Dissecting the impact of depression on decision-making.
Psychol Med
; 50(10): 1613-1622, 2020 07.
Article
en En
| MEDLINE
| ID: mdl-31280757
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.
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Texto completo:
1
Base de datos:
MEDLINE
Asunto principal:
Recompensa
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Toma de Decisiones
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Incertidumbre
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Trastorno Depresivo Mayor
Tipo de estudio:
Clinical_trials
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Diagnostic_studies
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Prognostic_studies
Idioma:
En
Revista:
Psychol Med
Año:
2020
Tipo del documento:
Article