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Functional neural circuits that underlie developmental stuttering

The aim of this study was to identify differences in functional and effective brain connectivity between persons who stutter (PWS) and typically developing (TD) fluent speakers, and to assess whether those differences can serve as biomarkers to distinguish PWS from TD controls. We acquired resting-s...

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Autores principales: Qiao, Jianping, Wang, Zhishun, Zhao, Guihu, Huo, Yuankai, Herder, Carl L., Sikora, Chamonix O., Peterson, Bradley S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5536300/
https://www.ncbi.nlm.nih.gov/pubmed/28759567
http://dx.doi.org/10.1371/journal.pone.0179255
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author Qiao, Jianping
Wang, Zhishun
Zhao, Guihu
Huo, Yuankai
Herder, Carl L.
Sikora, Chamonix O.
Peterson, Bradley S.
author_facet Qiao, Jianping
Wang, Zhishun
Zhao, Guihu
Huo, Yuankai
Herder, Carl L.
Sikora, Chamonix O.
Peterson, Bradley S.
author_sort Qiao, Jianping
collection PubMed
description The aim of this study was to identify differences in functional and effective brain connectivity between persons who stutter (PWS) and typically developing (TD) fluent speakers, and to assess whether those differences can serve as biomarkers to distinguish PWS from TD controls. We acquired resting-state functional magnetic resonance imaging data in 44 PWS and 50 TD controls. We then used Independent Component Analysis (ICA) together with Hierarchical Partner Matching (HPM) to identify networks of robust, functionally connected brain regions that were highly reproducible across participants, and we assessed whether connectivity differed significantly across diagnostic groups. We then used Granger Causality (GC) to study the causal interactions (effective connectivity) between the regions that ICA and HPM identified. Finally, we used a kernel support vector machine to assess how well these measures of functional connectivity and granger causality discriminate PWS from TD controls. Functional connectivity was stronger in PWS compared with TD controls in the supplementary motor area (SMA) and primary motor cortices, but weaker in inferior frontal cortex (IFG, Broca’s area), caudate, putamen, and thalamus. Additionally, causal influences were significantly weaker in PWS from the IFG to SMA, and from the basal ganglia to IFG through the thalamus, compared to TD controls. ICA and GC indices together yielded an accuracy of 92.7% in classifying PWS from TD controls. Our findings suggest the presence of dysfunctional circuits that support speech planning and timing cues for the initiation and execution of motor sequences in PWS. Our high accuracy of classification further suggests that these aberrant brain features may serve as robust biomarkers for PWS.
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spelling pubmed-55363002017-08-07 Functional neural circuits that underlie developmental stuttering Qiao, Jianping Wang, Zhishun Zhao, Guihu Huo, Yuankai Herder, Carl L. Sikora, Chamonix O. Peterson, Bradley S. PLoS One Research Article The aim of this study was to identify differences in functional and effective brain connectivity between persons who stutter (PWS) and typically developing (TD) fluent speakers, and to assess whether those differences can serve as biomarkers to distinguish PWS from TD controls. We acquired resting-state functional magnetic resonance imaging data in 44 PWS and 50 TD controls. We then used Independent Component Analysis (ICA) together with Hierarchical Partner Matching (HPM) to identify networks of robust, functionally connected brain regions that were highly reproducible across participants, and we assessed whether connectivity differed significantly across diagnostic groups. We then used Granger Causality (GC) to study the causal interactions (effective connectivity) between the regions that ICA and HPM identified. Finally, we used a kernel support vector machine to assess how well these measures of functional connectivity and granger causality discriminate PWS from TD controls. Functional connectivity was stronger in PWS compared with TD controls in the supplementary motor area (SMA) and primary motor cortices, but weaker in inferior frontal cortex (IFG, Broca’s area), caudate, putamen, and thalamus. Additionally, causal influences were significantly weaker in PWS from the IFG to SMA, and from the basal ganglia to IFG through the thalamus, compared to TD controls. ICA and GC indices together yielded an accuracy of 92.7% in classifying PWS from TD controls. Our findings suggest the presence of dysfunctional circuits that support speech planning and timing cues for the initiation and execution of motor sequences in PWS. Our high accuracy of classification further suggests that these aberrant brain features may serve as robust biomarkers for PWS. Public Library of Science 2017-07-31 /pmc/articles/PMC5536300/ /pubmed/28759567 http://dx.doi.org/10.1371/journal.pone.0179255 Text en © 2017 Qiao et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Qiao, Jianping
Wang, Zhishun
Zhao, Guihu
Huo, Yuankai
Herder, Carl L.
Sikora, Chamonix O.
Peterson, Bradley S.
Functional neural circuits that underlie developmental stuttering
title Functional neural circuits that underlie developmental stuttering
title_full Functional neural circuits that underlie developmental stuttering
title_fullStr Functional neural circuits that underlie developmental stuttering
title_full_unstemmed Functional neural circuits that underlie developmental stuttering
title_short Functional neural circuits that underlie developmental stuttering
title_sort functional neural circuits that underlie developmental stuttering
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5536300/
https://www.ncbi.nlm.nih.gov/pubmed/28759567
http://dx.doi.org/10.1371/journal.pone.0179255
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