TMS based lower extremity multi-muscle motor mapping in persons post-stroke with impaired muscle coordination

Srivastava, Shraddha; Kindred, John H.; Cash, Jasmine; Seamon, Bryant A.; Bowden, Mark G.; Kautz, Steven A.

doi:10.1016/j.brs.2021.10.203

Cited by 1 publication

(1 citation statement)

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“…In general, movement is the co-excitation and coordination of multiple independent muscle groups [1], for instance, by exploring the muscle synergy and coupling for a single finger, Liu et al studied the muscle-finger system and found multiple muscles actuated one single finger simultaneously [2], and by mimicking related muscle synergies, they further achieved the real-time estimation of finger energy [3]. Furthermore, multiple brain regions have also confirmed their respective contributions (e.g.…”

Section: Introductionmentioning

confidence: 99%

Dynamic corticomuscular multi-regional modulations during finger movement revealed by time-varying network analysis

Zhang¹,

Zhang²,

Lü³

et al. 2022

J. Neural Eng.

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Objective. A body movement involves the complicated information exchange between the central and peripheral systems, which is characterized by the dynamical coupling patterns between the multiple brain areas and multiple muscle units. How the central and peripheral nerves coordinate multiple internal brain regions and muscle groups is very important when accomplishing the action. Approach. In this study, we extend the adaptive directed transfer function to construct the time-varying networks between multiple corticomuscular regions and divide the movement duration into different stages by the time-varying corticomuscular network patterns. Main results. The inter dynamical corticomuscular network demonstrated the different interaction patterns between the central and peripheral systems during the different hand movement stages. The muscles transmit bottom-up movement information in the preparation stage, but the brain issues top-down control commands and dominates in the execution stage, and finally, the brain's dominant advantage gradually weakens in the relaxation stage. When classifying the different movement stages based on time-varying corticomuscular network indicators, an average accuracy above 74% could be reliably achieved. Significance. The findings of this study help deepen our knowledge of central-peripheral nerve pathways and coordination mechanisms, and also provide opportunities for monitoring and regulating movement disorders.

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Section: Introductionmentioning

confidence: 99%