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  Aberrant probabilistic reinforcement learning in first-degree relatives of individuals with bipolar disorder

Linke, J. O., Koppe, G., Scholz, V., Kanske, P., Durstewitz, D., & Wessa, M. (2020). Aberrant probabilistic reinforcement learning in first-degree relatives of individuals with bipolar disorder. Journal of Affective Disorders, 264, 400-406. doi:10.1016/j.jad.2019.11.063.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0005-8282-4 Version Permalink: http://hdl.handle.net/21.11116/0000-0006-F9E1-3
Genre: Journal Article

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 Creators:
Linke, Julia O.1, Author
Koppe, Georgia2, Author
Scholz, Vanessa1, Author
Kanske, Philipp3, 4, Author              
Durstewitz, Daniel2, Author
Wessa, Michèle1, Author
Affiliations:
1Department of Clinical Psychology and Neuropsychology, Institute of Psychology, Johannes Gutenberg University, Mainz, Germany, ou_persistent22              
2Department of Theoretical Neuroscience, Central Institute of Mental Health, Mannheim, Germany, ou_persistent22              
3Chair for Clinical Psychology and Behavioral Neuroscience, Faculty of Psychology, TU Dresden, Germany, ou_persistent22              
4Research Group Social Stress and Family Health, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_3025667              

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Free keywords: Bipolar disorder; First-degree relatives; Behavioral activation system (BAS); Reinforcement learning; Computational modeling
 Abstract: Background Motivational dysregulation represents a core vulnerability factor for bipolar disorder. Whether this also comprises aberrant learning of stimulus-reinforcer contingencies is less clear. Methods To answer this question, we compared healthy first-degree relatives of individuals with bipolar disorder (n = 42) known to convey an increased risk of developing a bipolar spectrum disorder and healthy individuals (n = 97). Further, we investigated the effects of the behavioral activation system (BAS) on reinforcement learning across the entire sample. All participants were assessed with a probabilistic learning task that distinguishes learning from positive and negative feedback. Main outcome measures included choice frequencies and learning rate parameters generated by computational reinforcement learning algorithms. Results First-degree relatives choose more rewarding stimuli more consistently and showed marginally reduced learning rates from unexpected negative feedback. Further, first-degree relatives had lower BAS scores than controls, which were negatively associated with learning rates from unexpected negative feedback. Limitations However as probands also reported other mental disorders such as Attention-Deficit/Hyperactivity Disorder and substance abuse among their first-degree relatives, we cannot know, whether these findings are specific to the risk for bipolar disorder. Conclusion The behavior of first-degree relatives of individuals with bipolar disorder, who also display increased BAS sensitivity, is less influenced by unexpected negative feedback. This reduced learning from unexpected negative feedback biases subsequent choices towards stimuli with higher probabilities for a reward. In sum, our results confirm the role of aberrant reinforcement learning in the pathophysiology of bipolar disorder.

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Language(s): eng - English
 Dates: 2019-09-222019-06-122019-11-102019-11-122020-03-01
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1016/j.jad.2019.11.063
Other: epub 2019
PMID: 32056775
 Degree: -

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Title: Journal of Affective Disorders
Source Genre: Journal
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Publ. Info: Amsterdam : Elsevier
Pages: - Volume / Issue: 264 Sequence Number: - Start / End Page: 400 - 406 Identifier: ISSN: 0165-0327
CoNE: https://pure.mpg.de/cone/journals/resource/954925480595