| Title | The emergence of connectivity in neuronal networks: From bootstrap percolation to auto-associative memory |
| Authors | Tatyana Turova |
| Alternative Location | http://dx.doi.org/10.1016/j..., Restricted Access |
| Publication | Brain Research |
| Year | 2012 |
| Volume | 1434 |
| Pages | 277 - 284 |
| Document type | Article |
| Status | Published |
| Quality controlled | Yes |
| Language | eng |
| Publisher | Elsevier Science BV |
| Abstract English | We consider a random synaptic pruning in an initially highly interconnected network. It is proved that a random network can maintain a self-sustained activity level for some parameters. For such a set of parameters a pruning is constructed so that in the resulting network each neuron/node has almost equal numbers of in- and out-connections. It is also shown that the set of parameters which admits a self-sustained activity level is rather small within the whole space of possible parameters. It is pointed out here that the threshold of connectivity for an auto-associative memory in a Hopfield model on a random graph coincides with the threshold for the bootstrap percolation on the same random graph. It is argued that this coincidence reflects the relations between the auto-associative memory mechanism and the properties of the underlying random network structure. This article is part of a Special Issue entitled "Neural Coding". (C) 2011 Elsevier B.V. All rights reserved. |
| Keywords | Integrate-and-fire network, Random graph, Storage capacity, Percolation, |
| ISBN/ISSN/Other | ISSN: 0006-8993 |
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