Abstract
The dynamical random graphs associated with a certain class of biological neural networks are introduced and studied. We describe the phase diagram revealing the parameters of a single neuron and of the synaptic strengths which allow formation of the stable strongly connected large groups of neurons. It is shown that the cycles are the most stable structures when the Hebb rule is implemented into the dynamics of the network of excitatory neurons. We discuss the role of cycles for the synchronization of the neuronal activity. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.
| Original language | English |
|---|---|
| Pages (from-to) | 281-286 |
| Journal | BioSystems |
| Volume | 67 |
| Issue number | 1-3 |
| DOIs | |
| Publication status | Published - 2002 |
Subject classification (UKÄ)
- Probability Theory and Statistics
Free keywords
- random graph process
- phase transition
- attractor
- neural network