Resolving Ambiguities of MVPA Using Explicit Models of Representation

Thomas Naselaris; Kendrick N. Kay

doi:10.1016/j.tics.2015.07.005

Resolving Ambiguities of MVPA Using Explicit Models of Representation

Thomas Naselaris, Kendrick N. Kay

Research output: Contribution to journal › Article › peer-review

66 Scopus citations

Abstract

We advocate a shift in emphasis within cognitive neuroscience from multivariate pattern analysis (MVPA) to the design and testing of explicit models of neural representation. With such models, it becomes possible to identify the specific representations encoded in patterns of brain activity and to map them across the brain.

Original language	English (US)
Article number	1476
Pages (from-to)	551-554
Number of pages	4
Journal	Trends in Cognitive Sciences
Volume	19
Issue number	10
DOIs	https://doi.org/10.1016/j.tics.2015.07.005
State	Published - Oct 1 2015

Bibliographical note

Funding Information:
This work was supported by the McDonnell Center for Systems Neuroscience and Arts & Sciences at Washington University (K.N.K.) and by grant NEI R01 EY023384 (T.N.).

Publisher Copyright:
© 2015.

Keywords

Computational modeling
Encoding model
FMRI
Multivariate pattern analysis
Representation

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10.1016/j.tics.2015.07.005

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keywords = "Computational modeling, Encoding model, FMRI, Multivariate pattern analysis, Representation",

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AU - Kay, Kendrick N.

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KW - Encoding model

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KW - Multivariate pattern analysis

KW - Representation

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Resolving Ambiguities of MVPA Using Explicit Models of Representation

Abstract

Bibliographical note

Keywords

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