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dc.contributor.author
Fló, Emilia  
dc.contributor.author
Fraiman Borrazás, Daniel Edmundo  
dc.contributor.author
Sitt, Jacobo Diego  
dc.date.available
2025-09-02T13:02:03Z  
dc.date.issued
2025-02  
dc.identifier.citation
Fló, Emilia; Fraiman Borrazás, Daniel Edmundo; Sitt, Jacobo Diego; Assessing brain-muscle networks during motor imagery to detect covert command-following; BioMed Central; Bmc Medicine; 23; 1; 2-2025; 1-22  
dc.identifier.issn
1741-7015  
dc.identifier.uri
http://hdl.handle.net/11336/270149  
dc.description.abstract
Background: In this study, we evaluated the potential of a network approach to electromyography and electroencephalography recordings to detect covert command-following in healthy participants. The motivation underlying this study was the development of a diagnostic tool that can be applied in common clinical settings to detect awareness in patients that are unable to convey explicit motor or verbal responses, such as patients that sufer from disorders of consciousness (DoC). Methods: We examined the brain and muscle response during movement and imagined movement of simple motor tasks, as well as during resting state. Brain-muscle networks were obtained using non-negative matrix factorization (NMF) of the coherence spectra for all the channel pairs. For the 15/38 participants who showed motor imagery, as indexed by common spatial flters and linear discriminant analysis, we contrasted the confguration of the networks during imagined movement and resting state at the group level, and subject-level classifers were implemented using as features the weights of the NMF together with trial-wise power modulations and heart response to classify resting state from motor imagery. Results: Kinesthetic motor imagery produced decreases in the mu-beta band compared to resting state, and a small correlation was found between mu-beta power and the kinesthetic imagery scores of the Movement Imagery Questionnaire-Revised Second version. The full-feature classifers successfully distinguished between motor imagery and resting state for all participants, and brain-muscle functional networks did not contribute to the overall classifcation. Nevertheless, heart activity and cortical power were crucial to detect when a participant was mentally rehearsing a movement. Conclusions: Our work highlights the importance of combining EEG and peripheral measurements to detect command-following, which could be important for improving the detection of covert responses consistent with volition in unresponsive patients.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
BioMed Central  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by/2.5/ar/  
dc.subject
Brain-muscle networks  
dc.subject
Motor imagery  
dc.subject
EEG  
dc.subject
Disorders of consciousness  
dc.subject.classification
Otras Ciencias Físicas  
dc.subject.classification
Ciencias Físicas  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
Assessing brain-muscle networks during motor imagery to detect covert command-following  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2025-09-02T12:38:21Z  
dc.journal.volume
23  
dc.journal.number
1  
dc.journal.pagination
1-22  
dc.journal.pais
Reino Unido  
dc.journal.ciudad
Londres  
dc.description.fil
Fil: Fló, Emilia. Sorbonne University; Francia  
dc.description.fil
Fil: Fraiman Borrazás, Daniel Edmundo. Universidad de San Andrés. Departamento de Matemáticas y Ciencias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina  
dc.description.fil
Fil: Sitt, Jacobo Diego. Sorbonne University; Francia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina  
dc.journal.title
Bmc Medicine  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-025-03846-0  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1186/s12916-025-03846-0