A neural network model of the olfactory system of mice: computer simulation of the attention behavior of mice for some components in an odor

Recently, it was observed that mice could identify an odor by paying attention to only a few of its components. Further, it has been reported that each individual is attracted to different components of an odor. This behavior is referred to as “attention”; however, its mechanism has yet to be completely elucidated. In this paper, we first propose a novel artificial neural network model based on the biological structure of an olfactory system. Then a series of computer simulations of odorant discrimination are performed to evaluate the attention ability of the proposed model. Finally, we changed the connective weights between the neurons to simulate individual differences. The simulation results indicate that the inhibitory connections from the piriform cortex to the olfactory bulb may contribute to the individual differences observed in the behavioral experiment. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007