Many complex neuronal circuits have been shown to display nonrandom features in their connectivity. However, the functional impact of nonrandom network topologies in neurological diseases is not well understood. The dentate gyrus is an excellent circuit in which to study such functional implications because proepileptic insults cause its structure to undergo a number of specific changes in both humans and animals, including the formation of previously nonexistent granule cell-to-granule cell recurrent excitatory connections. Here, we use a large-scale, biophysically realistic model of the epileptic rat dentate gyrus to reconnect the aberrant recurrent granule cell network in four biologically plausible ways to determine how nonrandom connectivity promotes hyperexcitability after injury. We find that network activity of the dentate gyrus is quite robust in the face of many major alterations in granule cell-to-granule cell connectivity. However, the incorporation of a small number of highly interconnected granule cell hubs greatly increases network activity, resulting in a hyperexcitable, potentially seizure-prone circuit. Our findings demonstrate the functional relevance of nonrandom microcircuits in epileptic brain networks, and they provide a mechanism that could explain the role of granule cells with hilar basal dendrites in contributing to hyperexcitability in the pathological dentate gyrus.basal dendrite ͉ computational model ͉ epilepsy ͉ granule cell ͉ scale-free N umerous studies have indicated that connectivity in a wide variety of neural systems exhibits highly nonrandom characteristics. For example, in the nervous system of the Caenorhabditis elegans worm, of which the complete structure has been described (1), it was shown that a number of local connectivity patterns (network motifs) are over-or underrepresented compared with what would be present in a random network (2-4). Furthermore, computational analysis has indicated that the dynamic properties of these network motifs could contribute to their relative abundance, closely tying functional properties to the structural network (5). Nonrandom connectivity features have been discovered in mammalian cortices as well (6-10). Such networks exhibit high degrees of local clustering with short path lengths [small-world topology (11-13)], power law distributions of connectivity [scale-free topology (11,13,14)], and nonrandom distributions of connection strengths (8). Additionally, it has been shown that connection probabilities demonstrate fine-scale specificity that depends both on neuronal type and the presence or absence of other connections in the network (15, 16).Although nonrandom structural features of neuronal networks have been of great interest recently, and the role of some of these features in network dynamics and information processing has been investigated (5,(17)(18)(19), the contribution of nonrandom microcircuit connectivity to the functional properties of large, complex brain regions, particularly in epilepsy, remains poorly understood. The...