Odor interactions and learning in a model of the insect antennal lobe

We present a new model of insect antennal lobe in the form of integro-di-erential equation with short-range inhibition. The learning in the model modi0es the odor-dependent input by adding a term that is proportional to the 0ring rates of the network in the pre-learning steady state. We study the modi0cation of odor-induced spatial patterns (steady states) by combination of odors (binary mixtures) and learning. We show that this type of learning applied to the inhibitory network “increases the contrast” of the network’s spatial activity patterns. We identify pattern modi0cations that could underlie insect behavioral phenomena. c © 2004 Elsevier B.V. All rights reserved.