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Criticality of spreading dynamics in hierarchical cluster networks without inhibition

Lookup NU author(s): Professor Marcus Kaiser



An essential requirement for the representation of functional patterns in complex neural networks, such as the mammalian cerebral cortex, is the existence of stable network activations within a limited critical range. In this range, the activity of neural populations in the network persists between the extremes of quickly dying out, or activating the whole network. The nerve fibre network of the mammalian cerebral cortex possesses a modular organization extending across several levels of organization. Using a basic spreading model without inhibition, we investigated how functional activations of nodes propagate through such a hierarchically clustered network. The simulations demonstrated that persistent and scalable activations could be produced in clustered networks, but not in random networks of the same size. Moreover, the parameter range yielding critical activations was substantially larger in hierarchical cluster networks than in smallworld networks of the same size. These findings indicate that a hierarchical cluster architecture may provide the structural basis for the stable and diverse functional patterns observed in cortical networks. © IOP Publishing Ltd and Deutsche Physikalische Gesellschaft.

Publication metadata

Author(s): Kaiser M, Gorner M, Hilgetag CC

Publication type: Article

Publication status: Published

Journal: New Journal of Physics

Year: 2007

Volume: 9

Issue: 110

Print publication date: 02/05/2007

ISSN (electronic): 1367-2630

Publisher: Institute of Physics Publishing Ltd.


DOI: 10.1088/1367-2630/9/5/110


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