Global signal regression acts as a temporal downweighting process in resting-state fMRI

NeuroImage

Volumn 152, Issue , 2017, Pages 602-618

  Nalci, Alican ^a,b   Rao, Bhaskar D ^b   Liu, Thomas T ^a,c  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Anti correlations; Censoring; FMRI; Global signal regression; Temporal downweighting

Indexed keywords

ARTICLE; BOLD SIGNAL; BRAIN MAPPING; CONTROLLED STUDY; DEFAULT MODE NETWORK; FUNCTIONAL CONNECTIVITY; FUNCTIONAL MAGNETIC RESONANCE IMAGING; GLOBAL SIGNAL REGRESSION; HUMAN; IMAGE ANALYSIS; NERVOUS SYSTEM PARAMETERS; RESTING STATE NETWORK; TASK POSITIVE NETWORK; VOXEL BASED MORPHOMETRY; BRAIN; FEMALE; IMAGE ENHANCEMENT; MALE; NERVE TRACT; NUCLEAR MAGNETIC RESONANCE IMAGING; PHYSIOLOGY; PROCEDURES; SIGNAL PROCESSING;

BRAIN; BRAIN MAPPING; FEMALE; HUMANS; IMAGE ENHANCEMENT; MAGNETIC RESONANCE IMAGING; MALE; NEURAL PATHWAYS; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 85016015989     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2017.01.015     Document Type: Article

References (54)

1. Anderson, J.S., Druzgal, T.J., Lopez-Larson, M., Jeong, E.-K., Desai, K., Yurgelun-Todd, D., Network anticorrelations, global regression, and phase-shifted soft tissue correction. Hum. Brain Mapp. 32:June (6) (2011), 919–934.
2. Biswal, B., Yetkin, F.Z., Haughton, V.M., Hyde, J.S., Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn. Reson. Med. 34:October (4) (1995), 537–541.
3. Carbonell, F., Bellec, P., Shmuel, A., Global and system-specific resting-state fMRI fluctuations are uncorrelated: principal component analysis reveals anti-correlated networks. Brain Connect. 1:6 (2011), 496–510.
4. Carbonell, F., Bellec, P., Shmuel, A., Quantification of the impact of a confounding variable on functional connectivity confirms anti-correlated networks in the resting-state. NeuroImage 86:February (2014), 343–353.
5. Chai, X.J., Castañón, A.N., Ongür, D., Whitfield-Gabrieli, S., Anticorrelations in resting state networks without global signal regression. NeuroImage 59:January (2) (2012), 1420–1428.
6. Chang, C., Glover, G.H., Effects of model-based physiological noise correction on default mode network anti-correlations and correlations. NeuroImage 47:October (4) (2009), 1448–1459.
7. Chang, C., Leopold, D.A., Schölvinck, M.L., Mandelkow, H., Picchioni, D., Liu, X., Ye, F.Q., Turchi, J.N., Duyn, J.H., Tracking brain arousal fluctuations with fMRI. Proc. Natl. Acad. Sci. U.S.A. 113:April (16) (2016), 4518–4523.
8. Cordes, D., Haughton, V.M., Arfanakis, K., Carew, J.D., Turski, P.A., Moritz, C.H., Quigley, M.A., Meyerand, M.E., Frequencies contributing to functional connectivity in the cerebral cortex in resting-state data. Am. J. Neuroradiol. 22:August (7) (2001), 1326–1333.
9. Cordes, D., Haughton, V.M., Arfanakis, K., Wendt, G.J., Turski, P.A., Moritz, C.H., Quigley, M.A., Meyerand, M.E., Mapping functionally related regions of brain with functional connectivity MR imaging. Am. J. Neuroradiol. 21:9 (2000), 1636–1644.
10. Cox, R.W., AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput. Biomed. Res., Int. J. 29:June (3) (1996), 162–173.
11. Draper, N.R., Smith, H., 2014. Applied Regression Analysis, 3rd edition. John Wiley & Sons, New York (August).
12. Falahpour, M., Wong, C.W., Liu, T.T., 2016. The resting state fMRI global signal is negatively correlated with time-varying EEG vigilance. In: Proceedings of the 24th Annual Meeting of the ISMRM, p. 641.
13. Fox, M.D., Corbetta, M., Snyder, A.Z., Vincent, J.L., Raichle, M.E., Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems. Proc. Natl. Acad. Sci. 103:26 (2006), 10046–10051.
14. Fox, M.D., Raichle, M.E., Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat. Rev. Neurosci. 8:September (9) (2007), 700–711.
15. Fox, M.D., Snyder, A.Z., Vincent, J.L., Corbetta, M., Van Essen, D.C., Raichle, M.E., The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc. Natl. Acad. Sci. U.S.A. 102:27 (2005), 9673–9678.
16. Fox, M.D., Snyder, A.Z., Vincent, J.L., Raichle, M.E., Intrinsic fluctuations within cortical systems account for intertrial variability in human behavior. Neuron 56:1 (2007), 171–184.
17. Fox, M.D., Zhang, D., Snyder, A.Z., Raichle, M.E., The global signal and observed anticorrelated resting state brain networks. J. Neurophysiol. 101:June (6) (2009), 3270–3283.
18. Gotts, S.J., Saad, Z.S., Jo, H.J., Wallace, G.L., Cox, R.W., Martin, A., The perils of global signal regression for group comparisons: a case study of Autism Spectrum Disorders. Front. Hum. Neurosci., 7, 2013, 356.
19. Hahamy, A., Calhoun, V., Pearlson, G., Harel, M., Stern, N., Attar, F., Malach, R., Salomon, R., Save the global: global signal connectivity as a tool for studying clinical populations with functional magnetic resonance imaging. Brain Connect. 4:August (6) (2014), 395–403.
20. Hampson, M., Peterson, B.S., Skudlarski, P., Gatenby, J.C., Gore, J.C., Detection of functional connectivity using temporal correlations in MR images. Hum. Brain Mapp. 15:4 (2002), 247–262.
21. He, H., Liu, T.T., A geometric view of global signal confounds in resting-state functional MRI. NeuroImage 59:February (3) (2012), 2339–2348.
22. Hoaglin, D.C., Welsch, R.E., The hat matrix in regression and ANOVA. Am. Stat. 32:February (1) (1978), 17–22.
23. Jones, B.E., From waking to sleeping: neuronal and chemical substrates. Trends Pharmacol. Sci. 26:November (11) (2005), 578–586.
24. Karahanoğlu, F.I., Van De Ville, D., Transient brain activity disentangles fMRI resting-state dynamics in terms of spatially and temporally overlapping networks. Nat. Commun., 6(July (7751)), 2015.
25. Lacadie, C.M., Fulbright, R.K., Rajeevan, N., Constable, R.T., Papademetris, X., More accurate Talairach coordinates for neuroimaging using non-linear registration. Neuroimage 42:2 (2008), 717–725.
26. Leys, C., Ley, C., Klein, O., Bernard, P., Licata, L., Detecting outliers: do not use standard deviation around the mean, use absolute deviation around the median. J. Exp. Soc. Psychol. 49:4 (2013), 764–766.
27. Li, J.M., Bentley, W.J., Snyder, A.Z., Raichle, M.E., Snyder, L.H., Functional connectivity arises from a slow rhythmic mechanism. Proc. Natl. Acad. Sci. U.S.A. 112:May (19) (2015), E2527–E2535.
28. Liang, Z., King, J., Zhang, N., Anticorrelated resting-state functional connectivity in awake rat brain. NeuroImage 59:January (2) (2012), 1190–1199.
29. Liu, X., Duyn, J.H., Time-varying functional network information extracted from brief instances of spontaneous brain activity. Proc. Natl. Acad. Sci. 110:11 (2013), 4392–4397.
30. Liu, X., Yanagawa, T., Leopold, D., Chang, C., Ishida, H., Fuji, I.N., Duyn, J., Arousal transitions in sleep, wakefulness, and anesthesia are characterized by an orderly sequence of cortical events. NeuroImage 116:August (2015), 222–231.
31. Macey, P.M., Macey, K.E., Kumar, R., Harper, R.M., A method for removal of global effects from fMRI time series. NeuroImage 22:May (1) (2004), 360–366.
32. Martinez, W.L., Martinez, A.R., Martinez, A., Solka, J., Exploratory Data Analysis With MATLAB. 2010, CRC Press, Boca Raton.
33. Murphy, K., Birn, R.M., Handwerker, D.A., Jones, T.B., Bandettini, P.A., The impact of global signal regression on resting state correlations: are anti-correlated networks introduced. NeuroImage 44:February (3) (2009), 893–905.
34. Picchioni, D., Duyn, J.H., Horovitz, S.G., Sleep and the functional connectome. NeuroImage 80:October (2013), 387–396.
35. Pisauro, M.A., Benucci, A., Carandini, M., Local and global contributions to hemodynamic activity in mouse cortex. J. Neurophysiol. 115:June (6) (2016), 2931–2936.
36. Power, J.D., Barnes, K.A., Snyder, A.Z., Schlaggar, B.L., Petersen, S.E., Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. NeuroImage 59:February (3) (2012), 2142–2154.
37. Power, J.D., Plitt, M., Laumann, T.O., Martin, A., 2017. Sources and implications of whole-brain fMRI signals in humans. NeuroImage, in press, http://dx.doi.org/10.1016/j.neuroimage.2016.09.038.
38. Power, J.D., Schlaggar, B.L., Petersen, S.E., Recent progress and outstanding issues in motion correction in resting state fMRI. NeuroImage 105:January (2015), 536–551.
39. Raichle, M.E., MacLeod, A.M., Snyder, A.Z., Powers, W.J., Gusnard, D.A., Shulman, G.L., A default mode of brain function. Proc. Natl. Acad. Sci. 98:2 (2001), 676–682.
40. Reimann, C., Filzmoser, P., Garrett, R.G., Background and threshold: critical comparison of methods of determination. Sci. Total Environ. 346:1 (2005), 1–16.
41. Remes, J.J., Starck, T., Nikkinen, J., Ollila, E., Beckmann, C.F., Tervonen, O., Kiviniemi, V., Silven, O., Effects of repeatability measures on results of fMRI sICA: a study on simulated and real resting-state effects. NeuroImage 56:May (2) (2011), 554–569.
42. Saad, Z.S., Gotts, S.J., Murphy, K., Chen, G., Jo, H.J., Martin, A., Cox, R.W., Trouble at rest: how correlation patterns and group differences become distorted after global signal regression. Brain Connect. 2:1 (2012), 25–32.
43. Schölvinck, M.L., Maier, A., Ye, F.Q., Duyn, J.H., Leopold, D.A., Neural basis of global resting-state fMRI activity. Proc. Natl. Acad. Sci. U.S.A. 107:June (22) (2010), 10238–10243.
44. Siegel, J.S., Power, J.D., Dubis, J.W., Vogel, A.C., Church, J.A., Schlaggar, B.L., Petersen, S.E., Statistical improvements in functional magnetic resonance imaging analyses produced by censoring high-motion data points. Hum. Brain Mapp. 35:May (5) (2014), 1981–1996.
45. Tagliazucchi, E., Balenzuela, P., Fraiman, D., Chialvo, D.R., Criticality in large-scale brain fMRI dynamics unveiled by a novel point process analysis. Front. Physiol., 3(15), 2012.
46. Van Dijk, K.R., Hedden, T., Venkataraman, A., Evans, K.C., Lazar, S.W., Buckner, R.L., Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization. J. Neurophysiol. 103:1 (2010), 297–321.
47. Wager, T.D., Keller, M.C., Lacey, S.C., Jonides, J., Increased sensitivity in neuroimaging analyses using robust regression. Neuroimage 26:1 (2005), 99–113.
48. Walther, A., Nili, H., Ejaz, N., Alink, A., Kriegeskorte, N., Diedrichsen, J., Reliability of dissimilarity measures for multi-voxel pattern analysis. NeuroImage 137:December (2015), 188–200.
49. Weissenbacher, A., Kasess, C., Gerstl, F., Lanzenberger, R., Moser, E., Windischberger, C., Correlations and anticorrelations in resting-state functional connectivity MRI: a quantitative comparison of preprocessing strategies. NeuroImage 47:October (4) (2009), 1408–1416.
50. Wen, H., Liu, Z., Broadband electrophysiological dynamics contribute to global resting-state fMRI signal. J. Neurosci. 36:June (22) (2016), 6030–6040.
51. Wong, C.W., Olafsson, V., Tal, O., Liu, T.T., Anti-correlated networks, global signal regression, and the effects of caffeine in resting-state functional MRI. NeuroImage 63:October (1) (2012), 356–364.
52. Wong, C.W., Olafsson, V., Tal, O., Liu, T.T., The amplitude of the resting-state fMRI global signal is related to EEG vigilance measures. NeuroImage 83:December (2013), 983–990.
53. Yan, L., Zhuo, Y., Ye, Y., Xie, S.X., An, J., Aguirre, G.K., Wang, J., Physiological origin of low-frequency drift in blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI). Magn. Reson. Med. 61:April (4) (2009), 819–827.
54. Yang, G.J., Murray, J.D., Repovs, G., Cole, M.W., Savic, A., Glasser, M.F., Pittenger, C., Krystal, J.H., Wang, X.-J., Pearlson, G.D., Glahn, D.C., Anticevic, A., Altered global brain signal in schizophrenia. Proc. Natl. Acad. Sci. U.S.A. 111:May (20) (2014), 7438–7443.