The multifaceted technological challenge of acquiring simultaneous EEG-correlated fMRI data has now been met and the potential exists for mapping electrophysiological activity with unprecedented spatio-temporal resolution. Work has already begun on studying a host of spontaneous EEG phenomena ranging from alpha rhythm and sleep patterns to epileptiform discharges and seizures, with far reaching clinical implications. However, the transformation of EEG data into linear models suitable for voxel-based statistical hypothesis testing is central to the endeavour. This in turn is predicated upon a number of assumptions regarding the manner in which the generators of EEG phenomena may engender changes in the blood oxygen level dependent (BOLD) signal. Furthermore, important limitations are posed by a set of considerations quite unique to 'paradigmless fMRI'. Here, these issues are assembled and explored to provide an overview of progress made and unresolved questions, with an emphasis on applications in epilepsy.