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Comment
. 2019 Sep 24;116(39):19243-19244.
doi: 10.1073/pnas.1909852116. Epub 2019 Aug 27.

Reply to Spreng et al.: Multiecho fMRI denoising does not remove global motion-associated respiratory signals

Jonathan D Power  1 , Charles J Lynch  2 , Adrian W Gilmore  3 , Stephen J Gotts  3 , Alex Martin  3
Affiliations
Comment

Reply to Spreng et al.: Multiecho fMRI denoising does not remove global motion-associated respiratory signals

Jonathan D Power et al. Proc Natl Acad Sci U S A. .
No abstract available

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Deep breath global signals, and relationships of global signal variance to respiratory variance and head motion in 3 datasets. (A) In the first column, for 4 well-isolated, spontaneous deep breaths in the NA dataset, global fMRI signals before and after multiecho ICA are shown, illustrating that the global signal is largely unchanged and therefore that the time-locked signals are largely T2* signals. In the second column, global fMRI signals of 20 widely spaced instructed deep breaths in a single subject are shown before and after multiecho ICA denoising, again showing little alteration by multiecho ICA denoising. Comparison of the spontaneous and instructed breath waveforms yields evident similarities. Both conditions include comparable respiratory phenomena, but endogenous “neural” signals that might prompt deep breaths ought to be minimized when an instructed paradigm is used. Data from ref. . (B) Cross-subject correlations between global signal variance and respiratory variability, and between respiratory variability and mean head motion, are shown separately for both runs of the multiecho ICA denoised NA data, for a separate single-echo dataset previously published [Modified from ref. 6. Copyright (2017), with permission from Elsevier. Data from ref. .], and for 56 AG subjects scanned with multiecho sequences [data partially published in Gilmore et al. (7)].
See this image and copyright information in PMC

Comment on

References

    1. Power J. D., et al. , Ridding fMRI data of motion-related influences: Removal of signals with distinct spatial and physical bases in multiecho data. Proc. Natl. Acad. Sci. U.S.A. 115, E2105–E2114 (2018). - PMC - PubMed
    1. Power J. D., A simple but useful way to assess fMRI scan qualities. Neuroimage 154, 150–158 (2017). - PMC - PubMed
    1. Spreng R. N., Fernández-Cabello S., Turner G. R., Stevens W. D., Take a deep breath: Multiecho fMRI denoising effectively removes head motion artifacts, obviating the need for global signal regression. Proc. Natl. Acad. Sci. U.S.A. 116, 19241–19242 (2019). - PMC - PubMed
    1. Kundu P., et al. , Integrated strategy for improving functional connectivity mapping using multiecho fMRI. Proc. Natl. Acad. Sci. U.S.A. 110, 16187–16192 (2013). - PMC - PubMed
    1. Power J. D., Temporal ICA has not properly separated global fMRI signals: A comment on Glasser et al. (2018). Neuroimage 197, 650–651 (2019). - PubMed

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