Expecting the unexpected: a review of learning under uncertainty across development

How adolescents learn to build social bonds: A developmental computational account of social explore-exploit decision-making

Building social bonds is a critical task of adolescence that affords opportunities for learning, identity formation, and social support. Failing to develop close relationships in adolescence hinders adult interpersonal functioning and contributes to problems such as loneliness and depression. During adolescence, increased reward sensitivity and greater social flexibility both contribute to healthy social development, yet we lack a clear theory of how these processes interact to support social functioning. Here, we propose synthesizing these two literatures using a computational reinforcement learning framework that recasts how adolescents pursue and learn from social rewards as a social explore-exploit problem. To become socially skilled, adolescents must balance both their efforts to form individual bonds within specific groups and manage memberships across multiple groups to maximize access to social resources. We draw on insights from sociological studies on social capital in collective networks and neurocognitive research on foraging and cooperation to describe the social explore-exploit dilemma faced by adolescents navigating a modern world with increasing access to diverse resources and group memberships. Our account provides important new directions for examining the dynamics of adolescent behavior in social groups and understanding how social value computations can support positive relationships into adulthood.

Functional connectivity between the nucleus accumbens and amygdala underlies avoidance learning during adolescence: Implications for developmental psychopathology

BACKGROUND

Reward and threat processes work together to support adaptive learning during development. Adolescence is associated with increasing approach behavior (e.g., novelty-seeking, risk-taking) but often also coincides with emerging internalizing symptoms, which are characterized by heightened avoidance behavior. Peaking engagement of the nucleus accumbens (NAcc) during adolescence, often studied in reward paradigms, may also relate to threat mechanisms of adolescent psychopathology.

METHODS

47 typically developing adolescents (9.9-22.9 years) completed an aversive learning task during functional magnetic resonance imaging, wherein visual cues were paired with an aversive sound or no sound. Task blocks involved an escapable aversively reinforced stimulus (CS+r), the same stimulus without reinforcement (CS+nr), or a stimulus that was never reinforced (CS-). Parent-reported internalizing symptoms were measured using Revised Child Anxiety and Depression Scales.

RESULTS

Functional connectivity between the NAcc and amygdala differentiated the stimuli, such that connectivity increased for the CS+r (p = .023) but not for the CS+nr and CS-. Adolescents with greater internalizing symptoms demonstrated greater positive functional connectivity for the CS- (p = .041).

CONCLUSIONS

Adolescents show heightened NAcc-amygdala functional connectivity during escape from threat. Higher anxiety and depression symptoms are associated with elevated NAcc-amygdala connectivity during safety, which may reflect poor safety versus threat discrimination.

Observational reinforcement learning in children and young adults

Observational learning is essential for the acquisition of new behavior in educational practices and daily life and serves as an important mechanism for human cognitive and social-emotional development. However, we know little about its underlying neurocomputational mechanisms from a developmental perspective. In this study we used model-based fMRI to investigate differences in observational learning and individual learning between children and younger adults. Prediction errors (PE), the difference between experienced and predicted outcomes, related positively to striatal and ventral medial prefrontal cortex activation during individual learning and showed no age-related differences. PE-related activation during observational learning was more pronounced when outcomes were worse than predicted. Particularly, negative PE-coding in the dorsal medial prefrontal cortex was stronger in adults compared to children and was associated with improved observational learning in children and adults. The current findings pave the way to better understand observational learning challenges across development and educational settings.

Flexible learning in complex worlds

Cognitive flexibility can enhance the ability to adjust to changing environments. Here, we use learning simulations to investigate the possible advantages of flexible learning in volatile (changing) environments. We compare two established learning mechanisms, one with constant learning rates and one with rates that adjust to volatility. We study an ecologically relevant case of volatility, based on observations of developing cleaner fish Labroides dimidiatus that experience a transition from a simpler to a more complex foraging environment. There are other similar transitions in nature, such as migrating to a new and different habitat. We also examine two traditional approaches to volatile environments in experimental psychology and behavioral ecology: reversal learning, and learning set formation (consisting of a sequence of different discrimination tasks). These provide experimental measures of cognitive flexibility. Concerning transitions to a complex world, we show that both constant and flexible learning rates perform well, losing only a small proportion of available rewards in the period after a transition, but flexible rates perform better than constant rates. For reversal learning, flexible rates improve the performance with each successive reversal because of increasing learning rates, but this does not happen for constant rates. For learning set formation, we find no improvement in performance with successive shifts to new stimuli to discriminate for either flexible or constant learning rates. Flexible learning rates might thus explain increasing performance in reversal learning but not in learning set formation, and this can shed light on the nature of cognitive flexibility in a given system.