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  Reward and avoidance learning in the context of aversive environments and possible implications for depressive symptoms

Sebold, M., Garbusow, M., Jetzschmann, P., Schad, D. J., Nebe, S., Schlagenhauf, F., et al. (2019). Reward and avoidance learning in the context of aversive environments and possible implications for depressive symptoms. Psychopharmacology. doi:10.1007/s00213-019-05299-9.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0004-42B0-A Version Permalink: http://hdl.handle.net/21.11116/0000-0004-6452-F
Genre: Journal Article

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 Creators:
Sebold, Miriam1, 2, Author
Garbusow, M.1, Author
Jetzschmann, P.1, Author
Schad, D. J.3, Author
Nebe, S.4, Author
Schlagenhauf, Florian1, 5, Author              
Heinz, A.1, Author
Rapp, M.2, Author
Romanczuk-Seiferth, N.1, Author
Affiliations:
1Department of Psychiatry and Psychotherapy, Charité University Medicine Berlin, Germany, ou_persistent22              
2Department of Social and Preventive Medicine, University of Potsdam, Germany, ou_persistent22              
3Research Focus Cognitive Sciences, University of Potsdam, Germany, ou_persistent22              
4Zurich Center for Neuroeconomics (ZNE), University of Zurich, Switzerland, ou_persistent22              
5Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              

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Free keywords: Reward learning; Avoidance learning; Reinforcement learning; Computational psychiatry; Decision-making; Affective modulation; Depression symptoms
 Abstract: Background Aversive stimuli in the environment influence human actions. This includes valence-dependent influences on action selection, e.g., increased avoidance but decreased approach behavior. However, it is yet unclear how aversive stimuli interact with complex learning and decision-making in the reward and avoidance domain. Moreover, the underlying computational mechanisms of these decision-making biases are unknown. Methods To elucidate these mechanisms, 54 healthy young male subjects performed a two-step sequential decision-making task, which allows to computationally model different aspects of learning, e.g., model-free, habitual, and model-based, goal-directed learning. We used a within-subject design, crossing task valence (reward vs. punishment learning) with emotional context (aversive vs. neutral background stimuli). We analyzed choice data, applied a computational model, and performed simulations. Results Whereas model-based learning was not affected, aversive stimuli interacted with model-free learning in a way that depended on task valence. Thus, aversive stimuli increased model-free avoidance learning but decreased model-free reward learning. The computational model confirmed this effect: the parameter lambda that indicates the influence of reward prediction errors on decision values was increased in the punishment condition but decreased in the reward condition when aversive stimuli were present. Further, by using the inferred computational parameters to simulate choice data, our effects were captured. Exploratory analyses revealed that the observed biases were associated with subclinical depressive symptoms. Conclusion Our data show that aversive environmental stimuli affect complex learning and decision-making, which depends on task valence. Further, we provide a model of the underlying computations of this affective modulation. Finally, our finding of increased decision-making biases in subjects reporting subclinical depressive symptoms matches recent reports of amplified Pavlovian influences on action selection in depression and suggests a potential vulnerability factor for mood disorders. We discuss our findings in the light of the involvement of the neuromodulators serotonin and dopamine.

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Language(s): eng - English
 Dates: 2019-01-112019-06-052019-06-28
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1007/s00213-019-05299-9
Other: Epub ahead of print
PMID: 31254091
 Degree: -

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Project name : Lern- und Gewöhnungsprozesse als Prädiktoren für die Entwicklung und Aufrechterhaltung alkoholbezogener Störungen / FOR 1617
Grant ID : HE2597/14-1 ; HE2597/14-2 ; RA1047/2-1 ; RA1047/2-2 ; RO 5046/2-2 ; SCHA1971/1-2 ; SCHL 1969/2-2 ; SCHL 1969/4-1
Funding program : -
Funding organization : German Research Foundation (DFG)
Project name : -
Grant ID : ZMVI1-2516DSM223
Funding program : -
Funding organization : German Federal Ministry of Education and Research (BMBF)

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Title: Psychopharmacology
Source Genre: Journal
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Publ. Info: Heidelberg : Springer-Verlag
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: ISSN: 0033-3158
CoNE: https://pure.mpg.de/cone/journals/resource/954925436478