Gray Box Modelling of Arterial Vasoaction

Gray box modelling of physiological systems involves constructing a model structure based on physical knowledge of the system and model parameterisation using numerical techniques. This paper presents a gray box model of arterial vasoaction (the process of constricting and dilating blood vessels in order to maintain an appropriate level of blood pressure and blood flow). The model structure is built in accordance with the physical system. The initial parameterisation was manual, with the model consequently optimised using gradient techniques and genetic algorithms. The model was validated by demonstrating good correlation between experimental results and model output

A nonlinear model for vasoconstriction

The control of blood pressure is a complex mixture of neural, hormonal and intrinsic interactions at the level of the heart, kidney and blood vessels. While experimental approaches to understanding these interactions remain useful, it remains difficult to conduct experiments to quantify these interactions as the number of parameters increases. Thus modelling approaches can offer considerable assistance. Typical mathematical models which describe the ability of the blood vessels to change their diameter (vasoconstriction) assume linearity of operation. However, due to the interaction of multiple vasocontrictive and vasodilative effectors, there is a significant nonlinear response to the in uence of neural factors, particularly at higher levels of nerve activity (often seen in subjects with high blood pressure) which leads to low blood ow rates. This paper proposes a nonlinear mathematical model for the relationship between neural in uences (sympathetic nerve activity (SNA) and blood ow, using a feedback path to model the predominently nonlinear effect of local vasoactive modulators such as Nitric Oxide, which oppose the action of SNA. The model, the structure of which is motivated by basic physiological principles, is parameterised using a numerical optimisation method using open-loop data collected from rabbits. The model responses are shown to be in good agreement with the experimental data

Investigation of events in the EEG signal correlated with changes in both oxygen and glucose in the brain

Since the brain has no constant energy reserves, a continuous supply of energy substrates is central to all processes that maintain the functionality of the neuronal cells. EEG has been found to be tightly related to variations in the concentration of the energy substrates such as oxygen and glucose. Prediction of neural activation is particularly useful as it could contribute significantly in the prevention, stabilization, or treatment of diseases such as Alzheimer's disease, migraine headache, and ischemic stroke, in which signaling between neurons and brain vessels is threatened because of dysfunctions that affect the neuronal, astroglial, and/or vascular components of the neurovascular unit. This work deals with investigation of events in the EEG signal correlated with changes in both oxygen and glucose signals in the brain. The topic is to implement a model that through measures of oxygen and glucose in the brain of rats allow to achieve a good estimation of the neural signals, which reflecting the simultaneous metabolic changes, during spontaneous oscillation and electrical stimulation

Investigation of events in the EEG signal correlated with changes in both oxygen and glucose in the brain

Since the brain has no constant energy reserves, a continuous supply of energy substrates is central to all processes that maintain the functionality of the neuronal cells. EEG has been found to be tightly related to variations in the concentration of the energy substrates such as oxygen and glucose. Prediction of neural activation is particularly useful as it could contribute significantly in the prevention, stabilization, or treatment of diseases such as Alzheimer's disease, migraine headache, and ischemic stroke, in which signaling between neurons and brain vessels is threatened because of dysfunctions that affect the neuronal, astroglial, and/or vascular components of the neurovascular unit. This work deals with investigation of events in the EEG signal correlated with changes in both oxygen and glucose signals in the brain. The topic is to implement a model that through measures of oxygen and glucose in the brain of rats allow to achieve a good estimation of the neural signals, which reflecting the simultaneous metabolic changes, during spontaneous oscillation and electrical stimulation

Gray Box Modelling of Arterial Vasoaction

Gray box modelling of physiological systems involves constructing a model structure based on physical knowledge of the system and model parameterisation using numerical techniques. This paper presents a gray box model of arterial vasoaction (the process of constricting and dilating blood vessels in order to maintain an appropriate level of blood pressure and blood flow). The model structure is built in accordance with the physical system. The initial parameterisation was manual, with the model consequently optimised using gradient techniques and genetic algorithms. The model was validated by demonstrating good correlation between experimental results and model output

Gray Box Modelling of Arterial Vasoaction

Gray box modelling of physiological systems involves constructing a model structure based on physical knowledge of the system and model parameterisation using numerical techniques. This paper presents a gray box model of arterial vasoaction (the process of constricting and dilating blood vessels in order to maintain an appropriate level of blood pressure and blood flow). The model structure is built in accordance with the physical system. The initial parameterisation was manual, with the model consequently optimised using gradient techniques and genetic algorithms. The model was validated by demonstrating good correlation between experimental results and model output

Graphical simulation environments for modelling and simulation of integrative physiology

Guyton’s original integrative physiology model was a milestone in integrative physiology, combining significant physiological knowledge with an engineering perspective to develop a computational diagrammatic model. It is still used in research and teaching, with a small number of variants on the model also in circulation. However, though new research has added significantly to the knowledge represented by Guyton’s model, and significant advances have been made in computing and simulation software, an accepted common platform to integrate this new knowledge has not emerged. This paper discusses the issues in the selection of a suitable platform, together with a number of current possibilities, and suggests a graphical computing environment for modelling and simulation. Byway of example, a validated version of Guyton’s 1992 model, implemented in the ubiquitous Simulink environment, is presented which provides a hierarchical representation amenable to extension and suitable for teaching and research uses. It is designed to appeal to the biomedical engineer and physiologist alike

A nonlinear model for vasoconstriction

The control of blood pressure is a complex mixture of neural, hormonal and intrinsic interactions at the level of the heart, kidney and blood vessels. While experimental approaches to understanding these interactions remain useful, it remains difficult to conduct experiments to quantify these interactions as the number of parameters increases. Thus modelling approaches can offer considerable assistance. Typical mathematical models which describe the ability of the blood vessels to change their diameter (vasoconstriction) assume linearity of operation. However, due to the interaction of multiple vasocontrictive and vasodilative effectors, there is a significant nonlinear response to the in uence of neural factors, particularly at higher levels of nerve activity (often seen in subjects with high blood pressure) which leads to low blood ow rates. This paper proposes a nonlinear mathematical model for the relationship between neural in uences (sympathetic nerve activity (SNA) and blood ow, using a feedback path to model the predominently nonlinear effect of local vasoactive modulators such as Nitric Oxide, which oppose the action of SNA. The model, the structure of which is motivated by basic physiological principles, is parameterised using a numerical optimisation method using open-loop data collected from rabbits. The model responses are shown to be in good agreement with the experimental data

Investigation of events in the EEG signal correlated with changes in both oxygen and glucose in the brain

Since the brain has no constant energy reserves, a continuous supply of energy substrates is central to all processes that maintain the functionality of the neuronal cells. EEG has been found to be tightly related to variations in the concentration of the energy substrates such as oxygen and glucose. Prediction of neural activation is particularly useful as it could contribute significantly in the prevention, stabilization, or treatment of diseases such as Alzheimer's disease, migraine headache, and ischemic stroke, in which signaling between neurons and brain vessels is threatened because of dysfunctions that affect the neuronal, astroglial, and/or vascular components of the neurovascular unit. This work deals with investigation of events in the EEG signal correlated with changes in both oxygen and glucose signals in the brain. The topic is to implement a model that through measures of oxygen and glucose in the brain of rats allow to achieve a good estimation of the neural signals, which reflecting the simultaneous metabolic changes, during spontaneous oscillation and electrical stimulation

A nonlinear model for vasoconstriction

The control of blood pressure is a complex mixture of neural, hormonal and intrinsic interactions at the level of the heart, kidney and blood vessels. While experimental approaches to understanding these interactions remain useful, it remains difficult to conduct experiments to quantify these interactions as the number of parameters increases. Thus modelling approaches can offer considerable assistance. Typical mathematical models which describe the ability of the blood vessels to change their diameter (vasoconstriction) assume linearity of operation. However, due to the interaction of multiple vasocontrictive and vasodilative effectors, there is a significant nonlinear response to the in uence of neural factors, particularly at higher levels of nerve activity (often seen in subjects with high blood pressure) which leads to low blood ow rates. This paper proposes a nonlinear mathematical model for the relationship between neural in uences (sympathetic nerve activity (SNA) and blood ow, using a feedback path to model the predominently nonlinear effect of local vasoactive modulators such as Nitric Oxide, which oppose the action of SNA. The model, the structure of which is motivated by basic physiological principles, is parameterised using a numerical optimisation method using open-loop data collected from rabbits. The model responses are shown to be in good agreement with the experimental data