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Functions of Learning Rate in Adaptive Reward Learning
As a crucial cognitive function, learning applies prediction error (the discrepancy between the prediction from learning and the world state) to adjust predictions of the future. How much prediction error affects this adjustment also depends on the learning rate. Our understanding to the learning ra...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5723661/ https://www.ncbi.nlm.nih.gov/pubmed/29270119 http://dx.doi.org/10.3389/fnhum.2017.00592 |
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author | Wu, Xi Wang, Ting Liu, Chang Wu, Tao Jiang, Jiefeng Zhou, Dong Zhou, Jiliu |
author_facet | Wu, Xi Wang, Ting Liu, Chang Wu, Tao Jiang, Jiefeng Zhou, Dong Zhou, Jiliu |
author_sort | Wu, Xi |
collection | PubMed |
description | As a crucial cognitive function, learning applies prediction error (the discrepancy between the prediction from learning and the world state) to adjust predictions of the future. How much prediction error affects this adjustment also depends on the learning rate. Our understanding to the learning rate is still limited, in terms of (1) how it is modulated by other factors, and (2) the specific mechanisms of how learning rate interacts with prediction error to update learning. We applied computational modeling and functional magnetic resonance imaging to investigate these issues. We found that, when human participants performed a reward learning task, reward magnitude modulated learning rate. Modulation strength further predicted the difference in behavior following high vs. low reward across subjects. Imaging results further showed that this modulation was reflected in brain regions where the reward feedback is also encoded, such as the medial prefrontal cortex (MFC), precuneus, and posterior cingulate cortex. Furthermore, for the first time, we observed that the integration of the learning rate and the reward prediction error was represented in MFC activity. These findings extend our understanding of adaptive learning by demonstrating how it functions in a chain reaction of prediction updating. |
format | Online Article Text |
id | pubmed-5723661 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-57236612017-12-21 Functions of Learning Rate in Adaptive Reward Learning Wu, Xi Wang, Ting Liu, Chang Wu, Tao Jiang, Jiefeng Zhou, Dong Zhou, Jiliu Front Hum Neurosci Neuroscience As a crucial cognitive function, learning applies prediction error (the discrepancy between the prediction from learning and the world state) to adjust predictions of the future. How much prediction error affects this adjustment also depends on the learning rate. Our understanding to the learning rate is still limited, in terms of (1) how it is modulated by other factors, and (2) the specific mechanisms of how learning rate interacts with prediction error to update learning. We applied computational modeling and functional magnetic resonance imaging to investigate these issues. We found that, when human participants performed a reward learning task, reward magnitude modulated learning rate. Modulation strength further predicted the difference in behavior following high vs. low reward across subjects. Imaging results further showed that this modulation was reflected in brain regions where the reward feedback is also encoded, such as the medial prefrontal cortex (MFC), precuneus, and posterior cingulate cortex. Furthermore, for the first time, we observed that the integration of the learning rate and the reward prediction error was represented in MFC activity. These findings extend our understanding of adaptive learning by demonstrating how it functions in a chain reaction of prediction updating. Frontiers Media S.A. 2017-12-06 /pmc/articles/PMC5723661/ /pubmed/29270119 http://dx.doi.org/10.3389/fnhum.2017.00592 Text en Copyright © 2017 Wu, Wang, Liu, Wu, Jiang, Zhou and Zhou. http://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) or licensor 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 Wu, Xi Wang, Ting Liu, Chang Wu, Tao Jiang, Jiefeng Zhou, Dong Zhou, Jiliu Functions of Learning Rate in Adaptive Reward Learning |
title | Functions of Learning Rate in Adaptive Reward Learning |
title_full | Functions of Learning Rate in Adaptive Reward Learning |
title_fullStr | Functions of Learning Rate in Adaptive Reward Learning |
title_full_unstemmed | Functions of Learning Rate in Adaptive Reward Learning |
title_short | Functions of Learning Rate in Adaptive Reward Learning |
title_sort | functions of learning rate in adaptive reward learning |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5723661/ https://www.ncbi.nlm.nih.gov/pubmed/29270119 http://dx.doi.org/10.3389/fnhum.2017.00592 |
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