ArticlePloS one2016
Linking Individual Learning Styles to Approach-Avoidance Motivational Traits and Computational Aspects of Reinforcement Learning.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 10 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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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.
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Who cites it
10 citing papers in PubMed, 24 citations in OpenAlex.
- Estimation-uncertainty affects decisions with and without learning opportunities.Nature communications · 2025Article
- Dynamics Learning Rate Bias in Pigeons: Insights from Reinforcement Learning and Neural Correlates.Animals : an open access journal from MDPI · 2024Article
- Reinforcement feedback impairs locomotor adaptation and retention.Frontiers in behavioral neuroscience · 2024Article
- Quantifying aberrant approach-avoidance conflict in psychopathology: A review of computational approaches.Neuroscience and biobehavioral reviews · 2023Review
- Irrelevant Threats Linger and Affect Behavior in High Anxiety.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Behavioral and physiological characteristics associated with learning performance on an appetitive probabilistic selection task.Physiology & behavior · 2020Article
- Driven by Pain, Not Gain: Computational Approaches to Aversion-Related Decision Making in Psychiatry.Biological psychiatry · 2020Review
- Confirmation bias in human reinforcement learning: Evidence from counterfactual feedback processing.PLoS computational biology · 2017Article
- Trial-by-Trial Modulation of Associative Memory Formation by Reward Prediction Error and Reward Anticipation as Revealed by a Biologically Plausible Computational Model.Frontiers in human neuroscience · 2017Article
- Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Learning how to gain rewards (approach learning) and avoid punishments (avoidance learning) is fundamental for everyday life. While individual differences in approach and avoidance learning styles have been related to genetics and aging, the contribution of personality factors, such as traits, remains undetermined. Moreover, little is known about the computational mechanisms mediating differences in learning styles. Here, we used a probabilistic selection task with positive and negative feedbacks, in combination with computational modelling, to show that individuals displaying better approach (vs. avoidance) learning scored higher on measures of approach (vs. avoidance) trait motivation, but, paradoxically, also displayed reduced learning speed following positive (vs. negative) outcomes. These data suggest that learning different types of information depend on associated reward values and internal motivational drives, possibly determined by personality traits.
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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.