A time-frequency analysis of the EEG evoked by negative and positive visual stimuli

Abstract

As a first step to discriminate between Yes and No, which are the most elementary expressions in communication between human beings, we distinguish likes from dislikes (emotional Yes and No). For this purpose, we perform a time-frequency analysis of the EEG evoked by negative and positive visual stimuli. We calculate the asymmetry ratio as a function of time in subbands of /spl theta/, /spl alpha/ and /spl beta/. From the change (increase or decrease) of the asymmetry ratio in specific subbands at early time (/spl sim/1s), we obtain a very simple classification rule, which is appropriate for the real-time application. We also train an artificial neural network with input patterns considering all the subbands.