HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Full Text Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Huerta, R. Articles by Rabinovich, M. I. Search for Related Content PubMed PubMed Citation Articles by Huerta, R. Articles by Rabinovich, M. I.

Learning Classification in the Olfactory System of Insects

rhuerta{at}ucsd.edu, Institute for Nonlinear Science, University of California San Diego, La Jolla CA 92093-0402, U.S.A., and GNB. Escuela Técnica Superior de Informática, Universidad Autónoma de Madrid, 28049 Madrid, Spain

Thomas Nowotny

tnowotny{at}ucsd.edu, Institute for Nonlinear Science, University of California San Diego, La Jolla CA 92093-0402, U.S.A.

Marta García-Sanchez

m.garcia{at}uam.es, GNB. Escuela Técnica Superior de Informática, Universidad Autónoma de Madrid, 28049 Madrid, Spain, and Institute for Nonlinear Science, University of California San Diego, La Jolla CA 92093-0402, U.S.A.

H. D. I. Abarbanel

hdia{at}jacobi.ucsd.edu, Institute for Nonlinear Science, University of California San Diego, La Jolla CA 92093-0402, U.S.A., and Department of Physics and Marine Physical Laboratory, Scripps Institute of Oceanography, University of California San Diego, La Jolla, CA 92093-0402, U.S.A.

M. I. Rabinovich

mrabinovich{at}ucsd.edu, Institute for Nonlinear Science, University of California San Diego, La Jolla CA 92093-0402, U.S.A.

We propose a theoretical framework for odor classification in the olfactory system of insects. The classification task is accomplished in two steps. The first is a transformation from the antennal lobe to the intrinsic Kenyon cells in the mushroom body. This transformation into a higher-dimensional space is an injective function and can be implemented without any type of learning at the synaptic connections. In the second step, the encoded odors in the intrinsic Kenyon cells are linearly classified in the mushroom body lobes. The neurons that perform this linear classification are equivalent to hyperplanes whose connections are tuned by local Hebbian learning and by competition due to mutual inhibition. We calculate the range of values of activity and size of the network required to achieve efficient classification within this scheme in insect olfaction. We are able to demonstrate that biologically plausible control mechanisms can accomplish efficient classification of odors.

This article has been cited by other articles:

				D. C. Sterratt and D. Willshaw Inhomogeneities in Heteroassociative Memories with Linear Learning Rules Neural Comput., February 1, 2008; 20(2): 311 - 344. [Abstract] [Full Text] [PDF]

				G. C. Turner, M. Bazhenov, and G. Laurent Olfactory Representations by Drosophila Mushroom Body Neurons J Neurophysiol, February 1, 2008; 99(2): 734 - 746. [Abstract] [Full Text] [PDF]

				M. Schmuker and G. Schneider Processing and classification of chemical data inspired by insect olfaction PNAS, December 18, 2007; 104(51): 20285 - 20289. [Abstract] [Full Text] [PDF]

				R. A. Jortner, S. S. Farivar, and G. Laurent A Simple Connectivity Scheme for Sparse Coding in an Olfactory System J. Neurosci., February 14, 2007; 27(7): 1659 - 1669. [Abstract] [Full Text] [PDF]