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@ARTICLE{Ramkiran:1007800,
author = {Ramkiran, Shukti and Veselinović, Tanja and Dammers,
Jürgen and Gaebler, Arnim Johannes and Rajkumar,
Ravichandran and Shah, N. Jon and Neuner, Irene},
title = {{H}ow brain networks tic: {P}redicting tic severity through
rs‐f{MRI} dynamics in {T}ourette syndrome},
journal = {Human brain mapping},
volume = {44},
number = {11},
issn = {1065-9471},
address = {New York, NY},
publisher = {Wiley-Liss},
reportid = {FZJ-2023-02195},
pages = {4225-4238},
year = {2023},
abstract = {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.},
cin = {INM-4 / INM-11 / JARA-BRAIN},
ddc = {610},
cid = {I:(DE-Juel1)INM-4-20090406 / I:(DE-Juel1)INM-11-20170113 /
I:(DE-Juel1)VDB1046},
pnm = {5253 - Neuroimaging (POF4-525)},
pid = {G:(DE-HGF)POF4-5253},
typ = {PUB:(DE-HGF)16},
pubmed = {37232486},
UT = {WOS:000994935800001},
doi = {10.1002/hbm.26341},
url = {https://juser.fz-juelich.de/record/1007800},
}