【作者】 李珊珊；

【导师】 唐一源；

【作者基本信息】 大连理工大学 ， 生物物理学， 2006， 硕士

【摘要】 脑科学是当前生命科学研究的热点。大脑是一个复杂的巨系统，把复杂性科学的研究成果应用到神经科学领域，用系统的观点来分析大脑的信息处理方式，对我们认识大脑、理解大脑的行为有着非常重要的意义。本文把复杂网络理论应用到脑科学领域，构建了一个基于功能磁共振成像数据的脑功能网络，并对其进行了的探讨。 下面将本文的所做的工作以及主要结论介绍如下： 1．对脑科学、复杂网络理论以及两者相互结合的最新研究成果进行了较为全面的综述；介绍了在构建脑功能网络时需要用到的直线相关理论和大脑连通性理论； 2．分析了视觉颜色辨别的功能磁共振成像实验，利用大脑在完成任务时显著激活的体素点构建脑功能网络，分别对单人网络和九人群体结果的网络进行了分析； 3．基于脑功能网络的拓扑学特性，提出了度值图的概念。度值图是一种能够反映神经团簇间的功能相互作用的图，它能够清晰的呈现在某一特定任务下，任何选定感兴趣区中的枢纽节点和功能簇的分布模式。度值是一个体素点与其它体素点之间相互联系是否广泛的量度，因此度值图所呈现的度值大的区域也许对于实现大脑功能具有更重要的意义。我们的结果显示，T值与度值之间存在着微弱的正相关，且T值最大点与度值最大点的解剖学定位是分离的。这表明这两个值可以从不同角度、不同层面刻画大脑激活区域体素点的性质。这是一种从系统角度对大脑成像数据进行多层面分析的方法； 4．最后讨论了脑功能网络的稳定性问题，对我们建立的这个视觉任务脑功能网络的抗毁能力进行了数值模拟。结果表明，该网络具有较好的稳定性。更多还原

【Abstract】 Neuroscience is an intensively discussed topic in the field of life science. It is of great importance to apply the results of complex research into neuroscience and use systematic views to analyze the brain activation. The present study was designed to apply the theory of complex network into neuroscience and construct a functional brain network based on the data from fMRI.A brief overview of the main work and discussion is introduced:1. The study began with the literature review of the newest research results of neuroscience, complex network and their combination and introduced the theory of linear correlation and brain connection.2. The study analyzed the data of Fmri visual color identity experiment, the brain functional network was constructed by voxels which were activated significantly in the task, based on which, the analysis of individual network and 9 persons’ average network is made.3. We propose a concept named ’degree map’, which can reflect the interrelationship among voxels, and can present the hub and spatial distribution of the functional clusters within each region of interest (ROI) for a specific task. The results show that, These two values can depict the property of voxels in activated brain region from different angles and levels. The degree reflects the functional interaction. Therefore degree may have more important significance in understanding the brain function. This work offers a feasible method to analyze the brain imaging data from a systematic perspective.4. At last, the stability of brain functional network was discussed and made numerical value simulation for the anti-dilapidated ability of brain functional network. The results indicated that the network is of higher stability.更多还原