The pairwise phase consistency: A bias-free measure of rhythmic neuronal synchronization
By Martin A. Vinck, Marijn van Wingerden, Thilo Womelsdorf, Pascal Fries, Cyriel M. A. Pennartz. NeuroImage, 2010
481 citations recorded by the source corpus.
Oscillatory activity is a widespread phenomenon in nervous systems and has been implicated in numerous functions. Signals that are generated by two separate neuronal sources often demonstrate a consistent phase-relationship in a particular frequency-band, i.e., they demonstrate rhythmic neuronal synchronization. This consistency is conventionally measured by the PLV (phase-locking value) or the spectral coherence measure. Both statistical measures suffer from significant bias, in that their sample estimates overestimate the population statistics for finite sample sizes. This is a significant problem in the neurosciences where statistical comparisons are often made between conditions with a different number of trials or between neurons with a different number of spikes. We introduce a new circular statistic, the PPC (pairwise phase consistency). We demonstrate that the sample estimate of the PPC is a bias-free and consistent estimator of its corresponding population parameter. We show, both analytically and by means of numerical simulations, that the population statistic of the PPC is equivalent to the population statistic of the squared PLV. The variance and mean squared error of the PPC and PLV are compared. Finally, we demonstrate the practical relevance of the method in actual neuronal data recorded from the orbitofrontal cortex of rats that engage in a two-odour discrimination task. We find a strong increase in rhythmic synchronization of spikes relative to the local field potential (as measured by the PPC) for a wide range of low frequencies (including the theta-band) during the anticipation of sucrose delivery in comparison to the anticipation of quinine delivery.
Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Sensory Systems
View Paper: https://www.semanticscholar.org/paper/e121d69c3be89cdf6d94e7bd2a1d08e41641e763
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In Cellular and Molecular Neuroscience
In Cognitive Neuroscience
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In Sensory Systems
Citations in the corpus
- Functional Magnetic Resonance Imaging Phase Synchronization as a Measure of Dynamic Functional Connectivity (2012, unknown): “As noted in the original article (Vinck et al., 2010), one possible disadvantage of using PPC is that small negative values are possible; this is a consequence of the un-biasedness of the PPC. Intersubject seed-based PS. ISBPS is a measure of functional synchrony, where we require all subjects to ha”
- An improved index of phase-synchronization for electrophysiological data in the presence of volume-conduction, noise and sample-size bias (2011, unknown): “It is often stated that the direct coherence estimator is positively biased, e.g., see (Vinck et al., 2010b; Maris et al., 2007; Womelsdorf et al., 2006; Benignus, 1969).”
- MNE software for processing MEG and EEG data (2013, background): “Currently, the connectivity module in MNE can compute coherence, coherency (complex-valued coherence), imaginary coherence (Nolte et al., 2004), phase-locking value (PLV) (Lachaux et al., 1999), pairwise phase consistency (PPC) (Vinck et al., 2010), which is an unbiased estimate of PLV, phase lag in”
- A Note on the Phase Locking Value and its Properties (2013, methodology): “The sample PLV is a biased measure, as previously shown by Vinck et al. (2010).”
- Gamma-band synchronization in the neocortex: novel analysis methods and their application to sensory and motivational systems (2013, methodology): “It has been shown, in primate occipital cortex, that human/primate subjects can have widely varying spectra, which likely has a genetic basis (Vinck et al., 2010a; Hoogenboom et al., 2006; van Pelt et al., 2012).”
- Cognitive Effort Drives Workspace Configuration of Human Brain Functional Networks (2011, background): “An alternative approach to the same statistical issues has been to construct an innovative estimator of pairwise phase consistency (Vinck et al., 2010) that is an analytically unbiased and consistent estimator of population parameters of oscillations, but does not address the problem of…”