Background Persistent motor deficits are very common in poststroke survivors and often lead to disability. Current clinical measures for profiling motor impairment and assessing poststroke recovery are largely subjective and lack precision. Objective A multimodal neuroimaging approach was developed based on concurrent functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) to identify biomarkers associated with motor function recovery and document the poststroke cortical reorganization. Methods EEG and fNIRS data were simultaneously recorded from 9 healthy controls and 18 stroke patients during a hand-clenching task. A novel fNIRS-informed EEG source imaging approach was developed to estimate cortical activity and functional connectivity. Subsequently, graph theory analysis was performed to identify network features for monitoring and predicting motor function recovery during a 4-week intervention. Results The task-evoked strength at ipsilesional primary somatosensory cortex was significantly lower in stroke patients compared with healthy controls (P < .001). In addition, across the 4-week rehabilitation intervention, the strength at ipsilesional premotor cortex (PMC) (R = 0.895, P = .006) and the connectivity between bilateral primary motor cortices (M1) (R = 0.9, P = .007) increased in parallel with the improvement of motor function. Furthermore, a higher baseline strength at ipsilesional PMC was associated with a better motor function recovery (R = 0.768, P = .007), while a higher baseline connectivity between ipsilesional supplementary motor cortex (SMA)–M1 implied a worse motor function recovery (R = −0.745, P = .009). Conclusion The proposed multimodal EEG/fNIRS technique demonstrates a preliminary potential for monitoring and predicting poststroke motor recovery. We expect such findings can be further validated in future study.

中文翻译：

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使用并发 EEG/fNIRS 进行中风后恢复评估的多模式神经成像：一项探索性研究

背景 持续性运动障碍在中风后幸存者中非常常见，并经常导致残疾。目前用于分析运动损伤和评估中风后恢复的临床措施在很大程度上是主观的，缺乏精确性。目的基于并发功能性近红外光谱 (fNIRS) 和脑电图 (EEG) 开发了一种多模式神经影像学方法，以识别与运动功能恢复相关的生物标志物并记录中风后皮质重组。方法同时记录 9 名健康对照者和 18 名中风患者在握紧手任务期间的 EEG 和 fNIRS 数据。开发了一种新的 fNIRS 知情 EEG 源成像方法来估计皮层活动和功能连接。随后，进行图论分析以识别网络特征，以在 4 周干预期间监测和预测运动功能恢复。结果与健康对照相比，卒中患者的同侧初级躯体感觉皮层的任务诱发强度显着降低（P < .001）。此外，在 4 周的康复干预中，同侧运动前皮层 (PMC) 的强度 (R = 0.895, P = .006) 和双侧初级运动皮层 (M1) 之间的连接性 (R = 0.9, P = .007 ) 随着运动功能的改善而增加。此外，较高的同侧 PMC 基线强度与更好的运动功能恢复相关（R = 0.768，P = .007），而同侧补充运动皮层 (SMA)-M1 之间更高的基线连接意味着更差的运动功能恢复（R = -0.745，P = .009）。结论 提议的多模式 EEG/fNIRS 技术展示了监测和预测中风后运动恢复的初步潜力。我们希望这些发现可以在未来的研究中得到进一步验证。