  Complex spatiotemporal patterns, called chimera states, consist of coexisting
coherent and incoherent domains and can be observed in networks of coupled
oscillators. The interplay of synchrony and asynchrony in complex brain
networks is an important aspect in studies of both brain function and disease.
We analyse the collective dynamics of FitzHugh-Nagumo neurons in complex
networks motivated by its potential application to epileptology and epilepsy
surgery. We compare two topologies: an empirical structural neural connectivity
derived from diffusion-weighted magnetic resonance imaging and a mathematically
constructed network with modular fractal connectivity. We analyse the
properties of chimeras and partially synchronized states, and obtain regions of
their stability in the parameter planes. Furthermore, we qualitatively simulate
the dynamics of epileptic seizures and study the influence of the removal of
nodes on the network synchronizability, which can be useful for applications to
epileptic surgery.
