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arXiv · 1610.02309

Measuring directed interactions using cellular neural networks with complex connection topologies

Henning Dickten·Christian E. Elger·Klaus Lehnertz
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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.

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Henning Dickten, Christian E. Elger, Klaus Lehnertz. 2016-10-06. Measuring directed interactions using cellular neural networks with complex connection topologies. https://arxiv.org/abs/1610.02309

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