A posture-based Markov analysis of behavioral states in Caenorhabditis elegans

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.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2019

Author dc:creator

• Clark, Rebekah I.

Advisor dc:contributor.advisor

• Steven W. Flavell.

• Electrical Engineering and Computer Science.

Statement dc:rights

• MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/128397

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/128397