A cognitive-computational account of mood swings in adolescence.

Teenagers have a reputation for being fickle, in both their choices and their moods. This variability may help adolescents as they begin to independently navigate novel environments. Recently, however, adolescent moodiness has also been linked to psychopathology. Here, we consider adolescents' mood swings from a novel computational perspective, grounded in reinforcement learning (RL). This model proposes that mood is determined by surprises about outcomes in the environment, and how much we learn from these surprises. It additionally suggests that mood biases learning and choice in a bidirectional manner. Integrating independent lines of research, we sketch a cognitive-computational account of how adolescents' mood, learning, and choice dynamics influence each other, with implications for normative and psychopathological development. Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.

Citation

Klára Gregorová, Eran Eldar, Lorenz Deserno, Andrea M F Reiter. A cognitive-computational account of mood swings in adolescence. Trends in cognitive sciences. 2024 Apr;28(4):290-303

Mesh Tags

PMID: 38503636

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