Literature DB >> 33900919

Alterations in Muscle Networks in the Upper Extremity of Chronic Stroke Survivors.

Michael Houston, Xiaoyan Li, Ping Zhou, Sheng Li, Jinsook Roh, Yingchun Zhang.   

Abstract

Muscle networks describe the functional connectivity between muscles quantified through the decomposition of intermuscular coherence (IMC) to identify shared frequencies at which certain muscles are co-modulated by common neural input. Efforts have been devoted to characterizing muscle networks in healthy subjects but stroke-linked alterations to muscle networks remain unexplored. Muscle networks were assessed for eight key upper extremity muscles during isometric force generation in stroke survivors with mild, moderate, and severe impairment and compared against healthy controls to identify stroke-specificalterations in muscle connectivity. Coherence matrices were decomposed using non-negative matrix factorization. The variance accounted for thresholding was then assessed to identify the number of muscle networks. Results showed that the number of muscle networks decreased in stroke survivors compared to age-matched healthy controls (four networks in the healthy control group) as the severity of post-stroke motor impairment increased (three in the mild- and two in the moderate- and severe-strokegroups). Statistically significant reductions of IMC in the synergistic deltoid muscles in the alpha-band in stroke patients versus healthy controls ( p < 0.05) were identified. This study represents the first effort, to the best of our knowledge, to assess stroke-linked alterations in functional intermuscular connectivity using muscle network analysis. The findings revealed a pattern of alterations to muscle networks in stroke survivors compared to healthy controls, as a result of the loss of brain function associated with the stroke. These alterations in muscle networks reflected underlying pathophysiology. These findings can help better understand the motor impairment and motor control in stroke and may advance rehabilitation efforts for stroke by identifying the impaired neuromuscular coordination among multiple muscles in the frequency domain.

Entities:  

Year:  2021        PMID: 33900919     DOI: 10.1109/TNSRE.2021.3075907

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  2 in total

1.  Myoelectric interface training enables targeted reduction in abnormal muscle co-activation.

Authors:  Marc W Slutzky; Jinsook Roh; Gang Seo; Ameen Kishta; Emily Mugler
Journal:  J Neuroeng Rehabil       Date:  2022-07-01       Impact factor: 5.208

2.  Alterations in motor modules and their contribution to limitations in force control in the upper extremity after stroke.

Authors:  Gang Seo; Sang Wook Lee; Randall F Beer; Amani Alamri; Yi-Ning Wu; Preeti Raghavan; William Z Rymer; Jinsook Roh
Journal:  Front Hum Neurosci       Date:  2022-07-28       Impact factor: 3.473

  2 in total

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