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The impact of global signal regression on resting state correlations: Are anti-correlated networks introduced?
Open accessAbstract
Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step.
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“Some physiological noises, such as cardiac and respiratory rates, can alias into the low-frequency domain of functional MRI signals (Strother, 2006;Murphy et al., 2009).”
From Identifying major depression using whole-brain functional connectivity: a multivariate pattern analysis (2012) · cites this paper as Murphy et al., 2009
In the citing paper
“The interpretation of negative correlations is especially controversial because they only become strongly evident after regressing out the global signal; therefore some argue that negative connections in functional data may be purely a statistical artifact (Murphy et al., 2009).”
From Characterizing heterogeneity in children with and without ADHD based on reward system connectivity (2015) · cites this paper as Murphy et al., 2009
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“Some experts have suggested that these techniques might introduce spurious negative correlations upon regressing out whole brain signals (Murphy et al, 2009;Van Dijk et al, 2009).”
From Understanding the Effects of Stimulant Medications on Cognition in Individuals with Attention-Deficit Hyperactivity Disorder: A Decade of Progress (2011) · cites this paper as Murphy et al, 2009
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“Though depression commonly co-occurs with PTSD in veteran populations (up to 80% by some estimations70)”
From Altered resting-state amygdala functional connectivity in men with posttraumatic stress disorder (2012) · cites this paper as [70]
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Cites
A default mode of brain function
Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.2.676 · Cited by 12,190
Co-Planar Stereotaxic Atlas of the Human Brain
Talairach, J., & Tournoux, P. (1988) · Medical Entomology and Zoology · Cited by 11,798
AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages
Cox, R. W. (1996) · Computers and Biomedical Research · doi:10.1006/cbmr.1996.0014 · Cited by 10,913
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
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 human brain is intrinsically organized into dynamic, anticorrelated functional networks
Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0504136102 · Cited by 8,553
Co-planar stereotaxic atlas of the human brain
Laitinen, L. (1989) · Clinical Neurology and Neurosurgery · doi:10.1016/0303-8467(89)90128-5 · Cited by 7,565
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
Functional connectivity in the resting brain: a network analysis of the default mode hypothesis
Greicius, M. D., Krasnow, B., Reiss, A. L., & Menon, V. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0135058100 · Cited by 6,358
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
Research works printed but not linked: 2
- Fox, M.D., Zhang, D., Snyder, A.Z., Raichle, M.E., 2008. Global signal regression and anticorrelations in resting state fMRI data. Proc. HBM, 575 W-AM.
- Weissenbacher, A., Lanzenberger, R., Moser, E., Windischberger, C., 2008. Increasing specificity of resting-state fMRI-data using multiple regression analysis. Proc. HBM, TH-AM.
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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
The minimal preprocessing pipelines for the Human Connectome Project
Glasser, M. F., Sotiropoulos, S. N., Wilson, J. A., Coalson, T. S., Fischl, B., Andersson, J. L., Xu, J., Jbabdi, S., Webster, M., Polimeni, J. R., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.127 · Cited by 5,253
Conn : A Functional Connectivity Toolbox for Correlated and Anticorrelated Brain Networks
Whitfield-Gabrieli, S., & Nieto-Castanon, A. (2012) · Brain Connectivity · doi:10.1089/brain.2012.0073 · Cited by 4,885
Methods to detect, characterize, and remove motion artifact in resting state fMRI
Power, J. D., Mitra, A., Laumann, T. O., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.08.048 · Cited by 3,748
DPARSF: a MATLAB toolbox for “pipeline” data analysis of resting-state fMRI
Yan (2010) · Frontiers in System Neuroscience · doi:10.3389/fnsys.2010.00013 · Cited by 3,475
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 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
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
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
ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data
Pruim, R. H. R., Mennes, M., van Rooij, D., Llera, A., Buitelaar, J. K., & Beckmann, C. F. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.02.064 · Cited by 1,684
Satterthwaite, T. D., Elliott, M. A., Gerraty, R. T., Ruparel, K., Loughead, J., Calkins, M. E., Eickhoff, S. B., Hakonarson, H. H., Gur, R. C., Gur, R. E., et al. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.08.052 · Cited by 1,982
REST: A Toolkit for Resting-State Functional Magnetic Resonance Imaging Data Processing
Song, X., Dong, Z.-Y., Long, X., Li, S., Zuo, X., Zhu, C.-Z., Yong He, A., Yan, C., & Zang, Y. (2011) · PLoS ONE · doi:10.1371/journal.pone.0025031 · Cited by 1,889
Multi-task connectivity reveals flexible hubs for adaptive task control
Cole, M. W., Reynolds, J. R., Power, J. D., Repovs, G., Anticevic, A., & Braver, T. S. (2013) · Nature Neuroscience · doi:10.1038/nn.3470 · Cited by 1,704
Emerging concepts for the dynamical organization of resting-state activity in the brain
Deco, G., Jirsa, V. K., & McIntosh, A. R. (2011) · Nature reviews. Neuroscience · doi:10.1038/nrn2961 · Cited by 1,798
Resting-state fMRI in the human connectome project
Smith, S. M., Beckmann, C. F., Andersson, J., Auerbach, E. J., Bijsterbosch, J., Douaud, G., Duff, E., Feinberg, D. A., Griffanti, L., Harms, M. P., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.039 · Cited by 1,502
Yan, C.-G., Cheung, B., Kelly, C., Colcombe, S., Craddock, R. C., Di Martino, A., Li, Q., Zuo, X.-N., Castellanos, F. X., & Milham, M. P. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.03.004 · Cited by 1,461
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Whitfield-Gabrieli, S., & Ford, J. M. (2012) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-032511-143049 · Cited by 1,465
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
GRETNA: a graph theoretical network analysis toolbox for imaging connectomics
Wang, J., Wang, X., Xia, M., Liao, X., Evans, A. C., & Yong He, A. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2015.00386 · Cited by 1,439
The dynamic functional connectome: State-of-the-art and perspectives
Preti, M. G., Bolton, T. A. W., & Ville, D. V. D. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.12.061 · Cited by 1,454
A Baseline for the Multivariate Comparison of Resting-State Networks
Allen, E. A., Erhardt, E. B., Damaraju, E., Gruner, W. E., Segall, J. M., Silva, R. F., Havlíček, M., Rachakonda, S., Fries, J. F., Kalyanam, R., et al. (2011) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2011.00002 · Cited by 1,329
Fox, M. D., Buckner, R. L., White, M. P., Greicius, M. D., & Pascual-Leone, A. (2012) · Biological Psychiatry · doi:10.1016/j.biopsych.2012.04.028 · Cited by 1,270
Griffanti, L., Salimi‐Khorshidi, G., Beckmann, C. F., Auerbach, E. J., Douaud, G., Sexton, C. E., Zsoldos, E., Ebmeier, K. P., Filippini, N., Mackay, C. E., et al. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.03.034 · Cited by 1,273
Clinical applications of resting state functional connectivity
Fox, M. (2010) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2010.00019 · Cited by 1,219
Anticorrelations in resting state networks without global signal regression
Chai, X. J., Nieto-Castañón, A., Öngür, D., & Whitfield, S. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.08.048 · Cited by 1,193
Brain Graphs: Graphical Models of the Human Brain Connectome
Bullmore, E. T., & Bassett, D. S. (2011) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-040510-143934 · Cited by 1,165
Resting-State fMRI: A Review of Methods and Clinical Applications
Lee, M. H., Smyser, C. D., & Shimony, J. S. (2012) · American Journal of Neuroradiology · doi:10.3174/ajnr.a3263 · Cited by 1,195
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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
Ciric, R., Wolf, D. H., Power, J. D., Roalf, D. R., Baum, G. L., Ruparel, K., Shinohara, R. T., Elliott, M. A., Eickhoff, S. B., Davatzikos, C., et al. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.03.020 · Cited by 1,042
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
Self-citationRecent progress and outstanding issues in motion correction in resting state fMRI
Power, J. D., Schlaggar, B. L., & Petersen, S. E. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.10.044 · Cited by 957
Spreng, R. N., & Grady, C. L. (2010) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2009.21282 · Cited by 985
The role of default network deactivation in cognition and disease
Anticevic, A., Cole, M. W., Murray, J. D., Corlett, P. R., Wang, X.-J., & Krystal, J. H. (2012) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2012.10.008 · Cited by 978
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
Opportunities and limitations of intrinsic functional connectivity MRI
Buckner, R. L., Krienen, F. M., & Yeo, B. T. T. (2013) · Nature Neuroscience · doi:10.1038/nn.3423 · Cited by 912
Advances and pitfalls in the analysis and interpretation of resting-state FMRI data
Cole, D. M. (2010) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2010.00008 · Cited by 1,011
Structure and function of complex brain networks
Sporns, O. (2013) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2013.15.3/osporns · Cited by 964
Resting-state functional connectivity in major depressive disorder: A review
Mulders, P. C., van Eijndhoven, P. F., Schene, A. H., Beckmann, C. F., & Tendolkar, I. (2015) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2015.07.014 · Cited by 884
The Resting Brain: Unconstrained yet Reliable
Shehzad, Z. E., Kelly, C. A. M., Reiss, P. T., Gee, D. G., Gotimer, K., Uddin, L. Q., Lee, S. H., Margulies, D. S., Roy, A. K., Biswal, B. B., et al. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhn256 · Cited by 948
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
Self-citationDisease and the brain's dark energy
Zhang, D., & Raichle, M. E. (2010) · Nature Reviews Neurology · doi:10.1038/nrneurol.2009.198 · Cited by 928
Damoiseaux, J. S., & Greicius, M. D. (2009) · Brain Structure and Function · doi:10.1007/s00429-009-0208-6 · Cited by 897
Betzel, R. F., Byrge, L., He, Y., Goñi, J., Zuo, X.-N., & Sporns, O. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.07.067 · Cited by 807
Weight-conserving characterization of complex functional brain networks
Rubinov, M., & Sporns, O. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.03.069 · Cited by 903
Harris, K. D., & Thiele, A. (2011) · Nature reviews. Neuroscience · doi:10.1038/nrn3084 · Cited by 915
Decreased segregation of brain systems across the healthy adult lifespan
Chan, M. Y., Park, D. C., Savalia, N. K., Petersen, S. E., & Wig, G. S. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1415122111 · Cited by 919
Hallquist, M. N., Hwang, K., & Luna, B. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.116 · Cited by 753
Cui, X., Bryant, D. M., & Reiss, A. L. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.09.003 · Cited by 807
On the relationship between the “default mode network” and the “social brain
Mars, R. B., Neubert, F.-X., Noonan, M. P., Sallet, J., Toni, I., & Rushworth, M. F. S. (2012) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2012.00189 · Cited by 766
Weissenbacher, A., Kasess, C., Gerstl, F., Lanzenberger, R., Moser, E., & Windischberger, C. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.05.005 · Cited by 776
Parkes, L., Fulcher, B., Yücel, M., & Fornito, A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.12.073 · Cited by 830
Signature of consciousness in the dynamics of resting-state brain activity
Barttfeld, P., Uhrig, L., Sitt, J. D., Sigman, M., Jarraya, B., & Dehaene, S. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1418031112 · Cited by 670
Key role of coupling, delay, and noise in resting brain fluctuations
Deco, G., Jirsa, V., McIntosh, A. R., Sporns, O., & Kötter, R. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0901831106 · Cited by 777
Zeng, L.-L., Shen, H., Liu, L., Wang, L., Li, B., Fang, P., Zhou, Z., Li, Y., & Hu, D. (2012) · Brain · doi:10.1093/brain/aws059 · Cited by 748
Zuo, X.-N., Kelly, C., Adelstein, J. S., Klein, D. F., Castellanos, F. X., & Milham, M. P. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.080 · Cited by 744
Schizophrenia, neuroimaging and connectomics
Fornito, A., Zalesky, A., Pantelis, C., & Bullmore, E. T. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.12.090 · Cited by 716
Graph analysis of the human connectome: Promise, progress, and pitfalls
Fornito, A., Zalesky, A., & Breakspear, M. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.087 · Cited by 743
A Brain-Wide Study of Age-Related Changes in Functional Connectivity
Geerligs, L., Renken, R. J., Saliasi, E., Maurits, N. M., & Lorist, M. M. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhu012 · Cited by 788
Hutchison, R. M., Womelsdorf, T., Gati, J. S., Everling, S., & Menon, R. S. (2012) · Human Brain Mapping · doi:10.1002/hbm.22058 · Cited by 732
Spreng, R. N., Sepulcre, J., Turner, G. R., Stevens, W. D., & Schacter, D. L. (2013) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00281 · Cited by 668
Dynamic reconfiguration of the default mode network during narrative comprehension
Simony, E., Honey, C. J., Chen, J., Lositsky, O., Yeshurun, Y., Wiesel, A., & Hasson, U. (2016) · Nature Communications · doi:10.1038/ncomms12141 · Cited by 588
Konrad, K., & Eickhoff, S. B. (2010) · Human Brain Mapping · doi:10.1002/hbm.21058 · Cited by 670
Etkin, A., Prater, K. E., Schatzberg, A. F., Menon, V., & Greicius, M. D. (2009) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2009.104 · Cited by 664
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
Self-citationLearning-induced autonomy of sensorimotor systems
Bassett, D. S., Yang, M., Wymbs, N. F., & Grafton, S. T. (2015) · Nature Neuroscience · doi:10.1038/nn.3993 · Cited by 603
Global Connectivity of Prefrontal Cortex Predicts Cognitive Control and Intelligence
Cole, M. W., Yarkoni, T., Repovs, G., Anticevic, A., & Braver, T. S. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.0536-12.2012 · Cited by 613
Zuo, X., & Xing, X.-X. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2014.05.009 · Cited by 678
Liu, X., & Duyn, J. H. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1216856110 · Cited by 663
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
Evidence for a large-scale brain system supporting allostasis and interoception in humans
Kleckner, I. R., Zhang, J., Touroutoglou, A., Chanes, L., Xia, C., Simmons, W. K., Quigley, K. S., Dickerson, B. C., & Feldman Barrett, L. (2017) · Nature Human Behaviour · doi:10.1038/s41562-017-0069 · Cited by 641
Dixon, M. L., De La Vega, A., Mills, C., Andrews-Hanna, J., Spreng, R. N., Cole, M. W., & Christoff, K. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1715766115 · Cited by 595
Uncovering Intrinsic Modular Organization of Spontaneous Brain Activity in Humans
Yong He, A., Wang, J., Wang, L. Y., Chen, Z. J., Yan, C., Yang, H., Tang, H., Zhu, C., Gong, Q., Zang, Y., et al. (2009) · PLoS ONE · doi:10.1371/journal.pone.0005226 · Cited by 635
Handbook of functional connectivity Magnetic Resonance Imaging methods in CONN
Nieto-Castañón, A. (2020) · Hilbert Press eBooks · doi:10.56441/hilbertpress.2207.6598 · Cited by 654
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
Fox, M. D., Buckner, R. L., Liu, H., Chakravarty, M. M., Lozano, A. M., & Pascual-Leone, A. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1405003111 · Cited by 617
Brier, M. R., Thomas, J. B., Snyder, A. Z., Benzinger, T. L., Zhang, D., Raichle, M. E., Holtzman, D. M., Morris, J. C., & Ances, B. M. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.5698-11.2012 · Cited by 595
Functional brain connectivity using fMRI in aging and Alzheimer’s disease
Dennis, E. L., & Thompson, P. M. (2014) · Neuropsychology Review · doi:10.1007/s11065-014-9249-6 · Cited by 583
Structural foundations of resting-state and task-based functional connectivity in the human brain
Hermundstad, A. M., Bassett, D. S., Brown, K., Aminoff, E., Clewett, D., Freeman, S., Frithsen, A., Johnson, A., Tipper, C. M., Miller, M. B., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1219562110 · Cited by 580
Causal interactions between fronto-parietal central executive and default-mode networks in humans
Chen, A. C., Oathes, D. J., Chang, C., Bradley, T., Zhou, Z.-W., Williams, L. M., Glover, G. H., Deisseroth, K. A., & Etkin, A. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1311772110 · Cited by 580
The functional architecture of the infant brain as revealed by resting-state fMRI
Fransson, P., Åden, U., Blennow, M., & Lagercrantz, H. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhq071 · Cited by 542
Identifying the brain's most globally connected regions
Cole, M. W., Pathak, S., & Schneider, W. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.11.001 · Cited by 572
Functional connectivity mapping of the human precuneus by resting state fMRI
Zhang, S., & Li, C. R. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.11.023 · 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
Fornito, A., Harrison, B. J., Zalesky, A., & Simons, J. S. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1204185109 · Cited by 555
Network localization of neurological symptoms from focal brain lesions
Boes, A. D., Prasad, S., Liu, H., Liu, Q., Pascual‐Leone, Á., Caviness, V. S., & Fox, M. (2015) · Brain · doi:10.1093/brain/awv228 · Cited by 556
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Dong, D., Wang, Y., Chang, X., Luo, C., & Yao, D. (2018) · Schizophrenia Bulletin · doi:10.1093/schbul/sbx034 · Cited by 486
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Cao, M., Wang, J.-H., Dai, Z.-J., Cao, X.-Y., Jiang, L.-L., Fan, F.-M., Song, X.-W., Xia, M.-R., Shu, N., Dong, Q., et al. (2014) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2013.11.004 · Cited by 440
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Mayer, A. R., Mannell, M. V., Ling, J. M., Gasparovic, C., & Yeo, R. A. (2011) · Human Brain Mapping · doi:10.1002/hbm.21151 · Cited by 500
Davey, J., Thompson, H. E., Hallam, G., Karapanagiotidis, T., Murphy, C., De Caso, I., Krieger-Redwood, K., Bernhardt, B. C., Smallwood, J., & Jefferies, E. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.05.051 · Cited by 433
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Self-citationSkudlarski, P., Jagannathan, K., Anderson, K., Stevens, M. C. G., Calhoun, V. D., Skudlarska, B. A., & Pearlson, G. D. (2010) · Biological Psychiatry · doi:10.1016/j.biopsych.2010.03.035 · Cited by 476
Li, W., Mai, X., & Liu, C. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00074 · Cited by 508
Palhano-Fontes, F., Andrade, K. C., Tofoli, L. F., Santos, A. C., Crippa, J. A. S., Hallak, J. E. C., Ribeiro, S., & de Araujo, D. B. (2015) · PLOS ONE · doi:10.1371/journal.pone.0118143 · Cited by 454
Metadata
- Authors
- Murphy, K., Birn, R. M., Handwerker, D. A., Jones, T. B., & Bandettini, P. A.
- Affiliations
- National Institutes of Health (US)
- Corresponding author
- Bandettini, Peter A.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2009-02
- Volume
- 44
- Issue
- 3
- Pages
- 893-905
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC2750906
- OpenAlex
- W2169787465
- Cited by
- 2,387
- References
- 64
- Citations by year
- 2026: 118 · 2025: 104 · 2024: 109 · 2023: 78 · 2022: 121 · 2021: 133 · 2020: 173 · 2019: 157 · 2018: 166 · 2017: 204 · 2016: 187 · 2015: 188 · 2014: 181 · 2013: 168 · 2012: 114
- FWCI
- 31.87
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Institute of Mental Health (Z01MH002783)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- global signal regression, resting-state functional connectivity, default mode network, attentional networks, posterior cingulate cortex, phase difference, breath-holding, visual task, seed-based correlation analysis
- MeSH terms
- Biological Clocks, Brain, Computer Simulation, Humans, Magnetic Resonance Imaging, Male, Models, Neurological, Nerve Net, Regression Analysis, Rest, Statistics as Topic, Young Adult
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