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Contributions of default mode network stability and deactivation to adolescent task engagement

Out of the several intrinsic brain networks discovered through resting-state functional analyses in the past decade, the default mode network (DMN) has been the subject of intense interest and study. In particular, the DMN shows marked suppression during task engagement, and has led to hypothesized...

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Autores principales: McCormick, Ethan M., Telzer, Eva H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6303343/
https://www.ncbi.nlm.nih.gov/pubmed/30575799
http://dx.doi.org/10.1038/s41598-018-36269-4
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author McCormick, Ethan M.
Telzer, Eva H.
author_facet McCormick, Ethan M.
Telzer, Eva H.
author_sort McCormick, Ethan M.
collection PubMed
description Out of the several intrinsic brain networks discovered through resting-state functional analyses in the past decade, the default mode network (DMN) has been the subject of intense interest and study. In particular, the DMN shows marked suppression during task engagement, and has led to hypothesized roles in internally-directed cognition that need to be down-regulated in order to perform goal-directed behaviors. Previous work has largely focused on univariate deactivation as the mechanism of DMN suppression. However, given the transient nature of DMN down-regulation during task, an important question arises: Does the DMN need to be strongly, or more stably suppressed to promote successful task learning? In order to explore this question, 65 adolescents (M(age) = 13.32; 21 females) completed a risky decision-making task during an fMRI scan. We tested our primary question by examining individual differences in absolute level of deactivation against the stability of activation across time in predicting levels of feedback learning on the task. To measure stability, we utilized a model-based functional connectivity approach that estimates the stability of activation across time within a region. In line with our hypothesis, the stability of activation in default mode regions predicted task engagement over and above the absolute level of DMN deactivation, revealing a new mechanism by which the brain can suppress the influence of brain networks on behavior. These results also highlight the importance of adopting model-based network approaches to understand the functional dynamics of the brain.
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spelling pubmed-63033432018-12-28 Contributions of default mode network stability and deactivation to adolescent task engagement McCormick, Ethan M. Telzer, Eva H. Sci Rep Article Out of the several intrinsic brain networks discovered through resting-state functional analyses in the past decade, the default mode network (DMN) has been the subject of intense interest and study. In particular, the DMN shows marked suppression during task engagement, and has led to hypothesized roles in internally-directed cognition that need to be down-regulated in order to perform goal-directed behaviors. Previous work has largely focused on univariate deactivation as the mechanism of DMN suppression. However, given the transient nature of DMN down-regulation during task, an important question arises: Does the DMN need to be strongly, or more stably suppressed to promote successful task learning? In order to explore this question, 65 adolescents (M(age) = 13.32; 21 females) completed a risky decision-making task during an fMRI scan. We tested our primary question by examining individual differences in absolute level of deactivation against the stability of activation across time in predicting levels of feedback learning on the task. To measure stability, we utilized a model-based functional connectivity approach that estimates the stability of activation across time within a region. In line with our hypothesis, the stability of activation in default mode regions predicted task engagement over and above the absolute level of DMN deactivation, revealing a new mechanism by which the brain can suppress the influence of brain networks on behavior. These results also highlight the importance of adopting model-based network approaches to understand the functional dynamics of the brain. Nature Publishing Group UK 2018-12-21 /pmc/articles/PMC6303343/ /pubmed/30575799 http://dx.doi.org/10.1038/s41598-018-36269-4 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
McCormick, Ethan M.
Telzer, Eva H.
Contributions of default mode network stability and deactivation to adolescent task engagement
title Contributions of default mode network stability and deactivation to adolescent task engagement
title_full Contributions of default mode network stability and deactivation to adolescent task engagement
title_fullStr Contributions of default mode network stability and deactivation to adolescent task engagement
title_full_unstemmed Contributions of default mode network stability and deactivation to adolescent task engagement
title_short Contributions of default mode network stability and deactivation to adolescent task engagement
title_sort contributions of default mode network stability and deactivation to adolescent task engagement
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6303343/
https://www.ncbi.nlm.nih.gov/pubmed/30575799
http://dx.doi.org/10.1038/s41598-018-36269-4
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