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@INPROCEEDINGS{Jung:905257,
author = {Jung, Kyesam and Eickhoff, Simon and Popovych, Oleksandr},
title = {{T}ractography density affects whole-brain structural
architecture and resting-state dynamical modeling},
reportid = {FZJ-2022-00540},
year = {2021},
abstract = {Dynamical modeling of the resting-state brain dynamics
essentially relies on the empirical neuroimaging data
utilized for the model derivation and validation. There is
however still no standardized data processing for magnetic
resonance imaging pipelines and the structural and
functionalconnectomes involved in the models. In this study,
we thus address how the parameters of diffusion-weighted
data processing for structural connectivity (SC) can
influence the validation results of thewhole-brain
mathematical models informed by SC. For this, we introduce a
set of simulation conditions including the varying number of
total streamlines of the whole-brain tractography (WBT)used
for extraction of SC, cortical parcellations based on
functional and anatomical brain propertiesand distinct model
fitting modalities. The main objective of this study is to
explore how the qualityof the model validation can vary
across the considered simulation conditions. We observed
that thegraph-theoretical network properties of structural
connectome can be affected by varying tractography density
and strongly relate to the model performance. We also found
that the optimal numberof the total streamlines of WBT can
vary for different brain atlases. Consequently, we suggest a
wayhow to improve the model performance based on the network
properties and the optimal parameter configurations from
multiple WBT conditions. Furthermore, the population of
subjects can bestratified into subgroups with divergent
behaviors induced by the varying WBT density such
thatdifferent recommendations can be made with respect to
the data processing for individual subjectsand brain
parcellations. Consequently, we list a few tentative
guidelines to possible evaluation ofpersonalized optimal
number of the WBT streamlines for the whole-brain model of
the resting-statebrain dynamics.},
month = {Oct},
date = {2021-10-05},
organization = {INM $\&$ IBI Retreat 2021,
Forschungszentrum Jülich, Virtual
Conference (Germany), 5 Oct 2021 - 6
Oct 2021},
subtyp = {After Call},
cin = {INM-7},
cid = {I:(DE-Juel1)INM-7-20090406},
pnm = {5232 - Computational Principles (POF4-523) / 5231 -
Neuroscientific Foundations (POF4-523) / 5254 -
Neuroscientific Data Analytics and AI (POF4-525) / HBP SGA2
- Human Brain Project Specific Grant Agreement 2 (785907) /
HBP SGA3 - Human Brain Project Specific Grant Agreement 3
(945539) / VirtualBrainCloud - Personalized Recommendations
for Neurodegenerative Disease (826421)},
pid = {G:(DE-HGF)POF4-5232 / G:(DE-HGF)POF4-5231 /
G:(DE-HGF)POF4-5254 / G:(EU-Grant)785907 /
G:(EU-Grant)945539 / G:(EU-Grant)826421},
typ = {PUB:(DE-HGF)24},
url = {https://juser.fz-juelich.de/record/905257},
}