A cognitive-computational account of mood swings in adolescence

Klára Gregorová, Eran Eldar, Lorenz Deserno, Andrea M.F. Reiter*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

Abstract

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.

Original languageAmerican English
JournalTrends in Cognitive Sciences
DOIs
StateAccepted/In press - 2024

Bibliographical note

Publisher Copyright:
© 2024 The Authors

Keywords

  • adolescence
  • emotional reactivity
  • mood fluctuations
  • mood instability
  • mood variability
  • prediction error
  • reinforcement learning

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