We present a model of an olfactory system that performs odor segmentation. Based on the anatomy and physiology of natural olfactory systems, it consists of a pair of coupled modules, bulb and cortex. The bulb encodes the odor inputs as oscillating patterns. The cortex functions as an associative memory: When the input from the bulb matches a pattern stored in the connections between its units, the cortical units resonate in an oscillatory pattern characteristic of that odor. Further circuitry transforms this oscillatory signal to a slowly-varying feedback to the bulb. This feedback implements olfactory segmentation by suppressing the bulbar response to the pre-existing odor, thereby allowing subsequent odors to be singled out for recognition.
Cite
@article{arxiv.cond-mat/0002289,
title = {Odor recognition and segmentation by a model olfactory bulb and cortex},
author = {Zhaoping Li and John Hertz},
journal= {arXiv preprint arXiv:cond-mat/0002289},
year = {2007}
}