A challenge for predictive coding: Representational or experiential diversity?

Vilas, Martina G.; Melloni, Lucia

doi:10.1017/S0140525X19003157

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A challenge for predictive coding: Representational or experiential diversity?

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Vilas, Martina G.
Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Max Planck Society;

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Melloni, Lucia
Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Max Planck Society;
Department of Neurology, NYU Comprehensive Epilepsy Center, School of Medicine, New York University;

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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.

Cite as: https://hdl.handle.net/21.11116/0000-0006-BBBE-2

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.