Event Abstract Back to Event Measuring Partial Phase Locking Value to Detect Synchronization in Multivariate Gaussian Systems Sergul Aydore1*, Dimitrios Pantazis2 and Richard Leahy1 1 University of Southern California, Signal and Image Processing Institute, United States 2 Massachusetts Institute of Technology, McGovern Institute for Brain Research, United States The phase locking value (PLV) is a widely used measure of brain synchronization and is often used to detect cortical networks that play a major role in cognitive integration. A limitation of pairwise PLV analysis is that it does not differentiate between direct and indirect interactions in a multiple-node network. Schelter et al [1] have investigated inversion of the matrix of pairwise PLVs to compute a partial phase locking value. This is analogous to inversion of cross-correlation and cross-spectral matrices to compute partial correlations and partial coherence, respectively. An alternative approach was proposed by Cadieu et al [2] who develop a multiple-node phase coupling model based on multivariate extension of the Von Mises distribution. Conditional phase coupling measures can be determined in a straightforward manner from this model. Both of these approaches use phase only information and implicitly assume the statistical independence between amplitude and phase in the signals being analyzed. We consider the multidimensional circular Gaussian model and show that phase and amplitude coupling are not independent. As a result, the associated phase-coupling distribution requires marginalization with respect to amplitude. Based on this analysis we derive an analytical expression for PLV and partial PLV. Not surprisingly, these expressions are able to accurately reveal phase coupling in simulated Gaussian data. However, we also applied these measures to data generated using coupled Roessler oscillators and compared the estimated coupling values with those determined using Cadieu's multivariate model [2] and Schelter's partial PLV method [1]. As illustrated in Fig. 1, even for this nonlinear system, the PLV based on a Gaussian model appears to outperform the alternatives in terms of either avoiding false positive interactions or through reduced estimator variance. [1] B. Schelter et al. (2006), ‘Partial phase synchronization for multivariate synchronizing system’, Phys. Rev. Lett., 96, 208103. [2] Cadieu, C. et al. (2010), ‘Phase coupling estimation from multivariate phase statistics’, Neural Computation, vol 22, no. 12, pp. 1-20. Figure 1 Keywords: computational neuroscience Conference: 4th INCF Congress of Neuroinformatics, Boston, United States, 4 Sep - 6 Sep, 2011. Presentation Type: Poster Presentation Topic: Computational neuroscience Citation: Aydore S, Pantazis D and Leahy R (2011). Measuring Partial Phase Locking Value to Detect Synchronization in Multivariate Gaussian Systems. Front. Neuroinform. Conference Abstract: 4th INCF Congress of Neuroinformatics. doi: 10.3389/conf.fninf.2011.08.00063 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 17 Oct 2011; Published Online: 19 Oct 2011. * Correspondence: Dr. Sergul Aydore, University of Southern California, Signal and Image Processing Institute, Los Angeles, United States, sergul@usc.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Sergul Aydore Dimitrios Pantazis Richard Leahy Google Sergul Aydore Dimitrios Pantazis Richard Leahy Google Scholar Sergul Aydore Dimitrios Pantazis Richard Leahy PubMed Sergul Aydore Dimitrios Pantazis Richard Leahy Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.