Abstract
The aim of this work is to study the coherence profile (dependence) of robust eyes-closed resting EEG sources isolated by group blind source separation (gBSS). We employ a test–retest strategy using two large sample normative databases (N = 57 and 84). Using a BSS method in the complex Fourier domain, we show that we can rigourously study the out-of-phase dependence of the extracted components, albeit they are extracted so as to be in-phase independent (by BSS definition). Our focus on lagged communication between components effectively yields dependence measures unbiased by volume conduction effects, which is a major concern about the validity of any dependence measures issued by EEG measurements. We are able to show the organization of the extracted components in two networks. Within each network components oscillate coherently with multiple-frequency dynamics, whereas between networks they exchange information at non-random multiple time-lag rates.
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References
Beckmann CF, DeLuca M, Devlin JT, Smith SM (2005) Investigations into resting-state connectivity using independent component analysis. Phil Trans R Soc B 360:1001–1013
Bloomfield P (2000) Fourier analysis of time series. Wiley, New York
Broyd SJ, Demanuele C, Debener S, Helps SK, James CJ, Sonuga-Barke EJ (2008) Default-mode brain dysfunction in mental disorders: a systematic review. Neurosci Biobehav Rev 33(3):279–296
Calhoun VD, Adali T, Pearlson GD, Pekar JJ (2001) A method for making group inferences from functional MRI data using independent component analysis. Hum Brain Mapp 14:140–151
Chen AC, Feng W, Zhao H, Yin Y, Wang P (2008) EEG default mode network in the human brain: spectral regional field powers. Neuroimage 41:561–574
Congedo M, Özen C, Sherlin L (2002) Notes on EEG resampling by natural cubic spline interpolation. J Neurotherapy 6(4):73–80
Congedo M, Gouy-Pailler C, Jutten C (2008) On the blind source separation of human electroencephalogram by approximate joint diagonalization of second order statistics. Clin neurophysiol 119:2677–2686
Damoiseaux JS, Rombouts SARB, Barkhof F, Scheltens P, Stam CJ, Smith SM (2006) Consistent resting-state networks across healthy subjects. Proc Natl Acad Sci USA 103(37):13848–13853
Fox MD, Raichle ME (2007) Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci 8(9):700–711
Greenblatt RE, Ossadtchi A, Pflieger ME (2005) Local linear estimators for the bioelectromagnetic inverse problem. IEEE Trans Sig Process 53(9):3403–3412
John ER, Ahn H, Prichep LS, Trepetin M, Brown D, Kaye H (1980) Developmental equations for the electroencephalogram. Science 210:1255–1258
Mantini D, Perrucci MG, Del Gratta C, Romani GL, Corbetta M (2007) Electrophysiological signatures of resting state networks in the human brain. Proc Natl Acad Sci USA 104(32):13170–13175
Nolte G, Bai O, Wheaton L, Mari Z, Vorback S et al (2004) Identifying true brain interaction from EEG data using the imaginery part of coherency. Clin Neurophisiol 115:2292–2307
Nunez PL, Srinivasan R (2006) Electric field of the brain, 2nd edn. Oxford University Press, New York
Pascual-Marqui RD (2007) Instantaneous and lagged measurements of linear and nonlinear dependence between groups of multivariate time series: frequency decomposition. arXiv:0711.1455v1
Pham D-T, Congedo M (2009) Least square joint diagonalization of matrices under an intrinsic scale constraint, ICA 2009. In: 8th international conference on independent component analysis and signal separation, March 15–18, Paraty, Brasil
Schmithorst VJ, Holland SK (2004) Comparison of three methods for generating group statistical inferences from independent component analysis of functional magnetic resonance imaging data. Magn Reson Imaging 19(3):365–368
van den Heuvel M, Mandl R, Hulshoff Pol H (2008) Normalized cut group clustering of resting-state FMRI data. PLoS ONE 3(4):e2001
Welch PD (1967) The use of fast fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms. IEEE Trans Audio Electroacoustics 15(2):70–74
Acknowledgments
This research has been partially supported by the French National Research Agency (ANR) within the project Open-ViBE (“Open Platform for Virtual Brain Environments”), grant # ANR05RNTL01601, and by the European COST Action B27 “Electric Neuronal Oscillations and Cognition”.
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Congedo, M., John, R.E., De Ridder, D. et al. On the “Dependence” of “Independent” Group EEG Sources; an EEG Study on Two Large Databases. Brain Topogr 23, 134–138 (2010). https://doi.org/10.1007/s10548-009-0113-6
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DOI: https://doi.org/10.1007/s10548-009-0113-6