Cortical substrates for exploratory decisions in humans

Nathaniel D Daw, John P O'Doherty, Peter Dayan, Ben Seymour, Raymond J Dolan, Nathaniel D Daw, John P O'Doherty, Peter Dayan, Ben Seymour, Raymond J Dolan

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' dilemma, 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 learning (RL) theory, indicates that a dopaminergic, striatal and medial prefrontal network mediates learning to exploit. In contrast, although exploration has been well studied from both theoretical and ethological 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.

Figures

Figure 1
Figure 1
Task design. a, Illustration of the timeline within a trial. Initially, four slots are presented. The subject chooses one, which then spins. Three seconds later the number of points won is revealed. After a further second the screen is cleared. The next trial is triggered after a fixed trial length of 6s and an additional variable inter-trial interval (mean 2 s). b, Example of mean payoffs that would be received for choosing each slot machine (four coloured lines) on each trial, demonstrating their independent random diffusion. The payoff received for a particular choice is corrupted by gaussian noise around this mean.
Figure 2
Figure 2
Reward-related activations. Activation maps (yellow, P 1/4 4.6]; medial prefrontal, [−3,33,−6, peak z 1/4 4.62]. The bar plot shows the average medial prefrontal BOLD response to decision, binned by choice probability (error bars represent s.e.m.).
Figure 3
Figure 3
Exploration-related activity in frontopolar cortex. a, Regions of left and right frontopolar cortex (lFP, rFP) showing significantly increased activation on exploratory compared with exploitative trials. Activation maps (yellow, P

Figure 4

Exploration-related activity in intraparietal sulcus.…

Figure 4

Exploration-related activity in intraparietal sulcus. a, Regions of left and right intraparietal sulcus…

Figure 4
Exploration-related activity in intraparietal sulcus. a, Regions of left and right intraparietal sulcus (lIPS and rIPS) showing significantly increased activation on exploratory compared with exploitative trials. Activation maps (yellow, P
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Figure 4
Figure 4
Exploration-related activity in intraparietal sulcus. a, Regions of left and right intraparietal sulcus (lIPS and rIPS) showing significantly increased activation on exploratory compared with exploitative trials. Activation maps (yellow, P

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