Head movements of children in MEG : quantification, effects on source estimation, and compensation

Abstract

Head movements during MEG recordings in children may lead to inaccurate localization of brain activity. In this thesis, we examined the effects of head movements on source estimation in twenty children performing a simple auditory cognitive task. In addition, we tested the ability of a recently introduced spherical harmonic expansion method, signal space separation (SSS), to compensate for the effects of head movements on two source models: equivalent current dipoles (ECDs) and minimum norm estimates (MNE). In the majority of subjects, the goodness-of-fit of ECDs fit to the peak of the auditory N100m response was increased following the SSS correction compared with the averaged forward solution method proposed earlier. The spatial spread of ECDs as determined with a bootstrapping approach was also reduced after SSS correction. In addition, the MNE source estimates were spatially sharpened following SSS application, indicative of an increase in signal to noise ratio. Together these results suggest that SSS is an effective method to compensate for head movements in MEG recordings in children.