Abstract
Directional connectivity measures exist with different theoretical backgrounds, i.e., information theoretic, parametric-modeling based or phase related. In this paper, we perform the first comparison in this extend of a set of conventional and directed connectivity measures [cross-correlation, coherence, phase slope index (PSI), directed transfer function (DTF), partial-directed coherence (PDC) and transfer entropy (TE)] with eight-node simulation data based on real resting closed eye electroencephalogram (EEG) source signal. The ability of the measures to differentiate the direct causal connections from the non-causal connections was evaluated with the simulated data. Also, the effects of signal-to-noise ratio (SNR) and decimation were explored. All the measures were able to distinguish the direct causal interactions from the non-causal relations. PDC detected less non-causal connections compared to the other measures. Low SNR was tolerated better with DTF and PDC than with the other measures. Decimation affected most the results of TE, DTF and PDC. In conclusion, parametric-modeling-based measures (DTF, PDC) had the highest sensitivity of connections and tolerance to SNR in simulations based on resting closed eye EEG. However, decimation of data has to be carefully considered with these measures.
References
Astolfi L, Cincotti F, Mattia D, Lai M, Baccalá L, Fallani F, Salinari S, Ursino M, Zavaglia M, Babiloni F (2007) Comparison of different cortical connectivity estimators for high-resolution EEG recordings. Hum Brain Mapp 28:143–157
Baccalá LA, Sameshima K (2001) Partial directed coherence: a new concept in neural structure determination. Biol Cybern 84(6):463–474
BioSig, “BioSig—toolbox for biosignal analysis” (online). Available: http://biosig.sourceforge.net/
Florin E, Gross J, Pfeifer J, Fink GR, Timmermann L (2010) The effect of filtering on Granger causality based multivariate causality measures. NeuroImage 50(2):577–588
Gómez-Herrero G, Wu W, Rutanen K, Soriano M, Pipa G, Vicente R (2010) Assessing coupling dynamics from an ensemble of time series (online). Available: arXiv:1008.0539v1
Kamiński MJ, Blinowska KJ (1991) A new method of the description of the information flow in the brain structures. Biol Cybern 65(3):203–210
Kamiński M (2007) Multichannel data analysis in biomedical research. In: Jirsa VK, McIntosh AR (eds) Handbook of brain connectivity. Springer, Berlin, pp 327–355
Kuś R, Kamiński M, Blinowska KJ (2004) Determination of EEG activity propagation: pair-wise versus multichannel estimate. IEEE Trans Biomed Eng 51(9):1501–1510
Nolte G, Ziehe A, Nikulin VV, Schlögl A, Krämer N, Brismar T, Müller K-R (2008) Robustly estimating the flow direction of information in complex physical systems. Phys Rev Lett 100(23):234101
Nolte G, Ziehe A, Nikulin VV, Schlögl A, Krämer N, Brismar T, Müller K-R, Phase-slope index—software (online). Available: http://ml.cs.tu-berlin.de/causality/
Pereda E, Quiroga RQ, Bhattacharya J (2005) Nonlinear multivariate analysis of neurophysiological signals. Prog Neurobiol 77(1–2):1–37
Porcaro C, Zappasodi F, Rossini PM, Tecchio F (2009) Choice of multivariate autoregressive model order affecting real network functional connectivity estimate. Clin Neurophysiol 120:436–448
Rutanen K, Gómez-Herrero G, TIM-toolbox for estimation of information-theoretic measures from time-series (online). Available: http://www.cs.tut.fi/~timhome/tim.htm
Schreiber T (2000) Measuring information transfer. Phys Rev Lett 85:461–464
Vélez-Pérez H, Louis-Dorr V, Ranta R, Dufaut M (2008) Connectivity estimation of three parametric methods on simulated electroencephalogram signals. Conf Proc IEEE Eng Med Biol Soc 2008:2606–2609
Winterhalder M, Schelter B, Hesse W, Schwab K, Leistritz L, Timmer J, Witte H (2006) Detection of directed information flow in biosignals. Biomed Tech (Berl) 51(5–6):281–287
Acknowledgments
This work was supported by the Academy of Finland.
Author information
Authors and Affiliations
Corresponding author
Appendix
Appendix
See Table 1.
Rights and permissions
About this article
Cite this article
Silfverhuth, M.J., Hintsala, H., Kortelainen, J. et al. Experimental comparison of connectivity measures with simulated EEG signals. Med Biol Eng Comput 50, 683–688 (2012). https://doi.org/10.1007/s11517-012-0911-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11517-012-0911-y