Sources of linear and non-linear synchrony between brain and muscles: linear and non-linear CMC sources
Fecha
2020Autor
Versión
Acceso abierto / Sarbide irekia
Tipo
Contribución a congreso / Biltzarrerako ekarpena
Versión
Versión aceptada / Onetsi den bertsioa
Identificador del proyecto
ES/1PE/TIN2016-77356-P
Impacto
|
10.1109/BCI48061.2020.9061667
Resumen
This manuscript shows that it is possible to find distinct sources of brain activity, at similar frequencies, arising from linear and non-linear interactions of the brain with the muscular system. Those sources were obtained by maximizing coherence between multivariate signals recorded from brain and a single channel from the muscles. To find linear phase synchrony we used unrectified electromyog ...
[++]
This manuscript shows that it is possible to find distinct sources of brain activity, at similar frequencies, arising from linear and non-linear interactions of the brain with the muscular system. Those sources were obtained by maximizing coherence between multivariate signals recorded from brain and a single channel from the muscles. To find linear phase synchrony we used unrectified electromyographic recordings, whereas to de-mix nonlinear sources, we used rectified muscular measurements. In order to obtain the brain sources, we employed a recently published method called 'cacoh' that is able to maximize coherence over the complete frequency range of interest and simultaneously find patterns of sources for each them. Our results show that cortico-muscular interactions even at the same frequency range can have spatially distinct neuronal sources depending on whether interactions had linear or non-linear character. [--]
Materias
Linear interactions,
Non-linear interactions,
Corticomuscular coherence,
Brain activity,
Muscular activity
Editor
IEEE
Publicado en
The 8th International Winter Conference on Brain-Computer Interface: Feb. 26-28, 2020, High 1 Resort, Korea. Piscataway: IEEE, 2020, pp. 1-5. ISBN 978-1-7281-4707-9
Departamento
Universidad Pública de Navarra. Departamento de Estadística, Informática y Matemáticas /
Nafarroako Unibertsitate Publikoa. Estatistika, Informatika eta Matematika Saila
Versión del editor
Entidades Financiadoras
C.V gratefully acknowledges funding from MINECO, RYC-2014-15671, G.N. was partially sponsored by DFG, SFB936 Z3 and TRR169, B4. V.V.N funding is from HSE Basic Research Program, Russian Academic Excellence Project ’5-100’.
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