ArticlePloS one2017
Anhedonia and anxiety underlying depressive symptomatology have distinct effects on reward-based decision-making.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A review on exploration-exploitation trade-off in psychiatric disorders.BMC psychiatry · 2025Pooled it
- A Web-Based Cognitive Behavior Therapy Intervention to Improve Social and Occupational Functioning in Adults With Type 2 Diabetes (The SpringboarD Trial): Randomized Controlled Trial.Journal of medical Internet research · 2019Trial
- Dissociating volatility and stochasticity reveals transdiagnostic computational signatures of psychopathology.bioRxiv : the preprint server for biology · 2026Article
- A Virtual Reality Intervention to Promote Uptake of Medications for Opioid Use Disorder in the Emergency Department Following Opioid-Involved Overdose Based on Input From People With Lived Experience: Development Study.JMIR XR and spatial computing · 2026Article
- Attenuated learning rates for negative outcomes in substance use disorders: A replication and extension of prior longitudinal computational modeling results.Drug and alcohol dependence · 2026Article
- Anhedonic Traits Do Not Impair Performance in a 3-Arm Bandit Task.Computational psychiatry (Cambridge, Mass.) · 2026Article
- Cross-species translational paradigms for assessing positive valence system as defined by the RDoC matrix.Journal of neurochemistry · 2025Review
- Article
- Assessing social anhedonia in a transdiagnostic sample: Insights from a computational psychiatry lens.Journal of mood and anxiety disorders · 2024Article
- Does the reliability of computational models truly improve with hierarchical modeling? Some recommendations and considerations for the assessment of model parameter reliability : Reliability of computational model parameters.Psychonomic bulletin & review · 2024Review
- Reviewing explore/exploit decision-making as a transdiagnostic target for psychosis, depression, and anxiety.Cognitive, affective & behavioral neuroscience · 2024Review
- You are How You Eat: Foraging Behavior as a Potential Novel Marker of Rat Affective State.Affective science · 2024Article
- Motivational context and neurocomputation of stop expectation moderate early attention responses supporting proactive inhibitory control.Frontiers in human neuroscience · 2024Article
- Inattentive responding can induce spurious associations between task behaviour and symptom measures.Nature human behaviour · 2023Article
- Functioning of the EROS-R Scale in a Clinical Sample of Psychiatric Patients: New Psychometric Evidence from the Classical Test Theory and the Item Response Theory.International journal of environmental research and public health · 2022Article
- Challenging the negative learning bias hypothesis of depression: reversal learning in a naturalistic psychiatric sample.Psychological medicine · 2022Article
- A model for learning based on the joint estimation of stochasticity and volatility.Nature communications · 2021Article
- Anxiety, avoidance, and sequential evaluation.Computational psychiatry (Cambridge, Mass.) · 2020Article
- Anhedonia modulates the effects of positive mood induction on reward-related brain activation.NeuroImage · 2019Article
- Diminished positive affect and traumatic stress: A biobehavioral review and commentary on trauma affective neuroscience.Neurobiology of stress · 2018Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Depressive pathology, which includes both heightened negative affect (e.g., anxiety) and reduced positive affect (e.g., anhedonia), is known to be associated with sub-optimal decision-making, particularly in uncertain environments. Here, we use a computational approach to quantify and disambiguate how individual differences in these affective measures specifically relate to different aspects of learning and decision-making in reward-based choice behavior. Fifty-three individuals with a range of depressed mood completed a two-armed bandit task, in which they choose between two arms with fixed but unknown reward rates. The decision-making component, which chooses among options based on current expectations about reward rates, is modeled by two different decision policies: a learning-independent Win-stay/Lose-shift (WSLS) policy that ignores all previous experiences except the last trial, and Softmax, which prefers the arm with the higher expected reward. To model the learning component for the Softmax choice policy, we use a Bayesian inference model, which updates estimated reward rates based on the observed history of trial outcomes. Softmax with Bayesian learning better fits the behavior of 55% of the participants, while the others are better fit by a learning-independent WSLS strategy. Among Softmax "users", those with higher anhedonia are less likely to choose the option estimated to be most rewarding. Moreover, the Softmax parameter mediates the inverse relationship between anhedonia and overall monetary gains. On the other hand, among WSLS "users", higher state anxiety correlates with increasingly better ability of WSLS, relative to Softmax, to explain subjects' trial-by-trial choices. In summary, there is significant variability among individuals in their reward-based, exploratory decision-making, and this variability is at least partly mediated in a very specific manner by affective attributes, such as hedonic tone and state anxiety.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.