Dissecting the impact of depression on decision-making

• Type of Material: Article
• Authors: Victoria M Lawlor, Harvard Medical School; Christian A Webb, Harvard Medical School; Thomas V Wiecki, Quantopian Inc.; Michael J Frank, Brown University; Madhukar Trivedi, UT Southwestern Medical Center; Diego A Pizzagalli, Harvard Medical School; Daneil G Dillon, Harvard Medical School
• Language: English
• Date: 2020-07-01
• Publisher: Cambridge University Press
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © Cambridge University Press 2019
• License: Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1017/S0033291719001570
• Title of Journal or Parent Work: Psychological Medicine
• Volume: 50
• Issue: 10
• Start Page: 1613
• End Page: 1622
• Grant/Funding Information: The analysis was made possible by funding from McLean Hospital and a grant from NIMH (R00MH094438) awarded to Dr. Dillon. Data collection and prior analyses were made possible by additional funding from NIMH (Pizzagalli: R01MH68376; Trivedi: U01MH092221; McGrath, Parsey, Weissman: U01MH092250). The authors are solely responsible for the content of this manuscript, which does not necessarily represent the official views of the NIH.
• Keywords: Reward; Male; Decision Making; Humans; Depressive Disorder, Major; depression; Regression Analysis; Reaction Time; Middle Aged; Uncertainty; decision-making; drift diffusion model; Psychological Tests; Female; Adult; Computational modeling; Young Adult; reward

Abstract

Background Cognitive deficits in depressed adults may reflect impaired decision-making. To investigate this possibility, we analyzed data from unmedicated adults with Major Depressive Disorder (MDD) and healthy controls as they performed a probabilistic reward task. The Hierarchical Drift Diffusion Model (HDDM) was used to quantify decision-making mechanisms recruited by the task, to determine if any such mechanism was disrupted by depression.Methods Data came from two samples (Study 1: 258 MDD, 36 controls; Study 2: 23 MDD, 25 controls). On each trial, participants indicated which of two similar stimuli was presented; correct identifications were rewarded. Quantile-probability plots and the HDDM quantified the impact of MDD on response times (RT), speed of evidence accumulation (drift rate), and the width of decision thresholds, among other parameters.Results RTs were more positively skewed in depressed v. healthy adults, and the HDDM revealed that drift rates were reduced - and decision thresholds were wider - in the MDD groups. This pattern suggests that depressed adults accumulated the evidence needed to make decisions more slowly than controls did.Conclusions Depressed adults responded slower than controls in both studies, and poorer performance led the MDD group to receive fewer rewards than controls in Study 1. These results did not reflect a sensorimotor deficit but were instead due to sluggish evidence accumulation. Thus, slowed decision-making - not slowed perception or response execution - caused the performance deficit in MDD. If these results generalize to other tasks, they may help explain the broad cognitive deficits seen in depression.