视觉信息是人类感知和认识外部世界的最主要途径之一。人脑在复杂视觉信息处理方面具有高效、鲁棒、抗噪等特点，具有计算机视觉无法比拟的优越性。fMRI和EEG作为能够对大脑的功能活动进行无损和反复测量的最佳手段，已成为研究人脑视觉感知机制的主要途径。本项目拟基于fMRI/EEG信号，用先进的计算方法建立从人类视觉系统与外界视觉刺激信息之间的映射模型，探索大脑视觉信息处理的过程和机理，并利用机器智能实现对人类视觉感知功能的模拟，从而提升计算机处理视觉信息的能力。与此同时，我们还将研究利用深度学习所得到的视觉特征与大脑视觉信息处理的关系，理解各层特征在大脑皮层的神经表达，并利用深度学习建立视觉信息的神经编解码模型。该研究对脑科学和智能技术具有重要的理论和现实意义。

Visual information is one of the most important ways of human perception and understanding of the world. The human brain has the characteristics of high efficiency, robust and anti-noise in complex visual information processing, compared with computer vision. FMRI and EEG as the best means to measure the brain activity, become the main way to study the mechanism of human visual perception. This project intends to use advanced computing method to establish the mapping model between the visual system and the external visual stimulation information, explore the mechanism of brain visual information processing, and use machine intelligence to simulate human visual perception function, and thus enhance the ability of computer processing visual information. At the same time, we will study the relationship between deep learning and brain visual information processing, understanding the expression of each layer in the cerebral cortex, and the use of deep learning's visual signal for the brain to encode and decode. This study has important theoretical and practical significance for brain science and intelligent technology.