In this paper we used simultaneously-recorded EEG and fMRI during a simple visual oddball task. We investigate the relationship between neural correlates of processing task-relevant sensory stimuli and brain states reflective of inattention to the task and sensory input. We use the single-trial analysis methodology ofGoldman et al. (2009), whereby machine learning methods are used to find a maximally discriminative projection of the EEG data, and the single-trial variability of that projection is used to construct the BOLD fMRI univariate model. Previous studies of the BOLD correlates of single-trial event-related EEG variability have focused mainly on the P3 and only a few other well-known components at selected stimulus-locked latencies, and have often used an arbitrary selection of electrodes (Benar et al., 2007; Warbrick et al., 2009), and many have studied this coupling without regressing out the effect of the externally-observable reaction time variability.Eichele et al. (2005) were one of the first to investigate the spatio-temporal evolution for BOLD correlates of event-related potential (ERP) components spanning the entire trial. Their approach, applied to an auditory oddball paradigm, used ICA to denoise
