1. Gatsby Computational Neuroscience Unit, University College London (UCL), Alexandra House, 17 Queen Square, London WC1N 3AR, UK
2. Wellcome Department of Imaging Neuroscience, UCL, 12 Queen Square, London WC1N 3BG, UK
3. †Present address: Division of Humanities and Social Sciences, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, USA
4. *These authors contributed equally to this work

Correspondence to: Nathaniel D. Daw^1,4John P. O'Doherty^2,4,3 Correspondence and requests for materials should be addressed to N.D. (Email: daw@gatsby.ucl.ac.uk) or J.O.D. (Email: jdoherty@hss.caltech.edu).

Abstract

Decision making in an uncertain environment poses a conflict between the opposing demands of gathering and exploiting information. In a classic illustration of this 'exploration–exploitation' dilemma¹, a gambler choosing between multiple slot machines balances the desire to select what seems, on the basis of accumulated experience, the richest option, against the desire to choose a less familiar option that might turn out more advantageous (and thereby provide information for improving future decisions). Far from representing idle curiosity, such exploration is often critical for organisms to discover how best to harvest resources such as food and water. In appetitive choice, substantial experimental evidence, underpinned by computational reinforcement learning² (RL) theory, indicates that a dopaminergic^{3, 4}, striatal^{5, 6, 7, 8, 9} and medial prefrontal network mediates learning to exploit. In contrast, although exploration has been well studied from both theoretical¹ and ethological¹⁰ perspectives, its neural substrates are much less clear. Here we show, in a gambling task, that human subjects' choices can be characterized by a computationally well-regarded strategy for addressing the explore/exploit dilemma. Furthermore, using this characterization to classify decisions as exploratory or exploitative, we employ functional magnetic resonance imaging to show that the frontopolar cortex and intraparietal sulcus are preferentially active during exploratory decisions. In contrast, regions of striatum and ventromedial prefrontal cortex exhibit activity characteristic of an involvement in value-based exploitative decision making. The results suggest a model of action selection under uncertainty that involves switching between exploratory and exploitative behavioural modes, and provide a computationally precise characterization of the contribution of key decision-related brain systems to each of these functions.

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