A comparison of ICA-based artifact reduction methods for MEG

Introduction In the analysis of MEG data one often faces the problem that noise from biological or technical origins (e.g. alpha activity or interference from the power line, respectively) is corrupting the measurements. We present a case study where we analyze the effects of artifact removal for a well-known experimental setting: measurements of somatosensory evoked fields (SEF, N20). We compare a classical signal processing approach to the recently developed independent component analysis (ICA) technology [9, 11]. The specific data set studied is an attractive testbed since the signal of interest (N20) is relatively strong, but contaminated by a 150 Hz component due to power line interference. 2 Methods 2.1 Data The right median nerve was stimulated electrically over 12000 epochs, while the magnetic field above the contralateral somatosensory cortex was measured by the Berlin 49 channel planar gradiometer system placed in a magnetically shielded room. A sampling rate of 2 kHz and