面向脑部复杂疾病的脑网络构建、分析及应用研究

Brain complex diseases such as neurodegenerative diseases and severe psychosis are increasingly threatening human health. Research on complex brain diseases has been widely concerned at home and abroad. In order to solve these complex brain diseases, many scientific and technological advanced countries and alliances in recent years have put forward their own brain science plans at their national development strategy on the basis of the financial support of the existing research on complex brain diseases. With the rapid development of neuroimaging technology and genomics technology, it provides a macro and micro data base for the study of brain complex diseases. How to make more reasonable use of image data and genomic data to mine effective information for the study of complex brain diseases has become a new challenge. Research on complex brain diseases based on network level is one of the hot issues at present. This project will focus on the brain network construction based on magnetic resonance multimodal image fusion, the brain network analysis of complex brain diseases, and the gene identification methods related to complex brain diseases. The aim of this project is to provide a macro-to-micro reference for the design of new disease animal models, the research and development of new drugs for treatment, and the development of individualized treatment schemes.

神经退行性疾病、重性精神病等脑部复杂疾病正越来越严重地威胁着人类健康。针对脑部复杂疾病的研究已经在国内外受到广泛关注。为了攻克这些脑部复杂疾病，近几年很多科技发达国家和联盟都在既有的脑部复杂疾病研究的财政支持基础上，相继提出了各自有所侧重的国家发展战略层面上的脑科学计划。随着神经影像技术和基因组学技术飞速发展，为脑部复杂疾病的研究提供了宏观和微观层面上数据基础。如何才能更加合理的利用影像数据和基因组数据去挖掘有效的信息来进行脑部复杂疾病的研究成为新的挑战。基于网络水平的脑部复杂疾病研究是当前热点问题之一。本项目将分别从基于磁共振多模态影像融合的脑网络构建、脑部复杂疾病的脑网络分析和脑部复杂疾病相关基因识别方法等三个方面展开研究，旨在为脑部复杂疾病的新的疾病动物模型设计、治疗新药物的研发指导和个体化的治疗方案制定提供从宏观到微观的参考。

脑网络构建、分析及应用研究是当前脑科学领域的重点课题。本项目从影像学角度出发，针对脑部复杂疾病的脑网络构建、分析及应用研究中存在的热点问题，利用复杂网络理论、概率统计方法、机器学习算法重点开展了基于磁共振多模态影像融合的脑网络构建、脑部复杂疾病的脑网络分析和脑部复杂疾病相关基因识别方法等三方面的研究，旨在从脑网络构建与分析视角解析和检测阿尔茨海默病、自闭症和精神分裂症等典型性脑部复杂疾病。本项目的成功实施将有助于脑网络构建与分析关键技术的突破，为脑部复杂疾病辅助诊断研究提供有价值的方法和工具，进而推动脑部复杂疾病辅助诊断应用系统落地，同时也为其它相似疾病辅助诊断研究提供强有力的技术支持和参考。本项目资助期内共发表论文10篇，其中国际知名SCI期刊论文8篇，中国计算机学会推荐会议论文2篇，培养副教授2人，已毕业博士生1人、已毕业硕士生4人，在读硕士生2人。项目投入直接经费27.00万元，结余0.12万元，各项支出基本与预算相符。