AN OLFACTORY RECOGNITION MODEL-BASED ON SPATIOTEMPORAL ENCODING OF ODOR QUALITY IN THE OLFACTORY-BULB

In order to study the problem how the olfactory neural system processe s the odorant molecular information for constructing the olfactory ima ge of each object, we present a dynamic model of the olfactory bulb co nstructed on the basis of well-established experimental and theoretica l results. The information relevant to a single odor, i.e. its constit uent odorant molecules and their mixing ratios, are encoded into a spa tio-temporal pattern of neural activity in the olfactory bulb, where t he activity pattern corresponds to a limit cycle attractor in the mitr al cell network. The spatio-temporal pattern consists of a temporal se quence of spatial firing patterns: each constituent molecule is encode d into a single spatial pattern, and the order of magnitude of the mix ing ratio is encoded into the temporal sequence. The formation of a li mit cycle attractor under the application of a novel odor is carried o ut based on the intensity-to-time-delay encoding scheme. The dynamic s tate of the olfactory bulb, which has learned many odors, becomes a ra ndomly itinerant state in which the current firing state of the bulb i tinerates randomly among limit cycle attractors corresponding to the l earned odors. The recognition of an odor is generated by the dynamic t ransition in the network from the randomly itinerant state to a limit cycle attractor state relevant to the odor, where the transition is in duced by the short-term synaptic changes made according to the Hebbian rule under the application of the odor stimulus.