Unknown

Dataset Information

Griffiths phases and localization in hierarchical modular networks.


ABSTRACT: We study variants of hierarchical modular network models suggested by Kaiser and Hilgetag [ Front. in Neuroinform., 4 (2010) 8] to model functional brain connectivity, using extensive simulations and quenched mean-field theory (QMF), focusing on structures with a connection probability that decays exponentially with the level index. Such networks can be embedded in two-dimensional Euclidean space. We explore the dynamic behavior of the contact process (CP) and threshold models on networks of this kind, including hierarchical trees. While in the small-world networks originally proposed to model brain connectivity, the topological heterogeneities are not strong enough to induce deviations from mean-field behavior, we show that a Griffiths phase can emerge under reduced connection probabiliti

SUBMITTER: Odor G 

PROVIDER: S-EPMC4585858 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature