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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...

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Autores principales: Ramkiran, Shukti, Veselinović, Tanja, Dammers, Jürgen, Gaebler, Arnim Johannes, Rajkumar, Ravichandran, Shah, N. Jon, Neuner, Irene
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2023
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.
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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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