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Brain-computer interfacing using modulations of alpha activity induced by covert shifts of attention

TREDER MS; BAHRAMISHARIF A; SCHMIDT NM; VAN GERVEN MA; BLANKERTZ B
J NEUROENG REHABIL , 2011, vol. 8, n° MAY, p. 24
Doc n°: 158887
Localisation : en ligne

D.O.I. : http://dx.doi.org/DOI:10.1186/1743-0003-8-24
Descripteurs : AF1 - ETUDES GENERALES - ENCEPHALE

Visual brain-computer interfaces (BCIs) often yield high performance
only when targets are fixated with the eyes. Furthermore, many paradigms use
intense visual stimulation, which can be irritating especially in long BCI
sessions. However, BCIs can more directly directly tap the neural processes
underlying visual attention. Covert shifts of visual attention induce changes in
oscillatory alpha activity in posterior cortex, even in the absence of visual
stimulation. The aim was to investigate whether different pairs of directions of
attention shifts can be reliably differentiated based on the
electroencephalogram. To this end, healthy participants (N = 8) had to strictly
fixate a central dot and covertly shift visual attention to one out of six cued
directions. RESULTS: Covert attention shifts induced a prolonged alpha
synchronization over posterior electrode sites (PO and O electrodes). Spectral
changes had specific topographies so that different pairs of directions could be
differentiated. There was substantial variation across participants with respect
to the direction pairs that could be reliably classified. Mean accuracy for the
best-classifiable pair amounted to 74.6%. Furthermore, an alpha power index
obtained during a relaxation measurement showed to be predictive of peak BCI
performance (r = .66). CONCLUSIONS: Results confirm posterior alpha power
modulations as a viable input modality for gaze-independent EEG-based BCIs. The
pair of directions yielding optimal performance varies across participants.
Consequently, participants with low control for standard directions such as
left-right might resort to other pairs of directions including top and bottom.
Additionally, a simple alpha index was shown to predict prospective BCI
performance.

Langue : ANGLAIS

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