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Abstract:
During the last 20 years several paradigms for Brain Computer Interfaces have been proposed
see [1] for a recent review. They can be divided into (a) stimulus-driven paradigms, using e.g.
event-related potentials or visual evoked potentials from an EEG signal, and (b) patient-driven
paradigms such as those that use premotor potentials correlated with imagined action, or slow
cortical potentials (e.g. [2]).
Our aim is to develop a stimulus-driven paradigm that is applicable in practice to patients.
Due to the unreliability of visual perception in locked-in patients in the later stages of disorders
such as Amyotrophic Lateral Sclerosis, we concentrate on the auditory modality. Speci-
cally, we look for the effects, in the EEG signal, of selective attention to one of two concurrent
auditory stimulus streams, exploiting the increased activation to attended stimuli that is seen
under some circumstances [3].
We present the results of our preliminary experiments on normal subjects. On each of
400 trials, two repetitive stimuli (sequences of drum-beats or other pulsed stimuli) could be
heard simultaneously. The two stimuli were distinguishable from one another by their acoustic
properties, by their source location (one from a speaker to the left of the subject, the other from
the right), and by their differing periodicities. A visual cue preceded the stimulus by 500 msec,
indicating which of the two stimuli to attend to, and the subject was instructed to count the
beats in the attended stimulus stream. There were up to 6 beats of each stimulus: with equal
probability on each trial, all 6 were played, or the fourth was omitted, or the fth was omitted.
The 40-channel EEG signals were analyzed ofine to reconstruct which of the streams was
attended on each trial. A linear Support Vector Machine [4] was trained on a random subset of
the data and tested on the remainder. Results are compared from two types of pre-processing
of the signal: for each stimulus stream, (a) EEG signals at the stream's beat periodicity are
emphasized, or (b) EEG signals following beats are contrasted with those following missing
beats. Both forms of pre-processing show promising results, i.e. that selective attention to
one or the other auditory stream yields signals that are classiable signicantly above chance
performance. In particular, the second pre-processing was found to be robust to reduction in
the number of features used for classication (cf. [5]), helping us to eliminate noise.
