@inbook{f19a7ef6facb4777bdc79f0c4668a2d1,
title = "Structural Characterization of Networks Using the Cat Cortex as an Example",
abstract = "In this chapter, Graph Theory will be introduced using cat corticocortical connectivity data as an example. Distinct graph measures will be summarized and examples of their usage shown, as well as hints about the kind of information one can obtain from them. Special attention will be paid to conflicting points in graph theory that often generate confusion and some algorithmic tips will be provided. It is not our aim to introduce graph theory to the reader in a detailed manner, nor to reproduce what other authors have written in several extensive reviews (see Sect. 3.8). Some of the examples placed in this chapter referring to the cat cortex are unpublished material and thus, not to be regarded as established scientific results. Otherwise, references will be provided.",
keywords = "Random Graph, Degree Distribution, Random Network, Real Network, Adjacency List",
author = "Gorka Zamora-L{\'o}pez and Changsong ZHOU and J{\"u}rgen Kurths",
note = "Copyright: Copyright 2008 Elsevier B.V., All rights reserved.",
year = "2007",
doi = "10.1007/978-3-540-73159-7_3",
language = "English",
isbn = "9783540731580",
series = "Understanding Complex Systems",
publisher = "Springer Berlin Heidelberg",
pages = "77--106",
editor = "Peter Graben and Marco Thiel and Changsong Zhou and Jurgen Kurths",
booktitle = "Lectures in Supercomputational Neurosciences",
edition = "1st",
}