Chaos and learning in the olfactory bulb

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. © 1995 John Wiley & Sons, Inc.