A Model for Chemosensory Reception

A new model for chemosensory reception is presented. The mathematical formulation of the reaction kinetics is transformed into an artificial neural network (ANN). The resulting feed-forward network provides a powerful means for parameter fitting by applying learning algorithms. The weights of the network corresponding to chemical parameters can be trained by presen(cid:173) ting experimental data. We demonstrate the simulation capabilities of the model with experimental data from honey bee chemosensory neurons.