Título : Synchronization of Slow Cortical Rhythms During Motor Imagery-Based Brain–Machine Interface Control |
Autor : Badesa, Francisco Javier García Aracil, Nicolás Nann, Marius Barios, Juan A. Ezquerro, Santiago Bertomeu Motos, Arturo Fernández, Eduardo Soekadar, Surjo R. |
Editor : World Scientific Publishing |
Departamento: Departamentos de la UMH::Ingeniería de Sistemas y Automática |
Fecha de publicación: 2018 |
URI : https://hdl.handle.net/11000/31257 |
Resumen :
Modulation 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 strok
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Palabras clave/Materias: Slow rhythms synchronization EEG coherence motor imagery BMI |
Tipo documento : application/pdf |
Derechos de acceso: info:eu-repo/semantics/closedAccess Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
DOI : https://doi.org/10.1142/S0129065718500454 |
Aparece en las colecciones: Artículos Ingeniería de Sistemas y Automática
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