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Functional MRI study of feedback-based reinforcement learning in depression
Reinforcement learning depends upon the integrity of emotional circuitry to establish associations between environmental cues, decisions, and positive or negative outcomes in order to guide behavior through experience. The emotional dysregulation characteristic of major depressive disorder (MDD) may...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9807874/ https://www.ncbi.nlm.nih.gov/pubmed/36605827 http://dx.doi.org/10.3389/fninf.2022.1028121 |
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author | Kustubayeva, Almira M. Nelson, Erik B. Smith, Michael L. Allendorfer, Jane B. Eliassen, James C. |
author_facet | Kustubayeva, Almira M. Nelson, Erik B. Smith, Michael L. Allendorfer, Jane B. Eliassen, James C. |
author_sort | Kustubayeva, Almira M. |
collection | PubMed |
description | Reinforcement learning depends upon the integrity of emotional circuitry to establish associations between environmental cues, decisions, and positive or negative outcomes in order to guide behavior through experience. The emotional dysregulation characteristic of major depressive disorder (MDD) may alter activity in frontal and limbic structures that are key to learning. Although reward and decision-making have been examined in MDD, the effects of depression on associative learning is less well studied. We investigated whether depressive symptoms would be related to abnormalities in learning-related brain activity as measured by functional magnetic resonance imaging (fMRI). Also, we explored whether melancholic and atypical features were associated with altered brain activity. We conducted MRI scans on a 4T Varian MRI system in 10 individuals with MDD and 10 healthy subjects. We examined event-related brain activation during feedback-based learning task using Analysis of Functional NeuroImages (AFNI) for image processing and statistical analysis. We observed that MDD patients exhibited reduced activation in visual cortex but increased activation in cingulate and insular regions compared to healthy participants. Also, in relation to features of depressive subtypes, we observed that levels of activation in striatal, thalamic, and precuneus regions were negatively correlated with atypical characteristics. These results suggest that the effects of MDD change the neural circuitry underlying associative learning, and these effects may depend upon subtype features of MDD. |
format | Online Article Text |
id | pubmed-9807874 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98078742023-01-04 Functional MRI study of feedback-based reinforcement learning in depression Kustubayeva, Almira M. Nelson, Erik B. Smith, Michael L. Allendorfer, Jane B. Eliassen, James C. Front Neuroinform Neuroscience Reinforcement learning depends upon the integrity of emotional circuitry to establish associations between environmental cues, decisions, and positive or negative outcomes in order to guide behavior through experience. The emotional dysregulation characteristic of major depressive disorder (MDD) may alter activity in frontal and limbic structures that are key to learning. Although reward and decision-making have been examined in MDD, the effects of depression on associative learning is less well studied. We investigated whether depressive symptoms would be related to abnormalities in learning-related brain activity as measured by functional magnetic resonance imaging (fMRI). Also, we explored whether melancholic and atypical features were associated with altered brain activity. We conducted MRI scans on a 4T Varian MRI system in 10 individuals with MDD and 10 healthy subjects. We examined event-related brain activation during feedback-based learning task using Analysis of Functional NeuroImages (AFNI) for image processing and statistical analysis. We observed that MDD patients exhibited reduced activation in visual cortex but increased activation in cingulate and insular regions compared to healthy participants. Also, in relation to features of depressive subtypes, we observed that levels of activation in striatal, thalamic, and precuneus regions were negatively correlated with atypical characteristics. These results suggest that the effects of MDD change the neural circuitry underlying associative learning, and these effects may depend upon subtype features of MDD. Frontiers Media S.A. 2022-12-20 /pmc/articles/PMC9807874/ /pubmed/36605827 http://dx.doi.org/10.3389/fninf.2022.1028121 Text en Copyright © 2022 Kustubayeva, Nelson, Smith, Allendorfer and Eliassen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Kustubayeva, Almira M. Nelson, Erik B. Smith, Michael L. Allendorfer, Jane B. Eliassen, James C. Functional MRI study of feedback-based reinforcement learning in depression |
title | Functional MRI study of feedback-based reinforcement learning in depression |
title_full | Functional MRI study of feedback-based reinforcement learning in depression |
title_fullStr | Functional MRI study of feedback-based reinforcement learning in depression |
title_full_unstemmed | Functional MRI study of feedback-based reinforcement learning in depression |
title_short | Functional MRI study of feedback-based reinforcement learning in depression |
title_sort | functional mri study of feedback-based reinforcement learning in depression |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9807874/ https://www.ncbi.nlm.nih.gov/pubmed/36605827 http://dx.doi.org/10.3389/fninf.2022.1028121 |
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