Name
Abstract | ||
|---|---|---|
A mathematical model is given for describing activity dynamics, learning, and associative memory in the olfactory bulb. Numerical bifurcation analysis and the calculation of Lyapunov-exponents suggest that chaotic behavior only occurs in the case of strong excitatory coupling in the mitral layer. A Hebbian-type learning rule, supplemented with a nonlinear decay term and a selective decreasing term, is defined and analyzed. Slow learning modifies the bulbar activity dynamics hence it plays a crucial role in odor information processing. (C) 1995 John Wiley and Sons, Inc. |
Year | DOI | Venue |
|---|---|---|
1995 | 10.1002/int.4550100108 | INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS |
Field | DocType | Volume |
Attractor,Olfactory bulb,Neuroscience,Olfactory system,Information processing,Content-addressable memory,Nonlinear system,Learning rule,Artificial intelligence,Chaotic,Mathematics,Machine learning | Journal | 10 |
Issue | ISSN | Citations |
1 | 0884-8173 | 8 |
PageRank | References | Authors |
1.30 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| I. Aradi | 1 | 8 | 1.30 |
| G. Barna | 2 | 20 | 5.32 |
| peter erdi | 3 | 9 | 2.17 |
| T. Grobler | 4 | 25 | 8.04 |