Decoding the neural correlates of consciousness.
OBJECTIVE
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.


RESULTS
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.


CONCLUSIONS
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.
Weil
Rimona S
RS
Wellcome Trust Centre for Neuroimaging at UCL, Institute of Neurology, University College London, London, UK. r.weil@fil.ion.ucl.ac.uk
Rees
Geraint
G
D003243:Consciousness / Q000145:classification* / Q000502:physiology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods* / Q000639:trends; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000639:trends; D009474:Neurons / Q000145:classification* / Q000502:physiology*; D010363:Pattern Recognition, Automated / Q000379:methods* / Q000639:trends