@ARTICLE{10.3389/fncom.2012.00050, AUTHOR={Garcia, Guadalupe and Lesne, Annick and Hütt, Marc-Thorsten and Hilgetag, Claus}, TITLE={Building Blocks of Self-Sustained Activity in a Simple Deterministic Model of Excitable Neural Networks}, JOURNAL={Frontiers in Computational Neuroscience}, VOLUME={6}, YEAR={2012}, URL={https://www.frontiersin.org/articles/10.3389/fncom.2012.00050}, DOI={10.3389/fncom.2012.00050}, ISSN={1662-5188}, ABSTRACT={Understanding the interplay of topology and dynamics of excitable neural networks is one of the major challenges in computational neuroscience. Here we employ a simple deterministic excitable model to explore how network-wide activation patterns are shaped by network architecture. Our observables are co-activation patterns, together with the average activity of the network and the periodicities in the excitation density. Our main results are: (1) the dependence of the correlation between the adjacency matrix and the instantaneous (zero time delay) co-activation matrix on global network features (clustering, modularity, scale-free degree distribution), (2) a correlation between the average activity and the amount of small cycles in the graph, and (3) a microscopic understanding of the contributions by 3-node and 4-node cycles to sustained activity.} }