.
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