Abstract：
The progress in neuroimaging and electrophysiological techniques has shown substantial promise in improving the clinical assessment of disorders of consciousness (DOC). Through the examination of both stimulus-induced and spontaneous brain activity, numerous comprehensive investigations have explored variations in brain activity patterns among patients with DOC, yielding valuable insights for clinical diagnosis and prognostic purposes. Nonetheless, reaching a consensus on precise neuroimaging biomarkers for patients with DOC remains a challenge. Therefore, in this review, we begin by summarizing the empirical evidence related to neuroimaging biomarkers for DOC using various paradigms, including active, passive, and resting-state approaches, by employing task-based fMRI, resting-state fMRI (rs-fMRI), electroencephalography (EEG), and positron emission tomography (PET) techniques. Subsequently, we conducted a review of studies examining the neural correlates of consciousness in patients with DOC, with the findings holding potential value for the clinical application of DOC. Notably, previous research indicates that neuroimaging techniques have the potential to unveil covert awareness that conventional behavioral assessments might overlook. Furthermore, when integrated with various task paradigms or analytical approaches, this combination has the potential to significantly enhance the accuracy of both diagnosis and prognosis in DOC patients. Nonetheless, the stability of these neural biomarkers still needs additional validation, and future directions may entail integrating diagnostic and prognostic methods with big data and deep learning approaches.
摘要：
神经影像学和电生理技术的进步在改善意识障碍（DOC）的临床评估方面显示出巨大的希望。通过检查刺激引起的和自发的大脑活动，许多全面的研究探索了DOC患者大脑活动模式的变化，为临床诊断和预后目的提供有价值的见解。尽管如此，就DOC患者的精确神经影像学生物标志物达成共识仍是一项挑战.因此,在这次审查中,我们首先总结了使用各种范式与DOC的神经影像学生物标志物相关的经验证据，包括活跃的,被动,和静息状态方法，通过使用基于任务的功能磁共振成像，静息状态功能磁共振成像（rs-fMRI），脑电图（EEG），和正电子发射断层扫描（PET）技术。随后，我们对DOC患者意识的神经相关性研究进行了综述，该研究结果对DOC的临床应用具有潜在价值。值得注意的是,先前的研究表明，神经成像技术有可能揭示传统行为评估可能忽略的秘密意识。此外，当与各种任务范式或分析方法相结合时，这种组合有可能显著提高DOC患者的诊断和预后的准确性.尽管如此，这些神经生物标志物的稳定性仍然需要额外的验证，未来的方向可能需要将诊断和预后方法与大数据和深度学习方法相结合。
