Abstract
A synaptic update rule for learning in networks of spiking neurons was presented. It was shown that irregular spiking similar to that observed in biological neurons could be used as the basis for a learning rule. The learning rule was derived based on a special class of model networks in which neurons fire spike trains. The learning was found to be compatible with forms of synaptic dynamics.
| Original language | English (US) |
|---|---|
| Article number | 041909 |
| Pages (from-to) | 041909-1-041909-10 |
| Journal | Physical Review E - Statistical, Nonlinear, and Soft Matter Physics |
| Volume | 69 |
| Issue number | 4 1 |
| State | Published - Apr 2004 |
All Science Journal Classification (ASJC) codes
- Statistical and Nonlinear Physics
- Statistics and Probability
- Condensed Matter Physics