Limits...
A model of brain circulation and metabolism: NIRS signal changes during physiological challenges.

Banaji M, Mallet A, Elwell CE, Nicholls P, Cooper CE - PLoS Comput. Biol. (2008)

Bottom Line: We anticipate that the model will play an important role in helping to understand the NIRS signals, in particular, the cytochrome signal, which has been hard to interpret.A range of model simulations are presented, and model outputs are compared to published data obtained from both in vivo and in vitro settings.The comparisons are encouraging, showing that the model is able to reproduce observed behaviour in response to various stimuli.

View Article: PubMed Central - PubMed

Affiliation: Department of Biological Sciences, University of Essex, Colchester, United Kingdom. m.banaji@ucl.ac.uk

ABSTRACT
We construct a model of brain circulation and energy metabolism. The model is designed to explain experimental data and predict the response of the circulation and metabolism to a variety of stimuli, in particular, changes in arterial blood pressure, CO(2) levels, O(2) levels, and functional activation. Significant model outputs are predictions about blood flow, metabolic rate, and quantities measurable noninvasively using near-infrared spectroscopy (NIRS), including cerebral blood volume and oxygenation and the redox state of the Cu(A) centre in cytochrome c oxidase. These quantities are now frequently measured in clinical settings; however the relationship between the measurements and the underlying physiological events is in general complex. We anticipate that the model will play an important role in helping to understand the NIRS signals, in particular, the cytochrome signal, which has been hard to interpret. A range of model simulations are presented, and model outputs are compared to published data obtained from both in vivo and in vitro settings. The comparisons are encouraging, showing that the model is able to reproduce observed behaviour in response to various stimuli.

Show MeSH
Summary of the main variables and processes in the simplified model.As in Figure 1,                            inputs are enclosed in solid ovals, while outputs are enclosed in dashed                            ovals. Components connected with blood flow have been removed from the                            model. O2 levels are now directly settable.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC2573000&req=5

pcbi-1000212-g003: Summary of the main variables and processes in the simplified model.As in Figure 1, inputs are enclosed in solid ovals, while outputs are enclosed in dashed ovals. Components connected with blood flow have been removed from the model. O2 levels are now directly settable.

Mentions: Apart from the model described above, in order to set parameters and compare model behaviour to experimental data a simpler submodel is also constructed. This model will be referred to as the simplified model while the model described above will be referred to as the full model. The simplified model is designed to simulate in vitro experiments on mitochondrial solutions, and so omits a number of processes in the full model. A schematic of this model is shown in Figure 3.


A model of brain circulation and metabolism: NIRS signal changes during physiological challenges.

Banaji M, Mallet A, Elwell CE, Nicholls P, Cooper CE - PLoS Comput. Biol. (2008)

Summary of the main variables and processes in the simplified model.As in Figure 1,                            inputs are enclosed in solid ovals, while outputs are enclosed in dashed                            ovals. Components connected with blood flow have been removed from the                            model. O2 levels are now directly settable.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2573000&req=5

pcbi-1000212-g003: Summary of the main variables and processes in the simplified model.As in Figure 1, inputs are enclosed in solid ovals, while outputs are enclosed in dashed ovals. Components connected with blood flow have been removed from the model. O2 levels are now directly settable.
Mentions: Apart from the model described above, in order to set parameters and compare model behaviour to experimental data a simpler submodel is also constructed. This model will be referred to as the simplified model while the model described above will be referred to as the full model. The simplified model is designed to simulate in vitro experiments on mitochondrial solutions, and so omits a number of processes in the full model. A schematic of this model is shown in Figure 3.

Bottom Line: We anticipate that the model will play an important role in helping to understand the NIRS signals, in particular, the cytochrome signal, which has been hard to interpret.A range of model simulations are presented, and model outputs are compared to published data obtained from both in vivo and in vitro settings.The comparisons are encouraging, showing that the model is able to reproduce observed behaviour in response to various stimuli.

View Article: PubMed Central - PubMed

Affiliation: Department of Biological Sciences, University of Essex, Colchester, United Kingdom. m.banaji@ucl.ac.uk

ABSTRACT
We construct a model of brain circulation and energy metabolism. The model is designed to explain experimental data and predict the response of the circulation and metabolism to a variety of stimuli, in particular, changes in arterial blood pressure, CO(2) levels, O(2) levels, and functional activation. Significant model outputs are predictions about blood flow, metabolic rate, and quantities measurable noninvasively using near-infrared spectroscopy (NIRS), including cerebral blood volume and oxygenation and the redox state of the Cu(A) centre in cytochrome c oxidase. These quantities are now frequently measured in clinical settings; however the relationship between the measurements and the underlying physiological events is in general complex. We anticipate that the model will play an important role in helping to understand the NIRS signals, in particular, the cytochrome signal, which has been hard to interpret. A range of model simulations are presented, and model outputs are compared to published data obtained from both in vivo and in vitro settings. The comparisons are encouraging, showing that the model is able to reproduce observed behaviour in response to various stimuli.

Show MeSH