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Network theory provides novel concepts that promise an improvedcharacterization of interacting dynamical systems. Within this framework,evolving networks can be considered as being composed of nodes, representingsystems, and of time-varying edges, representing interactions between thesesystems. This approach is highly attractive to further our understanding of thephysiological and pathophysiological dynamics in human brain networks. Indeed,there is growing evidence that the epileptic process can be regarded as alarge-scale network phenomenon. We here review methodologies for inferringnetworks from empirical time series and for a characterization of theseevolving networks. We summarize recent findings derived from studies thatinvestigate human epileptic brain networks evolving on timescales ranging fromfew seconds to weeks. We point to possible pitfalls and open issues, anddiscuss future perspectives.

Evolving networks in the human epileptic brain