Comparison of Hilbert transform and wavelet methods for the analysis of neuronal synchrony.

By M. Le Van Quyen, M. Quyen, Jack Foucher, Jean-Philippe Lachaux, Eugenio Rodríguez, Antoine Lutz, Jacques Martinerie, Francisco J. Varela. Journal of Neuroscience Methods, 2001

928 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/4d85ad577916479ff7d57b78162ef4de70cf895e

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Citations in the corpus

Classification of EEG signals using neural network and logistic regression (2005, methodology): “[6] M.”
Modelling event-related responses in the brain (2005, methodology): “In particular, we have used the Jansen model (Jansen and Rit, 1995) for each source, and a simplified version of the connection rules of Felleman and Van Essen, (1991) to couple these sources.”
Event-related EEG time-frequency analysis: an overview of measures and an analysis of early gamma band phase locking in schizophrenia. (2008, neutral): “in the baseline period, yielding baseline-adjusted z scores.(27,49,54,72) Methods 2 through 4 have the advantage of removing overall scale differences between frequencies and between individuals, rendering them more directly comparable.”
Functional Magnetic Resonance Imaging Phase Synchronization as a Measure of Dynamic Functional Connectivity (2012, neutral): “Thisisachievedbyconvertingtherealsig-nalintoitscomplexanalyticversion(Boashash,1992)withsignal processing techniques, like the Hilbert transform, Gabor expansion, or Wavelet ﬁltering (for comparisons see Le Van Quyen et al., 2001; Schack and Weiss, 2005; Sun and Small, 2009).”
Surrogate data for hypothesis testing of physical systems (2018, methodology): “concluded that the Hilbert transform is equivalent to the wavelet transform for the extraction of instantaneous phase from time series [249], but bandpass filtering was applied before the application of both methods.”
Time-dependent spectral analysis of epidemiological time-series with wavelets (2007, methodology): “As with the Morlet wavelet the W x (a, t) is a complex number, one can write W x (a, t) in terms of its phase f x (a, t) and modulus kW x (a, t)k (Le Van Quyen et al. 2001).”
Phase transfer entropy: A novel phase-based measure for directed connectivity in networks coupled by oscillatory interactions (2014, methodology): “We define, for a given frequency band, the instantaneous phase time-series of the signal X(t) as θ(t) in S(t) = A(t) exp (iθ(t)) where S(t) is obtained by complex filtering of X(t) (with e.g., Morlet wavelet or Hilbert transform (Le Van Quyen et al., 2001)).”
Classification of patterns of EEG synchronization for seizure prediction. (2009, neutral): “In parallel to comparative study (Mormann et al., 2005), and despite the current lack of a complete neurological understanding of the preictal brain state, researchers increasingly hypothesize that brainwave synchronization patterns might differentiate interictal, preictal and ictal states (Le Van Q”
Evaluation of different measures of functional connectivity using a neural mass model (2004, neutral): “This experiment was performed at the MEG Centre, La Salpêtrière Hospital, Paris, France, using a whole-head 151 sensors MEG system (CTF Inc., Vancouver, Canada).”
Single-Trial Normalization for Event-Related Spectral Decomposition Reduces Sensitivity to Noisy Trials (2011, result): “Fortunately, all of these spectral methods tend to return similar results (Le Van Quyen et al., 2001; Bruns, 2004) so we will focus on using simple sliding-window FFT decompositions in this report.”
Learning Temporal Information for Brain-Computer Interface Using Convolutional Neural Networks (2018, methodology): “2) The signal envelope of each signal is extracted using the Hilbert transform [35], which gives the analytic form of a signal that is complex-valued and interpreted as the one-sided version of the original signal’s frequency spectrum.”
The pairwise phase consistency: A bias-free measure of rhythmic neuronal synchronization (2010, methodology): “…to obtain a single-phase value per trial, in combination with a particular choice of tapering, such as multitapering (Mitra and Pesaran, 1999), whereas Hilbert or wavelet transform is often used to determine the instantaneous phase as a function of time (Lachaux et al., 1999; Quyen et al., 2001).”
Nonlinear multivariate analysis of neurophysiological signals. (2005, background): “…disease (Tass et al., 1998), mania (Bhattacharya, 2001), migraine (Angelini et al., 2004) and especially epilepsy (Bhattacharya, 2001; Jerger et al., 2001; Kraskov, 2004; Kraskov et al., 2002; Kreuz, 2004; Kreuz et al., 2004; Le van Quyen et al., 2001; Mormann et al., 2003; Mormann et al., 2000).”
A Note on the Phase Locking Value and its Properties (2013, result): “Quiroga et al. (2002) and Le Van Quyen et al. (2001) have shown that both approaches yield similar results.”