Separation and localisation of P300 sources and their subcomponents using constrained blind source separation

Authors:
Loukianos Spyrou;Min Jing;Saeid Sanei;Alex Sumich
Affiliations:
The Centre of Digital Signal Processing, School of Engineering, Cardiff University, Cardiff, Wales, UK;The Centre of Digital Signal Processing, School of Engineering, Cardiff University, Cardiff, Wales, UK;The Centre of Digital Signal Processing, School of Engineering, Cardiff University, Cardiff, Wales, UK;The Brain Image Analysis Unit, Institute of Psychiatry, King's College Hospital, London, UK
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2007

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Abstract

Separation and localisation of P300 sources and their constituent subcomponents for both visual and audio stimulations is investigated in this paper. An effective constrained blind source separation (CBSS) algorithm is developed for this purpose. The algorithm is an extension of the Infomax BSS system for which a measure of distance between a carefully measured P300 and the estimated sources is used as a constraint. During separation, the proposed CBSS method attempts to extract the corresponding P300 signals. The locations of the corresponding sources are then estimated with some indeterminancy in the results. It can be seen that the locations of the sources change for a schizophrenic patient. The experimental results verify the statistical significance of the method and its potential application in the diagnosis and monitoring of schizophrenia.