Search

To navigate our complex social world, it is crucial for people to deploy multiple learning strategies, such as learning from directly experiencing the outcomes of one’s actions – experiential learning (EL) – as well as learning from observing the behavior of other people – observational learning (OL). Despite the prevalence of EL and OL in humans and other social animals, two fundamental questions remain unaddressed: how is control over behavior assigned to one strategy over the other depending on the environment? And how do individuals vary in their strategy use? Here, we describe an arbitration mechanism in which the prediction errors associated with each learning strategy influence their weight over behavior. We designed an online behavioral task to test our computational model, in which the uncertainty of each strategy is manipulated, resulting in dynamic variations in prediction errors. Model comparisons revealed that a substantial proportion of participants rely on our proposed arbitration mechanism, but we also found some meaningful heterogeneity in how people solve this task, with four other groups identified: those who use a fixed mixture between the two strategies, those who rely on a single strategy (EL or OL) and non-learners who perform an irrelevant strategy. Furthermore, the groups were found to differ on key behavioral signatures, and on transdiagnostic symptom dimensions relevant to psychopathology, in particular autism traits and anxiety. Together, these results demonstrate the benefits of leveraging large heterogeneous datasets using computational methods to better characterize individual differences and pave the way toward individualized diagnoses and treatment.

We investigated the neural representation of reward probability recognition and its neural connectivity with other regions of the brain. Using functional magnetic resonance imaging (fMRI), we used a simple guessing task with different probabilities of obtaining rewards across trials to assay local and global regions processing reward probability. The results of whole brain analysis demonstrated that lateral prefrontal cortex, inferior parietal lobe, and postcentral gyrus were activated during probability-based decision making. Specifically, the higher the expected value was, the more these regions were activated. Fronto-parietal connectivity, comprising inferior parietal regions and right lateral prefrontal cortex, conjointly engaged during high reward probability recognition compared to low reward condition, regardless of whether the reward information was extrinsically presented. Finally, the result of a regression analysis identified that cortico-subcortical connectivity was strengthened during the high reward anticipation for the subjects with higher cognitive impulsivity. Our findings demonstrate that interregional functional involvement is involved in valuation based on reward probability and that personality trait such as cognitive impulsivity plays a role in modulating the connectivity among different brain regions.

When a stimulus is associated with an external reward, its chance of being consolidated into long-term memory is boosted via dopaminergic facilitation of long-term potentiation in the hippocampus. Given that higher temporal distance (TD) has been found to discount the subjective value of a reward, we hypothesized that memory performance associated with a more immediate reward will result in better memory performance. We tested this hypothesis by measuring both behavioral memory performance and brain activation using functional magnetic resonance imaging (fMRI) during memory encoding and retrieval tasks. Contrary to our hypothesis, both behavioral and fMRI results suggest that the TD of rewards might enhance the chance of the associated stimulus being remembered. The fMRI data demonstrate that the lateral prefrontal cortex, which shows encoding-related activation proportional to the TD, is reactivated when searching for regions that show activation proportional to the TD during retrieval. This is not surprising given that this region is not only activated to discriminate between future vs. immediate rewards, it is also a part of the retrieval-success network. These results provide support for the conclusion that the encoding-retrieval overlap provoked as the rewards are more delayed lead to better memory performance of the items associated with the rewards.