ArticleComputational psychiatry (Cambridge, Mass.)2017
Learning and Choice in Mood Disorders: Searching for the Computational Parameters of Anhedonia.
Article in Computational psychiatry (Cambridge, Mass.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
33 citing papers in PubMed.
- Metabolism and the Mind: Investigating the Link Between Glucose Control and Reinforcement Learning in Humans.Biological psychiatry global open science · 2026Article
- Predicting individual food valuation via vision-language embedding model.PLOS digital health · 2025Article
- 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
- Psilocybin increases optimistic engagement over time: computational modelling of behaviour in rats.Translational psychiatry · 2024Article
- Distinct alterations in probabilistic reversal learning across at-risk mental state, first episode psychosis and persistent schizophrenia.Scientific reports · 2024Article
- Postnatal Phencyclidine-Induced Deficits in Decision Making Are Ameliorated by Optogenetic Inhibition of Ventromedial Orbitofrontal Cortical Glutamate Neurons.Biological psychiatry global open science · 2024Article
- Examining social reinforcement learning in social anxiety.Journal of behavior therapy and experimental psychiatry · 2023Article
- A computational analysis of mouse behavior in the sucrose preference test.Nature communications · 2023Article
- Mood Symptom Dimensions and Developmental Differences in Neurocognition in Adolescence.Clinical psychological science : a journal of the Association for Psychological Science · 2023Article
- Individuals with problem gambling and obsessive-compulsive disorder learn through distinct reinforcement mechanisms.PLoS biology · 2023Article
- Article
- A Computational View on the Nature of Reward and Value in Anhedonia.Current topics in behavioral neurosciences · 2022Article
- Challenging the negative learning bias hypothesis of depression: reversal learning in a naturalistic psychiatric sample.Psychological medicine · 2022Article
- Components of Behavioral Activation Therapy for Depression Engage Specific Reinforcement Learning Mechanisms in a Pilot Study.Computational psychiatry (Cambridge, Mass.) · 2022Article
- Computational approaches to treatment response prediction in major depression using brain activity and behavioral data: A systematic review.Network neuroscience (Cambridge, Mass.) · 2022Article
- Psychiatric symptoms influence reward-seeking and loss-avoidance decision-making through common and distinct computational processes.Psychiatry and clinical neurosciences · 2021Article
- Sex difference in the weighting of expected uncertainty under chronic stress.Scientific reports · 2021Article
- Revisiting the importance of model fitting for model-based fMRI: It does matter in computational psychiatry.PLoS computational biology · 2021Article
- Affective Bias Through the Lens of Signal Detection Theory.Computational psychiatry (Cambridge, Mass.) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Computational approaches are increasingly being used to model behavioral and neural processes in mood and anxiety disorders. Here we explore the extent to which the parameters of popular learning and decision-making models are implicated in anhedonic symptoms of major depression. We first highlight the parameters of reinforcement learning that have been implicated in anhedonia, focusing, in particular, on the role that choice variability (i.e., "temperature") may play in explaining heterogeneity across previous findings. We then turn to neuroimaging findings implicating attenuated ventral striatum response in anhedonic responses and discuss possible causes of the heterogeneity in the literature. Taken together, the reviewed findings highlight the potential of the computational approach in teasing apart the observed heterogeneity in both behavioral and functional imaging results. Nevertheless, considerable challenges remain, and we conclude with five unresolved questions that seek to address issues highlighted by the reviewed data.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.