Multivariate pattern analysis and the search for neural representations

Synthese 199 (5-6):12869-12889 (2021)
  Copy   BIBTEX

Abstract

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.

Author's Profile

Felipe De Brigard
Duke University

Analytics

Added to PP
2021-08-05

Downloads
876 (#15,713)

6 months
156 (#20,829)

Historical graph of downloads since first upload
This graph includes both downloads from PhilArchive and clicks on external links on PhilPapers.
How can I increase my downloads?