  The study of dynamical systems defined on complex networks provides a natural
framework with which to investigate myriad features of neural dynamics, and has
been widely undertaken. Typically, however, networks employed in theoretical
studies bear little relation to the spatial embedding or connectivity of the
neural networks that they attempt to replicate. Here, we employ detailed
neuroimaging data to define a network whose spatial embedding represents
accurately the folded structure of the cortical surface of a rat and
investigate the propagation of activity over this network under simple
spreading and connectivity rules. By comparison with standard network models
with the same coarse statistics, we show that the cortical geometry influences
profoundly the speed propagation of activation through the network. Our
conclusions are of high relevance to the theoretical modelling of epileptic
seizure events, and indicate that such studies which omit physiological network
structure risk simplifying the dynamics in a potentially significant way.
