Neural mechanisms underlying loss of functional independence after stroke: EEG evidence of impaired motor-to-sensory directed connectivity on the affected side

Post-stroke reorganization of the prefrontal-sensorimotor network is critical for functional recovery, yet single connectivity metrics fail to capture its multidimensional characteristics. This exploratory study investigates network reorganization patterns and their clinical relevance to motor function and daily independence using multimodal electroencephalography (EEG) connectivity analysis, including Coherence (COH), phase lag index (PLI), and Granger causality (GC). Resting-state EEG from stroke patients ( n = 22) and healthy controls ( n = 22) was analyzed. COH, PLI, and GC metrics were computed for key regional connections involving the prefrontal (PFC), motor (MC), sensory (SC), and parietal (PC) cortices and correlated with Fugl-Meyer Assessment for Upper Extremity (FMA-UE) and Modified Barthel Index(MBI) scores. For stroke patients, hemispheres were classified as ipsilesional (i, affected) and contralesional (c, unaffected) based on the lesion side. Compared to healthy controls, stroke patients exhibited distinct reorganization patterns. Preliminary evidence suggests enhanced parietal-motor coherence (COH_cPC-cMC↑) in the unaffected hemisphere alongside reduced motor-to-prefrontal directed connectivity (GC_cMC→cPFC↓). Interhemispherically, the findings may indicate weakened information flow from the unaffected to affected motor/sensory areas (GC_cMC→iMC↓, GC_cMC→iSC↓), accompanied by reduced bilateral motor synchronization (PLI_iMC-cMC↓). Within the affected hemisphere, there was evidence of enhanced bidirectional parietal-motor phase transfer (PLI_iPC-iMC↑), whereas directed pathways were significantly impaired (GC_iMC→iSC↓, GC_iPC→iSC↓, GC_iPFC→iMC↓). Clinically, the affected motor-to-sensory pathway (GC_iMC→iSC) showed a strong negative correlation with the MBI ( r = -0.61, P = 0.002), and both interhemispheric motor regulation (GC_cMC→iMC) and synchronization (PLI_iMC-cMC) were significantly correlated with functional deficits ( P < 0.05). Post-stroke networks may exhibit a “local compensation-global impairment” reorganization pattern. The affected motor-sensory pathway (GC_iMC→iSC) may be a biomarker for functional independence and thus allow for guided sensory integration-based precision rehabilitation.

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Publication Details

Journal
Journal of NeuroEngineering and Rehabilitation
Published
2026-07-27
DOI
https://doi.org/10.1186/s12984-026-02089-1
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.00

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article

Neural mechanisms underlying loss of functional independence after stroke: EEG evidence of impaired motor-to-sensory directed connectivity on the affected side

Qiurong Xie, Wuxiang Shi, Y Li, Xi Zhang et al.
Journal of NeuroEngineering and Rehabilitation
EEG and Brain-Computer Interfaces
article

Neural mechanisms underlying loss of functional independence after stroke: EEG evidence of impaired motor-to-sensory directed connectivity on the affected side

Qiurong Xie, Wuxiang Shi, Y Li, Xi Zhang, Xiaoling Wang, Nan Zheng
article en

Abstract

Post-stroke reorganization of the prefrontal-sensorimotor network is critical for functional recovery, yet single connectivity metrics fail to capture its multidimensional characteristics. This exploratory study investigates network reorganization patterns and their clinical relevance to motor function and daily independence using multimodal electroencephalography (EEG) connectivity analysis, including Coherence (COH), phase lag index (PLI), and Granger causality (GC). Resting-state EEG from stroke patients ( n = 22) and healthy controls ( n = 22) was analyzed. COH, PLI, and GC metrics were computed for key regional connections involving the prefrontal (PFC), motor (MC), sensory (SC), and parietal (PC) cortices and correlated with Fugl-Meyer Assessment for Upper Extremity (FMA-UE) and Modified Barthel Index(MBI) scores. For stroke patients, hemispheres were classified as ipsilesional (i, affected) and contralesional (c, unaffected) based on the lesion side. Compared to healthy controls, stroke patients exhibited distinct reorganization patterns. Preliminary evidence suggests enhanced parietal-motor coherence (COH_cPC-cMC↑) in the unaffected hemisphere alongside reduced motor-to-prefrontal directed connectivity (GC_cMC→cPFC↓). Interhemispherically, the findings may indicate weakened information flow from the unaffected to affected motor/sensory areas (GC_cMC→iMC↓, GC_cMC→iSC↓), accompanied by reduced bilateral motor synchronization (PLI_iMC-cMC↓). Within the affected hemisphere, there was evidence of enhanced bidirectional parietal-motor phase transfer (PLI_iPC-iMC↑), whereas directed pathways were significantly impaired (GC_iMC→iSC↓, GC_iPC→iSC↓, GC_iPFC→iMC↓). Clinically, the affected motor-to-sensory pathway (GC_iMC→iSC) showed a strong negative correlation with the MBI ( r = -0.61, P = 0.002), and both interhemispheric motor regulation (GC_cMC→iMC) and synchronization (PLI_iMC-cMC) were significantly correlated with functional deficits ( P < 0.05). Post-stroke networks may exhibit a “local compensation-global impairment” reorganization pattern. The affected motor-sensory pathway (GC_iMC→iSC) may be a biomarker for functional independence and thus allow for guided sensory integration-based precision rehabilitation.

Journal of NeuroEngineering and Rehabilitation
Fujian University of Traditional Chinese Medicine (CN), Fujian Medical University (CN), Fuzhou University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Fujian Province
Openalex Percentile: Top 7%
EEG and Brain-Computer Interfaces
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