| Dynamics of random networks: connectivity and first order phase transitions, arxiv.org, Condensed Matter (2009) | |||||||||||||||
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| The connectivity of individual neurons of large neural networks determine both the steady state activity of the network and its answer to external stim-ulus. Highly diluted random networks have zero activity. We show that increasing the network connectivity the activity changes discontinuously from zero to a finite value as a critical value in the connectivity is reached. Theo-retical arguments and extensive numerical simulations indicate that the origin of this discontinuity in the activity of random networks is a first order phase transition from an inactive to an active state as the connectivity of the net-work is increased. 1 Typeset using REVTEX Networks of neuron type threshold elements have generated a lot of interest lately, mo-tivated by their potential for reproducing neurobiological processes and understanding the generic mechanism governing basic brain functions. Most of the studied models deal either | |||||||||||||||
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