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Year : 2010  |  Volume : 2  |  Issue : 8  |  Page : 341-352

Mathematical modeling the neuroregulation of blood pressure using a cognitive top-down approach


Montague Healthcare, Mulberry House, 6 Vine Farm Close, Cotgrave, Nottingham NG12 3TU, United Kingdom

Correspondence Address:
Graham Wilfred Ewing
Director, Montague Healthcare, Mulberry House, 6 Vine Farm Close, Cotgrave, Nottingham NG12 3TU
United Kingdom
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Source of Support: None, Conflict of Interest: None


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Background: The body's physiological stability is maintained by the influence of the autonomic nervous system upon the dynamic interaction of multiple systems. These physiological systems, their nature and structure, and the factors which influence their function have been poorly defined. A greater understanding of such physiological systems leads to an understanding of the synchronised function of organs in each neural network i.e. there is a fundamental relationship involving sensory input and/or sense perception, neural function and neural networks, and cellular and molecular biology. Such an approach compares with the bottom-up systems biology approach in which there may be an almost infinite degree of biochemical complexity to be taken into account. Aims: The purpose of this article is to discuss a novel cognitive, top-down, mathematical model of the physiological systems, in particular its application to the neuroregulation of blood pressure. Results: This article highlights the influence of sensori-visual input upon the function of the autonomic nervous system and the coherent function of the various organ networks i.e. the relationship which exists between visual perception and pathology. Conclusions: The application of Grakov's model may lead to a greater understanding of the fundamental role played by light e.g. regulating acidity, levels of Magnesium, activation of enzymes, and the various factors which contribute to the regulation of blood pressure. It indicates that the body's regulation of blood pressure does not reside in any one neural or visceral component but instead is a measure of the brain's best efforts to maintain its physiological stability.


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