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@inproceedings{1392141,
author = {Výtvarová, Eva and Fousek, Jan and Bartoň, Marek and Mareček, Radek and Gajdoš, Martin and Lamoš, Martin and Nováková, Marie and Slavíček, Tomáš and Peterlík, Igor and Mikl, Michal},
address = {Kos, Greece},
booktitle = {25th European Signal Processing Conference (EUSIPCO), Kos, Greece.},
doi = {http://dx.doi.org/10.23919/EUSIPCO.2017.8081690},
keywords = {functional magnetic resonance imaging; network analysis; preprocessing},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Kos, Greece},
isbn = {978-0-9928626-7-1},
pages = {2644-2648},
publisher = {IEEE},
title = {The Impact of Diverse Preprocessing Pipelines on Brain Functional Connectivity},
url = {http://ieeexplore.ieee.org/abstract/document/8081690/},
year = {2017}
}
TY - JOUR
ID - 1392141
AU - Výtvarová, Eva - Fousek, Jan - Bartoň, Marek - Mareček, Radek - Gajdoš, Martin - Lamoš, Martin - Nováková, Marie - Slavíček, Tomáš - Peterlík, Igor - Mikl, Michal
PY - 2017
TI - The Impact of Diverse Preprocessing Pipelines on Brain Functional Connectivity
PB - IEEE
CY - Kos, Greece
SN - 9780992862671
KW - functional magnetic resonance imaging
KW - network analysis
KW - preprocessing
UR - http://ieeexplore.ieee.org/abstract/document/8081690/
N2 - Brain functional connectivity measured by functional magnetic resonance imaging was shown to be influenced by preprocessing procedures. We aim to describe this influence separately for different preprocessing factors and in 20 different most used preprocessing pipelines. We evaluate the effects of slice-timing correction and physiological noise filtering by RETROICOR, diverse levels of motion correction, and white matter, cerebrospinal fluid, and global signal filtering. With usage of three datasets, we show the impact on global metrics of restingstate functional brain networks and their reliability. We show negative effect of RETROICOR on reliability of metrics and disrupting effect of global signal regression on network topology. We do not support the use of slice-timing correction because it does not significantly influence any of the measured features. We also show that the selected types of preprocessing may affect averaged node strength, normalized clustering coefficient, normalized characteristic path length and modularity.
ER -
VÝTVAROVÁ, Eva, Jan FOUSEK, Marek BARTOŇ, Radek MAREČEK, Martin GAJDOŠ, Martin LAMOŠ, Marie NOVÁKOVÁ, Tomáš SLAVÍČEK, Igor PETERLÍK a Michal MIKL. The Impact of Diverse Preprocessing Pipelines on Brain Functional Connectivity. Online. In \textit{25th European Signal Processing Conference (EUSIPCO), Kos, Greece.}. Kos, Greece: IEEE, 2017, s.~2644-2648. ISBN~978-0-9928626-7-1. Dostupné z: https://dx.doi.org/10.23919/EUSIPCO.2017.8081690.
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