title: L1-penalized N-way PLS for subset of electrodes selection in BCI experiments.
abstract: Recently, the N-way partial least squares (NPLS) approach was reported as an effective tool for neuronal signal decoding and brain-computer interface (BCI) system calibration. This method simultaneously analyzes data in several domains. It combines the projection of a data tensor to a low dimensional space with linear regression. In this paper the L1-Penalized NPLS is proposed for sparse BCI system calibration, allowing uniting the projection technique with an effective selection of subset of features. The L1-Penalized NPLS was applied for the binary self-paced BCI system calibration, providing selection of electrodes subset. Our BCI system is designed for animal research, in particular for research in non-human primates.
authors: Foundation Nanosciences, Grenoble, France.
authors: Andrey
authors: A
authors: Eliseyev
authors: Cecile
authors: C
authors: Moro
authors: Jean
authors: J
authors: Faber
authors: Alexander
authors: A
authors: Wyss
authors: Napoleon
authors: N
authors: Torres
authors: Corinne
authors: C
authors: Mestais
authors: Alim Louis
authors: AL
authors: Benabid
authors: Tetiana
authors: T
authors: Aksenova
mesh_terms: D000818:Animals; D062207:Brain-Computer Interfaces; D004566:Electrodes; D004569:Electroencephalography / Q000295:instrumentation* / Q000379:methods*; D000882:Haplorhini; D006801:Humans; D016018:Least-Squares Analysis