Decoding the neural correlates of consciousness

Purpose of review Multivariate pattern analysis (MVPA) is an emerging technique for analysing functional imaging data that is capable of a much closer approximation of neuronal activity than conventional methods. This review will outline the advantages, applications and limitations of MVPA in understanding the neural correlates of consciousness. Recent findings MVPA has provided important insights into the processing of perceptual information by revealing content-specific information at early stages of perceptual processing. It has also shed light on the processing of memories and decisions. In combination with techniques to reconstruct viewed images, MVPA can also be used to reveal the contents of consciousness. Summary The development of multivariate pattern analysis techniques allows content-specific and detailed information to be extracted from functional MRI data. This may lead to new therapeutic applications but also raises important ethical considerations.