Block Activity in Metric Neural Networks

The model of neural networks on the small-world topology, with metric (local and random connectivity) is investigated. The synaptic weights are random, driving the network towards a chaotic state for the neural activity. An ordered macroscopic neuron state is induced by a bias in the network connections. When the connections are mainly local, the network emulates a block-like structure. It is found that the topology and the bias compete to influence the network to evolve into a global or a block activity ordering, according to the initial conditions.

Authors:

• Mario Gonzalez
• David Dominguez
• Francisco B. Rodriguez

Keywords:

• Block attractor
• random interaction
• small world
• spin glass.

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