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A Neurocomputational Model for Intrinsic Reward
Standard economic indicators provide an incomplete picture of what we value both as individuals and as a society. Furthermore, canonical macroeconomic measures, such as GDP, do not account for non-market activities (e.g., cooking, childcare) that nevertheless impact well-being. Here, we introduce a...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Society for Neuroscience
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8549542/ https://www.ncbi.nlm.nih.gov/pubmed/34544831 http://dx.doi.org/10.1523/JNEUROSCI.0858-20.2021 |
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author | Chew, Benjamin Blain, Bastien Dolan, Raymond J. Rutledge, Robb B. |
author_facet | Chew, Benjamin Blain, Bastien Dolan, Raymond J. Rutledge, Robb B. |
author_sort | Chew, Benjamin |
collection | PubMed |
description | Standard economic indicators provide an incomplete picture of what we value both as individuals and as a society. Furthermore, canonical macroeconomic measures, such as GDP, do not account for non-market activities (e.g., cooking, childcare) that nevertheless impact well-being. Here, we introduce a computational tool that measures the affective value of experiences (e.g., playing a musical instrument without errors). We go on to validate this tool with neural data, using fMRI to measure neural activity in male and female human subjects performing a reinforcement learning task that incorporated periodic ratings of subjective affective state. Learning performance determined level of payment (i.e., extrinsic reward). Crucially, the task also incorporated a skilled performance component (i.e., intrinsic reward) which did not influence payment. Both extrinsic and intrinsic rewards influenced affective dynamics, and their relative influence could be captured in our computational model. Individuals for whom intrinsic rewards had a greater influence on affective state than extrinsic rewards had greater ventromedial prefrontal cortex (vmPFC) activity for intrinsic than extrinsic rewards. Thus, we show that computational modeling of affective dynamics can index the subjective value of intrinsic relative to extrinsic rewards, a “computational hedonometer” that reflects both behavior and neural activity that quantifies the affective value of experience. SIGNIFICANCE STATEMENT Traditional economic indicators are increasingly recognized to provide an incomplete picture of what we value as a society. Standard economic approaches struggle to accurately assign values to non-market activities that nevertheless may be intrinsically rewarding, prompting a need for new tools to measure what really matters to individuals. Using a combination of neuroimaging and computational modeling, we show that despite their lack of instrumental value, intrinsic rewards influence subjective affective state and ventromedial prefrontal cortex (vmPFC) activity. The relative degree to which extrinsic and intrinsic rewards influence affective state is predictive of their relative impacts on neural activity, confirming the utility of our approach for measuring the affective value of experiences and other non-market activities in individuals. |
format | Online Article Text |
id | pubmed-8549542 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Society for Neuroscience |
record_format | MEDLINE/PubMed |
spelling | pubmed-85495422021-10-28 A Neurocomputational Model for Intrinsic Reward Chew, Benjamin Blain, Bastien Dolan, Raymond J. Rutledge, Robb B. J Neurosci Research Articles Standard economic indicators provide an incomplete picture of what we value both as individuals and as a society. Furthermore, canonical macroeconomic measures, such as GDP, do not account for non-market activities (e.g., cooking, childcare) that nevertheless impact well-being. Here, we introduce a computational tool that measures the affective value of experiences (e.g., playing a musical instrument without errors). We go on to validate this tool with neural data, using fMRI to measure neural activity in male and female human subjects performing a reinforcement learning task that incorporated periodic ratings of subjective affective state. Learning performance determined level of payment (i.e., extrinsic reward). Crucially, the task also incorporated a skilled performance component (i.e., intrinsic reward) which did not influence payment. Both extrinsic and intrinsic rewards influenced affective dynamics, and their relative influence could be captured in our computational model. Individuals for whom intrinsic rewards had a greater influence on affective state than extrinsic rewards had greater ventromedial prefrontal cortex (vmPFC) activity for intrinsic than extrinsic rewards. Thus, we show that computational modeling of affective dynamics can index the subjective value of intrinsic relative to extrinsic rewards, a “computational hedonometer” that reflects both behavior and neural activity that quantifies the affective value of experience. SIGNIFICANCE STATEMENT Traditional economic indicators are increasingly recognized to provide an incomplete picture of what we value as a society. Standard economic approaches struggle to accurately assign values to non-market activities that nevertheless may be intrinsically rewarding, prompting a need for new tools to measure what really matters to individuals. Using a combination of neuroimaging and computational modeling, we show that despite their lack of instrumental value, intrinsic rewards influence subjective affective state and ventromedial prefrontal cortex (vmPFC) activity. The relative degree to which extrinsic and intrinsic rewards influence affective state is predictive of their relative impacts on neural activity, confirming the utility of our approach for measuring the affective value of experiences and other non-market activities in individuals. Society for Neuroscience 2021-10-27 /pmc/articles/PMC8549542/ /pubmed/34544831 http://dx.doi.org/10.1523/JNEUROSCI.0858-20.2021 Text en Copyright © 2021 Chew et al. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed. |
spellingShingle | Research Articles Chew, Benjamin Blain, Bastien Dolan, Raymond J. Rutledge, Robb B. A Neurocomputational Model for Intrinsic Reward |
title | A Neurocomputational Model for Intrinsic Reward |
title_full | A Neurocomputational Model for Intrinsic Reward |
title_fullStr | A Neurocomputational Model for Intrinsic Reward |
title_full_unstemmed | A Neurocomputational Model for Intrinsic Reward |
title_short | A Neurocomputational Model for Intrinsic Reward |
title_sort | neurocomputational model for intrinsic reward |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8549542/ https://www.ncbi.nlm.nih.gov/pubmed/34544831 http://dx.doi.org/10.1523/JNEUROSCI.0858-20.2021 |
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