Characterization of neurovascular and neurometabolic coupling of the negative BOLD response in human

项目摘要 对于基于任务的功能磁共振成像（fMRI），正血氧水平依赖 （BOLD）响应已被广泛使用，并且通常假定它线性地反映局部神经活动。 然而，大脑区域的很大一部分在激活时以信号减少来响应，称为“激活”。 阴性BOLD响应（NBR）。虽然负BOLD响应（NBR）及其起源已被 广泛探讨了NBR的时间特征和空间结构，以及相应的基础 生理动力学仍然知之甚少。 我们建议调查动态的NBR诱发的一个简短的刺激-负血流动力学 反应功能（nHRF）及其潜在的神经血管和神经代谢反应，使用我们的新的 高时空分辨率BOLD和动脉自旋标记（ASL）功能磁共振成像的实验范例 方式。高空间和时间分辨率BOLD测量将解决的时间动态的 nHRF作为皮质深度和沿皮质沿着与相邻正BOLD反应的距离的函数 面我们还通过测量NBR的动态来评估移位不变的时间线性， 刺激持续时间精细时空采样ASL测量结合新的刺激- 发作时间抖动方案将提供与脑缺血相关的脑血流的精确量化。 灰质内的NBR。我们提出了我们的新的计算模型的基础上提示动脉动力学 在最近的实验研究中观察到，能够估计现实的神经代谢反应相关的 与NHRF该模型将提供一个更好的详细解释的基本生理组成部分 与nHRF有关。 我们提出的研究将提供一个详细的了解神经血管和神经代谢 与nHRF相关的（去）耦合，扩展了我们对正常脑功能的了解。这些细节与 在以前的研究中，无法精确地了解NBR及其生理学。最终，成功 我们提出的研究将激励使用所提出的功能磁共振成像方法和大脑建模方案， 涉及神经血管和神经代谢偶联的病理学。

Project Summary For task-based functional magnetic resonance imaging (fMRI), the positive blood-oxygen-level-dependent (BOLD) response has been widely used and often assumed that it linearly reflects local neural activity. However, a significant portion of brain regions responds with signal decreases upon activation, known as the negative BOLD response (NBR). Although the negative BOLD response (NBR) and its origin have been explored extensively, temporal characteristics and spatial structure of the NBR, and corresponding underlying physiological dynamics are still poorly understood. We propose to investigate dynamics of the NBR evoked by a brief stimulus –the negative hemodynamic response function (nHRF) and its underlying neurovascular and neurometabolic responses using our novel experimental paradigms with high spatiotemporal resolution BOLD and arterial spin labelling (ASL) fMRI modalities. High spatial and temporal resolution BOLD measurements will resolve temporal dynamics of the nHRF as a functional of cortical depth and distance from adjacent positive BOLD responses along the cortical surface. We also evaluated shift-invariant temporal linearity by measuring dynamics of the NBR for varying stimulus durations. Fine spatiotemporal sampling ASL measurements in conjunction with a novel stimulus- onset-time dithering scheme will provide accurate quantification of the cerebral blood flow associated with the NBR within gray matter. We advance our novel computational model based on prompt arterial dynamics observed in recent experimental studies, enabling estimation of realistic neurometabolic response associated with the nHRF. The model will offer a better detailed interpretation of the underlying physiological components associated with the nHRF. Our proposed research will provide a detailed understanding of neurovascular and neurometabolic (de-)coupling associated with nHRF, expanding our knowledge of normal brain functions. Such details with precision to understand the NBR and its physiology was not available in previous studies. Ultimately, success of our proposed research will motivate use of the proposed fMRI approaches and modeling schemes for brain pathologies that involve neurovascular and neurometabolic coupling.