International Journal of Information Engineering and Electronic Business(IJIEEB)

ISSN: 2074-9023 (Print), ISSN: 2074-9031 (Online)

Published By: MECS Press

IJIEEB Vol.7, No.5, Sep. 2015

Time-Frequency Wavelet Based Coherence Analysis of EEG in EC and EO during Resting State

Full Text (PDF, 454KB), PP.55-61

Views:63   Downloads:1


Lal Hussain, Wajid Aziz

Index Terms

Wavelet Phase Coherence;Resting State;Electroencephalography (EEG)


The electrophysiological brain activities are nonlinear in nature as measured by Electroencephalography (EEG). There are coherent activities in brain not only seen during explicit tasks but also during rest. This article aims to employ most robust nonlinear dynamics Time - Frequency representation (TFR) techniques such as wavelet phase coherence to investigate brain activity in different frequency bands at temporal and spatial scale dynamics in form of topographic maps in resting state networks. The TFR has the advantages to study the combined effect of time and frequency domains simultaneously. The wavelet coherence computed in this way exhibit high precision to detect the phase coherence in different frequency intervals to analyze highly complex non-autonomous and non-stationary EEG signals. The spatiotemporal dynamics of resting state networks are investigated by computing coherence. We have investigated the Wavelet based Phase coherence of oscillations of eye closed and eye open signals during resting states. The wavelet coherence is computed for selected 19 electrodes according to 10-20 system from 129 channel EEG signals. The significance was obtained using Wilcoxon Signed Rank test and pairwise wavelet coherence was computed for each possible combination. The Wavelet Phase Coherence using Wavelet Transform gives significantly high results (P<0.05) in EC and EO signals during resting states in frequency interval 0.5-50 Hz overall as well as in the band intervals such as delta (05-4 Hz), theta (4-7 Hz), alpha (7-13 Hz), beta (13-22 Hz) and gamma (22-50 Hz). By computing the spatial wavelet phase coherence, we observed significant pathways including sagittal factor (anterior-posterior interhemispheric) and lateral factor (perpendicular to anterior-posterior axis). The lateral factor differences have less affect than the sagittal factor. Each band was involved in different activities in some way, however alpha band showed distinct anterior-posterior activity when the eye-closed coherence was higher than the eye open coherence.

Cite This Paper

Lal Hussain, Wajid Aziz,"Time-Frequency Wavelet Based Coherence Analysis of EEG in EC and EO during Resting State", IJIEEB, vol.7, no.5, pp.55-61, 2015. DOI: 10.5815/ijieeb.2015.05.08


[1]Barry, R. J., Clarke, A. R., Johnstone, S. J., Magee, C. A., & Rushby, J. A. (2007). EEG differences between eyes-closed and eyes-open resting conditions. Clinical Neurophysiology, 118(12), 2765-2773.

[2]O'gorman, R. L., Poil, S. S., Brandeis, D., Klaver, P., Bollmann, S., Ghisleni, C., ... & Michels, L. (2013). Coupling between resting cerebral perfusion and EEG. Brain topography, 26(3), 442-457.

[3]Clemson, P. T., Suprunenko, Y. F., Stankovski, T., & Stefanovska, A. (2014). Inverse approach to chronotaxic systems for single-variable time series. Physical Review E, 89(3), 032904.

[4]Sheppard, L. W., Stefanovska, A., & McClintock, P. V. E. (2012). Testing for time-localized coherence in bivariate data. Physical Review E, 85(4), 046205.

[5]Sankari, Z., Adeli, H., & Adeli, A. (2011). Intrahemispheric, interhemispheric, and distal EEG coherence in Alzheimer's disease. Clinical Neurophysiology, 122(5), 897-906.

[6]Laufs, H., Kleinschmidt, A., Beyerle, A., Eger, E., Salek-Haddadi, A., Preibisch, C., & Krakow, K. (2003). EEG-correlated fMRI of human alpha activity. Neuroimage, 19(4), 1463-1476.

[7]Schiavone, G., Linkenkaer-Hansen, K., Maurits, N. M., Plakas, A., Maassen, B. A., Mansvelder, H. D., ... & van Zuijen, T. L. (2014). Preliteracy signatures of poor-reading abilities in resting-state EEG. Frontiers in human neuroscience, 8.

[8]Murias, M., Swanson, J. M., & Srinivasan, R. (2007). Functional connectivity of frontal cortex in healthy and ADHD children reflected in EEG coherence. Cerebral Cortex, 17(8), 1788-1799.

[9]Bian, Z., Li, Q., Wang, L., Lu, C., Yin, S., & Li, X. (2014). Relative power and coherence of EEG series are related to amnestic mild cognitive impairment in diabetes. Frontiers in aging neuroscience, 6.

[10]Deco, G., Jirsa, V. K., Robinson, P. A., Breakspear, M., & Friston, K. (2008). The dynamic brain: from spiking neurons to neural masses and cortical fields. PLoS computational biology, 4(8), e1000092.

[11]Deco, G., Jirsa, V., McIntosh, A. R., Sporns, O., & Kötter, R. (2009).Key role of coupling, delay, and noise in resting brain fluctuations. Proceedings of the National Academy of Sciences, 106(25), 10302-10307.

[12]Rosenblum, M. G., & Pikovsky, A. S. (2001). Detecting direction of coupling in interacting oscillators. Physical Review E, 64(4), 045202.

[13]Sankari, Z., & Adeli, H. (2011). Probabilistic neural networks for diagnosis of Alzheimer's disease using conventional and wavelet coherence. Journal of neuroscience methods, 197(1), 165-170.

[14]Sheppard, L. W., Vuksanović, V., McClintock, P. V. E., & Stefanovska, A. (2011a). Oscillatory dynamics of vasoconstriction and vasodilation identified by time-localized phase coherence. Physics in medicine and biology, 56(12), 3583.

[15]Sheppard, L., Stefanovska, A., & McClintock, P. V. E. (2011b). Detecting the harmonics of oscillations with time-variable frequencies. Physical Review E, 83(1). 016206.

[16]Iatsenko, D., Bernjak, A., Stankovski, T., Shiogai, Y., Owen-Lynch, P. J., Clarkson, P. B. M., & Stefanovska, A. (2013). Evolution of cardiorespiratory interactions with age. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 371(1997), 20110622.

[17]Iatsenko, D., McClintock, P. V., & Stefanovska, A. (2015). Linear and synchrosqueezed time–frequency representations revisited: Overview, standards of use, resolution, reconstruction, concentration, and algorithms. Digital Signal Processing, 42, 1-26.

[18]Kaiser, G. A friendly guide to wavelets. pp. 60-77, 1994

[19]Lachaux, J. P., Lutz, A., Rudrauf, D., Cosmelli, D., Le Van Quyen, M., Martinerie, J., & Varela, F. (2002).Estimating the time-course of coherence between single-trial brain signals: an introduction to wavelet coherence. Neurophysiologie Clinique/Clinical Neurophysiology, 32(3), 157-174.