基于近红外成像的双脑神经解码关键技术研究

项目名称： 基于近红外成像的双脑神经解码关键技术研究

项目编号： No.61503030

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 自动化学科

项目作者： 段炼

作者单位： 深圳大学

项目金额： 20万元

中文摘要： 双脑神经解码是一项信息科学与社会神经科学交叉的最前沿技术。双脑神经解码利用多脑同时成像技术观测正在进行社会交互的两名个体的神经活动，基于模式识别技术从观测到的神经信号中解码两个人的社会交互模式信息，未来将可能对人机交互智能化等多个领域起到巨大的推动作用，具有重要的理论与应用价值。目前，双脑神经解码研究刚刚起步，还存在许多关键技术问题有待解决。本项目拟基于近红外脑成像技术对双脑神经解码的关键技术问题展开研究，包括双脑解码特征提取与选择、分类器构建、解码模型可靠性与影响因素分析等。作为信息科学与社会神经科学高度交叉融合的特色项目，本研究将为双脑神经解码技术的未来发展奠定基础，也将为人类社会交互的神经机制研究提供新方法和新技术。

中文关键词： 模式识别；社会交互；脑成像；脑机接口；智能交互

英文摘要： Two-brain neural decoding, which decodes the social interaction mode of two interacting human individuals from their hyperscanning brain signals using pattern recognition techniques, is a most cutting-edge technology at the intersection of information science and social neuroscience. Two-brain neural decoding can promote the development of many fields such as intelligent human-computer interaction, therefore has important theoretical and applied values. However, as a new emerging area, two-brain neural decoding has a lot of technical problems need to be solved. Based on the functional near-infrared spectroscopy (fNIRS), the present project planned to work on the key techniques of two-brain neural decoding, including feature extraction and selection, classifier construction, as well as the reliability of the decoding model, etc. The present project combined the research forces from both information science and social neuroscience, and would establish foundations for both future two-brain neural decoding studies and human social interaction studies.

英文关键词： pattern recognition;social interaction;brain imaging;brain-computer interface;intelligent interaction