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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 a 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, roč.~40, č.~4, s.~1114-1138. ISSN~1065-9471. Dostupné z: https://dx.doi.org/10.1002/hbm.24433.
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