The fMRI technique is particularly powerful in mapping correlates of mental states, another veryattractive feature for psychiatry, which deals predominantly with altered states of thought,

emotion, and behavior. For example, fMRI scans acquired from patients with chronic schizophrenia during the experience of auditory verbal hallucinations have revealed activation in the auditory cortex, very similar to that during stimulation with actual sounds.1 Beyond their major contribution to the understanding of the brain correlates of psyche-pathology, fMRI studies have Inhibitors,research,lifescience,medical also informed our understanding of the effects of risk genes on cognitive and affective networks.2 These important research contributions have led to strategies for the

development of fMRI paradigms for diagnostic, prognostic, or therapeutic use in mental disorders, and are reviewed in the September 2013 issue Inhibitors,research,lifescience,medical of Dialogues in Clinical Neuroscience (http://www.dialogues-cns.org/wp-content/themes/dcnsv2/publication.php?volume=15&issue=3) . Whereas concerns about power and reliability3 have dampened hopes for imminent diagnostic uses of functional Inhibitors,research,lifescience,medical imaging, there has recently been a surge of interest in a potential therapeutic application of fMRI-based neurofeedback (fMRI-NF). Imaging-based neurofeedback follows similar principles as other neuro- or Inhibitors,research,lifescience,medical biofeedback approaches. During neurofeedback training, participants receive feedback on their brain activity in real time and are instructed to change this activation. In the case of fMRI-NF, the feedback signal is computed from a real-time analysis of the time better course of the blood oxygenation level-dependent (BOLD) signal .(Figure 1) Thus, fMRI-NF can presently only be conducted while participants are in a magnetic resonance system.

The signal can be based on the average Inhibitors,research,lifescience,medical time course of an individual area (such as the left primary motor cortex or the right amygdala) or even on the time course of a single voxel anywhere in the brain (although this would make it rather susceptible to noise). However, it can also be based on results of more complex computations, such as the activation difference or correlation between two areas, or the output of a multivariate pattern classification algorithm. Unlike electrophysiological neurofeedback techniques, GSK-3 such as EEG (electroencephalography), the fMRI technique cannot provide truly “real-time” feedback because of the ”hemodynamic“ delay of =5 seconds between the actual neural activity and the vascular response that creates the fMRI signal. However, this delay does not pose an obstacle to neurofeedback training when participants are informed of it:4 Figure 1. Basic diagram of a real-time functional magnetic resonance imaging brain-computer interface for neurofeedback.