Chronic nicotine increases midbrain dopamine neuron activity and biases individual strategies towards reduced exploration in mice

Abstract

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.

Prolonged nicotine exposure reduces aversion to the drug in mice by altering nicotinic transmission in the interpeduncular nucleus

“…One important limitation of population-level analyses is that they greatly limit the ability to examine inter-individual differences in drug taking behaviors. It is indeed increasingly acknowledged that in mice, as in humans, there is a substantial variability in the susceptibility for developing drug use disorders [27][28][29][48][49][50][51] . Yet, it is still unclear why some individuals are more susceptible than others to become regular users.…”

Social Determinants of Inter-Individual Variability and Vulnerability: The Role of Dopamine

“…Experimental mice fall somewhere within the boundaries of these extreme behaviors. (Modified from Dongelmans et al, 2021 ).…”

“…With this method, the most extreme or specialized behavioral profiles possible from the entire data set are first defined as the archetypes. The number of archetypes and their associated behavioral patterns are derived from the dataset in an unsupervised manner, and each individual’s behavior can then be described as a convex mixture of archetypal profiles ( Cutler and Breiman, 1994 ; Shoval et al, 2012 ; Forkosh et al, 2019 ; Dongelmans et al, 2021 ). The individuals can be assigned to the archetype that best describes their behavior for experimental grouping purposes, rather than defining groups by an arbitrary threshold on any one continuous variable.…”

“…Archetypal analysis uses the key choice parameters from the task to reveal the three most extreme possible strategies: alternating exclusively between the two options with the highest probability of reward (A1), purely traveling in a circular pattern moving from the highest to lowest probability of reward (A2), or from the lowest to highest probability (A3). Therefore, individual behaviors find themselves somewhere between these extreme strategies, and can be defined as a linear combination of each archetype ( Figure 1C ; Dongelmans et al, 2021 ). These approaches have important consequences for introducing the notion of “personalized” behavioral assessment: by allowing the dissection of the contribution of inter- and intra-individual variability to phenotypic variability, they challenge classic approaches based on the analysis of average group behavior measured at a given moment.…”

“…Dopamine neuron activity is associated with the level of expression of many behavioral traits related to reward seeking, notably with the level of exploration ( Cohen et al, 2007 ; Frank et al, 2009 ; Humphries et al, 2012 ; Schiemann et al, 2012 ), but also the propensity for risk taking ( Onge and Floresco, 2008 ; Stopper et al, 2014 ), reaction to uncertainty ( Fiorillo et al, 2003 ; Naudé et al, 2016 ) and response vigor ( Niv et al, 2007 ). Several studies in rodents have now demonstrated the important role of tonic dopamine neuron activity in setting the balance point for the trade-off between environmental exploration and the exploitation of existing knowledge ( Beeler et al, 2010 ; Cinotti et al, 2019 ; Dongelmans et al, 2021 ). When mice were presented with two levers in a “closed economy” paradigm where each lever had different relative costs for food, but the two levers frequently switch position, wild-type mice optimally adapted their choices by distributing more effort on the least expensive lever.…”