Cerebral Neurovascular Networks May Serve as Potential Targets for Identifying Disorders of Consciousness: A Synchronous Electroencephalography and Functional Near-Infrared Spectroscopy Study
Nan Wang , Juanning Si , Yifang 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
MedComm ›› 2025, Vol. 6 ›› Issue (12) : e70530
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.
disorders of consciousness / electroencephalography / functional near-infrared spectroscopy / neurovascular coupling / noninvasive brain–computer interfaces / resting state
| [1] |
|
| [2] |
|
| [3] |
|
| [4] |
|
| [5] |
|
| [6] |
|
| [7] |
|
| [8] |
|
| [9] |
|
| [10] |
|
| [11] |
|
| [12] |
|
| [13] |
|
| [14] |
|
| [15] |
|
| [16] |
|
| [17] |
|
| [18] |
|
| [19] |
|
| [20] |
|
| [21] |
|
| [22] |
|
| [23] |
|
| [24] |
|
| [25] |
|
| [26] |
|
| [27] |
|
| [28] |
|
| [29] |
|
| [30] |
|
| [31] |
|
| [32] |
|
| [33] |
|
| [34] |
|
| [35] |
|
| [36] |
|
| [37] |
|
| [38] |
|
| [39] |
|
| [40] |
|
| [41] |
|
| [42] |
|
| [43] |
|
| [44] |
|
| [45] |
|
| [46] |
|
| [47] |
|
| [48] |
|
| [49] |
|
| [50] |
|
| [51] |
|
| [52] |
|
| [53] |
|
| [54] |
|
| [55] |
|
| [56] |
|
| [57] |
|
| [58] |
|
| [59] |
|
| [60] |
|
| [61] |
|
| [62] |
|
| [63] |
|
| [64] |
|
| [65] |
|
| [66] |
|
| [67] |
|
| [68] |
|
| [69] |
|
| [70] |
|
| [71] |
|
| [72] |
|
| [73] |
|
| [74] |
|
| [75] |
|
| [76] |
|
| [77] |
|
| [78] |
|
| [79] |
|
| [80] |
|
| [81] |
|
| [82] |
|
| [83] |
|
| [84] |
|
| [85] |
|
| [86] |
|
| [87] |
|
| [88] |
|
| [89] |
|
| [90] |
|
| [91] |
|
| [92] |
|
| [93] |
|
| [94] |
|
2025 The Author(s). MedComm published by Sichuan International Medical Exchange & Promotion Association (SCIMEA) and John Wiley & Sons Australia, Ltd.
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