The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Relationship between respiration, end-tidal CO2, and BOLD signals in resting-state fMRI
Open accessAbstract
A significant component of BOLD fMRI physiological noise is caused by variations in the depth and rate of respiration. It has previously been demonstrated that a breath-to-breath metric of respiratory variation (respiratory volume per time; RVT), computed from pneumatic belt measurements of chest expansion, has a strong linear relationship with resting-state BOLD signals across the brain. RVT is believed to capture breathing-induced changes in arterial CO2, which is a cerebral vasodilator; indeed, separate studies have found that spontaneous fluctuations in end-tidal CO2 (PETCO2) are correlated with BOLD signal time series. The present study quantifies the degree to which RVT and PETCO2 measurements relate to one another and explain common aspects of the resting-state BOLD signal. It is found that RVT (particularly when convolved with a particular impulse response, the “respiration response function”) is highly correlated with PETCO2, and that both explain remarkably similar spatial and temporal BOLD signal variance across the brain. In addition, end-tidal O2 is shown to be largely redundant with PETCO2. Finally, the latency at which PETCO2 and respiration belt measures are correlated with the time series of individual voxels is found to vary across the brain and may reveal properties of intrinsic vascular response delays.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation.
Kwong, K. K., Belliveau, J. W., Chesler, D. A., Goldberg, I. E., Weisskoff, R. M., Poncelet, B. P., Kennedy, D. N., Hoppel, B. E., Cohen, M. S., & Turner, R. (1992) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.89.12.5675 · Cited by 4,212
Time course EPI of human brain function during task activation
Bandettini, P. A., Wong, E. C., Hinks, R. S., Tikofsky, R. S., & Hyde, J. S. (1992) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910250220 · Cited by 1,935
Wise, R. G., Ide, K., Poulin, M. J., & Tracey, I. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2003.11.025 · Cited by 664
Regional Differences in the CBF and BOLD Responses to Hypercapnia: A Combined PET and fMRI Study
Rostrup, E., Law, I., Blinkenberg, M., Larsson, H. B. W., Born, A. P., Holm, S., & Paulson, O. B. (2000) · NeuroImage · doi:10.1006/nimg.1999.0526 · Cited by 216 · cited 2×
“This assumption is supported on several grounds: (1) the partial pressure of arterial CO2 (PaCO2) is a function of ventilation, which is defined as the product of the depth and rate of respiration (Berne and Levy, 1993); (2) inhaling elevated concentrations of CO2, as well as holding one's breath, initiates cerebral v…”
Background
Cited by
Dynamic functional connectivity: Promise, issues, and interpretations
Hutchison, R. M., Womelsdorf, T., Allen, E. A., Bandettini, P. A., Calhoun, V. D., Corbetta, M., Della Penna, S., Duyn, J. H., Glover, G. H., Gonzalez-Castillo, J., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.079 · Cited by 2,962
Self-citationVan Dijk, K. R. A., Hedden, T., Venkataraman, A., Evans, K. C., Lazar, S. W., & Buckner, R. L. (2010) · Journal of Neurophysiology · doi:10.1152/jn.00783.2009 · Cited by 1,844
Dynamic models of large-scale brain activity
Breakspear, M. (2017) · Nature Neuroscience · doi:10.1038/nn.4497 · Cited by 1,239
The Human Connectome Project's neuroimaging approach
Glasser, M. F., Smith, S. M., Marcus, D. S., Andersson, J. L. R., Auerbach, E. J., Behrens, T. E. J., Coalson, T. S., Harms, M. P., Jenkinson, M., Moeller, S., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4361 · Cited by 1,090
Overview of Functional Magnetic Resonance Imaging
Glover, G. H. (2011) · Neurosurgery Clinics of North America · doi:10.1016/j.nec.2010.11.001 · Cited by 1,024
Self-citation
Metadata
- Authors
- Chang, C., & Glover, G. H.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2009-10
- Volume
- 47
- Issue
- 4
- Pages
- 1381-1393
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2048034803
- Cited by
- 292
- References
- 4
- FWCI
- 8.93
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Relationship between respiration, end-tidal CO2, and BOLD signals in resting-state fMRI. https://app.cochat.ai/papers/10.1016/j.neuroimage.2009.04.048
- The paper
- Chang, C., & Glover, G. H. (2009). Relationship between respiration, end-tidal CO2, and BOLD signals in resting-state fMRI. NeuroImage. https://doi.org/10.1016/j.neuroimage.2009.04.048
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.