ArticleeLife2018
Associability-modulated loss learning is increased in posttraumatic stress disorder.
Article in eLife, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
What it found
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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.
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Who cites it
28 citing papers in PubMed, 47 citations in OpenAlex.
- In Cocaine Dependence, Neural Prediction Errors During Loss Avoidance Are Increased With Cocaine Deprivation and Predict Drug Use.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2019Trial
- Functional brain imaging in posttraumatic stress disorder: a review.Journal of neural transmission (Vienna, Austria : 1996) · 2026Article
- Choosing certainty over risk: Associations of PTSD symptom severity with memory sampling during experiential decision making.Journal of anxiety disorders · 2025Article
- Reinforcement learning processes as forecasters of depression remission.Journal of affective disorders · 2025Article
- Computational Mechanisms of Information-Seeking in Anxiety.Current topics in behavioral neurosciences · 2025Review
- Reinforcement-Learning-Informed Queries Guide Behavioral Change.Clinical psychological science : a journal of the Association for Psychological Science · 2024Article
- Psilocybin increases optimistic engagement over time: computational modelling of behaviour in rats.Translational psychiatry · 2024Article
- The challenge of learning adaptive mental behavior.Journal of psychopathology and clinical science · 2024Article
- Latent-state and model-based learning in PTSD.Trends in neurosciences · 2024Review
- Out of control: computational dynamic control dysfunction in stress- and anxiety-related disorders.Discover mental health · 2024Review
- Decision-making for concurrent reward and threat is differentially modulated by trauma exposure and PTSD symptom severity.Behaviour research and therapy · 2023Article
- A computational model for learning from repeated traumatic experiences under uncertainty.Cognitive, affective & behavioral neuroscience · 2023Article
- Anxiety as a disorder of uncertainty: implications for understanding maladaptive anxiety, anxious avoidance, and exposure therapy.Cognitive, affective & behavioral neuroscience · 2023Article
- Neural valuation of rewards and punishments in posttraumatic stress disorder: a computational approach.Translational psychiatry · 2023Article
- Latent cause inference during extinction learning in trauma-exposed individuals with and without PTSD.Psychological medicine · 2022Article
- Altered predictive control during memory suppression in PTSD.Nature communications · 2022Article
- Value estimation and latent-state update-related neural activity during fear conditioning predict posttraumatic stress disorder symptom severity.Cognitive, affective & behavioral neuroscience · 2022Article
- Computational Psychiatry Needs Time and Context.Annual review of psychology · 2022Review
- Trauma Disrupts Reinforcement Learning in Rats-A Novel Animal Model of Chronic Stress Exposure.Frontiers in behavioral neuroscience · 2022Article
- Advances in modeling learning and decision-making in neuroscience.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2022Review
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
Abstract
Disproportionate reactions to unexpected stimuli in the environment are a cardinal symptom of posttraumatic stress disorder (PTSD). Here, we test whether these heightened responses are associated with disruptions in distinct components of reinforcement learning. Specifically, using functional neuroimaging, a loss-learning task, and a computational model-based approach, we assessed the mechanistic hypothesis that overreactions to stimuli in PTSD arise from anomalous gating of attention during learning (i.e., associability). Behavioral choices of combat-deployed veterans with and without PTSD were fit to a reinforcement learning model, generating trial-by-trial prediction errors (signaling unexpected outcomes) and associability values (signaling attention allocation to the unexpected outcomes). Neural substrates of associability value and behavioral parameter estimates of associability updating, but not prediction error, increased with PTSD during loss learning. Moreover, the interaction of PTSD severity with neural markers of associability value predicted behavioral choices. These results indicate that increased attention-based learning may underlie aspects of PTSD and suggest potential neuromechanistic treatment targets.
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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.