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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...

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Autores principales: Swart, Jennifer C., Frank, Michael J., Määttä, Jessica I., Jensen, Ole, Cools, Roshan, den Ouden, Hanneke E. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
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.
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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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