Rejection of stimulus-related MEG artifacts using independent component analysis

Electro-gustatory (EG) stimuli have been used to investigate the gustatory information processing in the human brain with precise temporal and spatial accuracy. But this technique was not widely applicable to magnetoencephalographic measurements due to the difficulty in eliminating huge stimulus-related artifact. In this study, we used independent component decomposition of the measured signal to reject the stimulus-related artifact from other brain activities based on information maximization (infomax) approach. Infomax ICA was applied to raw MEG data measured by 122 magnetometer channels producing 122 temporally independent components, and the trials for each component were averaged separately. Each independent component was visually inspected and the components obviously representing the EG stimulus-related artifacts were excluded from remixing and the signal projection onto the original MEG signal space to reconstruct the artifact-free MEG signals. Results showed that large EG stimulus-related artifacts were clearly removed from MEG waveforms. We were also able to separate blink-related components and magnetocardiographic components as well as the components representing alpha-band (8-13 Hz) spontaneous brain activity.