Processing Fluency and Predictive Processing: How the Predictive Mind Becomes Aware of its Cognitive Limitations.
Autor: | Servajean P; Laboratory of Psychology and NeuroCognition, University of Grenoble Alpes.; EPSYLON EA 4556, University Paul-Valéry Montpellier 3., Wiese W; Institute for Philosophy II, Ruhr-University Bochum. |
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Jazyk: | angličtina |
Zdroj: | Topics in cognitive science [Top Cogn Sci] 2024 Nov 25. Date of Electronic Publication: 2024 Nov 25. |
DOI: | 10.1111/tops.12776 |
Abstrakt: | Predictive processing is an influential theoretical framework for understanding human and animal cognition. In the context of predictive processing, learning is often reduced to optimizing the parameters of a generative model with a predefined structure. This is known as Bayesian parameter learning. However, to provide a comprehensive account of learning, one must also explain how the brain learns the structure of its generative model. This second kind of learning is known as structure learning. Structure learning would involve true structural changes in generative models. The purpose of the current paper is to describe the processes involved upstream of these structural changes. To do this, we first highlight the remarkable compatibility between predictive processing and the processing fluency theory. More precisely, we argue that predictive processing is able to account for all the main theoretical constructs associated with the notion of processing fluency (i.e., the fluency heuristic, naïve theory, the discrepancy-attribution hypothesis, absolute fluency, expected fluency, and relative fluency). We then use this predictive processing account of processing fluency to show how the brain could infer whether it needs a structural change for learning the causal regularities at play in the environment. Finally, we speculate on how this inference might indirectly trigger structural changes when necessary. (© 2024 The Author(s). Topics in Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society.) |
Databáze: | MEDLINE |
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