Development of computational and experimental tools to study mechanotransduction in C.elegans and primates
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2012
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| Online Access: | http://hdl.handle.net/1721.1/69497 |
| _version_ | 1826201917603184640 |
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| author | Kumar, Siddarth |
| author2 | Mandayam A. Srinivasan. |
| author_facet | Mandayam A. Srinivasan. Kumar, Siddarth |
| author_sort | Kumar, Siddarth |
| collection | MIT |
| description | Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011. |
| first_indexed | 2024-09-23T11:59:18Z |
| format | Thesis |
| id | mit-1721.1/69497 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T11:59:18Z |
| publishDate | 2012 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/694972019-04-11T04:16:59Z Development of computational and experimental tools to study mechanotransduction in C.elegans and primates Kumar, Siddarth Mandayam A. Srinivasan. Massachusetts Institute of Technology. Dept. of Mechanical Engineering. Massachusetts Institute of Technology. Dept. of Mechanical Engineering. Mechanical Engineering. Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011. Cataloged from PDF version of thesis. Includes bibliographical references (p. 141-148). When an object comes into contact with the human fingertip, surface loads imposed on the fingerpad are transmitted to thousands of specialized nerve endings embedded in the skin tissue. These nerve endings, called mechanoreceptors, transduce the mechanical signals to generate a neural code of the incident stimuli enabling us to feel the object. The neural codes, generated by the spatial distribution of responding mechanoreceptors, are in the form of a temporal sequence of action potentials and tactile information is encoded in the timing of each generated action potential. This thesis presents the development of predictive models to gain an understanding of the processes leading to mechanosensation. More specifically we study and model (1) how surface loads are transmitted to embedded mechanoreceptors and (2) how one type of mechanoreceptor (slowly adapting type-i or SAl) transduce these mechanical signals to a sequence of action potentials. We study these processes in two model organisms, namely the nematode C.elegans and the primate Rhesus macaque, each presenting its own advantages. Due to the physiological similarity of their anatomy and readily available mechanoreceptor neurophysiological data, primates are a popular model organism used to study the human tactile system. The study of the nematode C.elegans provides us with the advantage of understanding the sense of touch at a molecular level. To understand how loads are transmitted to embedded mechanoreceptors, it is essential to understand and characterize the behavior of underlying tissue. Most models in literature describing the primate fingertip use elastic models and compare the strain energy density at a mechanoreceptor location with the static steady state firing rate of the mechanoreceptor. We present experiments to measure the bulk viscoelastic properties of the primate finger tissue in vivo and non-invasively through a combination of single point indentation and numerical simulation. We develop, calibrate and validate realistic finite element models for the finger and use it to show that the stress relaxation of tissue surrounding the mechanoreceptor seems to regulate the dynamic firing rate of SA- 1 mechanoreceptors. We then present a point process model, based on the Pareto distribution, to predict the dynamic frequency of action potentials and compare our predictions with experimental data where the finger is indented with a flat plate. In the last part of the thesis, we describe experiments to characterize the biomechanics of the nematode C.elegans. Current models in literature describe the body of the nematode as a shell with internal pressure. We propose a multilayer finite element model as an alternative to the shell model and show that it is better at predicting both force response data (obtained using AFM indentation) and surface deflection data due to indentation by a micro spherical indenter. Finally, we use the Hodgkin-Huxley model to predict the membrane potential of the PLM mechanoreceptor in C.elegans and compare our results with experimental data in literature. by Siddarth Kumar. Ph.D. 2012-02-29T18:21:42Z 2012-02-29T18:21:42Z 2011 2011 Thesis http://hdl.handle.net/1721.1/69497 775670690 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 168 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Mechanical Engineering. Kumar, Siddarth Development of computational and experimental tools to study mechanotransduction in C.elegans and primates |
| title | Development of computational and experimental tools to study mechanotransduction in C.elegans and primates |
| title_full | Development of computational and experimental tools to study mechanotransduction in C.elegans and primates |
| title_fullStr | Development of computational and experimental tools to study mechanotransduction in C.elegans and primates |
| title_full_unstemmed | Development of computational and experimental tools to study mechanotransduction in C.elegans and primates |
| title_short | Development of computational and experimental tools to study mechanotransduction in C.elegans and primates |
| title_sort | development of computational and experimental tools to study mechanotransduction in c elegans and primates |
| topic | Mechanical Engineering. |
| url | http://hdl.handle.net/1721.1/69497 |
| work_keys_str_mv | AT kumarsiddarth developmentofcomputationalandexperimentaltoolstostudymechanotransductionincelegansandprimates |