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Dynamics of learning in many option foraging| title | Dynamics of learning in many option foraging |
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| start_date | 2026/03/09 |
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| schedule | 11h00 |
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| online | no |
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| location_info | nc |
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| summary | In natural environments, animals must effectively allocate their choices across many concurrently available resources when foraging. This is a complex decision-making process not fully understood, nor well captured by existing models. In this talk I will describe a novel paradigm that we developed in which completely naïve mice were free to sample and learn about six options of differing quality positioned around the walls of a large (~2m) arena. Mice exhibited rapid learning, matching their choices to integrated reward ratios across all six options within tens of minutes. To develop a mechanistic description of this learning, we constructed a reinforcement learning model inspired by foraging theory. In combination with a dynamic, global (across all options) learning rate, this model was able to accurately reproduce mouse learning and decision-making. Finally, I will discuss results of fiber photometry recordings and optogenetic manipulations of dopamine levels in the nucleus accumbens core (NAcC), revealing a unique role of this signal in implementing the global learning rate. Altogether, our results provide insight into the neural substrate of a learning algorithm that allows mice to rapidly exploit multiple options when learning to forage in large spatial environments. |
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| responsibles | NC |
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| submitted | published | | 2026/02/27 09:29 UTC |
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