Abstract

Based on anatomical, physiological, and behavioral 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 odors and mating pheromones. In particular, we model how the dynamical patterns of the odor information emerging in the glomeruli of the antennal lobe (AL) rely on the interplay and synchronous oscillation of the ionic channel, the connectivity and the glomerular morphology of AL circuits. We study how weak signals can be amplified (sensitivity to individual odor molecules), how the noise can be suppressed and how different odors can be discriminated, based on stochastic resonance dynamics and the connectivity of the network. We further investigate the dose discrimination in a mixture in relation to the glomerular structure and timing patterns of the neuronal spiking activity. Here we summarize our model and main results in the following sections

Published in

Publisher: Vinnova

SLU Authors

• Liljenström, Hans

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

UKÄ Subject classification

Environmental Sciences related to Agriculture and Land-use


Permanent link to this page (URI)

https://res.slu.se/id/publ/7708