A posture-based Markov analysis of behavioral states in Caenorhabditis elegans
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2020
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| Online Access: | https://hdl.handle.net/1721.1/128397 |
| _version_ | 1826216082100191232 |
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| author | Clark, Rebekah I. |
| author2 | Steven W. Flavell. |
| author_facet | Steven W. Flavell. Clark, Rebekah I. |
| author_sort | Clark, Rebekah I. |
| collection | MIT |
| description | This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. |
| first_indexed | 2024-09-23T16:41:41Z |
| format | Thesis |
| id | mit-1721.1/128397 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T16:41:41Z |
| publishDate | 2020 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1283972020-11-07T03:01:23Z A posture-based Markov analysis of behavioral states in Caenorhabditis elegans Clark, Rebekah I. Steven W. Flavell. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Electrical Engineering and Computer Science. 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, 2019 Cataloged from student-submitted PDF of thesis. Includes bibliographical references (pages 63-66). 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. by Rebekah I. Clark. M. Eng. M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science 2020-11-06T21:07:53Z 2020-11-06T21:07:53Z 2019 2019 Thesis https://hdl.handle.net/1721.1/128397 1202814848 eng 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. http://dspace.mit.edu/handle/1721.1/7582 66 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Clark, Rebekah I. A posture-based Markov analysis of behavioral states in Caenorhabditis elegans |
| title | A posture-based Markov analysis of behavioral states in Caenorhabditis elegans |
| title_full | A posture-based Markov analysis of behavioral states in Caenorhabditis elegans |
| title_fullStr | A posture-based Markov analysis of behavioral states in Caenorhabditis elegans |
| title_full_unstemmed | A posture-based Markov analysis of behavioral states in Caenorhabditis elegans |
| title_short | A posture-based Markov analysis of behavioral states in Caenorhabditis elegans |
| title_sort | posture based markov analysis of behavioral states in caenorhabditis elegans |
| topic | Electrical Engineering and Computer Science. |
| url | https://hdl.handle.net/1721.1/128397 |
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