A Model of the Dynamic Relationship Between Blood Flow and Volume Changes During Brain Activation

Kong, Yazhuo; Zheng, Ying; Johnston, David; Martindale, John; Jones, Myles; Billings, S.A.; Mayhew, John E. W.

doi:10.1097/00004647-200412000-00007

Cited by 26 publications

(31 citation statements)

References 13 publications

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“…However, as noted by Boas et al (2008) it is not clear whether dominant volume changes occur on the arteriole side Kim et al, 2007;Lee et al, 2001;Vanzetta et al, 2005) or venous side (Buxton et al, 1998;Kong et al, 2004;Mandeville et al, 1999). Our results indicate that the arteriolar blood volume change comprises more than 96%, i.e., the major portion of the blood volume change.…”

Section: Blood Flow Control and Passive Responsesmentioning

confidence: 49%

“…Moreover, the relatively insignificant contribution of venous dilation has been recently observed experimentally Kim et al, 2007;Lee et al, 2001;Vanzetta et al (2005)). As pointed out by Vanzetta et al (2005), these recent results are inconsistent with the important role ascribed to venous compliance in previous theoretical models of the BOLD signal -e.g., the "balloon model" (Buxton and Frank, 1997;Buxton et al, 1998) and windkessel models (Kong et al, 2004;Mandeville et al, 1999). However, this contradiction might only be apparent.…”

Section: Blood Flow Control and Passive Responsesmentioning

confidence: 99%

“…As a conclusion, the approach presented here could provide a theoretical framework for analyzing the variations of ϕ among various brain areas of different architectural characteristics, in steady state conditions. Further methodological developments will however be needed to handle transient states in order to investigate the time dependence of ϕ during neuronal activation (Kong et al, 2004;Zheng and Mayhew, 2009). Although a simple model involving two resistances in series can accurately describe the hemodynamic variations induced by global vasodilations at network scale, this model cannot account for the heterogeneities we have evidenced throughout the network.…”

Section: Hemodynamic Variations Induced By Global Vasodilationsmentioning

confidence: 99%

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Simulation study of brain blood flow regulation by intra-cortical arterioles in an anatomically accurate large human vascular network. Part II: Flow variations induced by global or localized modifications of arteriolar diameters

Lorthois¹,

Cassot²,

Lauwers³

2011

NeuroImage

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OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. In a companion paper (Lorthois et al., Neuroimage, in press), we perform the first simulations of blood flow in an anatomically accurate large human intra-cortical vascular network (~10000 segments), using a 1D non-linear model taking into account the complex rheological properties of blood flow in microcirculation. This model predicts blood pressure, blood flow and hematocrit distributions, volumes of functional vascular territories, regional flow at voxel and network scales, etc. Using the same approach, we study flow reorganizations induced by global arteriolar vasodilations (an isometabolic global increase in cerebral blood flow). For small to moderate global vasodilations, the relationship between changes in volume and changes in flow is in close agreement with Grubb's law, providing a quantitative tool for studying the variations of its exponent with underlying vascular architecture. A significant correlation between blood flow and vascular structure at the voxel scale, practically unchanged with respect to baseline, is demonstrated. Furthermore, the effects of localized arteriolar vasodilations, representative of a local increase in metabolic demand, are analyzed. In particular, localized vasodilations induce flow changes, including vascular steal, in the neighboring arteriolar trunks at small distances (b 300 μm), while their influence in the neighboring veins is much larger (about 1 mm), which provides an estimate of the vascular point spread function. More generally, for the first time, the hemodynamic component of various functional neuroimaging techniques has been isolated from metabolic and neuronal components, and a direct relationship with several known characteristics of the BOLD signal has been demonstrated. IntroductionThere is increasing recognition that, by its structural implication in neuro-vascular coupling, underlying vascular architecture is a key player in hemodynamically based functional imaging techniques (including fMRI and PET) (Harrison et al., 2002;d'Esposito et al., 2003;Logothetis and Wandell, 2004;Lauwers et al., 2008;Weber et al., 2008). In particular, the spatial resolution and specificity of such techniques are bound to the density of blood capillary vasculature and blood flow regulating structures (Harel et al., 2006). This is especially important in the context of high field fMRI Harel et al., 2006), because, despite a dramatic increase in the theoretical spatial resolution obtained by using higher magnetic fields, associated with other hardware advancements, "the spatial extent of the hemodynamic response ultimately will impose a fundamental limitation on the spatial resolution of fMRI modalities" ).However, little is known about the fundamentals of the relationship between vascular structure and hemodynamic changes induced by brain activation. A growing body of evidence indicates that neurons, glia, and cerebral blood vessels, actin...

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Section: Blood Flow Control and Passive Responsesmentioning

confidence: 49%

Section: Blood Flow Control and Passive Responsesmentioning

confidence: 99%

Section: Hemodynamic Variations Induced By Global Vasodilationsmentioning

confidence: 99%

See 1 more Smart Citation

Simulation study of brain blood flow regulation by intra-cortical arterioles in an anatomically accurate large human vascular network. Part II: Flow variations induced by global or localized modifications of arteriolar diameters

Lorthois¹,

Cassot²,

Lauwers³

2011

NeuroImage

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“…Arteriolar dilation, a common denominator in evoked hemodynamic response, alters the vascular resistance and results in an increased blood flow into the vascular network and increased pressure in the downstream vascular segments. The compliant capillaries and venules subsequently expand in response to this increased pressure with some debate as to whether dominant volume changes occur on the arteriole side Kim et al, 2007;Lee et al, 2001) or venous side (Buxton et al, 1998;Kong et al, 2004;Mandeville et al, 1999). Consequently, increased flow results in a greater delivery of oxygenated hemoglobin.…”

Section: Introductionmentioning

confidence: 99%

A vascular anatomical network model of the spatio-temporal response to brain activation

Boas¹,

Jones²,

Devor³

et al. 2008

NeuroImage

202

240

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Neuronal activity-induced changes in vascular tone and oxygen consumption result in a dynamic evolution of blood flow, volume, and oxygenation. Functional neuroimaging techniques, such as functional magnetic resonance imaging, optical imaging, and PET, provide indirect measures of the neural-induced vascular dynamics driving the blood parameters. Models connecting changes in vascular tone and oxygen consumption to observed changes in the blood parameters are needed to guide more quantitative physiological interpretation of these functional neuroimaging modalities. Effective lumped-parameter vascular balloon and Windkessel models have been developed for this purpose, but the lumping of the complex vascular network into a series of arterioles, capillaries, and venules allows only qualitative interpretation. We have therefore developed a parallel vascular anatomical network (VAN) model based on microscopically measurable properties to improve quantitative interpretation of the vascular response. The model, derived from measured physical properties, predicts baseline blood pressure and oxygen saturation distributions and dynamic responses consistent with literature. Furthermore, the VAN model allows investigation of spatial features of the dynamic vascular and oxygen response to neuronal activity. We find that a passive surround negative vascular response ("negative BOLD") is predicted, but that it underestimates recently observed surround negativity suggesting that additional active surround vasoconstriction is required to explain the experimental data.

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“…This paper reports attempts to model the first of these relationships (that is, between neural activity and local blood flow changes); however, in the experiments described, both laser Doppler flowmetry (LDF) data (yielding blood flow changes) and optical imaging spectroscopy data (yielding blood volume changes) were acquired concurrently. Identification of a nonlinear system describing the second relationship (the coupling between flow and volume changes) based on the insights of Mandeville et al (1999) and Buxton et al (1998) is described elsewhere (Kong et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

Long Duration Stimuli and Nonlinearities in the Neural–Haemodynamic Coupling

Martindale

Berwick

Martin

et al. 2005

J Cereb Blood Flow Metab

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Recent studies have shown that the haemodynamic responses to brief (o2 secs) stimuli can be well characterised as a linear convolution of neural activity with a suitable haemodynamic impulse response. In this paper, we show that the linear convolution model cannot predict measurements of blood flow responses to stimuli of longer duration (42 secs), regardless of the impulse response function chosen. Modifying the linear convolution scheme to a nonlinear convolution scheme was found to provide a good prediction of the observed data. Whereas several studies have found a nonlinear coupling between stimulus input and blood flow responses, the current modelling scheme uses neural activity as an input, and thus implies nonlinearity in the coupling between neural activity and blood flow responses. Neural activity was assessed by current source density analysis of depthresolved evoked field potentials, while blood flow responses were measured using laser Doppler flowmetry. All measurements were made in rat whisker barrel cortex after electrical stimulation of the whisker pad for 1 to 16 secs at 5 Hz and 1.2 mA (individual pulse width 0.3 ms).

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A Model of the Dynamic Relationship Between Blood Flow and Volume Changes During Brain Activation

Cited by 26 publications

References 13 publications

Simulation study of brain blood flow regulation by intra-cortical arterioles in an anatomically accurate large human vascular network. Part II: Flow variations induced by global or localized modifications of arteriolar diameters

Simulation study of brain blood flow regulation by intra-cortical arterioles in an anatomically accurate large human vascular network. Part II: Flow variations induced by global or localized modifications of arteriolar diameters

A vascular anatomical network model of the spatio-temporal response to brain activation

Long Duration Stimuli and Nonlinearities in the Neural–Haemodynamic Coupling

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