Citation

Rier L, Zamyadi R, Zhang J, Emami Z, Seedat ZA, Mocanu S, Gascoyne LE, Allen CM, Scadding JW, Furlong PL, Gooding-Williams G, Woolrich MW, Evangelou N, Brookes MJ, Dunkley BT. Neuroimage (Amst) 2021; 32: e102841.

Copyright

(Copyright © 2021, Elsevier Publishing)

DOI

10.1016/j.nicl.2021.102841

PMID

34653838

Abstract

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.

Language: en

Keywords

Concussion; Networks; Beta bursts; MEG; mild Traumatic Brain Injury; mTBI