Beyond mind-reading: multi-voxel pattern analysis of fMRI data.
A key challenge for cognitive neuroscience is determining how mental representations map onto patterns of neural activity. Recently, researchers have started to address this question by applying sophisticated pattern-classification algorithms to distributed (multi-voxel) patterns of functional MRI data, with the goal of decoding the information that is represented in the subject's brain at a particular point in time. This multi-voxel pattern analysis (MVPA) approach has led to several impressive feats of mind reading. More importantly, MVPA methods constitute a useful new tool for advancing our understanding of neural information processing. We review how researchers are using MVPA methods to characterize neural coding and information processing in domains ranging from visual perception to memory search.
Norman
Kenneth A
KA
Department of Psychology, Princeton University, Green Hall, Washington Road, Princeton, NJ 08540, USA. knorman@princeton.edu
Polyn
Sean M
SM
Detre
Greg J
GJ
Haxby
James V
JV
D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000502:physiology*; D003071:Cognition / Q000502:physiology; D004193:Discrimination Learning / Q000502:physiology; D004569:Electroencephalography; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008568:Memory / Q000502:physiology; D008606:Mental Processes / Q000502:physiology*; D015999:Multivariate Analysis; D009949:Orientation / Q000502:physiology; D010363:Pattern Recognition, Automated; D010364:Pattern Recognition, Visual / Q000502:physiology; D012815:Signal Processing, Computer-Assisted; D014796:Visual Perception / Q000502:physiology