成年人脑老化全阶段的磁共振影像学研究

目前全世界尤其是中国社会即将面临严重的老龄化危机，但是我们对人脑的衰老机制知之甚少，对老化全阶段的定量度量和预测仍然缺乏无损客观定量的工具。从脑科学的角度，人脑从成年(20岁左右)已经停止发育性生长，之后为了适应环境需求开始有选择性的增强和退化(结构重塑和功能重组)，而在中年(45岁左右)之后则开始逐渐全面衰退。在上述老化全阶段，人脑的结构和功能具有怎样的变化曲线？有的群体可以在较长时间内保持较好的认知能力(甚至与青年被试相当，称为衰老延缓，successful aging)，这类群体在脑结构和功能网络上有什么特异性？能否从脑影像的角度评估和预测老化全阶段人脑的变化以及与认知能力的相关性？本项目拟以多模态磁共振脑影像(MRI)数据为基础系统地研究上述问题，在前期已有的研究基础上，进一步从脑结构和功能角度阐释成年人脑衰老全阶段的机制；建立评估和预测成年人大脑老化全阶段的客观定量模型。

At present, the world, especially the Chinese society, is confronting an unprecedented aging crisis. However, we know very little about the aging mechanism of the human brain. The quantitative measurement and prediction of the brain changes in adulthood lifespan still lacks non-invasive, rapid and quantitative tools. From the viewpoint of neuroscience, the human brain ceases developing growth around the early adulthood (~20 years old), and thereafter, selective alterations, both enhancements and deteriorations, occur during the adulthood while from the midlife the deteriorations will dominate both the brain structural and functional changes. Unfortunately, it remains elusive for many open questions about the brain in adulthood lifespan. For example, what are the change patterns for both structural and functional architectures of the brain? It is well known that many aged individuals show comparable cognitive capabilities to their younger counterparts, but what features can quantitatively characterize this successful aging process? And more generally, can we achieve an efficient way based on imaging biomarkers to quantitatively characterize the relationship between the changes in brain structures and cognitive capabilities across the adulthood lifespan? In this proposal, we will systematically investigate these questions by analyzing multiple modalities MRI data (including cognitive scales) of a large cohort from 3 imaging datasets. The entire dataset contains more than 1500 participants in cross-sectional studies and more than 500 participants in longitudinal studies. Based on our preliminary results obtained from this dataset, we will continue to explore specific features and accurate modes for evaluating and predicting the individual aging process, which has the potential to provide quantitative tools to train or intervene the aging process for successful aging.