Dopaminergic and prefrontal dynamics co-determine mouse decisions in a spatial gambling task

The neural mechanisms by which animals initiate goal-directed actions, choose between options, or explore opportunities remain unknown. Here, we develop a spatial gambling task in which mice, to obtain intracranial self-stimulation rewards, self-determine the initiation, direction, vigor, and pace of their actions based on their knowledge of the outcomes. Using electrophysiological recordings, pharmacology, and optogenetics, we identify a sequence of oscillations and firings in the ventral tegmental area (VTA), orbitofrontal cortex (OFC), and prefrontal cortex (PFC) that co-encodes and co-determines self-initiation and choices. This sequence appeared with learning as an uncued realignment of spontaneous dynamics. Interactions between the structures varied with the reward context, particularly the uncertainty associated with the different options. We suggest that self-generated choices arise from a distributed circuit based on an OFC-VTA core determining whether to wait for or initiate actions, while the PFC is specifically engaged by reward uncertainty in action selection and pace.

Mice adaptively generate choice variability in a deterministic task

Can decisions be made solely by chance? Can variability be intrinsic to the decision-maker or is it inherited from environmental conditions? To investigate these questions, we designed a deterministic setting in which mice are rewarded for non-repetitive choice sequences, and modeled the experiment using reinforcement learning. We found that mice progressively increased their choice variability. Although an optimal strategy based on sequences learning was theoretically possible and would be more rewarding, animals used a pseudo-random selection which ensures high success rate. This was not the case if the animal is exposed to a uniform probabilistic reward delivery. We also show that mice were blind to changes in the temporal structure of reward delivery once they learned to choose at random. Overall, our results demonstrate that a decision-making process can self-generate variability and randomness, even when the rules governing reward delivery are neither stochastic nor volatile.