Evidence map›Paper›PMID 29059254›Full record

ArticlePloS one2017

Anhedonia and anxiety underlying depressive symptomatology have distinct effects on reward-based decision-making.

Katia M Harlé, Dalin Guo, Shunan Zhang, Martin P Paulus, Angela J Yu

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  5. Article
  6. Anhedonic Traits Do Not Impair Performance in a 3-Arm Bandit Task.Computational psychiatry (Cambridge, Mass.) · 2026
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  18. Anxiety, avoidance, and sequential evaluation.Computational psychiatry (Cambridge, Mass.) · 2020
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Katia M HarléDepartment of Psychiatry, UCSD, La Jolla, CA, United States of America.ORCID http://orcid.org/0000-0002-5493-5245
Dalin GuoDepartment of Electrical and Computer Engineering, UCSD, La Jolla, CA, United States of America.
Shunan ZhangDepartment of Cognitive Science, UCSD, La Jolla, CA, United States of America.
Martin P PaulusDepartment of Psychiatry, UCSD, La Jolla, CA, United States of America.
Angela J YuDepartment of Cognitive Science, UCSD, La Jolla, CA, United States of America.

Funding

Bayesian modeling of mood-driven decision biases for predicting clinical outcomeIK2CX001584 · VA · VA SAN DIEGO HEALTHCARE SYSTEM · PI HARLE, KATIA · 2018 to 2022
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6 · The paper itself

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.

Indexed as

AnhedoniaDecision MakingRewardAdolescentAdultAnxietyDepressionFemaleHumansMaleYoung Adult

Identifiers

PMID29059254
PMCPMC5653291

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.