Drosophila Automated Olfactory Training and Testing System for Associative Learning

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.