Motion-related artefacts in EEG predict neuronally plausible patterns of activation in fMRI data.

ABSTRACT: The simultaneous acquisition and subsequent analysis of EEG and fMRI data is challenging owing to increased noise levels in the EEG data. A common method to integrate data from these two modalities is to use aspects of the EEG data, such as the amplitudes of event-related potentials (ERP) or oscillatory EEG activity, to predict fluctuations in the fMRI data. However, this relies on the acquisition of high quality datasets to ensure that only the correlates of neuronal activity are being studied. In this study, we investigate the effects of head-motion-related artefacts in the EEG signal on the predicted T2*-weighted signal variation. We apply our analyses to two independent datasets: 1) four participants were asked to move their feet in the scanner to generate small head movements, and 2)

SUBMITTER: Jansen M 

PROVIDER: S-EPMC3221044 | biostudies-literature | 2012 Jan

REPOSITORIES: biostudies-literature