Active inference, evidence accumulation, and the urn task

FitzGerald, Thomas H B, Schwartenbeck, Philipp, Moutoussis, Michael, Dolan, Raymond J and Friston, Karl (2015) Active inference, evidence accumulation, and the urn task. Neural Computation, 27 (2). pp. 306-328. ISSN 0899-7667

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Abstract

Deciding how much evidence to accumulate before making a decision is a problem we and other animals often face, but one that is not completely understood. This issue is particularly important because a tendency to sample less information (often known as reflection impulsivity) is a feature in several psychopathologies, such as psychosis. A formal understanding of information sampling may therefore clarify the computational anatomy of psychopathology. In this theoretical letter, we consider evidence accumulation in terms of active (Bayesian) inference using a generic model of Markov decision processes. Here, agents are equipped with beliefs about their own behavior--in this case, that they will make informed decisions. Normative decision making is then modeled using variational Bayes to minimize surprise about choice outcomes. Under this scheme, different facets of belief updating map naturally onto the functional anatomy of the brain (at least at a heuristic level). Of particular interest is the key role played by the expected precision of beliefs about control, which we have previously suggested may be encoded by dopaminergic neurons in the midbrain. We show that manipulating expected precision strongly affects how much information an agent characteristically samples, and thus provides a possible link between impulsivity and dopaminergic dysfunction. Our study therefore represents a step toward understanding evidence accumulation in terms of neurobiologically plausible Bayesian inference and may cast light on why this process is disordered in psychopathology.

Item Type: Article
Additional Information: Citation information: 'Active Inference, Evidence Accumulation, and the Urn Task No Access', Thomas H. B. FitzGerald, Philipp Schwartenbeck, Michael Moutoussis, Raymond J. Dolan, Karl Friston, Neural Computation February 2015, Vol. 27, No. 2: 306–328
Uncontrolled Keywords: animals,bayes theorem,brain,choice behavior,cognition,computer simulation,decision making,dopamine,entropy,game theory,humans,markov chains,theoretical models,reaction time
Faculty \ School: Faculty of Social Sciences > School of Psychology
Depositing User: Pure Connector
Date Deposited: 25 Apr 2016 13:00
Last Modified: 19 Jun 2020 23:44
URI: https://ueaeprints.uea.ac.uk/id/eprint/58356
DOI: 10.1162/NECO_a_00699

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