The pairwise phase consistency: a bias-free measure of rhythmic neuronal synchronization

NeuroImage
Martin VinckCyriel Pennartz

Abstract

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 demons...Continue Reading

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Citations

Dec 22, 2011·Journal of Computational Neuroscience·Martin VinckCyriel Pennartz
Mar 1, 2012·Proceedings of the National Academy of Sciences of the United States of America·Thilo WomelsdorfPascal Fries
Jan 8, 2014·Journal of Cognitive Neuroscience·Jolanda JansonCornelia Kranczioch
Jun 20, 2014·Neural Networks : the Official Journal of the International Neural Network Society·Zhaohui LiXiaoli Li
Feb 16, 2016·Nature Neuroscience·Nikolaos KaralisCyril Herry
Feb 24, 2016·Frontiers in Systems Neuroscience·Brett L FosterYuri B Saalmann
Jan 19, 2016·Frontiers in Systems Neuroscience·André M Bastos, Jan-Mathijs Schoffelen
Sep 19, 2012·Progress in Biophysics and Molecular Biology·Matej PlankarIgor Jerman
Mar 5, 2016·Neural Computation·Vinay ShirhattiSupratim Ray
May 12, 2012·Computational and Mathematical Methods in Medicine·Junfeng SunShanbao Tong
Jun 23, 2015·Journal of Neurotrauma·Darrin J LeeKiarash Shahlaie
Dec 8, 2011·Annals of the New York Academy of Sciences·Cyriel M A PennartzMartin Vinck
Apr 14, 2015·Human Brain Mapping·Roemer van der MeijEric Maris
Apr 4, 2016·Neurobiology of Learning and Memory·Hemi A I MalkkiCyriel M A Pennartz
Aug 20, 2015·Cerebral Cortex·Simon KornblithEarl K Miller
Aug 19, 2015·Current Biology : CB·Ayelet Nina LandauPascal Fries
Feb 26, 2013·NeuroImage·Sergul AydoreRichard M Leahy
Jun 9, 2015·Nature·Timothy SpellmanJoshua A Gordon
Oct 11, 2011·Neuron·Shigeyoshi Fujisawa, György Buzsáki
Mar 26, 2016·NeuroImage·Meng HuHualou Liang
Jul 17, 2012·Current Biology : CB·Maria WimberSimon Hanslmayr
Jul 17, 2012·NeuroImage·Andrea ZaunerWolfgang Klimesch
Oct 29, 2013·NeuroImage·Alexandre GramfortMatti S Hämäläinen
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Oct 6, 2014·Current Opinion in Neurobiology·Supratim Ray
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Nov 21, 2012·Journal of Neuroscience Methods·Kyle Q LepageRobert Desimone
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Feb 24, 2015·Frontiers in Physiology·Annika Lüttjohann, Gilles van Luijtelaar
Feb 21, 2014·Proceedings of the National Academy of Sciences of the United States of America·Nicolas M BrunetPascal Fries
May 18, 2016·Journal of Neuroscience Methods·Zhaohui LiXiaoli Li

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