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

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Title: Reward and avoidance learning in the context of aversive environments and possible implications for depressive symptoms.
Authors: Sebold, Miriam (AUTHOR), Garbusow, M. (AUTHOR), Jetzschmann, P. (AUTHOR), Schad, D. J. (AUTHOR), Nebe, S. (AUTHOR), Schlagenhauf, F. (AUTHOR), Heinz, A. (AUTHOR), Rapp, M. (AUTHOR), Romanczuk-Seiferth, N. (AUTHOR)
Source: Psychopharmacology. Aug2019, Vol. 236 Issue 8, p2437-2449. 13p. 1 Chart, 4 Graphs.
Subjects: Operant conditioning, Human behavior, Aversive stimuli, Human ecology, Ecology, Approach behavior, Adolescent friendships
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. [ABSTRACT FROM AUTHOR]
Copyright of Psychopharmacology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Reward and avoidance learning in the context of aversive environments and possible implications for depressive symptoms.
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  Data: <searchLink fieldCode="AR" term="%22Sebold%2C+Miriam%22">Sebold, Miriam</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Garbusow%2C+M%2E%22">Garbusow, M.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jetzschmann%2C+P%2E%22">Jetzschmann, P.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Schad%2C+D%2E+J%2E%22">Schad, D. J.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Nebe%2C+S%2E%22">Nebe, S.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Schlagenhauf%2C+F%2E%22">Schlagenhauf, F.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Heinz%2C+A%2E%22">Heinz, A.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Rapp%2C+M%2E%22">Rapp, M.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Romanczuk-Seiferth%2C+N%2E%22">Romanczuk-Seiferth, N.</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Psychopharmacology%22">Psychopharmacology</searchLink>. Aug2019, Vol. 236 Issue 8, p2437-2449. 13p. 1 Chart, 4 Graphs.
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  Data: 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. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Psychopharmacology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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