Multivariate pattern analysis and the search for neural representations

Multivariate pattern analysis, or MVPA, has become one of the most popular analytic methods in cognitive neuroscience. Since its inception, MVPA has been heralded as offering much more than regular univariate analyses, for-we are told-it not only can tell us which brain regions are engaged while processing particular stimuli, but also which patterns of neural activity represent the categories the stimuli are selected from. We disagree, and in the current paper we offer four conceptual challenges to the use of MVPA to make claims about neural representation. Our view is that the use of MVPA to make claims about neural representation is problematic.

Automated summary

MVPA, a popular analytic method in cognitive neuroscience, is believed to offer more information than regular univariate analyses. However, this paper challenges the use of MVPA to make claims about neural representation, suggesting it is problematic.