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Title: Encoding of odour blends in the moth antennal lobe
Author: Chong, Kwok Ying
ISNI:       0000 0001 3547 4036
Awarding Body: University of Leicester
Current Institution: University of Leicester
Date of Award: 2007
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Olfaction is a vital sense that informs moths of their environment, and as such moths are adept at chemical sensing. Natural odours are often complex mixtures of different compounds. Thus, odour components can interact along the olfactory pathway in a nonlinear fashion such that the mixture is not perceived simply as the sum of its components. Here an investigation is made into possible nonlinear interactions in the olfactory system of moths at two stages along the olfactory pathway. These are the input to and the output from the antennal lobe, the region of the insect brain responsible for the first neural processing of odour information.;The input to the antennal lobes is the neural representation of odours carried by the receptor neurons. By use of a calcium sensitive dye, this activity was observed optically as odour-evoked changes in Ca2+ concentration in the moth Spodoptera littoralis. This reveals the input pattern to functionally distinct neuropil in the antennal lobes, the so-called glomeruli. Such a calcium imaging analysis requires the identification of the glomeruli, and a novel method was developed to facilitate the automatic identification of olfactory glomeruli. By applying unsupervised clustering analysis to sets of calcium images, glomeruli were functionally identified. Binary odour blend responses were then analysed for nonlinear interactions, but no strong interactions were found.;The output from the antennal lobe, the projection neuron responses, was assessed by computational models. It was demonstrated in pheromone processing models that a spatiotemporal odour code is better able to encode for blend ratios than a spatial code. And it was shown that a spatiotemporal general odour model produces nonlinear component interactions, despite the data-motivated input having none.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available