Citation
Tootoonian, Sina (2013) On the Analysis and Design of the Locust Olfactory System. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/MAWA-GD04. https://resolver.caltech.edu/CaltechTHESIS:12282012-075056374
Abstract
The ~ 830 projection neurons (PNs) of the locust antennal lobe respond to odors with dense, odor-specific spatio-temporal activity patterns that are mapped via intrinsic and circuit properties into a sparse representation by the Kenyon cells of the mushroom body, which are in turn read out by the beta-lobe neurons (bLNs). In this thesis we present several analyses of this system. First, we describe metrics for quantifying the geometric properties of PN population responses in the full response space that verify the structures revealed by locally linear embedding. Second, we analyze the mixture responses of single PNs and find that in many cases the mixture response can be explained using one of the component responses. Grouping PNs by their single component preferences reveals a potentially simple substrate for olfactory computations. Third, we look for evidence of cycle-by-cycle decoding of PNs by KCs. We show that much of the variance in single KC responses can be explained using small numbers of PNs, and conversely, that PN odor response trajectories can be reconstructed using KC responses. Finally, in a theoretical / computational analysis, we assemble some of the basic biological facts about the locust olfactory system into an architecture for the online learning of arbitrary mappings from odors to valences.
Item Type: | Thesis (Dissertation (Ph.D.)) |
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Subject Keywords: | locust olfaction; antennal lobe; mushroom body; projection neuron; kenyon cell; |
Degree Grantor: | California Institute of Technology |
Division: | Engineering and Applied Science |
Major Option: | Computation and Neural Systems |
Thesis Availability: | Public (worldwide access) |
Research Advisor(s): |
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Thesis Committee: |
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Defense Date: | 9 November 2012 |
Non-Caltech Author Email: | sina.tootoonian (AT) gmail.com |
Record Number: | CaltechTHESIS:12282012-075056374 |
Persistent URL: | https://resolver.caltech.edu/CaltechTHESIS:12282012-075056374 |
DOI: | 10.7907/MAWA-GD04 |
Default Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. |
ID Code: | 7355 |
Collection: | CaltechTHESIS |
Deposited By: | Sina Tootoonian |
Deposited On: | 11 Jan 2013 17:52 |
Last Modified: | 01 Sep 2022 23:45 |
Thesis Files
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PDF (Sina Tootoonian PhD Thesis 2013)
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