Measuring directed interactions using cellular neural networks with complex connection topologies
Neurons and Cognition
2016-10-10 v1 Chaotic Dynamics
Cellular Automata and Lattice Gases
Abstract
We advance our approach of analyzing the dynamics of interacting complex systems with the nonlinear dynamics of interacting nonlinear elements. We replace the widely used lattice-like connection topology of cellular neural networks (CNN) by complex topologies that include both short- and long-ranged connections. With an exemplary time-resolved analysis of asymmetric nonlinear interdependences between the seizure generating area and its immediate surrounding we provide first evidence for complex CNN connection topologies to allow for a faster network optimization together with an improved approximation accuracy of directed interactions.
Cite
@article{arxiv.1610.02309,
title = {Measuring directed interactions using cellular neural networks with complex connection topologies},
author = {Henning Dickten and Christian E. Elger and Klaus Lehnertz},
journal= {arXiv preprint arXiv:1610.02309},
year = {2016}
}