Abstract
Neural networks in the brain display prominent hierarchical modular organization and complicated rhythmical oscillations. We systematically study the phenomenon of sustained activity in hierarchical modular networks, which are obtained by rewiring initially random networks. We find that a hierarchical modular architecture can generate sustained activity better than random networks. More importantly, the system can simultaneously support rhythmical oscillations and self-organized criticality, which are not present in the respective random networks. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity, allowing the system to take the advantages of both the sensitivity of critical state and predictability and timing of oscillations for efficient information processing.
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