触觉记忆DSTM任务中感觉-运动整合的信息表征研究

Research on Information Representation of Perception and Motion in Touch Memory DSTM Task-ordinary Report

大脑神经信号(如神经元放电信号、局部电位信号)的解析是现在神经科学、认知科学等学科的重要研究领域。对脑部信号的解析将会帮助我们了解大脑的编码、解码方式,进而设计出多样的脑机交互接口,并有可能应用到工业生产、医疗器械等方面。该文的研究由课题一提供猴脑信号数据,由课题三对数据进行了整理,并使用机器学习的方法对数据进行了一定的分析,比如:根据数据本身的特征进行了简单的分类;观察了数据的相关性;利用特异神经元的性质尝试设计分类器,通过猴脑信号对实验类型进行一定的预测。

Decoding of the brain neural signals （such as the spike signals and the local field potential） is an important field of the neuroscience and cognitive science. The analysis of brain neural signals will help us understand the brain’s encoding and decoding principles better, and then design a variety of brain-machine interfaces. This research may be finally applied to industrial production, medical equipment and other aspects. The research is based on the data provided by Project One, and the data analysis is provided by Project Three by using machine learning methods. Machine learning methods include simple clustering of data, computing correlation of the data from different parts of the cortex, making use of the nature of the specific neurons to design classifiers, in order to predict the pattern of experiment trials through monkey brain signals.