Decoding Saccadic Directions Using Epidural ECoG in Non-Human Primates
Journal of Korean Medical Science
;
: 1243-1250, 2017.
Article
Dans Anglais
| WPRIM
| ID: wpr-210880
ABSTRACT
A brain-computer interface (BCI) can be used to restore some communication as an alternative interface for patients suffering from locked-in syndrome. However, most BCI systems are based on SSVEP, P300, or motor imagery, and a diversity of BCI protocols would be needed for various types of patients. In this paper, we trained the choice saccade (CS) task in 2 non-human primate monkeys and recorded the brain signal using an epidural electrocorticogram (eECoG) to predict eye movement direction. We successfully predicted the direction of the upcoming eye movement using a support vector machine (SVM) with the brain signals after the directional cue onset and before the saccade execution. The mean accuracies were 80% for 2 directions and 43% for 4 directions. We also quantified the spatial-spectro-temporal contribution ratio using SVM recursive feature elimination (RFE). The channels over the frontal eye field (FEF), supplementary eye field (SEF), and superior parietal lobule (SPL) area were dominantly used for classification. The α-band in the spectral domain and the time bins just after the directional cue onset and just before the saccadic execution were mainly useful for prediction. A saccade based BCI paradigm can be projected in the 2D space, and will hopefully provide an intuitive and convenient communication platform for users.
Texte intégral:
Disponible
Indice:
WPRIM (Pacifique occidental)
Sujet Principal:
Lobe pariétal
/
Primates
/
Tétraplégie
/
Saccades
/
Encéphale
/
Classification
/
Haplorhini
/
Signaux
/
Mouvements oculaires
/
Machine à vecteur de support
Limites du sujet:
Humains
langue:
Anglais
Texte intégral:
Journal of Korean Medical Science
Année:
2017
Type:
Article
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