ArticleNeuroImage2022
Large-scale neural network computations and multivariate representations during approach-avoidance conflict decision-making.
Article in NeuroImage, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07369115 (Intra-Cellular Therapies, Inc. / "A Randomized, Double-blind, Placebo-controlled, Single Site Study to Evaluate the Efficacy of Lumateperone for the Treatment of Major Depressive Disorder), which is not on this map. Cited by 12 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.
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.
Intra-Cellular Therapies, Inc. / "A Randomized, Double-blind, Placebo-controlled, Single Site Study to Evaluate the Efficacy of Lumateperone for the Treatment of Major Depressive Disorder (MDD) and Early Life Trauma in Adult Patients Aged 21 to 70 Years
Who cites it
12 citing papers in PubMed.
- Physical and cognitive contributions to fatigue perception: The interplay between local muscle fatigue and sensory prediction error.iScience · 2026Article
- A novel approach-avoidance task to study decision making under outcome uncertainty.Psychonomic bulletin & review · 2026Article
- Physical activity moderates the relationship between PTSD symptom severity and approach-avoidance conflict decision-making.Journal of anxiety disorders · 2025Article
- Episodic Memories Bias Contextual Threat Inferences after Aerobic and Mind-Body Exercise.Mental health and physical activity · 2025Article
- Physical Activity Is Positively Associated with Model-Based Decision-Making in Pursuit of Reward in Trauma-Exposed Adults.Medicine and science in sports and exercise · 2025Article
- Agent-Based Behavioral Modeling of Human Associative Learning in a Complex Approach-Avoidance Conflict Task.Computational brain & behavior · 2025Article
- Decoding threat neurocircuitry representations during traumatic memory recall in PTSD.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2025Article
- How Distributed Subcortical Integration of Reward and Threat May Inform Subsequent Approach-Avoidance Decisions.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Cognitive Signatures of Depressive and Anhedonic Symptoms and Affective States Using Computational Modeling and Neurocognitive Testing.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2024Article
- Decoding context memories for threat in large-scale neural networks.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- Decision-making for concurrent reward and threat is differentially modulated by trauma exposure and PTSD symptom severity.Behaviour research and therapy · 2023Article
- Quantifying aberrant approach-avoidance conflict in psychopathology: A review of computational approaches.Neuroscience and biobehavioral reviews · 2023Review
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Many real-world situations require navigating decisions for both reward and threat. While there has been significant progress in understanding mechanisms of decision-making and mediating neurocircuitry separately for reward and threat, there is limited understanding of situations where reward and threat contingencies compete to create approach-avoidance conflict (AAC). Here, we leverage computational learning models, independent component analysis (ICA), and multivariate pattern analysis (MVPA) approaches to understand decision-making during a novel task that embeds concurrent reward and threat learning and manipulates congruency between reward and threat probabilities. Computational modeling supported a modified reinforcement learning model where participants integrated reward and threat value into a combined total value according to an individually varying policy parameter, which was highly predictive of decisions to approach reward vs avoid threat during trials where the highest reward option was also the highest threat option (i.e., approach-avoidance conflict). ICA analyses demonstrated unique roles for salience, frontoparietal, medial prefrontal, and inferior frontal networks in differential encoding of reward vs threat prediction error and value signals. The left frontoparietal network uniquely encoded degree of conflict between reward and threat value at the time of choice. MVPA demonstrated that delivery of reward and threat could accurately be decoded within salience and inferior frontal networks, respectively, and that decisions to approach reward vs avoid threat were predicted by the relative degree to which these reward vs threat representations were active at the time of choice. This latter result suggests that navigating AAC decisions involves generating mental representations for possible decision outcomes, and relative activation of these representations may bias subsequent decision-making towards approaching reward or avoiding threat accordingly.
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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.