神经科学
神经血管束
脑电图
持续植物状态
神经学
最小意识状态
医学
清醒
功能连接
神经影像学
心理学
神经精神病学
大脑活动与冥想
计算机科学
功能成像
意识
临床诊断
物理医学与康复
神经生理学
病理生理学
神经康复
神经系统疾病
作者
Nan Wang,Juanning Si,Yunteng He,Jiuxiang Song,Xiaoke Chai,Dongsheng Liu,Jingqi Li,Tan Zhang,Tianqing Cao,Qiheng He,Sipeng Zhu,Yitong Jia,Wenbin Ma,Yi Yang,Jizong Zhao
出处
期刊:MedComm
[Wiley]
日期:2025-12-01
卷期号:6 (12): e70530-e70530
摘要
The diagnosis and management of disorders of consciousness (DoC) remain a critical challenge in clinical medicine and neuroscience. The key bottleneck is the lack of reliable biomarkers and an incomplete understanding of the pathophysiological mechanisms that underlie DoC. In view of this, a bedside-compatible, multimodal technique based on electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) was utilized to simultaneously capture neuronal oscillations and accompanying hemodynamics, so as to explore neurovascular biomarkers that can effectively discriminate different states of DoC. Resting-state EEG-fNIRS data from 13 regions of interest (ROIs) were acquired and compared across healthy controls (HC), minimally conscious state (MCS), and unresponsive wakefulness syndrome (UWS) groups. Hemodynamics-based functional connectivity and the spectral power of neuronal activity were quantified and subsequently employed to interrogate neurovascular coupling. The results demonstrated significantly stronger neurovascular coupling and beta-band power in premotor and Broca's areas of the MCS group. A multimodal classifier achieved an accuracy of 87.9% in distinguishing between MCS and UWS. The noninvasive, bedside-suitable nature of this tool underscores its potential for routine monitoring and prognostic assessment in DoC, addressing a critical need for accessible and reliable biomarkers in both neurology and intensive-care practice.
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