Name
Abstract | ||
|---|---|---|
Time delays are ubiquitous in the nervous system. Empirical findings suggest that time delays are adapted when considering the synchronous activity of neurons. We introduce a framework for studying the dynamics of self-organized delay adaptation in systems which optimize coincidence of inputs. The framework comprises two families of delay adaptation mechanisms, delay shift and delay selection. For the important case of periodically modulated input we derive conditions for the existence and stability of solutions which constrain learning rules for reliable delay adaptation. Delay adaptation is also applicable in the case of several spatio-temporal neuronal input patterns. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1016/S0925-2312(00)00239-3 | Neurocomputing |
Keywords | Field | DocType |
Delay adaptation,Hebb rule,Learning,Spiking neurons | Control theory,Computer science,Nervous system,Artificial intelligence,Coincidence | Journal |
Volume | ISSN | Citations |
32-33 | 0925-2312 | 6 |
PageRank | References | Authors |
0.88 | 2 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christian W. Eurich | 1 | 103 | 22.51 |
| Klaus Pawelzik | 2 | 509 | 107.71 |
| Udo Ernst | 3 | 13 | 3.99 |
| Andreas Thiel | 4 | 16 | 2.76 |
| Jack D. Cowan | 5 | 527 | 529.18 |
| John G. Milton | 6 | 16 | 3.67 |