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Elevated emotion network connectivity is associated with fluctuations in depression

Elevated emotion network connectivity is thought to leave people vulnerable to become and stay depressed. The mechanism through which this arises is however unclear. Here, we test the idea that the connectivity of emotion networks is associated with more extreme fluctuations in depression over time,...

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Autores principales: Kelley, Sean W., Fisher, Aaron J., Lee, Chi Tak, Gallagher, Eoghan, Hanlon, Anna K., Robertson, Ian H., Gillan, Claire M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10636367/
https://www.ncbi.nlm.nih.gov/pubmed/37903279
http://dx.doi.org/10.1073/pnas.2216499120
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author Kelley, Sean W.
Fisher, Aaron J.
Lee, Chi Tak
Gallagher, Eoghan
Hanlon, Anna K.
Robertson, Ian H.
Gillan, Claire M.
author_facet Kelley, Sean W.
Fisher, Aaron J.
Lee, Chi Tak
Gallagher, Eoghan
Hanlon, Anna K.
Robertson, Ian H.
Gillan, Claire M.
author_sort Kelley, Sean W.
collection PubMed
description Elevated emotion network connectivity is thought to leave people vulnerable to become and stay depressed. The mechanism through which this arises is however unclear. Here, we test the idea that the connectivity of emotion networks is associated with more extreme fluctuations in depression over time, rather than necessarily more severe depression. We gathered data from two independent samples of N = 155 paid students and N = 194 citizen scientists who rated their positive and negative emotions on a smartphone app twice a day and completed a weekly depression questionnaire for 8 wk. We constructed thousands of personalized emotion networks for each participant and tested whether connectivity was associated with severity of depression or its variance over 8 wk. Network connectivity was positively associated with baseline depression severity in citizen scientists, but not paid students. In contrast, 8-wk variance of depression was correlated with network connectivity in both samples. When controlling for depression variance, the association between connectivity and baseline depression severity in citizen scientists was no longer significant. We replicated these findings in an independent community sample (N = 519). We conclude that elevated network connectivity is associated with greater variability in depression symptoms. This variability only translates into increased severity in samples where depression is on average low and positively skewed, causing mean and variance to be more strongly correlated. These findings, although correlational, suggest that while emotional network connectivity could predispose individuals to severe depression, it could also be leveraged to bring about therapeutic improvements.
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spelling pubmed-106363672023-11-15 Elevated emotion network connectivity is associated with fluctuations in depression Kelley, Sean W. Fisher, Aaron J. Lee, Chi Tak Gallagher, Eoghan Hanlon, Anna K. Robertson, Ian H. Gillan, Claire M. Proc Natl Acad Sci U S A Social Sciences Elevated emotion network connectivity is thought to leave people vulnerable to become and stay depressed. The mechanism through which this arises is however unclear. Here, we test the idea that the connectivity of emotion networks is associated with more extreme fluctuations in depression over time, rather than necessarily more severe depression. We gathered data from two independent samples of N = 155 paid students and N = 194 citizen scientists who rated their positive and negative emotions on a smartphone app twice a day and completed a weekly depression questionnaire for 8 wk. We constructed thousands of personalized emotion networks for each participant and tested whether connectivity was associated with severity of depression or its variance over 8 wk. Network connectivity was positively associated with baseline depression severity in citizen scientists, but not paid students. In contrast, 8-wk variance of depression was correlated with network connectivity in both samples. When controlling for depression variance, the association between connectivity and baseline depression severity in citizen scientists was no longer significant. We replicated these findings in an independent community sample (N = 519). We conclude that elevated network connectivity is associated with greater variability in depression symptoms. This variability only translates into increased severity in samples where depression is on average low and positively skewed, causing mean and variance to be more strongly correlated. These findings, although correlational, suggest that while emotional network connectivity could predispose individuals to severe depression, it could also be leveraged to bring about therapeutic improvements. National Academy of Sciences 2023-10-30 2023-11-07 /pmc/articles/PMC10636367/ /pubmed/37903279 http://dx.doi.org/10.1073/pnas.2216499120 Text en Copyright © 2023 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by/4.0/This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY) (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Social Sciences
Kelley, Sean W.
Fisher, Aaron J.
Lee, Chi Tak
Gallagher, Eoghan
Hanlon, Anna K.
Robertson, Ian H.
Gillan, Claire M.
Elevated emotion network connectivity is associated with fluctuations in depression
title Elevated emotion network connectivity is associated with fluctuations in depression
title_full Elevated emotion network connectivity is associated with fluctuations in depression
title_fullStr Elevated emotion network connectivity is associated with fluctuations in depression
title_full_unstemmed Elevated emotion network connectivity is associated with fluctuations in depression
title_short Elevated emotion network connectivity is associated with fluctuations in depression
title_sort elevated emotion network connectivity is associated with fluctuations in depression
topic Social Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10636367/
https://www.ncbi.nlm.nih.gov/pubmed/37903279
http://dx.doi.org/10.1073/pnas.2216499120
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