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Functional connectivity during frustration: a preliminary study of predictive modeling of irritability in youth
Irritability cuts across many pediatric disorders and is a common presenting complaint in child psychiatry; however, its neural mechanisms remain unclear. One core pathophysiological deficit of irritability is aberrant responses to frustrative nonreward. Here, we conducted a preliminary fMRI study t...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8134471/ https://www.ncbi.nlm.nih.gov/pubmed/33479511 http://dx.doi.org/10.1038/s41386-020-00954-8 |
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author | Scheinost, Dustin Dadashkarimi, Javid Finn, Emily S. Wambach, Caroline G. MacGillivray, Caroline Roule, Alexandra L. Niendam, Tara A. Pine, Daniel S. Brotman, Melissa A. Leibenluft, Ellen Tseng, Wan-Ling |
author_facet | Scheinost, Dustin Dadashkarimi, Javid Finn, Emily S. Wambach, Caroline G. MacGillivray, Caroline Roule, Alexandra L. Niendam, Tara A. Pine, Daniel S. Brotman, Melissa A. Leibenluft, Ellen Tseng, Wan-Ling |
author_sort | Scheinost, Dustin |
collection | PubMed |
description | Irritability cuts across many pediatric disorders and is a common presenting complaint in child psychiatry; however, its neural mechanisms remain unclear. One core pathophysiological deficit of irritability is aberrant responses to frustrative nonreward. Here, we conducted a preliminary fMRI study to examine the ability of functional connectivity during frustrative nonreward to predict irritability in a transdiagnostic sample. This study included 69 youths (mean age = 14.55 years) with varying levels of irritability across diagnostic groups: disruptive mood dysregulation disorder (n = 20), attention-deficit/hyperactivity disorder (n = 14), anxiety disorder (n = 12), and controls (n = 23). During fMRI, participants completed a frustrating cognitive flexibility task. Frustration was evoked by manipulating task difficulty such that, on trials requiring cognitive flexibility, “frustration” blocks had a 50% error rate and some rigged feedback, while “nonfrustration” blocks had a 10% error rate. Frustration and nonfrustration blocks were randomly interspersed. Child and parent reports of the affective reactivity index were used as dimensional measures of irritability. Connectome-based predictive modeling, a machine learning approach, with tenfold cross-validation was conducted to identify networks predicting irritability. Connectivity during frustration (but not nonfrustration) blocks predicted child-reported irritability (ρ = 0.24, root mean square error = 2.02, p = 0.03, permutation testing, 1000 iterations, one-tailed). Results were adjusted for age, sex, medications, motion, ADHD, and anxiety symptoms. The predictive networks of irritability were primarily within motor-sensory networks; among motor-sensory, subcortical, and salience networks; and between these networks and frontoparietal and medial frontal networks. This study provides preliminary evidence that individual differences in irritability may be associated with functional connectivity during frustration, a phenotype-relevant state. |
format | Online Article Text |
id | pubmed-8134471 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-81344712021-05-24 Functional connectivity during frustration: a preliminary study of predictive modeling of irritability in youth Scheinost, Dustin Dadashkarimi, Javid Finn, Emily S. Wambach, Caroline G. MacGillivray, Caroline Roule, Alexandra L. Niendam, Tara A. Pine, Daniel S. Brotman, Melissa A. Leibenluft, Ellen Tseng, Wan-Ling Neuropsychopharmacology Article Irritability cuts across many pediatric disorders and is a common presenting complaint in child psychiatry; however, its neural mechanisms remain unclear. One core pathophysiological deficit of irritability is aberrant responses to frustrative nonreward. Here, we conducted a preliminary fMRI study to examine the ability of functional connectivity during frustrative nonreward to predict irritability in a transdiagnostic sample. This study included 69 youths (mean age = 14.55 years) with varying levels of irritability across diagnostic groups: disruptive mood dysregulation disorder (n = 20), attention-deficit/hyperactivity disorder (n = 14), anxiety disorder (n = 12), and controls (n = 23). During fMRI, participants completed a frustrating cognitive flexibility task. Frustration was evoked by manipulating task difficulty such that, on trials requiring cognitive flexibility, “frustration” blocks had a 50% error rate and some rigged feedback, while “nonfrustration” blocks had a 10% error rate. Frustration and nonfrustration blocks were randomly interspersed. Child and parent reports of the affective reactivity index were used as dimensional measures of irritability. Connectome-based predictive modeling, a machine learning approach, with tenfold cross-validation was conducted to identify networks predicting irritability. Connectivity during frustration (but not nonfrustration) blocks predicted child-reported irritability (ρ = 0.24, root mean square error = 2.02, p = 0.03, permutation testing, 1000 iterations, one-tailed). Results were adjusted for age, sex, medications, motion, ADHD, and anxiety symptoms. The predictive networks of irritability were primarily within motor-sensory networks; among motor-sensory, subcortical, and salience networks; and between these networks and frontoparietal and medial frontal networks. This study provides preliminary evidence that individual differences in irritability may be associated with functional connectivity during frustration, a phenotype-relevant state. Springer International Publishing 2021-01-21 2021-06 /pmc/articles/PMC8134471/ /pubmed/33479511 http://dx.doi.org/10.1038/s41386-020-00954-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Scheinost, Dustin Dadashkarimi, Javid Finn, Emily S. Wambach, Caroline G. MacGillivray, Caroline Roule, Alexandra L. Niendam, Tara A. Pine, Daniel S. Brotman, Melissa A. Leibenluft, Ellen Tseng, Wan-Ling Functional connectivity during frustration: a preliminary study of predictive modeling of irritability in youth |
title | Functional connectivity during frustration: a preliminary study of predictive modeling of irritability in youth |
title_full | Functional connectivity during frustration: a preliminary study of predictive modeling of irritability in youth |
title_fullStr | Functional connectivity during frustration: a preliminary study of predictive modeling of irritability in youth |
title_full_unstemmed | Functional connectivity during frustration: a preliminary study of predictive modeling of irritability in youth |
title_short | Functional connectivity during frustration: a preliminary study of predictive modeling of irritability in youth |
title_sort | functional connectivity during frustration: a preliminary study of predictive modeling of irritability in youth |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8134471/ https://www.ncbi.nlm.nih.gov/pubmed/33479511 http://dx.doi.org/10.1038/s41386-020-00954-8 |
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