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

总结 短暂的神经活动会触发一种复杂但相当稳定的血管反应。这 血液动力学响应函数（HRF）在流行的功能成像方法中被广泛利用， 功能性磁共振成像（fMRI）和基于反射的光学成像。正确理解和 利用这些成像技术需要详细了解HRF。而且由于 大脑是持续活跃的，瞬态反应在健康的正常运作中可能是重要的。 个脑袋脑血管病变很可能会影响这种短暂的反应，所以更完整的 了解它们的正常特征将使它们能够用作早期或现存病理学的诊断。 HRF的生理学和物理学还没有得到很好的理解。标准的“气球”模型 结合了一个非线性的顺应性元素来解释流量和体积的变化。然而，静脉容量 气球模型的变化还没有得到实验证实，现在有很大的争议， 个话题吧我们已经开发了一个模型，结合了一个新的线性流动描述与空间分辨 氧气运输流动模型包括移动的血液的惯性动力学，其不能被忽略， 机械地调节流动反应的较大的小动脉。 我们建议进一步发展的模型，再加上详细的表征的HRF。的 模型将被扩展以处理血氧水平依赖性反应，并增加细节 和流描述的真实性。在实验中，我们将使用多感官刺激协议， 感觉整合任务，以唤起整个大脑的HRF，并使用高- 分辨率动脉自旋标记和功能磁共振成像，以检查这些反应的特点和变异性， 不同的脑组织结果将提供一个丰富的数据集，以进一步测试我们的模型，并评估各种 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.