Mice adaptively generate choice variability in a deterministic task

Belkaid, M.; Bousseyrol, E.; Durand-de Cuttoli, R.; Dongelmans, M.; Durante, E. K.; Yahia, T. A.; Didienne, S.; Hannesse, B.; Come, M.; Mourot, A.; Naude, J.; Sigaud, O.; Faure, P.

doi:10.1101/527580

bioRxiv · 10.1101/527580

Mice adaptively generate choice variability in a deterministic task

Belkaid, M.·Bousseyrol, E.·Durand-de Cuttoli, R.·Dongelmans, M.·Durante, E. K.·Yahia, T. A.·Didienne, S.·Hannesse, B.·Come, M.·Mourot, A.·Naude, J.·Sigaud, O.·Faure, P.

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Abstract

Can our choices just be driven by chance? To investigate this question, we designed a deterministic setting in which mice reinforce non-repetitive choice sequences, and modeled it using reinforcement learning. Mice progressively increased their choice variability using a memory-free, pseudo-random selection, rather than by learning complex sequences. Our results demonstrate that a decision-making process can self-generate variability and randomness even when the rules governing reward delivery are not stochastic.

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Belkaid, M., Bousseyrol, E., Durand-de Cuttoli, R., Dongelmans, M., Durante, E. K., Yahia, T. A., Didienne, S., Hannesse, B., Come, M., Mourot, A., Naude, J., Sigaud, O., Faure, P.. 2019-01-24. Mice adaptively generate choice variability in a deterministic task. https://doi.org/10.1101/527580

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