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Title: The Study of Complex Behavioral Changes with Age in Drosophila melanogaster Using a Quantitative Framework for Behavioral Description
Authors: Choi, Daniel Moon-hyung
Advisors: Shaevitz, Joshua W
Contributors: Molecular Biology Department
Keywords: aging
computational neuroscience
machine learning
quantitative ethology
Subjects: Behavioral sciences
Issue Date: 2017
Publisher: Princeton, NJ : Princeton University
Abstract: Aging is a set of complex, multi-factorial phenotypes that follow characteristic temporal profiles throughout an organism's life. Rather than looking at specific metabolic, hormonal, or genetic traits, researchers often focus on behaviors as a composite phenotype representative of an animal's physiological state. Behaviors, like aging, are also downstream of many biological processes, and are fundamentally dynamic traits. While some of the causal mechanisms of behavior have been studied at the genetic and physiological levels, we still have limited quantitative descriptions of behaviors. We present in this volume a framework for the study of animal behavior that establishes a mathematical language of ethological description. We demonstrate the feasibility of a quantitative phenomenology that can be used to wed the rigor of controlled behavioral experiments and the richness of observational data. Leveraging our ability to formally define a broad repertoire of behaviors, we examine age-related behavioral changes in the fruit fly Drosophila melanogaster, presenting novel findings in sexual dimorphism and models of neurodegenerative diseases. We use a data-driven approach to capture the quantitative profile of behavioral aging based on previous work developed to capture a broader behavioral repertoire. We find that individual behaviors exhibit qualitatively different aging profiles, and that these aging profiles differ depending on sex and across different neurodegenerative models. While we discover a number of findings that underscore the importance of specific pathways, the complexity of behavioral aging patterns uncovered by our work underscores the diversity of changes that occurs as an organism ages, highlighting the importance of examining multiple behavioral phenotypes in tandem in unraveling the programs and mechanisms of organismal aging. We believe that our work represents an important first step in obtaining a complete picture of how organisms behave throughout their lifespan, and it further serves as a compelling direction for the formalization of observational methods in ethology.
Alternate format: The Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog:
Type of Material: Academic dissertations (Ph.D.)
Language: en
Appears in Collections:Molecular Biology

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