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 pro...

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Detalles Bibliográficos
Publicado en:Synthese Vol. 199; no. 5/6; pp. 12869 - 12890
Autores principales: Gessell, Bryce, Geib, Benjamin, De Brigard, Felipe
Formato: Artículo
Publicado: Springer Nature Dec2021
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Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario: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.