Name
Abstract | ||
|---|---|---|
Previously, we developed two similar 3-variable models to explain the pattern of spontaneous rhythmic activity generated by the spinal cord of chick embryo. The models differ in the implementation of a slow depression variable, but each produces patterns of activity that qualitatively resemble experimental recordings. For both models, the ratio inter-episode interval/episode duration (i/d ratio) was too small compared to experiments. The introduction of a parameter representing the connectivity of the network has different effects on each model, therefore allowing them to be distinguished experimentally. Also, the model that seems to better satisfy experimental constraints is able to generate a large i/d ratio. |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1016/S0925-2312(99)00032-6 | Neurocomputing |
Keywords | Field | DocType |
Spontaneous activity,Synaptic depression,Excitatory network,Connectivity | Spinal cord,Pattern generation,Pattern recognition,Artificial intelligence,Rhythm,Mathematics | Journal |
Volume | ISSN | Citations |
26-27 | 0925-2312 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joël Tabak | 1 | 70 | 10.48 |
| Walter Senn | 2 | 66 | 10.79 |
| Michael J O'Donovan | 3 | 8 | 1.42 |
| John Rinzel | 4 | 459 | 219.68 |