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How brain networks tic: Predicting tic severity through rs‐fMRI dynamics in Tourette syndrome
Tourette syndrome (TS) is a neuropsychiatric disorder characterized by motor and phonic tics, which several different theories, such as basal ganglia‐thalamo‐cortical loop dysfunction and amygdala hypersensitivity, have sought to explain. Previous research has shown dynamic changes in the brain prio...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10318206/ https://www.ncbi.nlm.nih.gov/pubmed/37232486 http://dx.doi.org/10.1002/hbm.26341 |
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author | Ramkiran, Shukti Veselinović, Tanja Dammers, Jürgen Gaebler, Arnim Johannes Rajkumar, Ravichandran Shah, N. Jon Neuner, Irene |
author_facet | Ramkiran, Shukti Veselinović, Tanja Dammers, Jürgen Gaebler, Arnim Johannes Rajkumar, Ravichandran Shah, N. Jon Neuner, Irene |
author_sort | Ramkiran, Shukti |
collection | PubMed |
description | Tourette syndrome (TS) is a neuropsychiatric disorder characterized by motor and phonic tics, which several different theories, such as basal ganglia‐thalamo‐cortical loop dysfunction and amygdala hypersensitivity, have sought to explain. Previous research has shown dynamic changes in the brain prior to tic onset leading to tics, and this study aims to investigate the contribution of network dynamics to them. For this, we have employed three methods of functional connectivity to resting‐state fMRI data – namely the static, the sliding window dynamic and the ICA based estimated dynamic; followed by an examination of the static and dynamic network topological properties. A leave‐one‐out (LOO‐) validated regression model with LASSO regularization was used to identify the key predictors. The relevant predictors pointed to dysfunction of the primary motor cortex, the prefrontal‐basal ganglia loop and amygdala‐mediated visual social processing network. This is in line with a recently proposed social decision‐making dysfunction hypothesis, opening new horizons in understanding tic pathophysiology. |
format | Online Article Text |
id | pubmed-10318206 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-103182062023-07-05 How brain networks tic: Predicting tic severity through rs‐fMRI dynamics in Tourette syndrome Ramkiran, Shukti Veselinović, Tanja Dammers, Jürgen Gaebler, Arnim Johannes Rajkumar, Ravichandran Shah, N. Jon Neuner, Irene Hum Brain Mapp Research Articles Tourette syndrome (TS) is a neuropsychiatric disorder characterized by motor and phonic tics, which several different theories, such as basal ganglia‐thalamo‐cortical loop dysfunction and amygdala hypersensitivity, have sought to explain. Previous research has shown dynamic changes in the brain prior to tic onset leading to tics, and this study aims to investigate the contribution of network dynamics to them. For this, we have employed three methods of functional connectivity to resting‐state fMRI data – namely the static, the sliding window dynamic and the ICA based estimated dynamic; followed by an examination of the static and dynamic network topological properties. A leave‐one‐out (LOO‐) validated regression model with LASSO regularization was used to identify the key predictors. The relevant predictors pointed to dysfunction of the primary motor cortex, the prefrontal‐basal ganglia loop and amygdala‐mediated visual social processing network. This is in line with a recently proposed social decision‐making dysfunction hypothesis, opening new horizons in understanding tic pathophysiology. John Wiley & Sons, Inc. 2023-05-26 /pmc/articles/PMC10318206/ /pubmed/37232486 http://dx.doi.org/10.1002/hbm.26341 Text en © 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Research Articles Ramkiran, Shukti Veselinović, Tanja Dammers, Jürgen Gaebler, Arnim Johannes Rajkumar, Ravichandran Shah, N. Jon Neuner, Irene How brain networks tic: Predicting tic severity through rs‐fMRI dynamics in Tourette syndrome |
title | How brain networks tic: Predicting tic severity through rs‐fMRI dynamics in Tourette syndrome |
title_full | How brain networks tic: Predicting tic severity through rs‐fMRI dynamics in Tourette syndrome |
title_fullStr | How brain networks tic: Predicting tic severity through rs‐fMRI dynamics in Tourette syndrome |
title_full_unstemmed | How brain networks tic: Predicting tic severity through rs‐fMRI dynamics in Tourette syndrome |
title_short | How brain networks tic: Predicting tic severity through rs‐fMRI dynamics in Tourette syndrome |
title_sort | how brain networks tic: predicting tic severity through rs‐fmri dynamics in tourette syndrome |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10318206/ https://www.ncbi.nlm.nih.gov/pubmed/37232486 http://dx.doi.org/10.1002/hbm.26341 |
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