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Measuring asymmetric temporal interdependencies in simulated and biological networks
dc.contributor.authorDzakpasu, Rhondaen_US
dc.contributor.authorPatel, Kinjalen_US
dc.contributor.authorRobinson, Natalliaen_US
dc.contributor.authorHarrington, Melissa A.en_US
dc.contributor.authorŻochowski, Michałen_US
dc.date.accessioned2011-11-15T16:10:43Z
dc.date.available2011-11-15T16:10:43Z
dc.date.issued2006-12en_US
dc.identifier.citationDzakpasu, Rhonda; Patel, Kinjal; Robinson, Natallia; Harrington, Melissa A.; Żochowski, Michał (2006). "Measuring asymmetric temporal interdependencies in simulated and biological networks." Chaos 16(4): 043121-043121-8. <http://hdl.handle.net/2027.42/87883>en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/87883
dc.description.abstractWe use a newly developed metric to characterize asymmetric temporal interdependencies in networks of coupled dynamical elements. We studied the formation of temporal ordering in a system of coupled Rössler oscillators for different connectivity ratios and network topologies and also applied the metric to investigate the functional structure of a biological network (cerebral ganglia of Helix snail). In the former example we show how the local ordering evolves to the global one as a function of structural parameters of the network, while in the latter we show spontaneous emergence of functional interdependence between two groups of electrodes.en_US
dc.publisherThe American Institute of Physicsen_US
dc.rights© The American Institute of Physicsen_US
dc.titleMeasuring asymmetric temporal interdependencies in simulated and biological networksen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelPhysicsen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Physics University of Michigan, Ann Arbor, Michigan 48109en_US
dc.contributor.affiliationumDepartment of Physics and Biophysics Research Division University of Michigan, Ann Arbor, Michigan 48109en_US
dc.contributor.affiliationotherDepartment of Biological Sciences Delaware State University, Dover, Delaware 19901en_US
dc.identifier.pmid17199399en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/87883/2/043121_1.pdf
dc.identifier.doi10.1063/1.2401130en_US
dc.identifier.sourceChaosen_US
dc.identifier.citedreferenceC. Deransart, B. Hellwig, M. Heupel-Reuter, J. F. Leger, D. Heck, and C. H. Lucking, Epilepsia 44, 1513 (2003).en_US
dc.identifier.citedreferenceR. Ferri, C. J. Stam, B. Lanuzza, F. I. Cosentino, M. Elia, S. A. Musumeci, and G. Pennisi, Clin. Neurophysiol. 115, 1202 (2004).en_US
dc.identifier.citedreferenceW. Singer, Neuron 24, 49 (1999).en_US
dc.identifier.citedreferenceC. M. Gray, Neuron 24, 31 (1999).en_US
dc.identifier.citedreferenceC. von der Malsburg, Ber. Bunsenges. Phys. Chem. 89, 703 (1985).en_US
dc.identifier.citedreferenceF. Varela, J-P. Lachaux, E. Rodriguez, and J. Martinerie, Nat. Rev. Neurosci. 2, 229 (2001).en_US
dc.identifier.citedreferenceM. Stopfer, S. Bhagavan, B. H. Smith, and G. Laurent, Nature (London) 390, 70 (1997).en_US
dc.identifier.citedreferenceG. Q. Bi and M. M. Poo, Nature (London) 401, 792 (1998).en_US
dc.identifier.citedreferenceB. H. Singer, M. Derchansky, P. L. Carlen, and Michal Żochowski, Phys. Rev. E 73, 021910 (2006).en_US
dc.identifier.citedreferenceE. N. Brown, M. Okatan, and M. A. Wilson, Neural Comput. 17, 1927 (2005).en_US
dc.identifier.citedreferenceP. A. W. Lewis and D. R. Cox, Proceedings, Sixth Berkeley Symposium on Probability and Mathematical Statistics, 1972, Vol. 3, pp. 401–448.en_US
dc.identifier.citedreferenceM. S. Bartlett, An Introduction to Stochastic Processes, 2nd ed. (Cambridge University Press, Cambridge, 1966).en_US
dc.identifier.citedreferenceG. P. Moore, D. H. Perkel, and G. L. Gerstein, Biophys. J. 7, 419 (1967).en_US
dc.identifier.citedreferenceD. H. Perkel and G. L. Gerstein, Science 164, 828 (1969).en_US
dc.identifier.citedreferenceD. R. Brillinger, Ann. Probab. 3, 909 (1975).en_US
dc.identifier.citedreferenceL. Lin, R. Osan, S. Shoham, W. Jin, W. Zuo, and J. Z. Tsien, Proc. Natl. Acad. Sci. U.S.A. 102, 6125 (2005).en_US
dc.identifier.citedreferenceL. Abbott and E. Salinas, J. Comput. Neurosci. 1, 89 (1994).en_US
dc.identifier.citedreferenceK. Zhang, I. Ginsburg, B. L. McNaughton, and T. J. Sejnowski, J. Neurophysiol. 79, 1017 (1998).en_US
dc.identifier.citedreferenceA. F. Karr, E. S. Chornoboy, and L. P. Schramm, Biol. Cybern. 59, 265 (1988).en_US
dc.identifier.citedreferenceI. Baruchi and E. Ben-Jacob, Neuroinformatics 2, 333 (2004).en_US
dc.identifier.citedreferenceM. Żochowski and R. Dzakpasu, “J. Phys. A 37, 3823 (2004).en_US
dc.identifier.citedreferenceR. Dzakpasu and M. Żochowski, Physica D 208, 115 (2005).en_US
dc.identifier.citedreferenceM. S. Baptista, T. Pereira, J. C. Sartorelli, I. L. Caldas, and J. Kurths, Physica D 212, 216 (2005).en_US
dc.identifier.citedreferenceM. S. Baptista and J. Kurths, Phys. Rev. E 72, 045202 (2005).en_US
dc.identifier.citedreferenceJ. Brea, D. F. Russell, and A. B. Neiman, Chaos 16, 026111 (2006).en_US
dc.identifier.citedreferenceT. Schreiber and A. Kaiser, Int. J. Bifurcation Chaos Appl. Sci. Eng. 14, 1987 (2004).en_US
dc.identifier.citedreferenceR. Quian Quiroga, T. Kreuz, and P. Grassberger, Phys. Rev. E, 66, 041904, 2002.en_US
dc.identifier.citedreferenceM. G. Rosenblum, A. S. Pikovsky, and J. Kurths, Phys. Rev. Lett. 78, 4193 (1997).en_US
dc.identifier.citedreferenceM. G. Rosenblum, A. S. Pikovsky, and J. Kurths, Phys. Rev. Lett. 76, 1804 (1996).en_US
dc.identifier.citedreferenceD. Pazo, A. M. Zaks, and J. Kurths, Chaos 13, 309 (2003).en_US
dc.identifier.citedreferenceG. V. Osipov, A. S. Pikovsky, M. G. Rosenblum, and J. Kurths, Phys. Rev. E 55, 2353 (1997).en_US
dc.identifier.citedreferenceV. Braitenberg and A. Schüz, Cortex: Statistics and Geometry of Neuronal Connectivity (Springer-Verlag, Berlin, 1998).en_US
dc.identifier.citedreferenceD. J. Watts and S. H. Strogatz, Nature (London) 393, 440 (1998).en_US
dc.identifier.citedreferenceI. Belykh, V. Belykh, K. Nevidin, and M. Hasler, Chaos 13, 165 (2003).en_US
dc.identifier.citedreferenceA. Gelperin and D. W. Tank, Nature (London) 345, 437 (1990).en_US
dc.identifier.citedreferenceD. Kleinfeld, K. R. Delaney, M. S. Fee, J. A. Flores, D. W. Tank, and A. Gelperin, J. Neurophysiol. 72, 1402 (1994).en_US
dc.identifier.citedreferenceS. Kawahara, S. Toda, Y. Suzuki, and Y. Kirino, J. Exp. Biol. 200, 1851 (1997).en_US
dc.identifier.citedreferenceA. Gelperin, J. Exp. Biol. 202, 1855 (1999).en_US
dc.identifier.citedreferenceK. R. Delaney, A. Gelperin, M. S. Fee, J. A. Flores, R. Gervais, D. W. Tank, and D. Kleinfeld, Proc. Natl. Acad. Sci. U.S.A. 91, 669 (1994).en_US
dc.identifier.citedreferenceL. R. Rabiner and B. Gold, Theory and Application of Digital Signal Processing (Prentice-Hall, Englewood Cliffs, NJ, 1975).en_US
dc.owningcollnamePhysics, Department of


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