  Activity in coupled systems is often oscillatory, for example, the firing
pattern of neuronal populations. Whereas these oscillations have been studied
predominantly in local circuits, here we show how the topology of large-scale
networks, leading to large feedback loops, influences oscillations in the
resting state. We find that the hierarchical modular organization of neuronal
networks supports distinct spectral patterns of neural rhythms similar to those
observed experimentally in different species such as rat and human. For
individual neurons, multiple peak frequencies with non-integer ratios between
subsequent peaks occurred. These ratios occurred both for models with the
spatial size of the rat as well as for the human brain. We argue that the
potential influence of longer connections, and thus longer delays, are balanced
by a reduced number of long-distance connections in larger brain networks. In
conclusion, we show that a hierarchical neuronal network provides a scalable
backbone for multiple brain rhythms. This structural backbone could complement
well-studied regional and cellular mechanisms for the generation or prevention
of rhythms.
