4.7 Article

Vascular origins of low-frequency oscillations in the cerebrospinal fluid signal in resting-state fMRI: Interpretation using photoplethysmography

期刊

HUMAN BRAIN MAPPING
卷 42, 期 8, 页码 2606-2622

出版社

WILEY
DOI: 10.1002/hbm.25392

关键词

arterial BOLD; cerebrospinal fluid; functional connectivity; heart-rate variability; Mayer wave; photoplethysmograph; pulse-intensity ratio; resting-state fMRI; second derivative of PPG; vasomotion; venous BOLD

资金

  1. Canadian Institutes of Health Research [148398]

向作者/读者索取更多资源

This study found that signals in different CSF regions are not equally associated with vascular and tissue rs-fMRI signals; the PPG signal is most coherent with the arterial and CSF signals at the cardiac frequency, but coherent with brain tissue at around 0.2 Hz; PIR is most coherent with the CSF signal near 0.03 Hz; and PPG-related vascular oscillations contribute only about 15% to the CSF (and arterial) signal in rs-fMRI.
In vivo mapping of cerebrovascular oscillations in the 0.05-0.15 Hz remains difficult. Oscillations in the cerebrospinal fluid (CSF) represent a possible avenue for noninvasively tracking these oscillations using resting-state functional MRI (rs-fMRI), and have been used to correct for vascular oscillations in rs-fMRI functional connectivity. However, the relationship between low-frequency CSF and vascular oscillations remains unclear. In this study, we investigate this relationship using fast simultaneous rs-fMRI and photoplethysmogram (PPG), examining the 0.1 Hz PPG signal, heart-rate variability (HRV), pulse-intensity ratio (PIR), and the second derivative of the PPG (SDPPG). The main findings of this study are: (a) signals in different CSF regions are not equivalent in their associations with vascular and tissue rs-fMRI signals; (b) the PPG signal is maximally coherent with the arterial and CSF signals at the cardiac frequency, but coherent with brain tissue at similar to 0.2 Hz; (c) PIR is maximally coherent with the CSF signal near 0.03 Hz; and (d) PPG-related vascular oscillations only contribute to es similar to 15% of the CSF (and arterial) signal in rs-fMRI. These findings caution against averaging all CSF regions when extracting physiological nuisance regressors in rs-fMRI applications, and indicate the drivers of the CSF signal are more than simply cardiac. Our study is an initial attempt at the refinement and standardization of how the CSF signal in rs-fMRI can be used and interpreted. It also paves the way for using rs-fMRI in the CSF as a potential tool for tracking cerebrovascular health through, for instance, the potential relationship between PIR and the CSF signal.

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