A posture-based Markov analysis of behavioral states in Caenorhabditis elegans
Author(s)Clark, Rebekah I.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Steven W. Flavell.
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Organisms of varying degrees of complexity coordinate their diverse behavioral outputs over time, yet the internal neural dynamics underlying such behavioral organization is not completely understood. Behavior coordination can be captured through the quantitative description and subsequent analysis of behavioral states. Here, we develop an analytical method for the characterization of behavioral states in C. elegans. We observe posture sequences in wild type C. elegans and utilize a hidden Markov model to detect the behavioral states giving rise to these posture sequences. We then demonstrate that this method is generalizable to different C. elegans strains by applying this posture-based Markov analysis to C. elegans mutants and survey how these mutants differentially exhibit key behaviors within these behavioral states. This methodology provides a framework by which behavioral states can be quantified for further study of the neural dynamics underlying behavior coordination.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019Cataloged from student-submitted PDF of thesis.Includes bibliographical references (pages 63-66).
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology
Electrical Engineering and Computer Science.