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Accumulating evidence suggest that human behavior in trial-and-error learningtasks based on decisions between discrete actions may involve a combination ofreinforcement learning (RL) and working-memory (WM). While the understanding ofbrain activity at stake in this type of tasks often involve the comparison withnon-human primate neurophysiological results, it is not clear whether monkeysuse similar combined RL and WM processes to solve these tasks. Here we analyzedthe behavior of five monkeys with computational models combining RL and WM. Ourmodel-based analysis approach enables to not only fit trial-by-trial choicesbut also transient slowdowns in reaction times, indicative of WM use. We foundthat the behavior of the five monkeys was better explained in terms of acombination of RL and WM despite inter-individual differences. The samecoordination dynamics we used in a previous study in humans best explained thebehavior of some monkeys while the behavior of others showed the oppositepattern, revealing a possible different dynamics of WM process. We furtheranalyzed different variants of the tested models to open a discussion on howthe long pretraining in these tasks may have favored particular coordinationdynamics between RL and WM. This points towards either inter-speciesdifferences or protocol differences which could be further tested in humans.

Adaptive coordination of working-memory and reinforcement learning in non-human primates performing a trial-and-error problem solving task