Publication Date

2016-07-26

Availability

Open access

Embargo Period

2016-07-26

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PHD)

Department

Physics (Arts and Sciences)

Date of Defense

2016-06-29

First Committee Member

Sheyum Syed

Second Committee Member

Fulin Zuo

Third Committee Member

Mason Klein

Fourth Committee Member

Julia Dallman

Abstract

Grooming is nearly universal in terrestrial animals and is important for animals to maintain body surface condition. In insects, grooming is controlled by relatively simple nervous system, so the study of grooming may reveal basic principles of grooming. While recent progress is being made on understanding the mechanism of stimulated grooming control in Drosophila, the internal regulation of non-stimulated grooming remains unexplored. It is possible that the circadian clock plays an important role in the internal regulation of grooming. However, a key problem in the study of grooming’s circadian control is the difficulty of obtaining and interpreting long-term grooming data. This thesis focuses on long-term grooming and examines regulation of the behavior by the circadian clock. To quantify and categorize the long-term grooming data I developed a method based on machine learning technology that can identify grooming events automatically from recorded video clips of fly’s freely behaving. My research showed that grooming is regulated by the circadian clock and its circadian rhythm is related to the animal’s locomotion rhythms. However, I show that grooming does not occur as a direct response to locomotion.

Keywords

Grooming; Video-Tracking; Drosophila; Circadian

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