Journal Article

Dopamine blockade impairs the exploration-exploitation trade-off in rats

Aklil, Nassim, Girard, Benoît, Fresno, Virginie, Khamassi, Mehdi, Coutureau, Etienne, Cinotti, François, Marchand, Alain R.

2019

Overview

In a volatile environment where rewards are uncertain, successful performance requires a delicate balance between exploitation of the best option and exploration of alternative choices. It has theoretically been proposed that dopamine contributes to the control of this exploration-exploitation trade-off, specifically that the higher the level of tonic dopamine, the more exploitation is favored. We demonstrate here that there is a formal relationship between the rescaling of dopamine positive reward prediction errors and the exploration-exploitation trade-off in simple non-stationary multi-armed bandit tasks. We further show in rats performing such a task that systemically antagonizing dopamine receptors greatly increases the number of random choices without affecting learning capacities. Simulations and comparison of a set of different computational models (an extended Q-learning model, a directed exploration model, and a meta-learning model) fitted on each individual confirm that, independently of the model, decreasing dopaminergic activity does not affect learning rate but is equivalent to an increase in random exploration rate. This study shows that dopamine could adapt the exploration-exploitation trade-off in decision-making when facing changing environmental contingencies.

• Publisher: Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
• Subject: 631/378/1595/1396 / 631/378/1788 / 631/378/2649/1409 / Animals / Artificial Intelligence / Cognitive science / Computer applications / Computer Science / Decision Making / Dopamine / Dopamine - chemistry / Dopamine - metabolism / Dopamine Antagonists - pharmacology / Dopamine receptors / Environmental changes / Exploitation / Exploratory Behavior - drug effects / Exploratory Behavior - physiology / Humanities and Social Sciences / Learning / Male / Mathematical models / Models, Theoretical / multidisciplinary / Neural and Evolutionary Computing / Neuroscience / Probability Learning / Rats / Rats, Long-Evans / Reinforcement / Reward / Robotics / Scaling / Science / Science (multidisciplinary)