Nonlinear observer design and synchronization analysis for classical models of neural oscillators

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2013.

Bibliographic Details
Main Author: Bharath, Ranjeetha
Other Authors: Jean-Jacques Slotine.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2014
Subjects:
Online Access:http://hdl.handle.net/1721.1/83684
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author Bharath, Ranjeetha
author2 Jean-Jacques Slotine.
author_facet Jean-Jacques Slotine.
Bharath, Ranjeetha
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description Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2013.
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spelling mit-1721.1/836842019-04-11T07:04:39Z Nonlinear observer design and synchronization analysis for classical models of neural oscillators Bharath, Ranjeetha Jean-Jacques Slotine. Massachusetts Institute of Technology. Department of Mechanical Engineering. Massachusetts Institute of Technology. Department of Mechanical Engineering. Mechanical Engineering. Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2013. Cataloged from PDF version of thesis. Includes bibliographical references (pages 37-38). This thesis explores four nonlinear classical models of neural oscillators, the Hodgkin- Huxley model, the Fitzhugh-Nagumo model, the Morris-Lecar model, and the Hindmarsh-Rose model. Analysis techniques for nonlinear systems were used to develop a set of observers and perform synchronization analysis on the aforementioned neural systems. By using matrix analysis techniques, a study of biological background and motivation, and MATLAB simulation with mathematical computation, it was possible to do a preliminary contraction and nonlinear control systems structural study of these classical neural oscillator models. Neural oscillation and signaling models are based fundamentally on the biological function of the neuron, with behavior mediated through the channeling of ions across a cell membrane. The variable assumed to be measured for this study is the voltage or membrane potential, which could be measured empirically through the use of a neuronal force-clamp system. All other variables were estimated by using the partial state and full state observers developed here. Preliminary observer rate convergence analysis was done for the Fitzhugh-Nagumo system, and preliminary synchronization analysis was done for both the Fitzhugh-Nagumo and the Hodgkin- Huxley systems. It was found that by using a variety of techniques and mathematical matrix analyses methods (e.g. diagonal dominance or other norms), it was possible to develop a case-by-case nonlinear control systems approach to each particular system as a biomathematical entity. by Ranjeetha Bharath. S.B. 2014-01-09T19:44:41Z 2014-01-09T19:44:41Z 2013 Thesis http://hdl.handle.net/1721.1/83684 863159137 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 38 pages application/pdf Massachusetts Institute of Technology
spellingShingle Mechanical Engineering.
Bharath, Ranjeetha
Nonlinear observer design and synchronization analysis for classical models of neural oscillators
title Nonlinear observer design and synchronization analysis for classical models of neural oscillators
title_full Nonlinear observer design and synchronization analysis for classical models of neural oscillators
title_fullStr Nonlinear observer design and synchronization analysis for classical models of neural oscillators
title_full_unstemmed Nonlinear observer design and synchronization analysis for classical models of neural oscillators
title_short Nonlinear observer design and synchronization analysis for classical models of neural oscillators
title_sort nonlinear observer design and synchronization analysis for classical models of neural oscillators
topic Mechanical Engineering.
url http://hdl.handle.net/1721.1/83684
work_keys_str_mv AT bharathranjeetha nonlinearobserverdesignandsynchronizationanalysisforclassicalmodelsofneuraloscillators