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Towards Google matrix of brain

Published 24 Feb 2010 in cond-mat.dis-nn, cs.NI, nlin.AO, physics.soc-ph, q-bio.NC, and q-bio.TO | (1002.4583v2)

Abstract: We apply the approach of the Google matrix, used in computer science and World Wide Web, to description of properties of neuronal networks. The Google matrix ${\bf G}$ is constructed on the basis of neuronal network of a brain model discussed in PNAS {\bf 105}, 3593 (2008). We show that the spectrum of eigenvalues of ${\bf G}$ has a gapless structure with long living relaxation modes. The PageRank of the network becomes delocalized for certain values of the Google damping factor $\alpha$. The properties of other eigenstates are also analyzed. We discuss further parallels and similarities between the World Wide Web and neuronal networks.

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