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
Model responses to a step up in demand.(A) Change in CMRO2 (normalised). (B) Change in CBF                            (normalised). (C) Change in TOS (percent). (D) Change in ΔoxCCO                                (μM). All parameters are held at normal                            values apart from u which is stepped up from 1 to 1.2                            for a ten second duration, giving rise to an approximately 3.5 percent                            increase in CMRO2 and an approximately 6 percent increase in                            blood flow. TOS increased by a little under 1 percent, and                            ΔoxCCO also increased by about 0.05 μM                            corresponding to an oxidation of just under 1 percent.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC2573000&req=5

pcbi-1000212-g005: Model responses to a step up in demand.(A) Change in CMRO2 (normalised). (B) Change in CBF (normalised). (C) Change in TOS (percent). (D) Change in ΔoxCCO (μM). All parameters are held at normal values apart from u which is stepped up from 1 to 1.2 for a ten second duration, giving rise to an approximately 3.5 percent increase in CMRO2 and an approximately 6 percent increase in blood flow. TOS increased by a little under 1 percent, and ΔoxCCO also increased by about 0.05 μM corresponding to an oxidation of just under 1 percent.

Mentions: In order to shed light on such questions, functional activation was simulated in the model, via a step up in the demand parameter u. A ten second activation was simulated by running the model at normal parameter values for 10 seconds, followed by a 10 second increase in u, followed by a further ten seconds at baseline. The responses of various quantities are plotted in Figure 5.


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)

Model responses to a step up in demand.(A) Change in CMRO2 (normalised). (B) Change in CBF                            (normalised). (C) Change in TOS (percent). (D) Change in ΔoxCCO                                (μM). All parameters are held at normal                            values apart from u which is stepped up from 1 to 1.2                            for a ten second duration, giving rise to an approximately 3.5 percent                            increase in CMRO2 and an approximately 6 percent increase in                            blood flow. TOS increased by a little under 1 percent, and                            ΔoxCCO also increased by about 0.05 μM                            corresponding to an oxidation of just under 1 percent.
© Copyright Policy
Related In: Results  -  Collection

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

pcbi-1000212-g005: Model responses to a step up in demand.(A) Change in CMRO2 (normalised). (B) Change in CBF (normalised). (C) Change in TOS (percent). (D) Change in ΔoxCCO (μM). All parameters are held at normal values apart from u which is stepped up from 1 to 1.2 for a ten second duration, giving rise to an approximately 3.5 percent increase in CMRO2 and an approximately 6 percent increase in blood flow. TOS increased by a little under 1 percent, and ΔoxCCO also increased by about 0.05 μM corresponding to an oxidation of just under 1 percent.
Mentions: In order to shed light on such questions, functional activation was simulated in the model, via a step up in the demand parameter u. A ten second activation was simulated by running the model at normal parameter values for 10 seconds, followed by a 10 second increase in u, followed by a further ten seconds at baseline. The responses of various quantities are plotted in Figure 5.

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