Computational markers of experience- but not description-based decision-making are associated with future depressive symptoms in young adults

Chong Chen*, Yasuhiro Mochizuki, Kosuke Hagiwara, Masako Hirotsu, Toshio Matsubara, Shin Nakagawa

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Early prediction of high depressive symptoms is crucial for selective intervention and the minimization of functional impairment. Recent cross-sectional studies indicated decision-making deficits in depression, which may be an important contributor to the disorder. Our goal was to test whether description- and experience-based decision making, two major neuroeconomic paradigms of decision-making under uncertainty, predict future depressive symptoms in young adults. Methods: One hundred young adults performed two decision-making tasks, one description-based, in which subjects chose between two gambling options given explicitly stated rewards and their probabilities, and the other experience-based, in which subjects were shown rewards but had to learn the probability of those rewards (or cue-outcome contingencies) via trial-and-error experience. We evaluated subjects' depressive symptoms with BDI-II at baseline (T1) and half a year later (T2). Results: Comparing subjects with low versus high levels of depressive symptoms at T2 showed that the latter performed worse on the experience- but not description-based task at T1. Computational modeling of the decision-making process suggested that subjects with high levels of depressive symptoms had a more concave utility function, indicating enhanced risk aversion. Furthermore, a more concave utility function at T1 increased the odds of high depressive symptoms at T2, even after controlling depressive symptoms at T1, perceived stress at T2, and several covariates (OR = 0.251, 95% CI [0.085, 0.741]). Conclusions: This is the first study to demonstrate a prospective link between experience-based decision-making and depressive symptoms. Our results suggest that enhanced risk aversion in experience-based decision-making may be an important contributor to the development of depressive symptoms.

Original languageEnglish
Pages (from-to)307-314
Number of pages8
JournalJournal of Psychiatric Research
Volume154
DOIs
Publication statusPublished - 2022 Oct

Keywords

  • Computational psychiatry
  • Decision-making
  • Description-experience gap
  • Probability weighting
  • Reinforcement learning
  • Risk preference

ASJC Scopus subject areas

  • Psychiatry and Mental health
  • Biological Psychiatry

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