Cited by 664Advanced MRI Techniques and ApplicationsFunctional Brain Connectivity StudiesOptical Imaging and Spectroscopy Techniques

The DOI matches its Crossref record; 74 of the 75 references it cites were found in a registry or an index.

Resting fluctuations in arterial carbon dioxide induce significant low frequency variations in BOLD signal

Wise, Richard G, Ide, Kojiro, Poulin, Marc J, Tracey, Irene·2004·NeuroImage

DOI 10.1016/j.neuroimage.2003.11.025

Open this paper in CoChat — free account

Abstract

Carbon dioxide is a potent cerebral vasodilator. We have identified a significant source of low-frequency variation in blood oxygen level-dependent (BOLD) magnetic resonance imaging (MRI) signal at 3 T arising from spontaneous fluctuations in arterial carbon dioxide level in volunteers at rest. Fluctuations in the partial pressure of end-tidal carbon dioxide (Pet(CO(2))) of +/-1.1 mm Hg in the frequency range 0-0.05 Hz were observed in a cohort of nine volunteers. Correlating with these fluctuations were significant generalized grey and white matter BOLD signal fluctuations. We observed a mean (+/-standard error) regression coefficient across the group of 0.110 +/- 0.033% BOLD signal change per mm Hg CO(2) for grey matter and 0.049 +/- 0.022% per mm Hg in white matter. Pet(CO(2))-related BOLD signal fluctuations showed regional differences across the grey matter, suggesting variability of the responsiveness to carbon dioxide at rest. Functional magnetic resonance imaging (fMRI) results were corroborated by transcranial Doppler (TCD) ultrasound measurements of the middle cerebral artery (MCA) blood velocity in a cohort of four volunteers. Significant Pet(CO(2))-correlated fluctuations in MCA blood velocity were observed with a lag of 6.3 +/- 1.2 s (mean +/- standard error) with respect to Pet(CO(2)) changes. This haemodynamic lag was adopted in the analysis of the BOLD signal. Doppler ultrasound suggests that a component of low-frequency BOLD signal fluctuations is mediated by CO(2)-induced changes in cerebral blood flow (CBF). These fluctuations are a source of physiological noise and a potentially important confounding factor in fMRI paradigms that modify breathing. However, they can also be used for mapping regional vascular responsiveness to CO(2).

Integrity signals

Registry

Crossref · 10.1016/j.neuroimage.2003.11.025

Cites

74 of 74 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Functional connectivity in the motor cortex of resting human brain using echo‐planar mri
Biswal, B., Zerrin Yetkin, F., Haughton, V. M., & Hyde, J. S. (1995) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910340409 · Cited by 9,812
Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm
Zhang, Y., Brady, M., & Smith, S. M. (2001) · IEEE Transactions on Medical Imaging · doi:10.1109/42.906424 · Cited by 7,628
A global optimisation method for robust affine registration of brain images
Jenkinson, M., & Smith, S. M. (2001) · Medical Image Analysis · doi:10.1016/s1361-8415(01)00036-6 · Cited by 7,018
Improved assessment of significant activation in functional magnetic resonance imaging (fMRI): use of a cluster-size threshold
Forman, S. D., Cohen, J. D., Fitzgerald, M., Eddy, W. F., Mintun, M. A., & Noll, D. C. (1995) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910330508 · Cited by 3,202
Temporal Autocorrelation in Univariate Linear Modeling of FMRI Data
Woolrich, M. W., Ripley, B. D., Brady, M., & Smith, S. M. (2001) · NeuroImage · doi:10.1006/nimg.2001.0931 · Cited by 2,859
A three-dimensional statistical analysis for CBF activation studies in human brain
Worsley, K. J., Evans, A. C., Marrett, S., & Neelin, P. (1992) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.1992.127 · Cited by 2,036
Assessing the significance of focal activations using their spatial extent
Friston, K. J., Worsley, K. J., Frackowiak, R. S. J., Mazziotta, J. C., & Evans, A. C. (1994) · Human Brain Mapping · doi:10.1002/hbm.460010306 · Cited by 1,907
General multilevel linear modeling for group analysis in FMRI
Beckmann, C. F., Jenkinson, M., & Smith, S. M. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00435-x · Cited by 1,464
Functional connectivity in single and multislice echoplanar imaging using resting-state fluctuations
Lowe, M. J., Mock, B. J., & Sorenson, J. A. (1998) · NeuroImage · doi:10.1006/nimg.1997.0315 · Cited by 1,394
Continuous Recording and Control of Ventricular Fluid Pressure in Neurosurgical Practice
Lundberg, N. (1962) · Journal of Neuropathology & Experimental Neurology · doi:10.1097/00005072-196207000-00018 · Cited by 1,093

Flagged first, then by citations

Show all 75 references

1 of the 75 references couldn’t be matched to a known paper.

Research works printed but not linked: 2

Behrens, 2003, Multi-subject null hypothesis testing using a fully Bayesian framework: theory, NeuroImage, 19, S986
Biswal, 1997, Simultaneous assessment of flow BOLD signals in resting-state functional connectivity maps, NMR Biomed., 10, 165, 10.1002/(SICI)1099-1492(199706/08)10:4/5<165::AID-NBM454>3.0.CO;2-7 · DOI

Sorted by citations

The Brain's Default Network: Anatomy, Function, and Relevance to Disease
Buckner, R. L., Andrews‐Hanna, J. R., & Schacter, D. L. (2008) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1440.011 · Cited by 9,761
The organization of the human cerebellum estimated by intrinsic functional connectivity
Buckner, R. L., Krienen, F. M., Castellanos, A., Diaz, J. C., & Yeo, B. T. T. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00339.2011 · Cited by 7,304
Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging
Fox, M. D., & Raichle, M. E. (2007) · Nature Reviews Neuroscience · doi:10.1038/nrn2201 · Cited by 6,700
Consistent resting-state networks across healthy subjects
Damoiseaux, J. S., Rombouts, S. A. R. B., Barkhof, F., Scheltens, P., Stam, C. J., Smith, S. M., & Beckmann, C. F. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601417103 · Cited by 4,326
Investigations into resting-state connectivity using independent component analysis
Beckmann, C. F., DeLuca, M., Devlin, J. T., & Smith, S. M. (2005) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2005.1634 · Cited by 3,398
Exploring the brain network: A review on resting-state fMRI functional connectivity
van den Heuvel, M. P., & Hulshoff Pol, H. E. (2010) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2010.03.008 · Cited by 3,326
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
Cortical Hubs Revealed by Intrinsic Functional Connectivity: Mapping, Assessment of Stability, and Relation to Alzheimer's Disease
Buckner, R. L., Sepulcre, J., Talukdar, T., Krienen, F. M., Liu, H., Hedden, T., Andrews-Hanna, J. R., Sperling, R. A., & Johnson, K. A. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.5062-08.2009 · Cited by 2,862
The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?
Murphy, K., Birn, R. M., Handwerker, D. A., Jones, T. B., & Bandettini, P. A. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.09.036 · Cited by 2,387
An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: Fractional ALFF
Zou, Q., Zhu, C.-Z., Yang, Y., Zuo, X., Long, X., Cao, Q., Wang, Y., & Zang, Y. (2008) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2008.04.012 · Cited by 2,169
The global signal and observed anticorrelated resting state brain networks
Fox, M. D., Zhang, D., Snyder, A. Z., & Raichle, M. E. (2009) · Journal of Neurophysiology · doi:10.1152/jn.90777.2008 · Cited by 1,877
Evidence for a Frontoparietal Control System Revealed by Intrinsic Functional Connectivity
Vincent, J. L., Kahn, I., Snyder, A. Z., Raichle, M. E., & Buckner, R. L. (2008) · Journal of Neurophysiology · doi:10.1152/jn.90355.2008 · Cited by 1,869
Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization
Van 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
Time–frequency dynamics of resting-state brain connectivity measured with fMRI
Chang, C., & Glover, G. H. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.011 · Cited by 1,808
The oscillating brain: Complex and reliable
Zuo, X., Martino, A. D., Kelly, C. A. M., Shehzad, Z. E., Gee, D. G., Klein, D. F., Castellanos, F. X., Biswal, B. B., & Milham, M. P. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.09.037 · Cited by 1,466
Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI
Birn, R. M., Diamond, J. B., Smith, M. A., & Bandettini, P. A. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.02.048 · Cited by 1,381
fMRI resting state networks define distinct modes of long-distance interactions in the human brain
De Luca, M., Beckmann, C. F., De Stefano, N., Matthews, P. M., & Smith, S. M. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2005.08.035 · Cited by 1,241
Visceral influences on brain and behavior
Critchley, H. D., & Harrison, N. A. (2013) · Neuron · doi:10.1016/j.neuron.2013.02.008 · Cited by 1,177
Neural correlates of the psychedelic state as determined by fMRI studies with psilocybin
Carhart-Harris, R. L., Erritzoe, D., Williams, T., Stone, J. M., Reed, L. J., Colasanti, A., Tyacke, R. J., Leech, R., Malizia, A. L., Murphy, K., et al. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1119598109 · Cited by 1,172
Self-citation
Towards a consensus regarding global signal regression for resting state functional connectivity MRI
Murphy, K., & Fox, M. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.11.052 · Cited by 1,044
Functionally linked resting‐state networks reflect the underlying structural connectivity architecture of the human brain
van den Heuvel, M. P., Mandl, R. C. W., Kahn, R. S., & Hulshoff Pol, H. E. (2009) · Human Brain Mapping · doi:10.1002/hbm.20737 · Cited by 987
Neural basis of global resting-state fMRI activity
Schölvinck, M. L., Maier, A., Ye, F. Q., Duyn, J. H., & Leopold, D. A. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0913110107 · Cited by 939
Trouble at rest: how correlation patterns and group differences become distorted after global signal regression
Saad, Z. S., Gotts, S. J., Murphy, K., Chen, G., Jo, H. J., Martin, A., & Cox, R. W. (2012) · Brain Connectivity · doi:10.1089/brain.2012.0080 · Cited by 859
Plasticity of brain networks in a randomized intervention trial of exercise training in older adults
Voss (2010) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2010.00032 · Cited by 841
Segregated fronto-cerebellar circuits revealed by intrinsic functional connectivity
Krienen, F. M., & Buckner, R. L. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhp135 · Cited by 782
Intrinsic Fluctuations within Cortical Systems Account for Intertrial Variability in Human Behavior
Fox, M., Snyder, A. Z., Vincent, J. L., & Raichle, M. E. (2007) · Neuron · doi:10.1016/j.neuron.2007.08.023 · Cited by 773
Small-world and scale-free organization of voxel-based resting-state functional connectivity in the human brain
van den Heuvel, M. P., Stam, C. J., Boersma, M., & Pol, H. E. H. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.08.010 · Cited by 745
The restless brain
Raichle, M. E. (2011) · Brain Connectivity · doi:10.1089/brain.2011.0019 · Cited by 672
Electrophysiological correlates of the brain's intrinsic large-scale functional architecture
He, B. J., Snyder, A. Z., Zempel, J. M., Smyth, M. D., & Raichle, M. E. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0807010105 · Cited by 670
Influence of heart rate on the BOLD signal: The cardiac response function
Chang, C., Cunningham, J. P., & Glover, G. H. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.09.029 · Cited by 682
Resting-state fMRI confounds and cleanup
Murphy, K., Birn, R. M., & Bandettini, P. A. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.001 · Cited by 666
Two systems of resting state connectivity between the insula and cingulate cortex
Taylor, K. S., Seminowicz, D. A., & Davis, K. D. (2009) · Human Brain Mapping · doi:10.1002/hbm.20705 · Cited by 665
Revisiting the neurovascular unit
Schaeffer, S. M., & Iadecola, C. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00904-7 · Cited by 699
The respiration response function: The temporal dynamics of fMRI signal fluctuations related to changes in respiration
Birn, R. M., Smith, M. A., Jones, T. B., & Bandettini, P. A. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2007.11.059 · Cited by 651
Building a Science of Individual Differences from fMRI
Dubois, J., & Adolphs, R. (2016) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2016.03.014 · Cited by 644
Breakdown of within- and between-network resting state functional magnetic resonance imaging connectivity during propofol-induced loss of consciousness
Boveroux, P., Vanhaudenhuyse, A., Bruno, M.-A., Noirhomme, Q., Lauwick, S., Luxen, A., Degueldre, C., Plenevaux, A., Schnakers, C., Phillips, C., et al. (2010) · Anesthesiology · doi:10.1097/aln.0b013e3181f697f5 · Cited by 630
Amplitude of low frequency fluctuation within visual areas revealed by resting-state functional MRI
Yang, H., Long, X., Yang, Y., Yan, H., Zhu, C.-Z., Zhou, X.-P., Zang, Y., & Gong, Q. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.01.054 · Cited by 613
Disruption of Functional Connectivity in Clinically Normal Older Adults Harboring Amyloid Burden
Hedden, T., Van Dijk, K. R. A., Becker, J. A., Mehta, A., Sperling, R. A., Johnson, K. A., & Buckner, R. L. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.3189-09.2009 · Cited by 598
Low frequency BOLD fluctuations during resting wakefulness and light sleep: A simultaneous EEG‐fMRI study
Horovitz, S. G., Fukunaga, M., de Zwart, J. A., van Gelderen, P., Fulton, S. C., Balkin, T. J., & Duyn, J. H. (2008) · Human Brain Mapping · doi:10.1002/hbm.20428 · Cited by 616
Neuronal correlates of spontaneous fluctuations in fMRI signals in monkey visual cortex: Implications for functional connectivity at rest
Shmuel, A., & Leopold, D. A. (2008) · Human Brain Mapping · doi:10.1002/hbm.20580 · Cited by 584
The default-mode, ego-functions and free-energy: a neurobiological account of Freudian ideas
Carhart-Harris, R. L., & Friston, K. J. (2010) · Brain · doi:10.1093/brain/awq010 · Cited by 574
Sources and implications of whole-brain fMRI signals in humans
Power, J. D., Plitt, M. H., Laumann, T. O., & Martin, A. D. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.09.038 · Cited by 534
Methods for cleaning the BOLD fMRI signal
Caballero-Gaudes, C., & Reynolds, R. C. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2016.12.018 · Cited by 542
Low-frequency fluctuations in the cardiac rate as a source of variance in the resting-state fMRI BOLD signal
Shmueli, K., van Gelderen, P., de Zwart, J. A., Horovitz, S. G., Fukunaga, M., Jansma, J. M., & Duyn, J. H. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.07.037 · Cited by 546
Measuring functional connectivity using MEG: methodology and comparison with fcMRI
Brookes, M. J., Hale, J. R., Zumer, J. M., Stevenson, C. M., Francis, S. T., Barnes, G. R., Owen, J. P., Morris, P. G., & Nagarajan, S. S. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.02.054 · Cited by 519
Mapping sources of correlation in resting state FMRI, with artifact detection and removal
Jo, H. J., Saad, Z. S., Simmons, W. K., Milbury, L. A., & Cox, R. W. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.04.246 · Cited by 509
Distinct Cortical Anatomy Linked to Subregions of the Medial Temporal Lobe Revealed by Intrinsic Functional Connectivity
Kahn, I., Andrews‐Hanna, J. R., Vincent, J. L., Snyder, A. Z., & Buckner, R. L. (2008) · Journal of Neurophysiology · doi:10.1152/jn.00077.2008 · Cited by 509
Effects of model-based physiological noise correction on default mode network anti-correlations and correlations
Chang, C., & Glover, G. H. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.05.012 · Cited by 503
Ultra-fast magnetic resonance encephalography of physiological brain activity – Glymphatic pulsation mechanisms?
Kiviniemi, V., Wang, X., Korhonen, V., Keinänen, T., Tuovinen, T., Autio, J., LeVan, P., Keilholz, S., Zang, Y.-F., Hennig, J., et al. (2016) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x15622047 · Cited by 453
The Organization of Local and Distant Functional Connectivity in the Human Brain
Sepulcre, J., Liu, H., Talukdar, T., Martincorena, I., Yeo, B. T. T., & Buckner, R. L. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000808 · Cited by 428
The global signal in fMRI: Nuisance or Information?
Liu, T. T., Nalci, A., & Falahpour, M. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.02.036 · Cited by 405
Dynamic connectivity states estimated from resting fMRI Identify differences among Schizophrenia, bipolar disorder, and healthy control subjects
Rashid, B., Damaraju, E., Pearlson, G. D., & Calhoun, V. D. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00897 · Cited by 412
Large-amplitude, spatially correlated fluctuations in BOLD fMRI signals during extended rest and early sleep stages
Fukunaga, M., Horovitz, S. G., van Gelderen, P., de Zwart, J. A., Jansma, J. M., Ikonomidou, V. N., Chu, R., Deckers, R. H. R., Leopold, D. A., & Duyn, J. H. (2006) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2006.04.018 · Cited by 375
The role of physiological noise in resting-state functional connectivity
Birn, R. M. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.016 · Cited by 379
Association between heart rate variability and fluctuations in resting-state functional connectivity
Chang, C., Metzger, C. D., Glover, G. H., Duyn, J. H., Heinze, H., & Walter, M. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.11.038 · Cited by 368
Microstructural Organization of the Cingulum Tract and the Level of Default Mode Functional Connectivity
van den Heuvel, M., Mandl, R., Luigjes, J., & Hulshoff Pol, H. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.2964-08.2008 · Cited by 349
EEG correlates of time-varying BOLD functional connectivity
Chang, C., Liu, Z., Chen, M. C., Liu, X., & Duyn, J. H. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.01.049 · Cited by 355
Functional Magnetic Resonance Imaging Phase Synchronization as a Measure of Dynamic Functional Connectivity
Glerean, E., Salmi, J., Lahnakoski, J. M., Jääskeläinen, I. P., & Sams, M. (2012) · Brain Connectivity · doi:10.1089/brain.2011.0068 · Cited by 325
Applications of fMRI in translational medicine and clinical practice
Matthews, P. M., Honey, G. D., & Bullmore, E. T. (2006) · Nature reviews. Neuroscience · doi:10.1038/nrn1929 · Cited by 336
Differential Connectivity of Perirhinal and Parahippocampal Cortices within Human Hippocampal Subregions Revealed by High-Resolution Functional Imaging
Libby, L. A., Ekstrom, A. D., Ragland, J. D., & Ranganath, C. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.3711-11.2012 · Cited by 311
Loss of resting interhemispheric functional connectivity after complete section of the corpus callosum
Johnston, J. M., Vaishnavi, S. N., Smyth, M. D., Zhang, D., He, B. J., Zempel, J. M., Shimony, J. S., Snyder, A. Z., & Raichle, M. E. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.0573-08.2008 · Cited by 296
The (in)stability of functional brain network measures across thresholds
Garrison, K. A., Scheinost, D., Finn, E. S., Shen, X., & Constable, R. T. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.05.046 · Cited by 305
Relationship between respiration, end-tidal CO2, and BOLD signals in resting-state fMRI
Chang, C. E., & Glover, G. H. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.04.048 · Cited by 292
The Cortical Rhythms of Chronic Back Pain
Baliki, M. N., Baria, A. T., & Apkarian, A. V. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.1984-11.2011 · Cited by 291
Neurobiological basis of head motion in brain imaging
Zeng, L., Wang, D., Fox, M., Sabuncu, M. R., Hu, D., Ge, M., Buckner, R. L., & Liu, H. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1317424111 · Cited by 281
The effect of respiration variations on independent component analysis results of resting state functional connectivity.
Birn, R. M., Murphy, K., & Bandettini, P. A. (2008) · Human Brain Mapping · doi:10.1002/hbm.20577 · Cited by 283
Noise contributions to the fMRI signal: An overview
Liu, T. T. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.09.008 · Cited by 302
Anatomical and Functional Assemblies of Brain BOLD Oscillations
Baria, A. T., Baliki, M. N., Parrish, T. B., & Apkarian, A. V. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.1296-11.2011 · Cited by 268
Data Quality Influences Observed Links Between Functional Connectivity and Behavior
Siegel, J. S., Mitra, A., Laumann, T. O., Seitzman, B. A., Raichle, M. E., Corbetta, M., & Snyder, A. Z. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw253 · Cited by 254
Studying Brain Organization via Spontaneous fMRI Signal
Power, J. D., Schlaggar, B. L., & Petersen, S. E. (2014) · Neuron · doi:10.1016/j.neuron.2014.09.007 · Cited by 264
Functional connectivity: A source of variance in the association between cardiorespiratory fitness and cognition?
Voss, M. W., Erickson, K. I., Prakash, R. S., Chaddock, L., Malkowski, E., Alves, H., Kim, J., Morris, K. S., White, S. M., Wójcicki, T. R., et al. (2010) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2010.01.005 · Cited by 279
Functional brain networks in schizophrenia: a review
Calhoun, V. D. (2009) · Frontiers in Human Neuroscience · doi:10.3389/neuro.09.017.2009 · Cited by 270
Ridding fMRI data of motion-related influences: Removal of signals with distinct spatial and physical bases in multiecho data
Power, J. D., Plitt, M. H., Gotts, S. J., Kundu, P., Voon, V., Bandettini, P. A., & Martin, A. D. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1720985115 · Cited by 261
Altered functional connectivity in default mode network in absence epilepsy: A resting‐state fMRI study
Luo, C., Li, Q., Lai, Y., Yang, X., Qin, Y. F., Liao, W., Li, S., Zhou, D., Yao, D., & Gong, Q. (2010) · Human Brain Mapping · doi:10.1002/hbm.21034 · Cited by 258
Neurophysiological Investigation of Spontaneous Correlated and Anticorrelated Fluctuations of the BOLD Signal
Keller, C. J., Bickel, S., Honey, C. J., Groppe, D. M., Entz, L., Craddock, R. C., Lado, F. A., Kelly, C., Milham, M., & Mehta, A. D. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.4837-12.2013 · Cited by 245
Physiological noise modelling for spinal functional magnetic resonance imaging studies
Brooks, J. C. W., Beckmann, C. F., Miller, K. L., Wise, R. G., Porro, C. A., Tracey, I., & Jenkinson, M. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.09.018 · Cited by 243
Self-citation
Sources of functional magnetic resonance imaging signal fluctuations in the human brain at rest: a 7 T study
Bianciardi, M., Fukunaga, M., van Gelderen, P., Horovitz, S. G., de Zwart, J. A., Shmueli, K., & Duyn, J. H. (2009) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2009.02.004 · Cited by 240
Functional connectivity MRI in infants: Exploration of the functional organization of the developing brain
Smyser, C. D., Snyder, A. Z., & Neil, J. J. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.02.073 · Cited by 259
A brief history of the resting state: The Washington University perspective
Snyder, A. Z., & Raichle, M. E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.044 · Cited by 257
Quantifying the Microvascular Origin of BOLD-fMRI from First Principles with Two-Photon Microscopy and an Oxygen-Sensitive Nanoprobe
Gagnon, L., Sakadžić, S., Lesage, F., Musacchia, J. J., Lefebvre, J., Fang, Q., Yücel, M. A., Evans, K. C., Mandeville, E. T., Cohen‐Adad, J., et al. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.3555-14.2015 · Cited by 236
Brain Activation during Anticipation of Sound Sequences
Leaver, A. M., Lare, J. V., Zielinski, B. A., Halpern, A. R., & Rauschecker, J. P. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.4921-08.2009 · Cited by 238
Physiological Noise in Brainstem fMRI
Brooks, J. C. W., Harrison, O. K., Pattinson, K. T. S., & Jenkinson, M. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00623 · Cited by 227
Functional connectivity MR imaging reveals cortical functional connectivity in the developing brain
Lin, W., Zhu, Q., Gao, W., Chen, Y., Toh, C.-H., Styner, M., Gerig, G., Smith, J. K., Biswal, B., & Gilmore, J. H. (2008) · American Journal of Neuroradiology · doi:10.3174/ajnr.a1256 · Cited by 222
Functional Connectivity fMRI of the Rodent Brain: Comparison of Functional Connectivity Networks in Rat and Mouse
Jonckers, E., Audekerke, J. V., Visscher, G. D., der Linden, A. V., & Verhoye, M. (2011) · PLoS ONE · doi:10.1371/journal.pone.0018876 · Cited by 228
Modular preprocessing pipelines can reintroduce artifacts into fMRI data
Lindquist, M. A., Geuter, S., Wager, T. D., & Caffo, B. S. (2019) · Human Brain Mapping · doi:10.1002/hbm.24528 · Cited by 218
Spontaneous low-frequency blood oxygenation level-dependent fluctuations and functional connectivity analysis of the ‘resting’ brain
Auer, D. P. (2008) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2008.05.008 · Cited by 218
Functional segregation of the human cingulate cortex is confirmed by functional connectivity based neuroanatomical parcellation
Yu, C., Zhou, Y., Liu, Y., Jiang, T., Dong, H., Zhang, Y., & Walter, M. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.11.018 · Cited by 223
Evaluation of denoising strategies to address motion-correlated artifacts in resting-state functional magnetic resonance imaging data from the human connectome project
Burgess, G. C., Kandala, S., Nolan, D., Laumann, T. O., Power, J. D., Adeyemo, B., Harms, M. P., Petersen, S. E., & Barch, D. M. (2016) · Brain Connectivity · doi:10.1089/brain.2016.0435 · Cited by 216
BOLD functional MRI in disease and pharmacological studies: room for improvement?
Iannetti, G. D., & Wise, R. G. (2007) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2007.03.018 · Cited by 220
Self-citation
Functional Magnetic Resonance Imaging Methods
Chen, J. E., & Glover, G. H. (2015) · Neuropsychology Review · doi:10.1007/s11065-015-9294-9 · Cited by 249
The impact of physiological noise correction on fMRI at 7 T
Hutton, C., Josephs, O., Stadler, J., Featherstone, E., Reid, A., Speck, O., Bernarding, J., & Weiskopf, N. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.04.018 · Cited by 211
Correcting Brain-Wide Correlation Differences in Resting-State FMRI
Saad, Z. S., Reynolds, R. C., Jo, H. J., Gotts, S. J., Chen, G., Martin, A. D., & Cox, R. W. (2013) · Brain Connectivity · doi:10.1089/brain.2013.0156 · Cited by 200
Time lag dependent multimodal processing of concurrent fMRI and near-infrared spectroscopy (NIRS) data suggests a global circulatory origin for low-frequency oscillation signals in human brain
Tong, Y., & Frederick, B. B. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.06.049 · Cited by 208
BOLD study of stimulation-induced neural activity and resting-state connectivity in medetomidine-sedated rat
Zhao, F., Zhao, T., Zhou, L., Qiu-lin, W., & Hu, X. P. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.07.063 · Cited by 199
The role of fMRI in drug discovery
Wise, R. G., & Tracey, I. (2006) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.20584 · Cited by 186
Self-citation
The effect of ageing on f MRI : Correction for the confounding effects of vascular reactivity evaluated by joint f MRI and MEG in 335 adults
Tsvetanov, K. A., Henson, R. N., TYLER, L. K., Davis, S. W., Shafto, M. A., Taylor, J. R., Williams, N., Cam‐CAN, & Rowe, J. B. (2015) · Human Brain Mapping · doi:10.1002/hbm.22768 · Cited by 187
Alterations of the amplitude of low-frequency fluctuations in treatment-resistant and treatment-response depression: A resting-state fMRI study
Guo, W., Liu, F., Xue, Z., Xu, X., Wu, R., Ma, C., Wooderson, S. C., Tan, C., Sun, X., Chen, J., et al. (2012) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2012.01.011 · Cited by 182
Low Frequency Systemic Hemodynamic “Noise” in Resting State BOLD fMRI: Characteristics, Causes, Implications, Mitigation Strategies, and Applications
Tong, Y., Hocke, L. M., & Frederick, B. B. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00787 · Cited by 177
Functional connectivity between ventral prefrontal cortex and amygdala at low frequency in the resting state in bipolar disorder
Chepenik, L. G., Raffo, M., Hampson, M., Lacadie, C., Wang, F., Jones, M. M., Pittman, B., Skudlarski, P., & Blumberg, H. P. (2010) · Psychiatry Research: Neuroimaging · doi:10.1016/j.pscychresns.2010.04.002 · Cited by 175
EEG-Informed fMRI: A Review of Data Analysis Methods
Abreu, R., Leal, A., & Figueiredo, P. (2018) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2018.00029 · Cited by 171

Authors: Wise, R. G., Ide, K., Poulin, M. J., & Tracey, I.
Affiliations: John Radcliffe Hospital (GB)
University of Calgary (CA)
Corresponding author: Wise, Richard G
ORCID: Wise, Richard G
Ide, Kojiro
Poulin, Marc J
Tracey, Irene
Venue: NeuroImage
Publisher: Elsevier BV
Published: 2004-04
Volume: 21
Issue: 4
Pages: 1652-1664
ISSN: 1053-8119 (ISSN-L)
DOI: 10.1016/j.neuroimage.2003.11.025
OpenAlex: W2145403933
Cited by: 664
References: 75
Citations by year: 2026: 12 · 2025: 34 · 2024: 30 · 2023: 33 · 2022: 22 · 2021: 34 · 2020: 31 · 2019: 32 · 2018: 32 · 2017: 28 · 2016: 40 · 2015: 31 · 2014: 33 · 2013: 42 · 2012: 44
FWCI: 12.29
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: NeuroImage (publishedVersion)
PubMed (publishedVersion)
Funders: Heart and Stroke Foundation of Canada
Wellcome Trust
Health Research Board
Heritage Medical Research Institute
University of Oxford
Alberta Heritage Foundation for Medical Research
Council for Higher Education
Yükseköğretim Kurulu
Canadian Institutes of Health Research
Medical Research Council
Topics: Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Optical Imaging and Spectroscopy Techniques
Keywords: arterial carbon dioxide, end-tidal carbon dioxide, BOLD signal fluctuations, cerebral vasodilation, physiological noise, middle cerebral artery blood flow velocity, cerebral blood flow, gray and white matter, transcranial Doppler, resting state
MeSH terms: Adult, Blood Flow Velocity, Brain, Carbon Dioxide, Female, Fourier Analysis, Humans, Image Enhancement, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Oxygen, Reference Values, Rest, Software, Tomography, Emission-Computed, Vasodilation, Linear Models, Echo-Planar Imaging, Ultrasonography, Doppler, Transcranial

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

Resting fluctuations in arterial carbon dioxide induce significant low frequency variations in BOLD signal

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks