© PHOTO CREDIT © STOCKBYTE & DIGITAL VISION B rain-computer interfaces (BCIs) utilize neurophysiological signals originating in the brain to activate or deactivate external devices or computers [1]. Different neuroelec- tric signals have been used to control external devices, including EEG oscillations, electrocorticograms (ECoGs) from implanted electrodes, event-related potentials (ERPs) such as the P300 and slow cortical potential (SCP), short latency subcortical potentials and visually evoked potentials, and action potential spike trains from implanted multi- electrodes. In comparison, the development of BCIs based on metabolic activity of the brain using two different imaging methods, functional magnetic resonance imaging (fMRI) [2] and functional near infrared spectroscopy [3], has been more recent. fMRI is a noninvasive technique that measures the task-induced blood oxygen level-dependent (BOLD) changes correlating with neuronal activity in the brain [4]. Further progress has been made in real-time fMRI since the first description of the method by Cox et al., [5]. In contrast to conventional fMRI, which allows analysis of images only after the scan is finished, real-time fMRI fMRI Brain-Computer Interfaces [ A tutorial on methods and applications ] [ Ranganatha Sitaram, Nikolaus Weiskopf, Andrea Caria, Ralf Veit, Michael Erb, and Niels Birbaumer ] Digital Object Identifier 10.1109/MSP.2007.910456 1053-5888/08/$25.00©2008IEEE IEEE SIGNAL PROCESSING MAGAZINE [95] JANUARY 2008