Selective attention to visual-spatial stimuli causes decrements of power in alpha band and increments in beta. For steady-state visual evoked potentials (SSVEP) selective attention affects electroencephalogram (EEG) recordings, modulating the power in the range 8-27 Hz. The same behaviour can be seen for auditory stimuli as well, although for auditory steady-state response (ASSR), it is not fully confirmed yet. The design of selective attention based braincomputer interfaces (BCIs) has two major advantages: First, no much training is needed. Second, if properly designed, a steady-state response corresponding to spectral peaks can be elicited, easy to filter and classify. In this paper we study the behaviour of Kohonen Maps as feature selector for a selective attention to auditory stimuli based BCI system. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Lopez, M. A., Pomares, H., Damas, M., Prieto, A., & De La Hernandez, E. M. P. (2007). Use of Kohonen Maps as feature selector for selective attention brain-computer interfaces. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4527 LNCS, pp. 407–415). Springer Verlag. https://doi.org/10.1007/978-3-540-73053-8_41
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