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
- December 1, 2021
Published In
Volume / Issue
- 199 / 5-6
Start / End Page
- 12869 - 12889
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