Multivariate pattern analysis and the search for neural representations

Journal Article (Journal Article)

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.

Full Text

Duke Authors

Cited Authors

  • Gessell, B; Geib, B; De Brigard, F

Published Date

  • January 1, 2021

Published In

Electronic International Standard Serial Number (EISSN)

  • 1573-0964

International Standard Serial Number (ISSN)

  • 0039-7857

Digital Object Identifier (DOI)

  • 10.1007/s11229-021-03358-3

Citation Source

  • Scopus