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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: 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.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.

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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 normalvalues apart from u which is stepped up from 1 to 1.2for a ten second duration, giving rise to an approximately 3.5 percentincrease in CMRO2 and an approximately 6 percent increase inblood flow. TOS increased by a little under 1 percent, andΔoxCCO also increased by about 0.05 μMcorresponding to an oxidation of just under 1 percent.
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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 normalvalues apart from u which is stepped up from 1 to 1.2for a ten second duration, giving rise to an approximately 3.5 percentincrease in CMRO2 and an approximately 6 percent increase inblood flow. TOS increased by a little under 1 percent, andΔoxCCO also increased by about 0.05 μMcorresponding to an oxidation of just under 1 percent.

Mentions: In order to shed light on such questions, functional activation was simulated inthe model, via a step up in the demand parameter u. A tensecond activation was simulated by running the model at normal parameter valuesfor 10 seconds, followed by a 10 second increase in u, followedby a further ten seconds at baseline. The responses of various quantities areplotted 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 normalvalues apart from u which is stepped up from 1 to 1.2for a ten second duration, giving rise to an approximately 3.5 percentincrease in CMRO2 and an approximately 6 percent increase inblood flow. TOS increased by a little under 1 percent, andΔoxCCO also increased by about 0.05 μMcorresponding to an oxidation of just under 1 percent.
© Copyright Policy
Related In: Results  -  Collection

License
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 normalvalues apart from u which is stepped up from 1 to 1.2for a ten second duration, giving rise to an approximately 3.5 percentincrease in CMRO2 and an approximately 6 percent increase inblood flow. TOS increased by a little under 1 percent, andΔoxCCO also increased by about 0.05 μMcorresponding to an oxidation of just under 1 percent.
Mentions: In order to shed light on such questions, functional activation was simulated inthe model, via a step up in the demand parameter u. A tensecond activation was simulated by running the model at normal parameter valuesfor 10 seconds, followed by a 10 second increase in u, followedby a further ten seconds at baseline. The responses of various quantities areplotted in Figure 5.

Bottom Line: 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.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