The Impact of Diverse Preprocessing Pipelines on Brain Functional Connectivity

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Publikace nespadá pod Ekonomicko-správní fakultu, ale pod Fakultu informatiky. Oficiální stránka publikace je na webu muni.cz.
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VÝTVAROVÁ Eva FOUSEK Jan BARTOŇ Marek MAREČEK Radek GAJDOŠ Martin LAMOŠ Martin NOVÁKOVÁ Marie SLAVÍČEK Tomáš PETERLÍK Igor MIKL Michal

Rok publikování 2017
Druh Článek ve sborníku
Konference 25th European Signal Processing Conference (EUSIPCO), Kos, Greece.
Fakulta / Pracoviště MU

Fakulta informatiky

Citace
www http://ieeexplore.ieee.org/abstract/document/8081690/
Doi http://dx.doi.org/10.23919/EUSIPCO.2017.8081690
Obor Neurologie, neurochirurgie, neurovědy
Klíčová slova functional magnetic resonance imaging; network analysis; preprocessing
Popis 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.
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