The Effects of Subthreshold Vibratory Noise on Cortical Activity During Motor Imagery.
brain–computer interface
electroencephalography
event-related desynchronization
kinesthetic motor imagery
machine learning
vibratory stimulation
virtual reality
Journal
Motor control
ISSN: 1087-1640
Titre abrégé: Motor Control
Pays: United States
ID NLM: 9706297
Informations de publication
Date de publication:
01 Jul 2023
01 Jul 2023
Historique:
received:
18
05
2022
revised:
04
12
2022
accepted:
08
01
2023
medline:
28
6
2023
pubmed:
22
2
2023
entrez:
21
2
2023
Statut:
epublish
Résumé
Previous studies have demonstrated that both visual and proprioceptive feedback play vital roles in mental practice of movements. Tactile sensation has been shown to improve with peripheral sensory stimulation via imperceptible vibratory noise by stimulating the sensorimotor cortex. With both proprioception and tactile sensation sharing the same population of posterior parietal neurons encoding within high-level spatial representations, the effect of imperceptible vibratory noise on motor imagery-based brain-computer interface is unknown. The objective of this study was to investigate the effects of this sensory stimulation via imperceptible vibratory noise applied to the index fingertip in improving motor imagery-based brain-computer interface performance. Fifteen healthy adults (nine males and six females) were studied. Each subject performed three motor imagery tasks, namely drinking, grabbing, and flexion-extension of the wrist, with and without sensory stimulation while being presented a rich immersive visual scenario through a virtual reality headset. Results showed that vibratory noise increased event-related desynchronization during motor imagery compared with no vibration. Furthermore, the task classification percentage was higher with vibration when the tasks were discriminated using a machine learning algorithm. In conclusion, subthreshold random frequency vibration affected motor imagery-related event-related desynchronization and improved task classification performance.
Identifiants
pubmed: 36801814
doi: 10.1123/mc.2022-0061
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM