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Title page for ETD etd-01122015-133013


Type of Document Master's Thesis
Author Jiang, Hui
Author's Email Address hui.jiang@vanderbilt.edu
URN etd-01122015-133013
Title Drosophila Automated Olfactory Training and Testing System for Associative Learning
Degree Master of Science
Department Electrical Engineering
Advisory Committee
Advisor Name Title
Bharat L. Bhuva Committee Member
Kendal S. Broadie Committee Member
Keywords
  • Pavlovian classical conditioning
  • automation
  • learning
  • Drosophila
  • memory
Date of Defense 2014-12-11
Availability unrestricted
Abstract
This thesis demonstrates the feasibility of designing and building a Drosophila automated training and testing system for Pavlovian classical associative learning/memory analyses using inexpensive hardware and software (total design under $700US). There were two platforms designed using inexpensive electronic devices, 3D printed parts, and different configurations. Both were controlled by an open source Arduino microcontroller, eight solenoid valves, and a square pulse stimulator. The two platform data were logged by an odor sensor and three air flow sensors. This thesis presents the system design and the results of biological testing. The results show that controlling and data logging electronic devices work well for this application.
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