Parallel Olfactory Processing in the Honey Bee Brain: Odor Learning and Generalization under Selective Lesion of a Projection Neuron Tract

Frontiers in Integrative Neuroscience
Julie CarcaudJean Christophe Sandoz

Abstract

The function of parallel neural processing is a fundamental problem in Neuroscience, as it is found across sensory modalities and evolutionary lineages, from insects to humans. Recently, parallel processing has attracted increased attention in the olfactory domain, with the demonstration in both insects and mammals that different populations of second-order neurons encode and/or process odorant information differently. Among insects, Hymenoptera present a striking olfactory system with a clear neural dichotomy from the periphery to higher-order centers, based on two main tracts of second-order (projection) neurons: the medial and lateral antennal lobe tracts (m-ALT and l-ALT). To unravel the functional role of these two pathways, we combined specific lesions of the m-ALT tract with behavioral experiments, using the classical conditioning of the proboscis extension response (PER conditioning). Lesioned and intact bees had to learn to associate an odorant (1-nonanol) with sucrose. Then the bees were subjected to a generalization procedure with a range of odorants differing in terms of their carbon chain length or functional group. We show that m-ALT lesion strongly affects acquisition of an odor-sucrose association. However, lesi...Continue Reading

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Citations

Aug 31, 2017·Biological cybernetics·Irina SinakevitchBrian H Smith
Jul 26, 2017·Scientific Reports·Florian BastinJean-Christophe Sandoz
Sep 27, 2018·Journal of Comparative Physiology. A, Neuroethology, Sensory, Neural, and Behavioral Physiology·Harald Tichy, Maria Hellwig
May 23, 2017·Frontiers in Neural Circuits·Hidehiro WatanabeFumio Yokohari
Sep 10, 2020·Frontiers in Behavioral Neuroscience·HaDi MaBouDiLars Chittka
Apr 1, 2021·Cognitive Neurodynamics·Pamela B PyzzaDavid Cai

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Methods Mentioned

BETA
confocal microscopy
chip

Software Mentioned

IDL
ImageJ
STATISTICA

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