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Abstract
In natural environments, animals must allocate choices across multiple concurrently available resources when foraging, a complex decision-making process not fully captured by existing models. To understand how rodents learn to navigate this challenge, we developed a novel paradigm in which naive, water-restricted mice freely sampled six options of varying quality arranged around a large (∼2 m) arena. Mice exhibited rapid learning, matching their choices to integrated reward probabilities across six options within tens of minutes. A reinforcement learning model with distinct states for staying vs. leaving an option, as well as a dynamic global learning rate, accurately reproduced behavior. Fiber photometry recordings revealed that dopamine in the nucleus accumbens core (NAcC), but not the dorsomedial striatum (DMS), reflected this learning rate. Moreover, optogenetic manipulation of NAcC dopamine bidirectionally altered learning in quantitative agreement with model predictions. Together, we identified a neural substrate of a learning algorithm enabling efficient multi-option foraging in large spatial environments.
