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增强注意力网络时空动力学以促进帕金森病的运动康复

Enhancing Attention Network Spatiotemporal Dynamics for Motor Rehabilitation in Parkinson's Disease.

作者信息

Pei Guangying, Hu Mengxuan, Ouyang Jian, Jin Zhaohui, Wang Kexin, Meng Detao, Wang Yixuan, Chen Keke, Wang Li, Cao Li-Zhi, Funahashi Shintaro, Yan Tianyi, Fang Boyan

机构信息

School of Medical Technology, Beijing Institute of Technology, Beijing, China.

Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China.

出版信息

Cyborg Bionic Syst. 2025 Jun 19;6:0293. doi: 10.34133/cbsystems.0293. eCollection 2025.

Abstract

Optimizing resource allocation for Parkinson's disease (PD) motor rehabilitation necessitates identifying biomarkers of responsiveness and dynamic neuroplasticity signatures underlying efficacy. A cohort study of 52 early-stage PD patients undergoing 2-week multidisciplinary intensive rehabilitation therapy (MIRT) was conducted, which stratified participants into responders and nonresponders. A multimodal analysis of resting-state electroencephalography (EEG) microstates and functional magnetic resonance imaging (fMRI) coactivation patterns was performed to characterize MIRT-induced spatiotemporal network reorganization. Responders demonstrated clinically meaningful improvement in motor symptoms, exceeding the minimal clinically important difference threshold of 3.25 on the Unified PD Rating Scale part III, alongside significant reductions in bradykinesia and a significant enhancement in quality-of-life scores at the 3-month follow-up. Resting-state EEG in responders showed a significant attenuation in microstate C and a significant enhancement in microstate D occurrences, along with significantly increased transitions from microstate A/B to D, which significantly correlated with motor function, especially in bradykinesia gains. Concurrently, fMRI analyses identified a prolonged dwell time of the dorsal attention network coactivation/ventral attention network deactivation pattern, which was significantly inversely associated with microstate C occurrence and significantly linked to motor improvement. The identified brain spatiotemporal neural markers were validated using machine learning models to assess the efficacy of MIRT in motor rehabilitation for PD patients, achieving an average accuracy rate of 86%. These findings suggest that MIRT may facilitate a shift in neural networks from sensory processing to higher-order cognitive control, with the dynamic reallocation of attentional resources. This preliminary study validates the necessity of integrating cognitive-motor strategies for the motor rehabilitation of PD and identifies novel neural markers for assessing treatment efficacy.

摘要

优化帕金森病(PD)运动康复的资源分配需要确定反应性生物标志物以及疗效背后的动态神经可塑性特征。对52名接受为期2周多学科强化康复治疗(MIRT)的早期PD患者进行了一项队列研究,将参与者分为反应者和无反应者。对静息态脑电图(EEG)微状态和功能磁共振成像(fMRI)共激活模式进行了多模态分析,以表征MIRT诱导的时空网络重组。反应者在运动症状方面表现出具有临床意义的改善,在统一PD评定量表第三部分超过了3.25的最小临床重要差异阈值,同时在3个月随访时运动迟缓显著减少,生活质量评分显著提高。反应者的静息态EEG显示微状态C显著衰减,微状态D出现显著增强,同时从微状态A/B到D的转换显著增加,这与运动功能显著相关,尤其是在运动迟缓改善方面。同时,fMRI分析确定背侧注意网络共激活/腹侧注意网络失活模式的停留时间延长,这与微状态C的出现显著负相关,并与运动改善显著相关。使用机器学习模型验证了所确定的脑时空神经标志物,以评估MIRT对PD患者运动康复的疗效,平均准确率达到86%。这些发现表明,MIRT可能促进神经网络从感觉处理向高阶认知控制的转变,伴随着注意力资源的动态重新分配。这项初步研究验证了整合认知-运动策略对PD运动康复的必要性,并确定了评估治疗效果的新型神经标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a247/12178139/a76f6ac55418/cbsystems.0293.fig.001.jpg

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