Decoding Steady-State Visual Evoked Potentials From Electrocorticography

Frontiers in Neuroinformatics

Dirk Van Roost¹  Benjamin Wittevrongel²  Marc M. Van Hulle²  Mansoureh Fahimi Hnazaee²  Elvira Khachatryan²  Flavio Camarrone²  Leen De Taeye³  Alfred Meurs³  Paul Boon³  Evelien Carrette³ 

[1] Department of Neurosurgery, Ghent University Hospital, Ghent, Belgium;Laboratory for Neuro- and Psychophysiology, Department of Neurosciences, KU Leuven, Leuven, Belgium;Laboratory of Clinical and Experimental Neurophysiology, Neurology Department, Ghent University Hospital, Ghent, Belgium;

关键词: BCI;    ECoG;    scalp-EEG;    SSVEP;    decoding;    beamforming;   

DOI  :  10.3389/fninf.2018.00065

来源: DOAJ

【 摘 要 】

We report on a unique electrocorticography (ECoG) experiment in which Steady-State Visual Evoked Potentials (SSVEPs) to frequency- and phase-tagged stimuli were recorded from a large subdural grid covering the entire right occipital cortex of a human subject. The paradigm is popular in EEG-based Brain Computer Interfacing where selectable targets are encoded by different frequency- and/or phase-tagged stimuli. We compare the performance of two state-of-the-art SSVEP decoders on both ECoG- and scalp-recorded EEG signals, and show that ECoG-based decoding is more accurate for very short stimulation lengths (i.e., less than 1 s). Furthermore, whereas the accuracy of scalp-EEG decoding benefits from a multi-electrode approach, to address interfering EEG responses and noise, ECoG decoding enjoys only a marginal improvement as even a single electrode, placed over the posterior part of the primary visual cortex, seems to suffice. This study shows, for the first time, that EEG-based SSVEP decoders can in principle be applied to ECoG, and can be expected to yield faster decoding speeds using less electrodes.

【 授权许可】

Unknown