Resting-state EEG as Biomarker of Maladaptive Motor Function and Depressive Profile in Stroke Patients.

Clinical EEG and neuroscience Pub Date : 2024-07-01 Epub Date: 2024-03-09 DOI:10.1177/15500594241234394
Lucas M Marques, Sara Pinto Barbosa, Anna Carolyna Gianlorenço, K Pacheco-Barrios, Daniel R Souza, Denise Matheus, Linamara Battistella, Marcel Simis, Felipe Fregni
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Abstract

Objective: Investigate the relationship between resting-state EEG-measured brain oscillations and clinical and demographic measures in Stroke patients. Methods: We performed a cross-sectional analysis of a cohort study (DEFINE cohort), Stroke arm, with 85 patients, considering demographic, clinical, and stroke characteristics. Resting-state EEG relative power from delta, theta, alpha, and beta oscillations were measured from the central region. Multivariate regression models were used for both affected and non-affected hemispheres. Results: Motor function was negatively associated with Delta and Theta oscillations, while positively associated with Alpha oscillations (both hemispheres). Similarly, cognition levels measured were negatively associated with Delta activity. Depression levels were negatively associated with Alpha activity specifically in the affected hemisphere, while positively associated with Beta activity in both hemispheres. Regarding pain measures, no significant association was observed, while CPM measure showed a positive association with Alpha activity in the non-affected hemisphere. Finally, we found that theta/alpha ratio was negatively associated with motor function and CPM scores. Conclusion: The results lead us to propose a framework for brain oscillations in stroke, whereas Delta and Beta would represent disrupted mal-adaptive brain plasticity and Theta and Alpha would represent compensatory and functional brain oscillations for motor and sensory deficits in stroke, respectively.

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静息态脑电图是脑卒中患者适应不良运动功能和抑郁特征的生物标记。
目的研究脑卒中患者静息态脑电图测量的大脑振荡与临床和人口统计学指标之间的关系。方法: 我们对一项队列研究(DEFINE 队列)进行了横断面分析:我们对一项队列研究(DEFINE 队列)的 85 名中风患者进行了横断面分析,考虑了人口统计学、临床和中风特征。我们测量了中心区域静息态脑电图中δ、θ、α和β振荡的相对功率。对受影响半球和非受影响半球采用多变量回归模型。结果显示运动功能与 Delta 和 Theta 振荡呈负相关,而与 Alpha 振荡呈正相关(两个半球)。同样,测量的认知水平与德尔塔活动呈负相关。抑郁水平与受影响半球的 Alpha 活动呈负相关,而与两个半球的 Beta 活动呈正相关。在疼痛测量方面,没有观察到明显的相关性,而在未受影响的大脑半球,CPM 测量与 Alpha 活动呈正相关。最后,我们发现θ/α比值与运动功能和CPM评分呈负相关。结论这些结果使我们提出了脑卒中大脑振荡的框架,Delta 和 Beta 代表被破坏的不良适应性大脑可塑性,而 Theta 和 Alpha 则分别代表脑卒中运动和感觉缺陷的代偿性和功能性大脑振荡。
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