Though technically possible, it is at present neither practical nor economically feasible to use neurofeedback to modify fMRI RSS. Furthermore, although fMRI provides high confidence in the identification of anatomical regions that contribute to the executive control and appetitive drive networks, it is unable to reflect the sequential neural activity underlying cognitive states of readiness or execution of a task due to the poor time resolution of the BOLD response, which at best is on the scale of hundreds of milliseconds, compared to the millisecond resolution of EEG. Converging evidence suggests that the fMRI BOLD response reflects the summed neural activity of several oscillatory EEG networks (for a review, see (Whitman et al., 2013)). These EEG networks may oscillate at multiple frequencies (e.g., theta, alpha, or gamma) and the activity of separate networks may vary as a function of cognitive states lasting only a few hundred milliseconds. fMRI networks involved in task processing are likely to be comprised of multiple oscillatory EEG networks reflecting both induced and evoked EEG responses, including those that derive from frequency-dependent changes in phase alignment
