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Generative models as parsimonious descriptions of sensorimotor loops

Published online by Cambridge University Press:  28 November 2019

Manuel Baltieri Open the ORCID record for Manuel Baltieri [Opens in a new window]  and
Christopher L. Buckley Open the ORCID record for Christopher L. Buckley [Opens in a new window]
Manuel Baltieri
Affiliation:
EASY Group – Sussex Neuroscience, Department of Informatics, University of Sussex, BrightonBN1 9RH, United Kingdom. m.baltieri@sussex.ac.ukc.l.buckley@sussex.ac.ukhttps://manuelbaltieri.comhttps://christopherlbuckley.com/
Christopher L. Buckley
Affiliation:
EASY Group – Sussex Neuroscience, Department of Informatics, University of Sussex, BrightonBN1 9RH, United Kingdom. m.baltieri@sussex.ac.ukc.l.buckley@sussex.ac.ukhttps://manuelbaltieri.comhttps://christopherlbuckley.com/
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Abstract

The Bayesian brain hypothesis, predictive processing, and variational free energy minimisation are typically used to describe perceptual processes based on accurate generative models of the world. However, generative models need not be veridical representations of the environment. We suggest that they can (and should) be used to describe sensorimotor relationships relevant for behaviour rather than precise accounts of the world.

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Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 42 , 2019 , e218
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Copyright
Copyright © Cambridge University Press 2019

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