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Resting-State Brain Signal Variability in Prefrontal Cortex Is Associated With ADHD Symptom Severity in Children

Atypical brain function in attention-deficit/hyperactivity disorder (ADHD) has been identified using both task-activation and functional connectivity fMRI approaches. Recent work highlights the potential for another measure derived from functional neuroimaging data, brain signal variability, to reve...

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Autores principales: Nomi, Jason S., Schettini, Elana, Voorhies, Willa, Bolt, Taylor S., Heller, Aaron S., Uddin, Lucina Q.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5857584/
https://www.ncbi.nlm.nih.gov/pubmed/29593515
http://dx.doi.org/10.3389/fnhum.2018.00090
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author Nomi, Jason S.
Schettini, Elana
Voorhies, Willa
Bolt, Taylor S.
Heller, Aaron S.
Uddin, Lucina Q.
author_facet Nomi, Jason S.
Schettini, Elana
Voorhies, Willa
Bolt, Taylor S.
Heller, Aaron S.
Uddin, Lucina Q.
author_sort Nomi, Jason S.
collection PubMed
description Atypical brain function in attention-deficit/hyperactivity disorder (ADHD) has been identified using both task-activation and functional connectivity fMRI approaches. Recent work highlights the potential for another measure derived from functional neuroimaging data, brain signal variability, to reveal insights into clinical conditions. Higher brain signal variability has previously been linked with optimal behavioral performance. At present, little is known regarding the relationship between resting-state brain signal variability and ADHD symptom severity. The current study examined the relationship between a measure of moment-to-moment brain signal variability called mean-square successive difference (MSSD) and ADHD symptomatology in a group of children (7–12 years old) with (n = 40) and without (n = 30) a formal diagnosis of ADHD. A categorical analysis comparing subjects with and without a clinical diagnosis of ADHD showed no differences in MSSD between groups. A dimensional analysis revealed a positive relationship between MSSD and overall ADHD symptom severity and inattention across children with and without an ADHD diagnosis. Specifically, this positive relationship was found in medial prefrontal areas comprising the default mode network. These results demonstrate a link between intrinsic brain signal variability and ADHD symptom severity that cuts across diagnostic categories, and point to a locus of dysfunction consistent with previous neuroimaging literature.
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spelling pubmed-58575842018-03-28 Resting-State Brain Signal Variability in Prefrontal Cortex Is Associated With ADHD Symptom Severity in Children Nomi, Jason S. Schettini, Elana Voorhies, Willa Bolt, Taylor S. Heller, Aaron S. Uddin, Lucina Q. Front Hum Neurosci Neuroscience Atypical brain function in attention-deficit/hyperactivity disorder (ADHD) has been identified using both task-activation and functional connectivity fMRI approaches. Recent work highlights the potential for another measure derived from functional neuroimaging data, brain signal variability, to reveal insights into clinical conditions. Higher brain signal variability has previously been linked with optimal behavioral performance. At present, little is known regarding the relationship between resting-state brain signal variability and ADHD symptom severity. The current study examined the relationship between a measure of moment-to-moment brain signal variability called mean-square successive difference (MSSD) and ADHD symptomatology in a group of children (7–12 years old) with (n = 40) and without (n = 30) a formal diagnosis of ADHD. A categorical analysis comparing subjects with and without a clinical diagnosis of ADHD showed no differences in MSSD between groups. A dimensional analysis revealed a positive relationship between MSSD and overall ADHD symptom severity and inattention across children with and without an ADHD diagnosis. Specifically, this positive relationship was found in medial prefrontal areas comprising the default mode network. These results demonstrate a link between intrinsic brain signal variability and ADHD symptom severity that cuts across diagnostic categories, and point to a locus of dysfunction consistent with previous neuroimaging literature. Frontiers Media S.A. 2018-03-12 /pmc/articles/PMC5857584/ /pubmed/29593515 http://dx.doi.org/10.3389/fnhum.2018.00090 Text en Copyright © 2018 Nomi, Schettini, Voorhies, Bolt, Heller and Uddin. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Nomi, Jason S.
Schettini, Elana
Voorhies, Willa
Bolt, Taylor S.
Heller, Aaron S.
Uddin, Lucina Q.
Resting-State Brain Signal Variability in Prefrontal Cortex Is Associated With ADHD Symptom Severity in Children
title Resting-State Brain Signal Variability in Prefrontal Cortex Is Associated With ADHD Symptom Severity in Children
title_full Resting-State Brain Signal Variability in Prefrontal Cortex Is Associated With ADHD Symptom Severity in Children
title_fullStr Resting-State Brain Signal Variability in Prefrontal Cortex Is Associated With ADHD Symptom Severity in Children
title_full_unstemmed Resting-State Brain Signal Variability in Prefrontal Cortex Is Associated With ADHD Symptom Severity in Children
title_short Resting-State Brain Signal Variability in Prefrontal Cortex Is Associated With ADHD Symptom Severity in Children
title_sort resting-state brain signal variability in prefrontal cortex is associated with adhd symptom severity in children
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5857584/
https://www.ncbi.nlm.nih.gov/pubmed/29593515
http://dx.doi.org/10.3389/fnhum.2018.00090
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