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11 - The construction of olfactory representations

Published online by Cambridge University Press:  14 August 2009

By
Thomas A. Cleland
Edited by
Christian Holscher  and
Matthias Munk
Christian Holscher
Affiliation:
University of Ulster
Matthias Munk
Affiliation:
Max-Planck-Institut für biologische Kybernetik, Tübingen
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Summary

Introduction

Sensory information progresses centrally from the primary sensors in the periphery to the central neural structures that derive relevant environmental information from these sensory data and determine appropriate physiological and behavioral responses. In this chapter, I present a general theory of early olfactory sensory processing in the primary olfactory epithelium and olfactory bulb (OB). The theory depicts olfactory sensory processing as a cascade of representations, each of which exhibits characteristic physical properties and is sampled by appropriate neural mechanisms in order to construct the subsequent representation. The primary olfactory representation is mediated by the activation pattern across the population of primary olfactory sensory neurons (OSNs) in the sensory epithelium. The secondary olfactory representation is similarly mediated by the activation pattern across the population of principal neurons immediately postsynaptic to the OSNs, known as mitral cells. (Mitral cell axons diverge dramatically, projecting to roughly ten different central structures within the brain; the resulting tertiary and subsequent olfactory representations are constructed outside the olfactory bulb and are not discussed at length herein.) The transformation between the primary and secondary representations is a robust, intricate, two-stage process that corrects for artefacts that can hinder the recognition of odor qualities, regulates stimulus selectivity, and transduces the underlying mechanics from a robust but costly rate-coding scheme on a slow respiratory (theta-band) timescale to a sparse dynamical representation operating on the beta- and gamma-band timescales and suitable for integration with other central neural processes.

Type
Chapter
Information
Information Processing by Neuronal Populations , pp. 247 - 280
Publisher: Cambridge University Press
Print publication year: 2008

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