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

• Published in: Journal of psychiatric research Vol. 154; pp. 307 - 314
• Main Authors: Chen, Chong, Mochizuki, Yasuhiro, Hagiwara, Kosuke, Hirotsu, Masako, Matsubara, Toshio, Nakagawa, Shin
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.10.2022
• Subjects: Computational psychiatry; Decision-making; Description-experience gap; Probability weighting; Reinforcement learning; Risk preference; Decision-making; PSS; Risk preference; Computational psychiatry; iBIC; Reinforcement learning; Description-experience gap; PH; BDI-II; Probability weighting; RL
• ISSN: 0022-3956; 1879-1379; 1879-1379
• DOI: 10.1016/j.jpsychires.2022.08.003

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. 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). 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]). 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.