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@article{1495078,
author = {Bartoň, Marek and Mareček, Radek and Krajčovičová, Lenka and Slavíček, Tomáš and Kašpárek, Tomáš and Holštajn Zemánková, Petra and Říha, Pavel and Mikl, Michal},
article_number = {4},
doi = {http://dx.doi.org/10.1002/hbm.24433},
keywords = {cerebrospinal fluid; filtering; fMRI; functional connectivity; nuisance regression; principal component analysis; psychophysiological interactions; RETROICOR; white matter},
language = {eng},
issn = {1065-9471},
journal = {Human Brain Mapping},
title = {Evaluation of different cerebrospinal fluid and white matter fMRI filtering strategies—Quantifying noise removal and neural signal preservation},
url = {https://onlinelibrary.wiley.com/doi/full/10.1002/hbm.24433},
volume = {40},
year = {2019}
}
TY - JOUR
ID - 1495078
AU - Bartoň, Marek - Mareček, Radek - Krajčovičová, Lenka - Slavíček, Tomáš - Kašpárek, Tomáš - Holštajn Zemánková, Petra - Říha, Pavel - Mikl, Michal
PY - 2019
TI - Evaluation of different cerebrospinal fluid and white matter fMRI filtering strategies—Quantifying noise removal and neural signal preservation
JF - Human Brain Mapping
VL - 40
IS - 4
SP - 1114-1138
EP - 1114-1138
PB - Wiley-Liss
SN - 10659471
KW - cerebrospinal fluid
KW - filtering
KW - fMRI
KW - functional connectivity
KW - nuisance regression
KW - principal component analysis
KW - psychophysiological interactions
KW - RETROICOR
KW - white matter
UR - https://onlinelibrary.wiley.com/doi/full/10.1002/hbm.24433
L2 - https://onlinelibrary.wiley.com/doi/full/10.1002/hbm.24433
N2 - This study examines the impact of using different cerebrospinal fluid (CSF) and white matter (WM) nuisance signals for data-driven filtering of functional magnetic resonance imaging (fMRI) data as a cleanup method before analyzing intrinsic brain fluctuations. The routinely used temporal signal-to-noise ratio metric is inappropriate for assessing fMRI filtering suitability, as it evaluates only the reduction of data variability and does not assess the preservation of signals of interest. We defined a new metric that evaluates the preservation of selected neural signal correlates, and we compared its performance with a recently published signal-noise separation metric. These two methods provided converging evidence of the unfavorable impact of commonly used filtering approaches that exploit higher numbers of principal components from CSF and WM compartments (typically 5 + 5 for CSF and WM, respectively). When using only the principal components as nuisance signals, using a lower number of signals results in a better performance (i.e., 1 + 1 performed best). However, there was evidence that this routinely used approach consisting of 1 + 1 principal components may not be optimal for filtering resting-state (RS) fMRI data, especially when RETROICOR filtering is applied during the data preprocessing. The evaluation of task data indicated the appropriateness of 1 + 1 principal components, but when RETROICOR was applied, there was a change in the optimal filtering strategy. The suggested change for extracting WM (and also CSF in RETROICOR-corrected RS data) is using local signals instead of extracting signals from a large mask using principal component analysis.
ER -
BARTOŇ, Marek, Radek MAREČEK, Lenka KRAJČOVIČOVÁ, Tomáš SLAVÍČEK, Tomáš KAŠPÁREK, Petra HOLŠTAJN ZEMÁNKOVÁ, Pavel ŘÍHA and Michal MIKL. Evaluation of different cerebrospinal fluid and white matter fMRI filtering strategies—Quantifying noise removal and neural signal preservation. \textit{Human Brain Mapping}. Wiley-Liss, 2019, vol.~40, No~4, p.~1114-1138. ISSN~1065-9471. Available from: https://dx.doi.org/10.1002/hbm.24433.
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