1. Major Depression Impairs the Use of Reward Values for Decision-Making
- Author
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Rupprechter, Samuel, Stankevicius, Aistis, Huys, Quentin J M, Steele, J Douglas, Seriès, Peggy, University of Zurich, and Seriès, Peggy
- Subjects
Adult ,Male ,Reward Probability ,Pavlovian Conditioning Task ,Adolescent ,Science ,Conditioning, Classical ,Decision Making ,610 Medicine & health ,Neuropsychological Tests ,Choice Behavior ,Article ,170 Ethics ,Reward ,Human behaviour ,Humans ,Learning ,10237 Institute of Biomedical Engineering ,Computer Simulation ,Translational research ,Pilot Dataset ,1000 Multidisciplinary ,Depressive Disorder, Major ,Multidisciplinary ,Depression ,Leaky Model ,Magnetic Resonance Imaging ,Fractional Stimuli ,Medicine ,Female ,Reinforcement, Psychology ,psychological phenomena and processes - Abstract
Depression is a debilitating condition with a high prevalence. Depressed patients have been shown to be diminished in their ability to integrate their reinforcement history to adjust future behaviour during instrumental reward learning tasks. Here, we tested whether such impairments could also be observed in a Pavlovian conditioning task. We recruited and analysed 32 subjects, 15 with depression and 17 healthy controls, to study behavioural group differences in learning and decision-making. Participants had to estimate the probability of some fractal stimuli to be associated with a binary reward, based on a few passive observations. They then had to make a choice between one of the observed fractals and another target for which the reward probability was explicitly given. Computational modelling was used to succinctly describe participants’ behaviour. Patients performed worse than controls at the task. Computational modelling revealed that this was caused by behavioural impairments during both learning and decision phases. Depressed subjects showed lower memory of observed rewards and had an impaired ability to use internal value estimations to guide decision-making in our task., Scientific Reports, 8, ISSN:2045-2322
- Published
- 2018