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Odor recognition and segmentation by a model olfactory bulb and cortex

Zhaoping, L; Hertz, J; (2000) Odor recognition and segmentation by a model olfactory bulb and cortex. Network: Computation in Neural Systems , 11 (1) 83 - 102. 10.1088/0954-898X/11/1/305.

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Abstract

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.

Type:Article
Title:Odor recognition and segmentation by a model olfactory bulb and cortex
DOI:10.1088/0954-898X/11/1/305
Additional information:Imported via OAI, 7:29:01 24th Apr 2008
UCL classification:UCL > School of BEAMS > Faculty of Engineering Science > Computer Science

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