How brain networks tic: Predicting tic severity through rs-fMRI dynamics in Tourette syndrome.
dynamic functional connectivity
dynamic network topology
resting state fMRI
static network topology
tic pathophysiology
visual social-processing network
Journal
Human brain mapping
ISSN: 1097-0193
Titre abrégé: Hum Brain Mapp
Pays: United States
ID NLM: 9419065
Informations de publication
Date de publication:
01 08 2023
01 08 2023
Historique:
revised:
28
04
2023
received:
18
07
2022
accepted:
02
05
2023
medline:
5
7
2023
pubmed:
26
5
2023
entrez:
26
5
2023
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 37232486
doi: 10.1002/hbm.26341
pmc: PMC10318206
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
4225-4238Informations de copyright
© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.
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