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- W1890969174 abstract "Focusing on visual perceptual organization, this article contrasts the free-energy (FE) version of predictive coding (a recent Bayesian approach) to structural coding (a long-standing representational approach). Both use free-energy minimization as metaphor for processing in the brain, but their formal elaborations of this metaphor are fundamentally different. FE predictive coding formalizes it by minimization of prediction errors, whereas structural coding formalizes it by minimization of the descriptive complexity of predictions. Here, both sides are evaluated. A conclusion regarding competence is that FE predictive coding uses a powerful modeling technique, but that structural coding has more explanatory power. A conclusion regarding performance is that FE predictive coding-though more detailed in its account of neurophysiological data-provides a less compelling cognitive architecture than that of structural coding, which, for instance, supplies formal support for the computationally powerful role it attributes to neuronal synchronization." @default.
- W1890969174 created "2016-06-24" @default.
- W1890969174 creator A5076733661 @default.
- W1890969174 date "2015-09-25" @default.
- W1890969174 modified "2023-10-14" @default.
- W1890969174 title "Structural coding versus free-energy predictive coding" @default.
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- W1890969174 doi "https://doi.org/10.3758/s13423-015-0938-9" @default.
- W1890969174 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/26407895" @default.
- W1890969174 hasPublicationYear "2015" @default.
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