Evaluation of different cerebrospinal fluid and white matter fMRI filtering strategies-Quantifying noise removal and neural signal preservation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00159816%3A_____%2F19%3A00070691" target="_blank" >RIV/00159816:_____/19:00070691 - isvavai.cz</a>

Alternative codes found

RIV/00216224:14740/19:00107257 RIV/65269705:_____/19:00070691

Result on the web

<a href="https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/hbm.24433" target="_blank" >https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/hbm.24433</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/hbm.24433" target="_blank" >10.1002/hbm.24433</a>

Result language

angličtina

Original language name

Evaluation of different cerebrospinal fluid and white matter fMRI filtering strategies-Quantifying noise removal and neural signal preservation

Original language description

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.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

30103 - Neurosciences (including psychophysiology)

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2019

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Human Brain Mapping

ISSN

1065-9471

e-ISSN

—

Volume of the periodical

40

Issue of the periodical within the volume

4

Country of publishing house

US - UNITED STATES

Number of pages

25

Pages from-to

1114-1138

UT code for WoS article

000459470400006

EID of the result in the Scopus database

2-s2.0-85056167637