增强帕金森病患者运动康复的注意网络时空动态。

IF 18.1 Q1 ENGINEERING, BIOMEDICAL
Cyborg and bionic systems (Washington, D.C.) Pub Date : 2025-06-19 eCollection Date: 2025-01-01 DOI:10.34133/cbsystems.0293
Guangying Pei, Mengxuan Hu, Jian Ouyang, Zhaohui Jin, Kexin Wang, Detao Meng, Yixuan Wang, Keke Chen, Li Wang, Li-Zhi Cao, Shintaro Funahashi, Tianyi Yan, Boyan Fang
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引用次数: 0

摘要

优化帕金森病(PD)运动康复的资源分配需要识别反应性和动态神经可塑性特征的生物标志物。对52例接受2周多学科强化康复治疗(MIRT)的早期PD患者进行队列研究,将参与者分为应答者和无应答者。通过静息状态脑电图(EEG)微态和功能磁共振成像(fMRI)共激活模式的多模态分析来表征mirt诱导的时空网络重组。应答者在运动症状方面表现出具有临床意义的改善,超过了统一PD评定量表第三部分的最小临床重要差异阈值3.25,同时在3个月的随访中,运动迟缓显著减少,生活质量评分显著提高。反应者静息状态脑电图显示微状态C显著衰减,微状态D显著增强,同时微状态a /B到D的转换显著增加,这与运动功能显著相关,尤其是运动迟缓增益。同时,fMRI分析发现,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的发生呈显著负相关,与运动改善显著相关。使用机器学习模型验证识别的脑时空神经标记物,以评估MIRT在PD患者运动康复中的疗效,平均准确率为86%。这些发现表明,MIRT可能会促进神经网络从感觉处理向高阶认知控制的转变,并伴有注意力资源的动态重新分配。本初步研究验证了PD运动康复整合认知-运动策略的必要性,并确定了新的神经标记物来评估治疗效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing Attention Network Spatiotemporal Dynamics for Motor Rehabilitation in Parkinson's Disease.

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.

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CiteScore
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