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  A challenge for predictive coding: Representational or experiential diversity?

Vilas, M. G., & Melloni, L. (2020). A challenge for predictive coding: Representational or experiential diversity? Behavioral and Brain Sciences, 43: e150. doi:10.1017/S0140525X19003157.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0006-BBBE-2 Version Permalink: https://hdl.handle.net/21.11116/0000-0006-BBBF-1
Genre: Journal Article

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 Creators:
Vilas, Martina G.1, Author           
Melloni, Lucia1, 2, Author           
Affiliations:
1Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Max Planck Society, ou_2421697              
2Department of Neurology, NYU Comprehensive Epilepsy Center, School of Medicine, New York University, New York, NY 10016, ou_persistent22              

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 Abstract:

To become a unifying theory of brain function, predictive processing (PP) must accommodate its rich representational diversity. Gilead et al. claim such diversity requires a multi-process theory, and thus is out of reach for PP, which postulates a universal canonical computation. We contend this argument and instead propose that PP fails to account for the experiential level of representations.

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Language(s): eng - English
 Dates: 2020-06-19
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1017/S0140525X19003157
 Degree: -

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Title: Behavioral and Brain Sciences
Source Genre: Journal
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Publ. Info: New York : Cambridge University Press.
Pages: - Volume / Issue: 43 Sequence Number: e150 Start / End Page: - Identifier: ISSN: 0140-525X
CoNE: https://pure.mpg.de/cone/journals/resource/954925341730