Name
Abstract | ||
|---|---|---|
The noisy integrate-and-fire neuron is difficult to treat analytically. In particular, interspike-interval densities have to be computed numerically. We compare here the noisy integrate-and-fire neuron with three escape noise models for neuronal spiking which can be solved analytically. We show that an escape model with an instantaneous rate depending on the momentary membrane potential and its derivative provides an excellent approximation to the dynamics of the noisy integrate-and-fire model. We also demonstrate that the method of images does not yield reliable interspike-interval densities. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1016/S0925-2312(00)00167-3 | Neurocomputing |
Keywords | Field | DocType |
Integrate-and-fire neuron,Diffusion approximation,Hazard,Escape noise,Interspike-interval distribution | Artificial intelligence,Mathematics,Machine learning,Method of images,Heavy traffic approximation | Journal |
Volume | ISSN | Citations |
32-33 | 0925-2312 | 2 |
PageRank | References | Authors |
0.43 | 3 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hans E Plesser | 1 | 133 | 20.47 |
| Wulfram Gerstner | 2 | 2437 | 410.08 |