Improving estimates of the cerebral metabolic rate of oxygen from optical imaging data

Barrett, Matthew; Suresh, V.

doi:10.1016/j.neuroimage.2014.11.041

Cited by 7 publications

(16 citation statements)

References 55 publications

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“…In addition, it is also important to note that, despite previous assumptions to the contrary (Davis et al, 1998;Dunn et al, 2005;Hoge et al, 1999;Mayhew et al, 2000), capillaries and even arterioles contain a non-negligible amount of deoxyhemoglobin (Section 7; (Lyons et al, 2016;Sakadžić et al, 2014;Yaseen et al, 2011)). Evidence from a recent modeling study suggests that assuming arterial hemoglobin is completely saturated can lead to errors when estimating CMRO2 (Barrett and Suresh, 2015).…”

Section: Baseline Blood Volume and Deoxyhemoglobin Concentrationmentioning

confidence: 99%

Vascular density and distribution in neocortex

et al. 2019

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An amazingly wide range of complex behavior emerges from the cerebral cortex. Much of the information processing that leads to these behaviors is performed in neocortical circuits that span throughout the six layers of the cortex. Maintaining this circuit activity requires substantial quantities of oxygen and energy substrates, which are delivered by the complex yet well-organized and tightly-regulated vascular system. In this review, we provide a detailed characterization of the most relevant anatomical and functional features of the cortical vasculature. This includes a compilation of the available data on laminar variation of vascular density and the topological aspects of the microvascular system. We also review the spatio-temporal dynamics of cortical blood flow regulation and oxygenation, many aspects of which remain poorly understood. Finally, we discuss some of the important implications of vascular density, distribution, oxygenation and blood flow regulation for (laminar) fMRI.

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Section: Baseline Blood Volume and Deoxyhemoglobin Concentrationmentioning

confidence: 99%

Vascular density and distribution in neocortex

et al. 2019

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“…The interaction graph describes all of the reactions and interactions of the model. In practice, the presented model is the combination of multiple previous studies, where Section 2.2.1-2.2.3 builds upon the work of [41], 2.2.4-2.2.5 corresponds to the work of Barrett et al [34,42,43], and finally, 2.2.6 corresponds to the work of Griffeth et al [44]. The stimulus is given by the following equation: (2) where on , off are the times when the signal goes on and off, respectively.…”

Section: Model Structurementioning

confidence: 99%

“…We describe the dynamics of three cerebrovascular compartments, corresponding to arteries/arterioles ( ), capillaries ( ), and veins/venules ( ), respectively. The compartments are represented by an electrical circuit analogy, as originally presented in the work by Barrett et al [34,42,43]. We use the derivative work of [62], and only present the fully derived equations to improve the clarity for the reader.…”

Section: Cerebrovascular Dynamics Described By An Electrical Circuit mentioning

confidence: 99%

“…1C & 2A-C). We have connected a mechanistic NVC model for the control of arterioles (presented in [41]) with a Windkessel model of blood flow, pressure, volume, and hemoglobin content in arterioles, capillaries, and venules (presented by Barrett et al [34,42,43]), which finally is combined into a complete description of the BOLD signal using the model by Griffeth et al [44]. Our approach is the first model that is able to describe previously published data from different species (humans, mice, and macaques), consisting of multiple different measurement variables (diameter change of the vessels, different measures of CBV, CBF, transient hemoglobin changes, BOLD responses, and LFP) gathered using both optogenetic and sensory perturbations.…”

Section: Introductionmentioning

confidence: 99%

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A multi-data based quantitative model for the neurovascular coupling in the brain

Sten

Sundqvist

et al. 2021

Preprint

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The neurovascular coupling (NVC) forms the foundation for functional imaging techniques of the brain, since NVC connects neural activity with observable hemodynamic changes. Many aspects of the NVC have been studied both experimentally and with mathematical models: various combinations of blood volume and flow, electrical activity, oxygen saturation measures, blood oxygenation level-dependent (BOLD) response, and optogenetics have been measured and modeled in rodents, primates, or humans. We now present a first inter-connected mathematical model that describes all such data types simultaneously. The model can predict independent validation data not used for training. Using simulations, we show for example how complex bimodal behaviors appear upon stimulation. These simulations thus demonstrate how our new quantitative model, incorporating most of the core aspects of the NVC, can be used to mechanistically explain each of its constituent datasets.

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“…Optical techniques can provide advantages in the study of the functional activation in the brain by using intrinsic changes that can detect variations in fluorescence light, absorption, or light scattering. Techniques, such as optical intrinsic signal imaging (OISI), functional near-infrared spectroscopy, or photoacoustics study changes in the blood volume and blood oxygen saturation due to changes in the concentration of oxy- and deoxyhemoglobin induced by the neuronal activity 10 – 13 Indirect information about cerebral blood flow (CBF) can be obtained by looking at the changes of the blood volume over time by using contrast agents.…”

Section: Introductionmentioning

confidence: 99%

Longitudinal, transcranial measurement of functional activation in the rat brain by diffuse correlation spectroscopy

et al. 2017

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Abstract. Neural activity is an important biomarker for the presence of neurodegenerative diseases, cerebrovascular alterations, and brain trauma; furthermore, it is a surrogate marker for treatment effects. These pathologies may occur and evolve in a long time-period, thus, noninvasive, transcutaneous techniques are necessary to allow a longitudinal follow-up. In the present work, we have customized noninvasive, transcutaneous, diffuse correlation spectroscopy (DCS) to localize changes in cerebral blood flow (CBF) induced by neural activity. We were able to detect changes in CBF in the somatosensory cortex by using a model of electrical forepaw stimulation in rats. The suitability of DCS measurements for longitudinal monitoring was demonstrated by performing multiple sessions with the same animals at different ages (from 6 to 18 months). In addition, functional DCS has been cross-validated by comparison with functional magnetic resonance imaging (fMRI) in the same animals in a subset of the time-points. The overall results obtained with transcutaneous DCS demonstrates that it can be utilized in longitudinal studies safely and reproducibly to locate changes in CBF induced by neural activity in the small animal brain. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Improving estimates of the cerebral metabolic rate of oxygen from optical imaging data

Cited by 7 publications

References 55 publications

Vascular density and distribution in neocortex

Vascular density and distribution in neocortex

A multi-data based quantitative model for the neurovascular coupling in the brain

Longitudinal, transcranial measurement of functional activation in the rat brain by diffuse correlation spectroscopy

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