Analysis of stroke-induced changes in connectivity and neural activity

项目摘要 认知功能障碍是脑卒中常见的功能性后遗症，但其神经基础是脑卒中后的认知功能障碍。 尚待确认白色高信号（WMH）是一种进行性变性形式，也是 小血管疾病是脑卒中后认知功能障碍的主要危险因素。新兴研究支持 WMH负荷与海马体积之间呈反比关系，海马是一个关键的大脑结构 可能会发生二次退化。初步数据显示海马体 远离皮质卒中，卒中后不受急性影响。但是我们的电生理数据显示 大脑皮层和海马体之间的网络通讯在慢性中风中被破坏， 这与基于连接体的分析一致，显示受损的皮质区域与 神经网络参与空间学习。我们假设WM损伤易导致卒中后认知功能障碍， 由于学习和记忆区域中的连接性丧失和远程退化加剧而导致的损伤。 我们的近期目标是从脑的角度了解中风如何影响海马功能 连通性。作为一个原理性的转化研究，我们将在自发性高血压大鼠中进行 在检测到自发性WM病变的年龄。确定脑卒中后连接丧失的作用 在WM损伤的情况下，我们将首先绘制WM和WM中的损伤位置和程度， GM，并量化海马子区体积。然后我们将确定结构连接性的变化 利用基于neuroVIISAS的连接体平台，利用束追踪和DTI流线型数据构建， 全球和地方网络受到影响。与海马有直接或间接联系的病变区域 将被识别。将确定中风和WM损伤对学习/记忆功能的动态影响 通过模拟一对病变区和功能区之间的共激活模式， 使用加权和定向连接体的FitzHugh-Nagumo神经元模拟学习。 将评估海马活动和网络通信的电生理学相关性， 补充神经行为和连接方面的数据。我们预计，病变范围，位置， 而高血压对网络连接的影响将为研究WM损伤的作用提供线索 中风后认知能力下降它也可以使识别中继大脑区域进行功能性 变化以及可能的连接丢失的进展。

Project Summary Cognitive impairment is a common functional sequela of stroke, although the neural substrate underlying which is yet to be identified. White matter hyperintensity (WMH), a progressive form of degeneration and a marker of small vessel disease, is a major risk factor for post stroke cognitive impairment. Emerging studies support an inverse relationship between WMH burden and the volume of the hippocampus, which is a key brain structure for memory function and may undergo secondary degeneration. Preliminary data show that the hippocampus is remote from cortical stroke and not affected acutely after stroke. However, our electrophysiology data suggest that network communication between the cortex and hippocampus became disrupted during chronic stroke, which is consistent with connectome-based analysis showing damaged cortical regions are well connected with neural networks involved in spatial learning. We hypothesize that WM lesions predispose to post stroke cognitive impairment due to exacerbated connectivity loss and remote degeneration in the learning and memory region. Our immediate goal is to understand how stroke affects hippocampal function from the perspective of brain connectivity. As a proof-of-principle translational study, we will carry it out in the spontaneously hypertensive rats at an age when spontaneous WM lesion is detected. To determine the role of connectivity loss in post stroke cognitive impairment in the setting of WM lesion, we will first map the lesion location and extent in both WM and GM, and quantify hippocampal subfield volume. We will then determine the changes in structural connectivity with the neuroVIISAS-based connectome platform built with tract tracing and DTI streamline data to reveal how global and local networks are affected. Lesioned regions with direct or indirect connections with the hippocampus will be identified. The dynamic effect of stroke and WM lesion on learning/memory function will be determined by modeling the coactivation pattern between a pair of lesioned region and functional region involved in spatial learning with FitzHugh-Nagumo neuron simulation using the weighted and directed connectome. Electrophysiology correlates of hippocampal activity and network communication will be assessed to complement data in neurobehavior and connectivity. We anticipate that the knowledge of lesion extent, location, and the effect on network connectivity in the setting of hypertension will provide insight into the role of WM lesion in post stroke cognitive decline. It may also enable the identification of relay brain regions undergoing functional changes and possibly the progression of connectivity loss.