Volume 3 Supplement 1

Proceedings of the 1st International Workshop on Odor Spaces

Open Access

A spatiotemporal coding mechanism for background independent recognition of odors

  • Baranidharan Raman1
Flavour20143(Suppl 1):O14

DOI: 10.1186/2044-7248-3-S1-O14

Published: 16 April 2014

Sensory stimuli often evoke temporal patterns of spiking activity across a population of neurons in the early processing stages. These neural responses are considered a ‘temporal code’ if they change on a timescale that is different than the stimulus variations that caused them and when they convey useful information about the stimulus. A fundamental problem in sensory neuroscience is determining what stimulus-specific information is encoded by dynamic patterns of ensemble neural activity and whether this information is behaviorally relevant. Furthermore, since the same stimulus can be encountered in a variety of ways in natural environments, what attributes of the spatiotemporal population responses are invariant to any or all such variations in stimulus features?

In this talk, I will describe how dynamic processing of odor signals allows an invertebrate olfactory system to recognize odorants in a background-independent manner. I will first discuss how freshly introduced odors are received by olfactory receptor neurons in the locust antenna (Schistocerca americana), and then show how the generated sensory input is transformed, step-by-step, into background-invariant neural representations. I will conclude with a brief discussion of correlations between temporally patterned neural activity and behavioral performance of locusts in an odor recognition task.

Authors’ Affiliations

Department of Biomedical Engineering, Washington University


© Raman; licensee BioMed Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.