Neurocognitive predictors of self‐reported reward responsivity and approach motivation in depression: A data‐driven approach. Issue 7 (24th June 2020)
- Record Type:
- Journal Article
- Title:
- Neurocognitive predictors of self‐reported reward responsivity and approach motivation in depression: A data‐driven approach. Issue 7 (24th June 2020)
- Main Title:
- Neurocognitive predictors of self‐reported reward responsivity and approach motivation in depression: A data‐driven approach
- Authors:
- Hsu, Kean J.
McNamara, Mary E.
Shumake, Jason
Stewart, Rochelle A.
Labrada, Jocelyn
Alario, Alexandra
Gonzalez, Guadalupe D. S.
Schnyer, David M.
Beevers, Christopher G. - Abstract:
- Abstract: Background: Individual 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. Methods: We 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. Results: Models 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. Conclusions: Self‐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 areAbstract: Background: Individual 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. Methods: We 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. Results: Models 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. Conclusions: Self‐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. … (more)
- Is Part Of:
- Depression and anxiety. Volume 37:Issue 7(2020)
- Journal:
- Depression and anxiety
- Issue:
- Volume 37:Issue 7(2020)
- Issue Display:
- Volume 37, Issue 7 (2020)
- Year:
- 2020
- Volume:
- 37
- Issue:
- 7
- Issue Sort Value:
- 2020-0037-0007-0000
- Page Start:
- 682
- Page End:
- 697
- Publication Date:
- 2020-06-24
- Subjects:
- attentional bias -- behavioral activation system -- cognitive processing -- depression -- machine learning -- memory
Anxiety -- Periodicals
Depression, Mental -- Periodicals
Depression -- Periodicals
Anxiety -- Periodicals
Anxiety Disorders -- Periodicals
616.8527005 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1520-6394 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/da.23042 ↗
- Languages:
- English
- ISSNs:
- 1091-4269
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3554.590040
British Library DSC - BLDSS-3PM
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- 13341.xml