“Mice alternate between inference- and stimulus-bound strategies during probabilistic foraging”.
During this CONECT seminar, Danny Burnham will present his recent work on “Mice alternate between inference- and stimulus-bound strategies during probabilistic foraging”
Abstract : Essential features of the world are often hidden and must be inferred by constructing internal models based on indirect evidence. During foraging, animals must continually choose between trying to exploit a depleting food source at their current location and leaving to explore a new source at the expense of costly travel epochs. In a deterministic environment, the optimal strategy is to leave the current site when the immediate rate of reward drops below the average rate - a stimulus-bound strategy, assigning each action a value that is updated based on its immediate outcome. This strategy, however, is not optimal in a realistic foraging scenario, where rewards are encountered probabilistically and the optimal strategy is inference-bound, requiring the animal to infer the hidden structure of the world. Motivated by recent studies showing that mice alternate between discrete strategies during perceptual decision-making, we test the hypothesis that mouse behavior during a probabilistic foraging task switches between inference- and stimulus-bound strategies within the same session. To this end, we developed a novel hidden Markov model with linear emissions (LM-HMM) to capture this switching dynamic. When applied to mice engaged in the task, the LM-HMM revealed that mice switch between distinct inference bound and stimulus bound strategies exhibiting varying impulsivities.