Mild cognitive impairment (MCI) is the early stage of Alzheimer's disease (AD). Inductive reasoning is one of the most important advanced thinking functions of the human brain. The neural basis of its cognitive components and the mechanism of brain injury in MCI remain unclear. We will collect magnetic resonance imaging (MRI) data of MCI and normal controls. In this project, we will combine the blood oxygen level dependent functional MRI (BOLD-fMRI) and the arterial spin labeling perfusion weighted image (ASL-PWI) technique to process the MRI data. By using task based BOLD-fMRI method,we first indentified brain activation area under different inductive reasoning tasks and compared the differences between MCI and the control group. And then, by using resting state BOLD-fMRI method, we plan to construct the whole brain functional network based on the key activation area, and acquire the abnormal network characteristics of MCI. By using ASL-PWI method, we will show the brain regions of the decreased regional cerebral blood flow in MCI patients and extract the measurable information. By the experimental design of different inductive reasoning tasks and comprehensive analysis of multimodal MRI technology, the study aims to clarify the relationship among the inductive reasoning activation area, abnormal network characteristics and perfusion, deeply understand the brain injury mechanism of impaired inductive reasoning ability of MCI, and acquire the sensitive imaging biomarker of MCI early diagnosis based on multi-feature parameters.
轻度认知功能障碍(MCI)是阿尔茨海默病(AD)的早期阶段,归纳推理是人脑最重要的高级思维功能之一,对其认知成分的神经基础及其在MCI中的脑损伤机制仍不清楚,本课题拟收集MCI和正常人磁共振数据,将血氧水平依赖的功能磁共振成像(BOLD-fMRI)和动脉自旋标记的脑灌注成像(ASL-PWI)两种新技术融合,采用任务态BOLD-fMRI识别不同归纳推理任务的脑激活区,分析MCI和正常对照组的差异,采用静息态BOLD-fMRI方法构建基于关键激活脑区的全脑功能网络,提取MCI的异常网络,采用ASL-PWI显示MCI患者脑血流量减低脑区,获取定量信息,本课题通过不同归纳推理任务的实验设计及多模态磁共振技术综合分析,旨在阐明归纳推理激活区、异常网络属性与脑灌注损伤的关联规律,深入理解MCI归纳推理能力异常的脑损伤机制,同时基于多特征参数,筛选早期诊断MCI的敏感影像学指标。
归纳推理是人脑最重要的高级思维功能之一,在阿尔茨海默病(Alzheimer's disease, AD)的早期阶段,即轻度认知功能障碍(Mild cognitive impairment, MCI)时已出现功能异常,然而MCI 归纳推理能力下降的脑损伤机制并不清楚。本课题应用多模态磁共振技术,通过大量实验数据,我们主要取得了如下成果:(1)揭示了归纳推理过程中重要认知成分的神经机制;并研究了规则有效性和时间压力对数字归纳推理的影响。(2)利用多模态磁共振技术发现了MCI和AD患者的脑功能网络和血流改变模式,探讨了其关联规律及脑损伤机制。(3)建立了基于多特征参数的早期认知障碍预测分类模型,获取了敏感的影像学指标。这些成果为深入探索MCI归纳推理认知异常的脑损伤机制及早期诊断提供了科学依据,具有重要的理论意义和实践价值。
{{i.achievement_title}}
数据更新时间:2023-05-31
跨社交网络用户对齐技术综述
基于 Kronecker 压缩感知的宽带 MIMO 雷达高分辨三维成像
基于SSVEP 直接脑控机器人方向和速度研究
伴有轻度认知障碍的帕金森病~(18)F-FDG PET的统计参数图分析
城市轨道交通车站火灾情况下客流疏散能力评价
针刺调节轻度认知障碍患者默认网络的多模态神经影像学研究
基于多模态磁共振轻度创伤性脑损伤后认知障碍神经机制的纵向研究
视神经脊髓炎患者认知功能障碍脑机制的MRI研究
帕金森病轻度认知功能障碍转归预测的多模态核磁共振成像研究