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dc.contributor.authorBadesa, Francisco Javier-
dc.contributor.authorGarcía Aracil, Nicolás-
dc.contributor.authorNann, Marius-
dc.contributor.authorBarios, Juan A.-
dc.contributor.authorEzquerro, Santiago-
dc.contributor.authorBertomeu Motos, Arturo-
dc.contributor.authorFernández, Eduardo-
dc.contributor.authorSoekadar, Surjo R.-
dc.contributor.otherDepartamentos de la UMH::Ingeniería de Sistemas y Automáticaes_ES
dc.date.accessioned2024-02-07T17:56:30Z-
dc.date.available2024-02-07T17:56:30Z-
dc.date.created2018-
dc.identifier.citationInternational Journal of Neural Systems, Vol. 29, No. 5 (2019) 1850045es_ES
dc.identifier.issn1793-6462-
dc.identifier.issn0129-0657-
dc.identifier.urihttps://hdl.handle.net/11000/31257-
dc.description.abstractModulation of sensorimotor rhythm (SMR) power, a rhythmic brain oscillation physiologically linked to motor imagery, is a popular Brain–Machine Interface (BMI) paradigm, but its interplay with slower cortical rhythms, also involved in movement preparation and cognitive processing, is not entirely understood. In this study, we evaluated the changes in phase and power of slow cortical activity in delta and theta bands, during a motor imagery task controlled by an SMR-based BMI system. In Experiment I, EEG of 20 right-handed healthy volunteers was recorded performing a motor-imagery task using an SMR-based BMI controlling a visual animation, and during task-free intervals. In Experiment II, 10 subjects were evaluated along five daily sessions, while BMI-controlling same visual animation, a buzzer, and a robotic hand exoskeleton. In both experiments, feedback received from the controlled device was proportional to SMR power (11–14 Hz) detected by a real-time EEG-based system. Synchronization of slow EEG frequencies along the trials was evaluated using inter-trial-phase coherence (ITPC). Results: cortical oscillations of EEG in delta and theta frequencies synchronized at the onset and at the end of both active and task-free trials; ITPC was significantly modulated by feedback sensory modality received during the tasks; and ITPC synchronization progressively increased along the training. These findings suggest that phase-locking of slow rhythms and resetting by sensory afferences might be a functionally relevant mechanism in cortical control of motor function. We propose that analysis of phase synchronization of slow cortical rhythms might also improve identification of temporal edges in BMI tasks and might help to develop physiological markers for identification of context task switching and practice-related changes in brain function, with potentially important implications for design and monitoring of motor imagery-based BMI systems, an emerging tool in neurorehabilitation of strokes_ES
dc.formatapplication/pdfes_ES
dc.format.extent14es_ES
dc.language.isoenges_ES
dc.publisherWorld Scientific Publishinges_ES
dc.rightsinfo:eu-repo/semantics/closedAccesses_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectSlow rhythmses_ES
dc.subjectsynchronizationes_ES
dc.subjectEEGes_ES
dc.subjectcoherencees_ES
dc.subjectmotor imageryes_ES
dc.subjectBMIes_ES
dc.titleSynchronization of Slow Cortical Rhythms During Motor Imagery-Based Brain–Machine Interface Controles_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://doi.org/10.1142/S0129065718500454es_ES
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