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Effects of Depressive Symptoms, Feelings, and Interoception on Reward-Based Decision-Making: Investigation Using Reinforcement Learning Model
Background: In this study, we examined the relationships between reward-based decision-making in terms of learning rate, memory rate, exploration rate, and depression-related subjective emotional experience, in terms of interoception and feelings, to understand how reward-based decision-making is im...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7464008/ https://www.ncbi.nlm.nih.gov/pubmed/32752282 http://dx.doi.org/10.3390/brainsci10080508 |
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author | Ogishima, Hiroyoshi Maeda, Shunta Tanaka, Yuki Shimada, Hironori |
author_facet | Ogishima, Hiroyoshi Maeda, Shunta Tanaka, Yuki Shimada, Hironori |
author_sort | Ogishima, Hiroyoshi |
collection | PubMed |
description | Background: In this study, we examined the relationships between reward-based decision-making in terms of learning rate, memory rate, exploration rate, and depression-related subjective emotional experience, in terms of interoception and feelings, to understand how reward-based decision-making is impaired in depression. Methods: In all, 52 university students were randomly assigned to an experimental group and a control group. To manipulate interoception, the participants in the experimental group were instructed to tune their internal somatic sense to the skin-conductance-response waveform presented on a display. The participants in the control group were only instructed to stay relaxed. Before and after the manipulation, the participants completed a probabilistic reversal-learning task to assess reward-based decision-making using reinforcement learning modeling. Similarly, participants completed a probe-detection task, a heartbeat-detection task, and self-rated scales. Results: The experimental manipulation of interoception was not successful. In the baseline testing, reinforcement learning modeling indicated a marginally-significant correlation between the exploration rate and depressive symptoms. However, the exploration rate was significantly associated with lower interoceptive attention and higher depressive feeling. Conclusions: The findings suggest that situational characteristics may be closely involved in reward exploration and highlight the clinically-meaningful possibility that intervention for affective processes may impact reward-based decision-making in those with depression. |
format | Online Article Text |
id | pubmed-7464008 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-74640082020-09-04 Effects of Depressive Symptoms, Feelings, and Interoception on Reward-Based Decision-Making: Investigation Using Reinforcement Learning Model Ogishima, Hiroyoshi Maeda, Shunta Tanaka, Yuki Shimada, Hironori Brain Sci Article Background: In this study, we examined the relationships between reward-based decision-making in terms of learning rate, memory rate, exploration rate, and depression-related subjective emotional experience, in terms of interoception and feelings, to understand how reward-based decision-making is impaired in depression. Methods: In all, 52 university students were randomly assigned to an experimental group and a control group. To manipulate interoception, the participants in the experimental group were instructed to tune their internal somatic sense to the skin-conductance-response waveform presented on a display. The participants in the control group were only instructed to stay relaxed. Before and after the manipulation, the participants completed a probabilistic reversal-learning task to assess reward-based decision-making using reinforcement learning modeling. Similarly, participants completed a probe-detection task, a heartbeat-detection task, and self-rated scales. Results: The experimental manipulation of interoception was not successful. In the baseline testing, reinforcement learning modeling indicated a marginally-significant correlation between the exploration rate and depressive symptoms. However, the exploration rate was significantly associated with lower interoceptive attention and higher depressive feeling. Conclusions: The findings suggest that situational characteristics may be closely involved in reward exploration and highlight the clinically-meaningful possibility that intervention for affective processes may impact reward-based decision-making in those with depression. MDPI 2020-08-01 /pmc/articles/PMC7464008/ /pubmed/32752282 http://dx.doi.org/10.3390/brainsci10080508 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ogishima, Hiroyoshi Maeda, Shunta Tanaka, Yuki Shimada, Hironori Effects of Depressive Symptoms, Feelings, and Interoception on Reward-Based Decision-Making: Investigation Using Reinforcement Learning Model |
title | Effects of Depressive Symptoms, Feelings, and Interoception on Reward-Based Decision-Making: Investigation Using Reinforcement Learning Model |
title_full | Effects of Depressive Symptoms, Feelings, and Interoception on Reward-Based Decision-Making: Investigation Using Reinforcement Learning Model |
title_fullStr | Effects of Depressive Symptoms, Feelings, and Interoception on Reward-Based Decision-Making: Investigation Using Reinforcement Learning Model |
title_full_unstemmed | Effects of Depressive Symptoms, Feelings, and Interoception on Reward-Based Decision-Making: Investigation Using Reinforcement Learning Model |
title_short | Effects of Depressive Symptoms, Feelings, and Interoception on Reward-Based Decision-Making: Investigation Using Reinforcement Learning Model |
title_sort | effects of depressive symptoms, feelings, and interoception on reward-based decision-making: investigation using reinforcement learning model |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7464008/ https://www.ncbi.nlm.nih.gov/pubmed/32752282 http://dx.doi.org/10.3390/brainsci10080508 |
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