Temporal Autocorrelation-Based Beamforming with MEG Neuroimaging Data

Most source reconstruction procedures are performed in terms of power comparison. However, in the presence of voxel-specific noises, the direct power analysis can be misleading due to the power distortion as suggested by our multiple trial MEG study on a face-perception experiment.

To tackle the issue, we propose a temporal autocorrelation-based method for the above analysis. The new method improves the face-perception analysis and identifies several differences between neuronal responses to face and scrambled-face stimuli. By the simulated and real data analyses, we demonstrate that compared to the existing methods, the new proposal can be more robust to voxel-specific noises without compromising on its accuracy in source localization.