Measurements and modeling of the hemodynamic response function in human cerebral cortex

摘要 短暂的神经活动以一种复杂但相当稳定的形式触发血管反应。这 血流动力学响应函数(HRF)在流行的功能成像方法中得到了广泛的应用，例如 功能磁共振成像(FMRI)和基于反射的光学成像。正确的解释和 利用这些成像技术需要对高频辐射有详细的了解。此外，因为 大脑是持续活跃的，瞬时反应很可能是健康的人正常运行的重要因素 大脑。脑血管病变很可能会影响这种瞬时反应，所以更完整 了解它们的正常特征将使它们能够用于早期或现有病理学的诊断。 HRF的生理学和物理学还没有被很好地理解。标准的“气球”模型 结合了一个非线性顺应元素来解释流量和体积变化。然而，静脉容量 气球模型的改变还没有得到实验证实，现在关于气球模型的改变存在很大争议 主题。我们开发了一种新的线性流动描述与空间分辨相结合的模型 氧气输送。流动模型包含了运动的血液的惯性动力学，这是不能忽略的 机械调节血流反应的较大小动脉。 我们建议进一步发展该模型，并详细描述HRF。这个 将模型扩展为处理血氧水平依赖的反应，并增加细节 和流程描述的现实主义。在实验中，我们将使用多感官刺激方案 感觉整合任务，以在整个大脑中广泛地唤起HRF，并使用High-Ware来评估反应 分辨率动脉自旋标记和fMRI检查这些反应的特征和变异性 不同的脑组织。结果将提供丰富的数据集，以进一步测试我们的模型和评估各种 关于神经血管和神经代谢耦合的假说。

Summary Brief periods of neural activity trigger a vascular response with a complex but fairly stable form. This hemodynamic response function (HRF) is extensively exploited in popular functional imaging methods such as functional magnetic resonance imaging (fMRI) and reflectance based optical imaging. Proper interpretation and utilization of these imaging techniques requires a detailed understanding the HRF. Moreover, because the brain is continually active, transient responses are likely to be important in normal operation of the healthy brain. Cerebrovascular pathology is likely to affect such transient responses, so a more complete understanding of their normal character will enable their use as diagnostics of incipient or extant pathology. The physiology and physics of the HRF are not well understood. The standard “balloon” model incorporates a non-linear compliant element to explain flow and volume changes. However, the venous volume changes of the balloon model have not been confirmed experimentally, and there is now great controversy on the subject. We have developed a model that combines a novel linear flow description with spatially resolved oxygen transport. The flow model includes the inertial dynamics of moving blood, which cannot be neglected in the larger arterioles that mechanically mediate the flow response. We propose further development of the model, coupled with detailed characterization of the HRF. The model will be expanded to deal with the blood oxygen-level dependent response, and to increase the detail and realism of the flow description. Experimentally, we will use a multi-sensory stimulus protocol with a sensory integration task to evoke the HRF broadly across the brain, and evaluate the responses using high- resolution arterial spin labeling and fMRI to examine the character and variability of these responses within different brain tissues. The results will provide a rich dataset to further test our model and evaluate various hypotheses about neurovascular and neurometabolic coupling.