RESUMO
Long-term exposure to nicotine alters brain circuits and induces profound changes in decision-making strategies, affecting behaviors both related and unrelated to drug seeking and consumption. Using an intracranial self-stimulation reward-based foraging task, we investigated in mice the impact of chronic nicotine on midbrain dopamine neuron activity and its consequence on the trade-off between exploitation and exploration. Model-based and archetypal analysis revealed substantial inter-individual variability in decision-making strategies, with mice passively exposed to nicotine shifting toward a more exploitative profile compared to non-exposed animals. We then mimicked the effect of chronic nicotine on the tonic activity of dopamine neurons using optogenetics, and found that photo-stimulated mice adopted a behavioral phenotype similar to that of mice exposed to chronic nicotine. Our results reveal a key role of tonic midbrain dopamine in the exploration/exploitation trade-off and highlight a potential mechanism by which nicotine affects the exploration/exploitation balance and decision-making.
Assuntos
Comportamento Exploratório/efeitos dos fármacos , Mesencéfalo/efeitos dos fármacos , Nicotina/efeitos adversos , Animais , Comportamento Animal/efeitos dos fármacos , Comportamento Animal/fisiologia , Dopamina/metabolismo , Neurônios Dopaminérgicos/efeitos dos fármacos , Neurônios Dopaminérgicos/metabolismo , Comportamento Exploratório/fisiologia , Masculino , Mesencéfalo/citologia , Mesencéfalo/metabolismo , Camundongos , Modelos Animais , Nicotina/administração & dosagem , Optogenética , Preconceito , Recompensa , Autoadministração , Técnicas EstereotáxicasRESUMO
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
RESUMO
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.
