Real-Time fMRI and Neurofeedback

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Recent progress in computer hard- and software allows real-time analysis of fMRI data, providing the basis for brain-computer interface (BCI) applications such as neurofeedback, control of external devices and motor-independent communication. In neurofeedback studies, subjects can see different kinds of representations of their own brain activity while they are being measured in the MRI scanner. FMRI-based Neurofeedback is performed by reading, analysing and visualising the hemodynamic brain signals in real-time during an ongoing experiment. This real-time approach is in contrast to the standard analysis approach in which the huge amount of incoming fMRI signals are recorded first and then analysed hours or days after the experiment. During this course, there will be a discussion of fMRI neurofeedback applications which have demonstrated that with sufficient practice, subjects are indeed able to learn to modulate activity in certain brain areas. These results are extremely important for basic neuroscience research, because they allow researchers to study the degree to which the brain can modulate its own activity and to potentially unravel the function of hitherto unknown brain areas. Neurofeedback research also touches on deep philosophical issues, such as the neural correlates of free will. It might also be possible in the future to help people with pain or depression by regulating at will the activity in relevant brain areas. In fMRI-based communication studies, activation patterns evoked by participants are ‘decoded’ and interpreted online, e.g. as letters of the alphabet, offering the possibility for people with severe motor impairments to ‘write’ letters purely controlled by mental imagery. In this course, a number of online analysis strategies will be discussed for decoding mental states, including analysis of the mean signal of regions-of-interest (ROIs) and the use of pattern classifiers operating at the voxel level.