Traumatic Brain Injury (TBI) is a prevalent disorder mostly characterized by persistent impairments in cognitive function that poses a substantial burden on caregivers and the healthcare system worldwide. Crucially, severity classification is primarily based on clinical evaluations, which are non-specific and poorly predictive of long-term disability. In this Mini Review, we first provide a description of our model-free and model-based approaches within the turbulent dynamics framework as well as our vision on how they can potentially contribute to provide new neuroimaging biomarkers for TBI. In addition, we report the main findings of our recent study examining longitudinal changes in moderate-severe TBI (msTBI) patients during a one year spontaneous recovery by applying the turbulent dynamics framework (model-free approach) and the Hopf whole-brain computational model (model-based approach) combined with in silico perturbations. Given the neuroinflammatory response and heightened risk for neurodegeneration after TBI, we also offer future directions to explore the association with genomic information. Moreover, we discuss how whole-brain computational modeling may advance our understanding of the impact of structural disconnection on whole-brain dynamics after msTBI in light of our recent findings. Lastly, we suggest future avenues whereby whole-brain computational modeling may assist the identification of optimal brain targets for deep brain stimulation to promote TBI recovery.

中文翻译：

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湍流动力学和全脑建模：面向创伤性脑损伤的新临床应用

创伤性脑损伤 (TBI) 是一种普遍存在的疾病，其主要特征是认知功能持续受损，给全世界的护理人员和医疗保健系统带来沉重负担。至关重要的是，严重程度分类主要基于临床评估，而临床评估不具有特异性，并且不能很好地预测长期残疾。在这篇迷你综述中，我们首先描述了湍流动力学框架内的无模型和基于模型的方法，以及我们对它们如何可能为 TBI 提供新的神经影像生物标志物做出贡献的愿景。此外，我们还报告了我们最近研究的主要结果，该研究通过应用湍流动力学框架（无模型方法）和 Hopf 全脑计算模型，检查中重度 TBI（msTBI）患者在一年自发恢复期间的纵向变化（基于模型的方法）结合计算机模拟扰动。鉴于 TBI 后的神经炎症反应和神经退行性变的风险增加，我们还提供了探索与基因组信息关联的未来方向。此外，根据我们最近的发现，我们讨论了全脑计算模型如何促进我们对 msTBI 后结构性断开对全脑动力学影响的理解。最后，我们建议未来的途径，全脑计算模型可以帮助识别深部脑刺激的最佳大脑目标，以促进 TBI 恢复。