The anatomical, structural, and functional adaptations that occur in the brain during adolescence are thought to facilitate improvements in decision-making functions that are known to occur during this stage of development. The mechanisms that underlie these neural adaptations are not known, but deviations in developmental trajectories have been proposed to contribute to the emergence of mental illness, including addiction. Direct evidence supporting this hypothesis, however, has been limited. Here, we used a recently developed reversal-learning protocol to investigate the predictive relationship between adolescent decision-making trajectories and cocaine-taking behaviors in adulthood. Decision-making functions in the reversal-learning task were assessed throughout adolescence and into adulthood in male and female Long–Evans rats. Trial-by-trial choice data was fitted with a reinforcement-learning model to quantify the degree to which choice behavior of individual rats was influenced by rewarded (e.g., ∆+ parameter) and unrewarded (e.g., ∆0 parameter) outcomes. We report that reversal-learning performance improved during adolescence and that this was due to an increase in value updating for rewarded outcomes (e.g., ∆+ parameter). Furthermore, the rate of change in the ∆+ parameter predicted individual differences in the ∆+ parameter and, notably, cocaine-taking behaviors in adulthood: Rats that had a shallower adolescent trajectory were found to have a lower ∆+ parameter and greater cocaine self-administration in adulthood. These data indicate that adolescent development plays a critical role in drug use susceptibility. Future studies aimed at understanding the neurobiological mechanisms that underlie these age-related changes in decision-making could provide new insights into the biobehavioral mechanisms mediating addiction susceptibility.
Bibliographical noteFunding Information:
This work was supported by Public Health Service grants from the National Institute on Drug Abuse (DA051598 and DA051977 to SMG) and the State of Minnesota through its support of the Medical Discovery Team on Addiction. We acknowledge and thank the Drug Supply Program at the National Institute on Drug Abuse for providing cocaine HCl. The authors thank Dr. Summer Thompson for her insightful comments and critiques of an earlier draft of the manuscript.
© 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
- Addiction susceptibility
- Computational psychiatry
- Decision making
- Reward learning
PubMed: MeSH publication types
- Journal Article