Linking cognitive mechanisms of instrumental learning to age and symptoms of anxiety and depression in adolescence

Adolescence is a sensitive period characterized by significant neurocognitive development, with important implications for learning and decision-making. Working memory and reinforcement learning are essential for decision making and real-life dynamic adaptation to the environment and are often affected in individuals with anxiety and depression. Using a cognitive computational approach, we investigated associations between working memory, reinforcement learning, age, and symptoms of generalized anxiety and depression in 193 adolescents aged 12-24 years.Participants completed the Reinforcement Learning Working Memory (RLWM) task. We employed a computational model that combines the RLWM model with a Linear Ballistic Accumulator (RLWM-LBA), to quantify processes related to working memory and reinforcement learning, as well as choice dynamics underlying reaction times. Bayesian regression models revealed strong evidence for an association (β = -.92, 95% CI = [-1.31 to -.53]) between age and the start point variability parameter of the LBA module, indicating that older adolescents exhibit reduced choice stochasticity. In contrast to literature on working memory impairments in depression, we found anecdotal evidence of a positive association between working memory capacity and depressive symptoms (β = .46, 95% CI = [.08109 to .84]). We found anecdotal to moderate evidence for no associations between RLWM-LBA parameters and symptoms of generalized anxiety. Lastly, we trained regression models testing the utility of RLWM-LBA parameters for predicting age and symptom burden, yielding poor predictive performance. This study highlights age-related differences in decision-making dynamics throughout adolescence and suggests complex interrelations between cognitive functioning and mental health in a population-based youth sample.