Performance of Prewhitening Beamforming in MEG Dual Experimental Conditions

This paper presents an analysis on the performance of the prewhitening beamformer when applied to magnetoencephalography (MEG) experiments involving dual (task and control) conditions. We first analyze the method's robustness to two types of violations of the prerequisites for the prewhitening method that may arise in real-life two-condition experiments. In one type of violation, some sources exist only in the control condition but not in the task condition. In the other type of violation, some signal sources exist both in the control and the task conditions, and that they change intensity between the two conditions. Our analysis shows that the prewhitening method is very robust to these nonideal conditions. In this paper, we also present a theoretical analysis showing that the prewhitening method is considerably insensitive to overestimation of the signal-subspace dimensionality. Therefore, the prewhitening beamformer does not require accurate estimation of the signal subspace dimension. Results of our theoretical analyses are validated in numerical experiments and in experiments using a real MEG data set obtained during self-paced hand movements.