M. Le Van Quyen et al., Comparison of Hilbert transform and wavelet methods for the analysis of neuronal synchrony, J NEUROSC M, 111(2), 2001, pp. 83-98
The quantification of phase synchrony between neuronal signals is of crucia
l importance for the study of large-scale interactions in the brain. Two me
thods have been used to date in neuroscience, based on two distinct approac
hes which pen-nit a direct estimation of the instantaneous phase of a signa
l [Phys. Rev. Lett. 81 (1998) 3291; Human Brain Mapping 8 (1999) 194]. The
phase is either estimated by using the analytic concept of Hilbert transfor
m or, alternatively, by convolution with a complex wavelet. In both methods
the stability of the instantaneous phase over a window of time requires qu
antification by means of various statistical dependence parameters (standar
d deviation, Shannon entropy or mutual information). The purpose of this pa
per is to conduct a direct comparison between these two methods on three si
gnal sets: (1) neural models; (2) intracranial signals from epileptic patie
nts; and (3) scalp EEG recordings. Levels of synchrony that can be consider
ed as reliable are estimated by using the technique of surrogate data. Our
results demonstrate that the differences between the methods are minor, and
we conclude that they are fundamentally equivalent for the study of neuroe
lectrical signals. This offers a common language and framework that can be
used for future research in the area of synchronization. (C) 2001 Published
by Elsevier Science B.V.