Revealing Network Connectivity From Dynamics
Disordered Systems and Neural Networks
2009-11-11 v1 Neurons and Cognition
Abstract
We present a method to infer network connectivity from collective dynamics in networks of synchronizing phase oscillators. We study the long-term stationary response to temporally constant driving. For a given driving condition, measuring the phase differences and the collective frequency reveals information about how the oscillators are interconnected. Sufficiently many repetitions for different driving conditions yield the entire network connectivity from measuring the dynamics only. For sparsely connected networks we obtain good predictions of the actual connectivity even for formally under-determined problems.
Cite
@article{arxiv.cond-mat/0610188,
title = {Revealing Network Connectivity From Dynamics},
author = {Marc Timme},
journal= {arXiv preprint arXiv:cond-mat/0610188},
year = {2009}
}
Comments
10 pages, 4 figures