ORIGINAL RESEARCH article
Front. Neurol.
Sec. Stroke
Volume 16 - 2025 | doi: 10.3389/fneur.2025.1653349
This article is part of the Research TopicRedefining Stroke Recovery: Current Trends and Recent AdvancesView all 8 articles
Associations Between Structural Injury and Task-Based Corticomuscular Connectivity After Stroke
Provisionally accepted- The University of North Carolina at Chapel Hill Libraries, Chapel Hill, United States
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Stroke-related damage to structural pathways and functional connections disrupts neural network communication, contributing to deficits. A critical step is to determine whether relationships between connectivity and behavior align with established neurobiological frameworks. This involves investigating structural-functional relationships as structural connectivity provides the scaffold for functional communication. Prior work explored structural-functional relationships at rest, particularly between structural measures and cortico-cortical functional connectivity. However, because stroke impacts both cortical and muscular systems, incorporating task-based functional connectivity measurements that reflect synchronous activity between cortex and muscle may offer insight. Therefore, we examined relationships between structural injury and integrity measures with task-based functional connectivity between electrodes overlying sensorimotor regions and affected upper-extremity musculature (referred to as corticomuscular coherence; CMC). Individuals with subacute stroke admitted to an inpatient rehabilitation facility completed simultaneous electroencephalography (EEG) and electromyography (EMG) recordings during a grip task. Corticospinal tract (CST) injury and integrity were computed. CMC measurements involving electrodes overlying ipsilesional motor areas and affected upper-extremity musculature were computed in frequency bands relevant to neural injury (delta, 1-3 Hz) and motor function (low beta, 13-19 Hz; high beta, 20-30 Hz). Correlational analyses were performed to ascertain relationships between structural and coherence measurements. Analyses were repeated for CST injury and integrity subgroups. Of the 30 individuals enrolled, EEG data from 21 individuals who completed the task were analyzed (10 females; 67.9±9.8 years; 11.3±4.1 days post-stroke). No significant structure-function associations were observed across the group. However, in the mild-moderate CST injury subgroup (n=11), greater injury correlated with higher coherence between electrodes overlying the supplementary motor area and affected extensor digitorum (high beta: ρ=0.83, p=0.001). Similarly, in the higher CST integrity subgroup (n=9), CST integrity related to coherence between electrodes overlying the ipsilesional primary motor cortex and affected biceps (low beta: r=0.94, p=0.0001). Findings exclusive to CST injury/integrity subgroups underscore the complexity of structure-function relationships post-stroke. Associations between CMC measures in motor-relevant frequency bands with measures reflecting CST microstructure suggest that structural injury modulates task-based corticomuscular connectivity. The identification of specific cortical regions and muscles depicts varying adaptive and/or compensatory neuroplastic-like mechanisms, providing mechanistic insights that could inform rehabilitation strategies to optimize recovery.
Keywords: Stroke, structural injury, task-based corticomuscular connectivity, corticomuscular coherence, CMC, Electroencephalography, EEG, Electromyography
Received: 24 Jun 2025; Accepted: 13 Oct 2025.
Copyright: © 2025 Gangwani, Mark, Huang and Cassidy. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Jessica M Cassidy, jcassidy@med.unc.edu
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