Organization of excitable dynamics in hierarchical networks - Theoretical analysis, numerical simulation and application to neuroscience

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Hierarchy is an obvious, but only minimally understood feature of biological, and particularly neural, networks. We will characterize different types of hierarchical networks and identify the topological parameters that most strongly shape their functional dynamics. Moreover, we will determine which of the parameters are invariant to coarse- and fine-graining of the networks due to their hierarchical structure, and investigate how different excitable mechanisms at the node level affect the global network dynamics. For a large and biologically important class of excitable networks, we thus want to obtain a deep theoretical understanding of how network topology and dynamical processes interact.