This study aimed to investigate the link between reinforcement learning and structure learning. Reinforcement learning is a framework where humans learn to make decisions by interacting with their...Show moreThis study aimed to investigate the link between reinforcement learning and structure learning. Reinforcement learning is a framework where humans learn to make decisions by interacting with their environment, receiving rewards or punishments based on their actions, with the goal of maximizing cumulative reward over time. While structure learning is the cognitive process by which individuals acquire and internalize the underlying organizational principles or structures of information. It enables individuals to perceive patterns, rules, and relationships, allowing for effective organization and comprehension of knowledge. In the context of the environment, structure learning involves the representation and understanding of stimulus or action-outcome associations within one's surroundings. By recognizing and learning the environmental structure, individuals can better navigate, anticipate, and respond to stimuli, optimizing their interactions and adapting their behaviours accordingly. The link could be shown by the presence of a cognitive module, between reinforcement and structure learning. The cognitive module refers to the mental processes involved in acquiring, processing, and using information. Participants completed three tasks, as they are a good representation of reinforcement learning and structure learning, as well as, learning and decision-making, and have been shown to be reliably linked to e.g., specific neural correlates. The tasks are the two-stage bandit task, the weather prediction task, and the credit assignment task, Participants performed above chance in all three tasks. Interestingly, we found significant correlations between central (performance) metrics between tasks. The main analysis using Pearson correlation revealed significant correlations between the credit assignment task and the two-stage bandit task, as well as between the credit assignment task and the weather prediction task. There was only a marginal correlation between the weather prediction task and the two-stage bandit task, which disappeared after controlling for shared variance with the credit assignment task using partial correlation. The findings indicate that reinforcement learning and structure learning share common variances and behavioural metrics, such as reaction time, accuracy, performance, and outcome, suggesting a link between the two forms of learning and supporting the presence of a shared cognitive module underlying these processes. This has implications that structure learning seems to be a promising link between different learning tasks, highlighting its importance for understanding learning and decision-making across different contexts and across individuals.Show less
Anxiety is known to affect cognitive processes and learning. Studies have shown that people with anxiety tend to be biased towards negative feedback and learn better from it. This phenomenon has...Show moreAnxiety is known to affect cognitive processes and learning. Studies have shown that people with anxiety tend to be biased towards negative feedback and learn better from it. This phenomenon has been studied in reinforcement learning, but its effect on less known structure learning has not yet been studied. Structure learning refers to inferring the structure of an ambiguous environment to which reinforcement learning adds reward values on. This research paper aims to investigate if bias towards negative feedback caused by high level of trait anxiety found in reinforcement learning is also present in structure learning. We measured reinforcement learning and structure learning capacities with three well-known and validated tasks and trait anxiety with the STAI-T questionnaire in 48 students. Negative feedback bias was quantified via the win-stay-lose-shift behaviour. Using simple linear regression analyses, we found no significant effects of trait anxiety on negative feedback bias in reinforcement and structure learning tasks. Using moderation analysis in exploratory data analysis we found no significant results of the level of trait anxiety moderating the relationship between performance in the tasks and various independent variables. This could be due to the limitations of this study, for example using a behavioural instead of a neural measure to measure negative feedback bias, which raises a question of whether behavioural measures are sensitive enough to measure negative feedback bias in trait anxiety.Show less
