Abstract
Previous resting-state functional magnetic resonance imaging (rs-fMRI) studies frequently applied the spatial normalization on fMRI time series before the calculation of temporal features (here referred to as “Prenorm”). We hypothesized that calculating the rs-fMRI features, for example, functional connectivity (FC), regional homogeneity (ReHo), or amplitude of low-frequency fluctuation (ALFF) in individual space, before the spatial normalization (referred to as “Postnorm”) can be an improvement to avoid artifacts and increase the results’ reliability. We utilized two datasets: (1) simulated images where temporal signal-to-noise ratio (tSNR) is kept a constant and (2) an empirical fMRI dataset with 50 healthy young subjects. For simulated images, the tSNR is constant as generated in individual space but increased after Prenorm and intersubject variability of tSNR was induced. In contrast, tSNR was kept constant after Postnorm. Consistently, for empirical images, higher tSNR, ReHo, and FC (default mode network, seed in precuneus) and lower ALFF were found after Prenorm compared to those of Postnorm. Coefficient of variability of tSNR and ALFF was higher after Prenorm compared to those of Postnorm. Moreover, the significant correlation was found between simulated tSNR after Prenorm and empirical tSNR, ALFF, and ReHo after Prenorm, indicating algorithmic variation in empirical rs-fMRI features. Furthermore, comparing to Prenorm, ALFF and ReHo showed higher intraclass correlation coefficients between two serial scans after Postnorm. Our results indicated that Prenorm may induce algorithmic intersubject variability on tSNR and reduce its reliability, which also significantly affected ALFF and ReHo. We suggest using Postnorm instead of Prenorm for future rs-fMRI studies using ALFF/ReHo.
Highlights
MATERIALS AND METHODSResting-state functional magnetic resonance imaging, which uses blood oxygenation level-dependent (BOLD) signal to measure spontaneous brain activity, has been developed and widely applied in neuroscience and clinical research studies (Raichle, 2010; Zhang and Raichle, 2010; Haak et al, 2018)
It is still unclear if this effect is an algorithmic bias and if and how it may affect the reliability of resting-state functional magnetic resonance imaging (rs-fMRI) features
For functional connectivity (FC), Prenorm have higher FC value in most of default mode network (DMN) regions and lower FC value in the regions of task-positive networks compared to Postnorm
Summary
MATERIALS AND METHODSResting-state functional magnetic resonance imaging (rs-fMRI), which uses blood oxygenation level-dependent (BOLD) signal to measure spontaneous brain activity, has been developed and widely applied in neuroscience and clinical research studies (Raichle, 2010; Zhang and Raichle, 2010; Haak et al, 2018). Calculate the certain temporal feature of the time series, for example, functional connectivity (FC) (Biswal et al, 1995; Fox et al, 2005; Raichle, 2015), regional homogeneity (ReHo) (Zang et al, 2004; Jiang and Zuo, 2016), or amplitude of lowfrequency fluctuation (ALFF) (Zang et al, 2007; Zuo et al, 2013) This Prenorm strategy has been widely used in large portion of fMRI studies from a decade ago until recently (Fox et al, 2005; Cooper et al, 2017; Archer et al, 2018) and was the default option in several popular pipeline tools like DPABI and GRENTA (Yan and Zang, 2010; Wang et al, 2015; Yan et al, 2016). It is still unclear if this effect is an algorithmic bias and if and how it may affect the reliability of rs-fMRI features
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
