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Frontal network dynamics reflect neurocomputational mechanisms for reducing maladaptive biases in motivated action
Motivation exerts control over behavior by eliciting Pavlovian responses, which can either match or conflict with instrumental action. We can overcome maladaptive motivational influences putatively through frontal cognitive control. However, the neurocomputational mechanisms subserving this control...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6207318/ https://www.ncbi.nlm.nih.gov/pubmed/30335745 http://dx.doi.org/10.1371/journal.pbio.2005979 |
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author | Swart, Jennifer C. Frank, Michael J. Määttä, Jessica I. Jensen, Ole Cools, Roshan den Ouden, Hanneke E. M. |
author_facet | Swart, Jennifer C. Frank, Michael J. Määttä, Jessica I. Jensen, Ole Cools, Roshan den Ouden, Hanneke E. M. |
author_sort | Swart, Jennifer C. |
collection | PubMed |
description | Motivation exerts control over behavior by eliciting Pavlovian responses, which can either match or conflict with instrumental action. We can overcome maladaptive motivational influences putatively through frontal cognitive control. However, the neurocomputational mechanisms subserving this control are unclear; does control entail up-regulating instrumental systems, down-regulating Pavlovian systems, or both? We combined electroencephalography (EEG) recordings with a motivational Go/NoGo learning task (N = 34), in which multiple Go options enabled us to disentangle selective action learning from nonselective Pavlovian responses. Midfrontal theta-band (4 Hz–8 Hz) activity covaried with the level of Pavlovian conflict and was associated with reduced Pavlovian biases rather than reduced instrumental learning biases. Motor and lateral prefrontal regions synchronized to the midfrontal cortex, and these network dynamics predicted the reduction of Pavlovian biases over and above local, midfrontal theta activity. This work links midfrontal processing to detecting Pavlovian conflict and highlights the importance of network processing in reducing the impact of maladaptive, Pavlovian biases. |
format | Online Article Text |
id | pubmed-6207318 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-62073182018-11-19 Frontal network dynamics reflect neurocomputational mechanisms for reducing maladaptive biases in motivated action Swart, Jennifer C. Frank, Michael J. Määttä, Jessica I. Jensen, Ole Cools, Roshan den Ouden, Hanneke E. M. PLoS Biol Research Article Motivation exerts control over behavior by eliciting Pavlovian responses, which can either match or conflict with instrumental action. We can overcome maladaptive motivational influences putatively through frontal cognitive control. However, the neurocomputational mechanisms subserving this control are unclear; does control entail up-regulating instrumental systems, down-regulating Pavlovian systems, or both? We combined electroencephalography (EEG) recordings with a motivational Go/NoGo learning task (N = 34), in which multiple Go options enabled us to disentangle selective action learning from nonselective Pavlovian responses. Midfrontal theta-band (4 Hz–8 Hz) activity covaried with the level of Pavlovian conflict and was associated with reduced Pavlovian biases rather than reduced instrumental learning biases. Motor and lateral prefrontal regions synchronized to the midfrontal cortex, and these network dynamics predicted the reduction of Pavlovian biases over and above local, midfrontal theta activity. This work links midfrontal processing to detecting Pavlovian conflict and highlights the importance of network processing in reducing the impact of maladaptive, Pavlovian biases. Public Library of Science 2018-10-18 /pmc/articles/PMC6207318/ /pubmed/30335745 http://dx.doi.org/10.1371/journal.pbio.2005979 Text en © 2018 Swart et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Swart, Jennifer C. Frank, Michael J. Määttä, Jessica I. Jensen, Ole Cools, Roshan den Ouden, Hanneke E. M. Frontal network dynamics reflect neurocomputational mechanisms for reducing maladaptive biases in motivated action |
title | Frontal network dynamics reflect neurocomputational mechanisms for reducing maladaptive biases in motivated action |
title_full | Frontal network dynamics reflect neurocomputational mechanisms for reducing maladaptive biases in motivated action |
title_fullStr | Frontal network dynamics reflect neurocomputational mechanisms for reducing maladaptive biases in motivated action |
title_full_unstemmed | Frontal network dynamics reflect neurocomputational mechanisms for reducing maladaptive biases in motivated action |
title_short | Frontal network dynamics reflect neurocomputational mechanisms for reducing maladaptive biases in motivated action |
title_sort | frontal network dynamics reflect neurocomputational mechanisms for reducing maladaptive biases in motivated action |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6207318/ https://www.ncbi.nlm.nih.gov/pubmed/30335745 http://dx.doi.org/10.1371/journal.pbio.2005979 |
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