A hierarchical network organization helps to retain comparable   oscillation patterns in rats and human-sized brains
  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. 
Marcus Kaiser
q-bio.NC