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大脑激活后耗氧量增加:使用桶状皮层光谱数据的理论注释

Increased oxygen consumption following activation of brain: theoretical footnotes using spectroscopic data from barrel cortex.

作者信息

Mayhew J, Johnston D, Martindale J, Jones M, Berwick J, Zheng Y

机构信息

Artificial Intelligence Vision Research Unit, University of Sheffield, Western Bank, Sheffield S10 2TP, United Kingdom.

出版信息

Neuroimage. 2001 Jun;13(6 Pt 1):975-87. doi: 10.1006/nimg.2001.0807.

Abstract

Optical imaging spectroscopy (OIS) and laser Doppler flowmetry (LDF) data sequences from anesthetized rats were used to determine the relationship between changes in oxy-and deoxygenated hemoglobin concentration and changes in blood volume and flow in the presence and absence of stimulation. The data from Jones et al. (accompanying paper) were used to explore the differences between two theoretical models of flow activation coupling. The essential difference between the two models is the extension of the model of Buxton and Frank by Hyder et al. (1998, J. Appl. Physiol. 85: 554--564) to incorporate change in capillary diffusivity coupled to flow. In both models activation-increased flow changes increase oxygen transport from the capillary; however, in Hyder et al.'s model the diffusivity of the capillary itself is increased. Hyder et al. proposed a parameter (Omega), a scaling "constant" linking increased blood flow and oxygen "diffusivity" in the capillary bed. Thus, in Buxton and Frank's theory, Omega = 0; i.e., there are no changes in diffusivity. In Hyder et al.'s theory, 0 < Omega < 1, and changes in diffusivity are assumed to be linearly related to flow changes. We elaborate the theoretical position of both models to show that, in principle, the different predictions from the two theories can be evaluated using optical imaging spectroscopy data. We find that both theoretical positions have limitations when applied to data from brief stimulation and when applied to data from mild hypercapnia. In summary, the analysis showed that although Hyder et al.'s proposal that diffusivity increased during activation did occur; it was shown to arise from an implementation of Buxton and Frank's theory under episodes of brief stimulation. The results also showed that the scaling parameter Omega is not a constant as the Hyder et al. model entails but in fact varies over the time course of the flow changes. Data from experiments in which mild hypercapnia was administered also indicated changes in the diffusivity of the capillary bed, but in this case the changes were negative; i.e., oxygen transport from the capillary decreased relative to baseline under hypercapnia. Neither of the models could account for the differences between the hypercapnia and activation data when matched for equivalent flow changes. A modification to the models to allow non-null tissue oxygen concentrations that can be moderated by changes due to increased metabolic demand following increased neural activity is proposed. This modification would allow modulation of oxygen transport from the capillary bed (e.g., changes in diffusivity) by tissue oxygen tension and would allow a degree of decoupling of flow and oxygen delivery, which can encompass both the data from stimulation and from hypercapnia.

摘要

利用来自麻醉大鼠的光学成像光谱(OIS)和激光多普勒血流仪(LDF)数据序列,来确定在有无刺激的情况下,氧合血红蛋白和脱氧血红蛋白浓度变化与血容量和血流变化之间的关系。来自琼斯等人(随附论文)的数据用于探究两种血流激活耦合理论模型之间的差异。这两种模型的本质区别在于,海德等人(1998年,《应用生理学杂志》85: 554 - 564)对巴克斯顿和弗兰克模型进行了扩展,纳入了与血流耦合的毛细血管扩散率变化。在这两种模型中,激活导致的血流变化增加会使从毛细血管的氧气输送增加;然而,在海德等人的模型中,毛细血管本身的扩散率增加。海德等人提出了一个参数(Ω),这是一个标度“常数”,将毛细血管床中增加的血流与氧气“扩散率”联系起来。因此,在巴克斯顿和弗兰克的理论中,Ω = 0;即扩散率没有变化。在海德等人的理论中,0 < Ω < 1,并且假设扩散率的变化与血流变化呈线性相关。我们详细阐述了这两种模型的理论观点,以表明原则上,可以使用光学成像光谱数据来评估这两种理论的不同预测。我们发现,当应用于短暂刺激的数据以及应用于轻度高碳酸血症的数据时,这两种理论观点都存在局限性。总之,分析表明,尽管海德等人提出的激活期间扩散率增加的观点确实存在;但结果表明,这是在短暂刺激期间巴克斯顿和弗兰克理论的一种表现形式。结果还表明,标度参数Ω并非如海德等人的模型所要求的那样是一个常数,实际上它会在血流变化的时间过程中发生变化。给予轻度高碳酸血症的实验数据也表明毛细血管床的扩散率发生了变化,但在这种情况下变化是负的;即高碳酸血症时从毛细血管的氧气输送相对于基线下降。当匹配等效血流变化时,这两种模型都无法解释高碳酸血症和激活数据之间的差异。有人提出对模型进行修改,以允许非零的组织氧浓度,这种浓度可因神经活动增加后代谢需求增加所导致的变化而受到调节。这种修改将允许组织氧张力调节从毛细血管床的氧气输送(例如,扩散率的变化),并且将允许血流与氧气输送有一定程度的解耦,这可以涵盖刺激和高碳酸血症的数据。

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