Modelling efficiency in insect olfactory information processing

Abstract

The olfactory system of insects is essential for the search of food and mates, and weak signals can be detected, amplified and discriminated in a fluctuating environment. The olfactory system also allows for learning and recall of odour memories. Based on anatomical, physiological, and behavioural data from the olfactory system of insects, we have developed a cross-scale dynamical neural network model to simulate the presentation, amplification and discrimination of host plant odours and sex pheromones. In particular, we model how the spatial and temporal patterns of the odour information emerging in the glomeruli of the antennal lobe (AL) rely on the glomerular morphology, the connectivity and the complex dynamics of the AL circuits. We study how weak signals can be amplified, how different odours can be discriminated, based on stochastic (resonance) dynamics and the connectivity of the network. We further investigate the spatial and temporal coding of sex pheromone components and plant volatile compounds, in relation to the glomerular structure, arborizing patterns of the projection neurons (PNs) and timing patterns of the neuronal spiking activity. (C) 2006 Elsevier Ireland Ltd. All rights reserved

Keywords

Olfaction; Antennal lobe; Oscillations; Noise; Amplification; Discrimination; Spatio-temporal coding

Published in

BioSystems
2007, volume: 89, number: 1-3, pages: 236-243
Publisher: ELSEVIER SCI LTD

SLU Authors

• Liljenström, Hans

  • Department of Energy and Technology, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Horticulture
Environmental Sciences and Nature Conservation
Agricultural Science

Publication identifier

• DOI: https://doi.org/10.1016/j.biosystems.2006.04.021

Permanent link to this page (URI)

https://res.slu.se/id/publ/9742