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中文摘要：
针对视感知中的特征捆绑问题主要通过以下三个方面进行研究：首先，构建静息态和任务态的脑网络，利用堆结构贪婪算法进行模块划分；其次，计算视觉脑区之间的z值；再次，计算视觉脑区之间的连接度。实验证明了视觉信息加工的两条通路、脑网络动态平衡特性以及参与绑定的重要脑区。研究视觉特征捆绑认知过程，有助于计算机视觉建模，为提高图像识别技术奠定基础。
英文摘要：
In order to research feature binding of visual perception, this paper used three different methods as follows. First- ly, constructed brain networks in resting state and tasking state, and divided them into some modules by use of CNM. Second- ly, computed Z values between visual regions. Thirdly, computed the degrees of connection between different visual brain re- gions. Experiments confirm the two pathways of visual information processing, dynamic equilibrium characteristics of brain net- work and the important brain areas of visual feature binding. By means of studying cognitive processes of visual feature bin- ding, these will help contribute to computer visual modeling process and improve the technology of image recognition.
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Machine learning classifier using abnormal brain network topological metrics in major depressive dis
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