Decoding of top-down cognitive processing for SSVEP-controlled BMI

Byoung-Kyong Min, Sven Dähne, Min Hee Ahn, Yung Kyun Noh, Klaus Muller

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

We present a fast and accurate non-invasive brain-machine interface (BMI) based on demodulating steady-state visual evoked potentials (SSVEPs) in electroencephalography (EEG). Our study reports an SSVEP-BMI that, for the first time, decodes primarily based on top-down and not bottom-up visual information processing. The experimental setup presents a grid-shaped flickering line array that the participants observe while intentionally attending to a subset of flickering lines representing the shape of a letter. While the flickering pixels stimulate the participant's visual cortex uniformly with equal probability, the participant's intention groups the strokes and thus perceives a 'letter Gestalt'. We observed decoding accuracy of 35.81% (up to 65.83%) with a regularized linear discriminant analysis; on average 2.05-fold, and up to 3.77-fold greater than chance levels in multi-class classification. Compared to the EEG signals, an electrooculogram (EOG) did not significantly contribute to decoding accuracies. Further analysis reveals that the top-down SSVEP paradigm shows the most focalised activation pattern around occipital visual areas; Granger causality analysis consistently revealed prefrontal top-down control over early visual processing. Taken together, the present paradigm provides the first neurophysiological evidence for the top-down SSVEP BMI paradigm, which potentially enables multi-class intentional control of EEG-BMIs without using gaze-shifting.

Original languageEnglish
Article number36267
JournalScientific Reports
Volume6
DOIs
Publication statusPublished - 2016 Nov 3

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Brain-Computer Interfaces
Visual Evoked Potentials
Electroencephalography
Electrooculography
Discriminant Analysis
Visual Cortex
Automatic Data Processing
Causality
Stroke

ASJC Scopus subject areas

  • General

Cite this

Decoding of top-down cognitive processing for SSVEP-controlled BMI. / Min, Byoung-Kyong; Dähne, Sven; Ahn, Min Hee; Noh, Yung Kyun; Muller, Klaus.

In: Scientific Reports, Vol. 6, 36267, 03.11.2016.

Research output: Contribution to journalArticle

Min, Byoung-Kyong ; Dähne, Sven ; Ahn, Min Hee ; Noh, Yung Kyun ; Muller, Klaus. / Decoding of top-down cognitive processing for SSVEP-controlled BMI. In: Scientific Reports. 2016 ; Vol. 6.
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