ArticleDepression and anxiety2020
Neurocognitive predictors of self-reported reward responsivity and approach motivation in depression: A data-driven approach.
Article in Depression and anxiety, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Catch the drift: Depressive symptoms track neural response during more efficient decision-making for negative self-referents.Journal of affective disorders reports · 2023Article
- Comparing resting state and task-based EEG using machine learning to predict vulnerability to depression in a non-clinical population.Scientific reports · 2023Article
- Associating broad and clinically defined polygenic scores for depression with depression-related phenotypes.Scientific reports · 2023Article
- Computational Modeling of Self-Referential Processing Reveals Domain General Associations with Adolescent Anxiety Symptoms.Research on child and adolescent psychopathology · 2023Article
- Supervised Machine Learning: A Brief Primer.Behavior therapy · 2020Review
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9 authors.
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Abstract
backgroundIndividual differences in reward-related processes, such as reward responsivity and approach motivation, appear to play a role in the nature and course of depression. Prior work suggests that cognitive biases for valenced information may contribute to these reward processes. Yet there is little work examining how biased attention, processing, and memory for positively and negatively valenced information may be associated with reward-related processes in samples with depression symptoms.
methodsWe used a data-driven, machine learning (elastic net) approach to identify the best predictors of self-reported reward-related processes using multiple tasks of attention, processing, and memory for valenced information measured across behavioral, eye tracking, psychophysiological, and computational modeling approaches (n = 202). Participants were adults (ages 18-35) who ranged in depression symptom severity from mild to severe.
resultsModels predicted between 5.0-12.2% and 9.7-28.0% of held-out test sample variance in approach motivation and reward responsivity, respectively. Low self-referential processing of positively valenced information was the most robust, albeit modest, predictor of low approach motivation and reward responsivity.
conclusionsSelf-referential processing of positive information is the strongest predictor of reward responsivity and approach motivation in a sample ranging from mild to severe depression symptom severity. Experiments are now needed to clarify the causal relationship between self-referential processing of positively valenced information and reward processes in depression.
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