Niël le Roux, Pieter Schoonees (Erasmus University)
This research focuses on methods for assessing the similarity of brain responses within and across subjects (individuals). Typically, the data comes from fMRI or EEG studies, and concern spatiotemporal measures of brain activity while the subject is exposed to some stimulus. A particular focus of these studies is on naturalistic stimuli, which typically means video content such as television and films. This is an important departure from traditional neuroimaging studies where subjects perform simple tasks multiple times in a highly controlled setting. fMRI offers high spatial resolution through dividing the brain into many voxels, but this comes at the cost of lower temporal resolution as it takes roughly two seconds to complete a single scan of the brain. In contrast, EEG trades spatial resolution for high temporal resolution. In EEG, a limited number of electrodes (e.g., 64) are placed on the scalp to measure activity, but by sacrificing temporal resolution in this way measurements can be made several times a second (typically 256 of 512 times). Our focus is on the statistical analysis of EEG data. To this end we developed an extensive R-based EEG simulation statistical model for generating EEG data in a wide variety of controlled conditions. This allows us to evaluate statistical procedures currently in use in the field of analysing EEG data.