Evidence map›Paper›PMID 42037329›Full record

ArticleSheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi2026

[Gait event-driven dynamic changes in brain-muscle networks and neuromuscular coordination mechanisms].

Xiaoguang Liu, Aoqi Guo, Tie Liang, Xiuling Liu, Liang Qin

Abstract readEnglish Abstract
In one paragraph

Article in Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Xiaoguang LiuCollege of Electronic Information Engineering, Hebei University, Baoding, Hebei 071002, P. R. China.
Aoqi GuoCollege of Electronic Information Engineering, Hebei University, Baoding, Hebei 071002, P. R. China.
Tie LiangCollege of Electronic Information Engineering, Hebei University, Baoding, Hebei 071002, P. R. China.
Xiuling LiuCollege of Electronic Information Engineering, Hebei University, Baoding, Hebei 071002, P. R. China.
Liang QinDivision of Rehabilitation Medicine, ​The Affiliated Hospital of Hebei University, Baoding, Hebei 071002, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Walking is a fundamental component of daily human activity, in which orderly execution of key gait events [such as heel strike (HS) and toe-off (TO) ] is essential for maintaining gait coordination and stability. However, the underlying brain-muscle neural coordination mechanisms associated with these events remain unclear. In this study, electroencephalography (EEG) signals from 19 channels and surface electromyography (sEMG) signals from 14 lower-limb muscles were synchronously recorded from 18 healthy participants during steady-state walking at a constant speed of 3.2 km/h. Brain-muscle connectivity networks were constructed using the adaptive directed transfer function (ADTF), and the dynamic connectivity characteristics associated with HS and TO events were quantitatively analyzed. The results showed that brain-muscle connectivity was strongest in the β frequency band. Intra-brain (EEG-EEG), brain-to-muscle (EEG-sEMG), and intra-muscle (sEMG-sEMG) connections were significantly stronger than muscle-to-brain (sEMG-EEG) connections. At both HS and TO events, information exchange between frontal-central cortical regions and the muscles of the supporting leg was markedly enhanced. Furthermore, compared with TO, the brain-muscle network at HS exhibited higher clustering coefficient, global efficiency, and betweenness centrality. These findings suggest that brain-muscle interactions during walking are predominantly mediated in the β band and dynamically modulated by gait events. Accurate characterization of gait event-related brain-muscle connectivity may provide important technical support for clarifying the neuromuscular coordination mechanisms underlying fine gait control.

Indexed as

BrainGaitMuscle, SkeletalNerve NetWalkingAdultElectroencephalographyElectromyographyFemaleHumansMaleAdaptive directed transfer functionBrain-muscle networkDynamic connectionGait event

Identifiers

PMID42037329
PMCPMC13112238

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.