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.

轻度创伤性脑损伤 (mTBI) 给医疗保健系统带来了相当大的负担。尽管大多数患者恢复得很快，但也有相当一部分患者患有不伴有可测量的结构损伤的后遗症。了解这些使人衰弱的影响的神经基础并开发一种检测损伤的方法，将解决一个重要的未满足的临床需求。它可以为干预措施提供信息并帮助预测预后。脑磁图 (MEG) 在探测神经功能方面具有出色的灵敏度，并为评估 mTBI 提供了重要的前景，异常的神经振荡是一种潜在的特异性生物标志物。然而，越来越多的证据表明，神经动力学（至少部分）是由瞬态、泛谱爆发驱动的，在本文中，我们使用这个模型来研究 mTBI。我们将隐马尔可夫模型应用于在静息状态和运动任务期间记录的 MEG 数据，并表明先前发现的 mTBI 个体内在 β 振幅减少主要是由于脉冲的 β 波段光谱含量减少，并且减少了 β 连接结果由于突发状态的时间一致性丢失。在运动任务中，mTBI 会导致突发幅度减小，运动过程中突发概率的调制改变，以及运动网络中的连接性丢失。这些结果表明，从机制上讲，mTBI 破坏了神经同步的结构框架，从而损害了网络功能。虽然损伤对于结构成像来说可能过于细微，但其功能性后果是可以检测到的，并且在受伤后仍然存在。