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EEG correlates of time-varying BOLD functional connectivity

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Chang, Catie, Liu, Zhongming, Chen, Michael C., Liu, Xiao, Duyn, Jeff H.·2013·NeuroImage

Abstract

Recent resting-state fMRI studies have shown that the apparent functional connectivity (FC) between brain regions may undergo changes on time-scales of seconds to minutes, the basis and importance of which are largely unknown. Here, we examine the electrophysiological correlates of within-scan FC variations during a condition of eyes-closed rest. A sliding window analysis of simultaneous EEG-fMRI data was performed to examine whether temporal variations in coupling between three major networks (default mode; DMN, dorsal attention; DAN, and salience network; SN) are associated with temporal variations in mental state, as assessed from the amplitude of alpha and theta oscillations in the EEG. In our dataset, alpha power showed a significant inverse relationship with the strength of connectivity between DMN and DAN. In addition, alpha power covaried with the spatial extent of anticorrelation between DMN and DAN, with higher alpha power associated with larger anticorrelation extent. Results suggest an electrical signature of the time-varying FC between the DAN and DMN, potentially reflecting neural and state-dependent variations.

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Research works printed but not linked: 54

  1. Birn, 2006, Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI, Neuroimage, 31, 1536, 10.1016/j.neuroimage.2006.02.048 · DOI · Paper page
  2. Brookes, 2012, The electrophysiological basis of resting state networks, Proc. Int. Soc. Magn. Reson. Med., 20, 132
  3. Cantero, 2002, Human alpha oscillations in wakefulness, drowsiness period, and REM sleep: different electroencephalographic phenomena within the alpha band, Neurophysiol. Clin., 32, 54, 10.1016/S0987-7053(01)00289-1 · DOI
  4. Chang, 2009, Effects of model-based physiological noise correction on default mode network anti-correlations and correlations, Neuroimage, 47, 1448, 10.1016/j.neuroimage.2009.05.012 · DOI · Paper page
  5. Chang, 2009, Influence of heart rate on the BOLD signal: The cardiac response function, Neuroimage, 44, 857, 10.1016/j.neuroimage.2008.09.029 · DOI · Paper page
  6. Chang, 2010, Time-frequency dynamics of resting-state brain connectivity measured with fMRI, Neuroimage, 50, 81, 10.1016/j.neuroimage.2009.12.011 · DOI · Paper page
  7. Christoff, 2009, Experience sampling during fMRI reveals default network and executive system contributions to mind wandering, Proc. Natl. Acad. Sci. U. S. A., 106, 8719, 10.1073/pnas.0900234106 · DOI · Paper page
  8. de Munck, 2008, A study of the brain's resting state based on alpha band power, heart rate and fMRI, Neuroimage, 42, 112, 10.1016/j.neuroimage.2008.04.244 · DOI
  9. de Pasquale, 2010, Temporal dynamics of spontaneous MEG activity in brain networks, Proc. Natl. Acad. Sci. U. S. A., 107, 6040, 10.1073/pnas.0913863107 · DOI · Paper page
  10. Foster, 2012, Resting oscillations and cross-frequency coupling in the human posteromedial cortex, Neuroimage, 60, 384, 10.1016/j.neuroimage.2011.12.019 · DOI
  11. Fox, 2005, The human brain is intrinsically organized into dynamic, anticorrelated functional networks, Proc. Natl. Acad. Sci. U. S. A., 102, 9673, 10.1073/pnas.0504136102 · DOI · Paper page
  12. Fransson, 2005, Spontaneous low-frequency BOLD signal fluctuations: an fMRI investigation of the resting-state default mode of brain function hypothesis, Hum. Brain Mapp., 26, 15, 10.1002/hbm.20113 · DOI · Paper page
  13. Fukunaga, 2006, Large-amplitude, spatially correlated fluctuations in BOLD fMRI signals during extended rest and early sleep stages, Magn. Reson. Imaging, 24, 979, 10.1016/j.mri.2006.04.018 · DOI · Paper page
  14. Glover, 2001, Spiral-in/out BOLD fMRI for increased SNR and reduced susceptibility artifacts, Magn. Reson. Med., 46, 515, 10.1002/mrm.1222 · DOI · Paper page
  15. Glover, 2000, Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR, Magn. Reson. Med., 44, 162, 10.1002/1522-2594(200007)44:1<162::AID-MRM23>3.0.CO;2-E · doi:10.1002/1522-2594(200007)44:1<162::aid-mrm23>3.0.co;2-e
  16. Goldman, 2002, Simultaneous EEG and fMRI of the alpha rhythm, Neuroreport, 13, 2487, 10.1097/00001756-200212200-00022 · DOI · Paper page
  17. Greicius, 2008, Persistent default-mode network connectivity during light sedation, Hum Brain Mapp, 29, 839, 10.1002/hbm.20537 · DOI · Paper page
  18. Handwerker, 2012, Periodic changes in fMRI connectivity, Neuroimage, 63, 1712, 10.1016/j.neuroimage.2012.06.078 · DOI · Paper page
  19. He, 2008, Electrophysiological correlates of the brain's intrinsic large-scale functional architecture, Proc. Natl. Acad. Sci. U. S. A., 105, 16039, 10.1073/pnas.0807010105 · DOI · Paper page
  20. Hlinka, 2010, Slow EEG pattern predicts reduced intrinsic functional connectivity in the default mode network: an inter-subject analysis, Neuroimage, 53, 239, 10.1016/j.neuroimage.2010.06.002 · DOI · Paper page
  21. Honey, 2007, Network structure of cerebral cortex shapes functional connectivity on multiple time scales, Proc. Natl. Acad. Sci. U. S. A., 104, 10240, 10.1073/pnas.0701519104 · DOI · Paper page
  22. Horovitz, 2008, Low frequency BOLD fluctuations during resting wakefulness and light sleep: a simultaneous EEG–fMRI study, Hum. Brain Mapp., 29, 671, 10.1002/hbm.20428 · DOI · Paper page
  23. Hutchison, 2012, Resting-state networks show dynamic functional connectivity in awake humans and anesthetized macaques, Hum. Brain Mapp.
  24. Jann, 2010, Association of individual resting state EEG alpha frequency and cerebral blood flow, Neuroimage, 51, 365, 10.1016/j.neuroimage.2010.02.024 · DOI
  25. Kiviniemi, 2011, A sliding time-window ICA reveals spatial variability of the default mode network in time, Brain Connect., 1, 339, 10.1089/brain.2011.0036 · DOI · Paper page
  26. Klimesch, 1999, EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis, Brain Res. Brain Res. Rev., 29, 169, 10.1016/S0165-0173(98)00056-3 · DOI · Paper page
  27. Larson-Prior, 2011, Modulation of the brain's functional network architecture in the transition from wake to sleep, Prog. Brain Res., 193, 277, 10.1016/B978-0-444-53839-0.00018-1 · DOI
  28. Laufs, 2003, EEG-correlated fMRI of human alpha activity, Neuroimage, 19, 1463, 10.1016/S1053-8119(03)00286-6 · DOI · Paper page
  29. Laufs, 2006, Where the BOLD signal goes when alpha EEG leaves, Neuroimage, 31, 1408, 10.1016/j.neuroimage.2006.02.002 · DOI · Paper page
  30. Liu, 2012, Statistical feature extraction for artifact removal from concurrent fMRI-EEG recordings, Neuroimage, 59, 2073, 10.1016/j.neuroimage.2011.10.042 · DOI · Paper page
  31. Lu, 2007, Synchronized delta oscillations correlate with the resting-state functional MRI signal, Proc. Natl. Acad. Sci. U. S. A., 104, 18265, 10.1073/pnas.0705791104 · DOI · Paper page
  32. Magri, 2012, The amplitude and timing of the BOLD signal reflects the relationship between local field potential power at different frequencies, J. Neurosci., 32, 1395, 10.1523/JNEUROSCI.3985-11.2012 · DOI · Paper page
  33. Makeig, 1993, Lapses in alertness: coherence of fluctuations in performance and EEG spectrum, Electroencephalogr. Clin. Neurophysiol., 86, 23, 10.1016/0013-4694(93)90064-3 · DOI · Paper page
  34. Moosmann, 2003, Correlates of alpha rhythm in functional magnetic resonance imaging and near infrared spectroscopy, Neuroimage, 20, 145, 10.1016/S1053-8119(03)00344-6 · DOI · Paper page
  35. Niazy, 2005, Removal of FMRI environment artifacts from EEG data using optimal basis sets, Neuroimage, 28, 720, 10.1016/j.neuroimage.2005.06.067 · DOI · Paper page
  36. Nir, 2008, Interhemispheric correlations of slow spontaneous neuronal fluctuations revealed in human sensory cortex, Nat. Neurosci., 11, 1100, 10.1038/nn.2177 · DOI · Paper page
  37. Olbrich, 2009, EEG-vigilance and BOLD effect during simultaneous EEG/fMRI measurement, Neuroimage, 45, 319, 10.1016/j.neuroimage.2008.11.014 · DOI · Paper page
  38. Pan, 2011, Broadband local field potentials correlate with spontaneous fluctuations in functional magnetic resonance imaging signals in the rat somatosensory cortex under isoflurane anesthesia, Brain Connect., 1, 119, 10.1089/brain.2011.0014 · DOI
  39. Petridou, 2012, Periods of rest in fMRI contain individual spontaneous events which are related to slowly fluctuating spontaneous activity, Hum. Brain Mapp.
  40. Popa, 2009, Contrasting activity profile of two distributed cortical networks as a function of attentional demands, J. Neurosci., 29, 1191, 10.1523/JNEUROSCI.4867-08.2009 · DOI
  41. Rack-Gomer, 2012, Caffeine increases the temporal variability of resting-state BOLD connectivity in the motor cortex, Neuroimage, 59, 2994, 10.1016/j.neuroimage.2011.10.001 · DOI
  42. Sadaghiani, 2010, Intrinsic connectivity networks, alpha oscillations, and tonic alertness: a simultaneous electroencephalography/functional magnetic resonance imaging study, J. Neurosci., 30, 10243, 10.1523/JNEUROSCI.1004-10.2010 · DOI · Paper page
  43. Sakoglu, 2010, A method for evaluating dynamic functional network connectivity and task-modulation: application to schizophrenia, MAGMA, 23, 351, 10.1007/s10334-010-0197-8 · DOI · Paper page
  44. Samann, 2011, Development of the brain's default mode network from wakefulness to slow wave sleep, Cereb. Cortex, 21, 2082, 10.1093/cercor/bhq295 · DOI · Paper page
  45. Scheeringa, 2012, EEG alpha power modulation of fMRI resting state connectivity, Brain Connect., 2, 254, 10.1089/brain.2012.0088 · DOI · Paper page
  46. Scholvinck, 2010, Neural basis of global resting-state fMRI activity, Proc. Natl. Acad. Sci. U. S. A., 107, 10238, 10.1073/pnas.0913110107 · DOI · Paper page
  47. Shirer, 2012, Decoding subject-driven cognitive states with whole-brain connectivity patterns, Cereb. Cortex, 22, 158, 10.1093/cercor/bhr099 · DOI · Paper page
  48. Shmueli, 2007, Low-frequency fluctuations in the cardiac rate as a source of variance in the resting-state fMRI BOLD signal, Neuroimage, 38, 306, 10.1016/j.neuroimage.2007.07.037 · DOI · Paper page
  49. Smallwood, 2004, Subjective experience and the attentional lapse: task engagement and disengagement during sustained attention, Conscious. Cogn., 13, 657, 10.1016/j.concog.2004.06.003 · DOI · Paper page
  50. Smith, 2009, Correspondence of the brain's functional architecture during activation and rest, Proc. Natl. Acad. Sci. U. S. A., 106, 13040, 10.1073/pnas.0905267106 · DOI · Paper page
  51. Sporns, 2011, The non-random brain: efficiency, economy, and complex dynamics, Front. Comput. Neurosci., 5, 5, 10.3389/fncom.2011.00005 · DOI
  52. Stamatakis, 2010, Changes in resting neural connectivity during propofol sedation, PLoS One, 5, e14224, 10.1371/journal.pone.0014224 · DOI
  53. Thompson, 2012, Short-time windows of correlation between large-scale functional brain networks predict vigilance intraindividually and interindividually, Hum. Brain Mapp.
  54. Yuan, 2012, Correlated slow fluctuations in respiration, EEG, and BOLD fMRI: what is the origin of physiological noise?, Proc. Int. Soc. Magn. Reson. Med., 20, 2843

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Metadata

Authors
Chang, C., Liu, Z., Chen, M. C., Liu, X., & Duyn, J. H.
Venue
NeuroImage
Publisher
Elsevier BV
Published
2013-05
Volume
72
Pages
227-236
ISSN
1053-8119 (ISSN-L)
OpenAlex
W2114303782
Cited by
345
References
19
FWCI
14.98
Type
journal article
Language
en
Open access
green
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Funders
Intramural Research Program of the National Institute of Neurological Disorders and Stroke, National Institutes of Health

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Chang, C., Liu, Z., Chen, M. C., Liu, X., & Duyn, J. H. (2013). EEG correlates of time-varying BOLD functional connectivity. NeuroImage. https://doi.org/10.1016/j.neuroimage.2013.01.049

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