Frontal network dynamics reveal the neurocomputational mechanisms for cognitive control over motivated action

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Frontal network dynamics reveal the neurocomputational mechanisms for cognitive control over motivated action. / Swart, J.C.; Frank, M.J.; Määttä, J.I.; Jensen, Ole; Cools, Roshan; Den Ouden, Hanneke E M.

In: PLoS Biology, 18.10.2018.

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Swart, J.C. ; Frank, M.J. ; Määttä, J.I. ; Jensen, Ole ; Cools, Roshan ; Den Ouden, Hanneke E M. / Frontal network dynamics reveal the neurocomputational mechanisms for cognitive control over motivated action. In: PLoS Biology. 2018.

Bibtex

@article{3fde89b02f3948e395f5811b0d5440bc,
title = "Frontal network dynamics reveal the neurocomputational mechanisms for cognitive control over motivated action",
abstract = "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.",
author = "J.C. Swart and M.J. Frank and J.I. M{\"a}{\"a}tt{\"a} and Ole Jensen and Roshan Cools and {Den Ouden}, {Hanneke E M}",
year = "2018",
month = oct,
day = "18",
doi = "10.1371/journal.pbio.2005979",
language = "English",
journal = "PLoS Biol.",
issn = "1544-9173",
publisher = "Public Library of Science (PLOS)",

}

RIS

TY - JOUR

T1 - Frontal network dynamics reveal the neurocomputational mechanisms for cognitive control over motivated action

AU - Swart, J.C.

AU - Frank, M.J.

AU - Määttä, J.I.

AU - Jensen, Ole

AU - Cools, Roshan

AU - Den Ouden, Hanneke E M

PY - 2018/10/18

Y1 - 2018/10/18

N2 - 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.

AB - 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.

U2 - 10.1371/journal.pbio.2005979

DO - 10.1371/journal.pbio.2005979

M3 - Article

JO - PLoS Biol.

JF - PLoS Biol.

SN - 1544-9173

ER -