Decoding the neural correlates of consciousness.
Current Opinion in Neurology December 1, 2010 DOI: 10.1097/wco.0b013e32834028c7 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Review Peer reviewed |
|---|---|
| Key findings | MVPA reveals content-specific information at early stages of perceptual processing and can be used to reveal the contents of consciousness. |
Abstract
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.