Reply to ``Comment on `Performance of different synchronization measures in real data: A case study on electroencephalographic signals' ''

By R. Quian Quiroga, Alexander Kraskov, Thomas Kreuz, Peter Grassberger. 2001

730 citations recorded by the source corpus.

We agree with the Comment by Duckrow and Albano [Phys. Rev. E 67, 063901 (2003)] that mutual information, estimated with an optimized algorithm, can be a useful tool for studying synchronization in real data. However, we point out that the improvement they found is mainly due to an interesting but nonstandard embedding technique used, and not so much due to the algorithm used for the estimation of mutual information itself. We also address the issue of stationarity of electroencephalographic (EEG) data.

Subfields: Cognitive Neuroscience, Computer Networks and Communications, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/a49a37864ba188943d7011ecdee44f41d8bf67ec

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Citations in the corpus

A comparative study of synchrony measures for the early diagnosis of Alzheimer's disease based on EEG (2010, neutral): “additional information about phase synchrony can be found in ( Quiroga et al., 2002 ).”
Surrogate data for hypothesis testing of physical systems (2018, background): “It should be emphasized that in [170,171] time-shifted surrogates are not used as surrogates in the usual sense, but by plotting the dependence of some nonlinear measure on the relative time shift between two time series, i.”
Analyzing multiple nonlinear time series with extended Granger causality (2004, methodology): “The idea above is actually very similar to other ideas of detecting directional interdependence based on nonlinear mutual prediction [9,10, 11 ,12,14,15,16,17].”
Graph analysis of functional brain networks: practical issues in translational neuroscience (2014, background): “ivity). A few studies that have attempted to compare a subset of FC methods with respect to their ability to correctly detect the presence of simulated connectivity schemes in a multivariate data set [58, 59, 60]. Unfortunately the results are not unequivocal and the performance of the measures seem”