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| Author(s): |
Breno Teixeira Santos
Total Authors: 1
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| Document type: | Master's Dissertation |
| Press: | São Paulo. |
| Institution: | Universidade de São Paulo (USP). Instituto de Biociências (IBIOC/SB) |
| Defense date: | 2008-10-08 |
| Examining board members: |
José Guilherme de Souza Chaui Mattos Berlinck;
Jose Eduardo Pereira Wilken Bicudo;
Luiz Henrique Alves Monteiro
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| Advisor: | José Guilherme de Souza Chaui Mattos Berlinck |
| Abstract | |
Objectives: Classical studies showed that the transition among gait patterns, in vertebrate locomotion, occur when there is an increase in energetic demand. Since the muscular movement is performed under central nervous system control, it is this one that determines the gait pattern in the end. Therefore, this structure is able to translate mechanical events related to force/energy and more, it is capable to operate the whole system in such a way to put it in a demand optimum. Our approach aims to create a central nervous system mapping of the afferences and efferences present in a mechanical system to create a motor control network model, and then, find the operation range that minimizes the entropy generation of the mechanical system. Methods: Mathematical models of working skeletal muscles and tendons, linked to a pendulum system, and their a afferences (i.e., spindles and Golgi tendon organs) were developed and validated as a biomechanical platform. These afferences were used as inputs to another model describing a Biological Neural Network that generate the efferences used as inputs to muscle control. All models were explicited as differential equations and numerically solved in the Simulink environment. Results: The proposed neural network was able to control the biomechanical system, driving it to oscillate similarly to a gait, autonomously, using signals from Ib and Ia fibers as inputs. Optimization measures based in muscular enthalpy generation calculations pointed out that the network is capable to operate the biomechanical machinery in regions of best enthalpy generation by velocity or distance relations. Conclusions: The theoretical results of this work present some interesting experimental questions about possible relations between muscle activation patterns and biological scaling. It also gives support to the idea that exist some basic neural architecture involved in the control of biological mechanical processes in vertebrates. (AU) | |