基于函数型聚类方法的事件相关电位分析

Analysis of the Event Related Potential Based on the Functional Clustering

研究社会决策的动态过程对理解社会决策的认知及神经机制问题起关键作用,尤其是可提高预测的准确性.通过分解决策过程中的关键成分,提高这些成分在决策过程中发生的时间(起始点)和幅度的测量是解决这一领域的关键问题.利用函数型数据聚类方法识别匹配试验条件在额叶和枕叶诱发的ERP早期成分(如)是否存在差异,分析结果显示被试在观察不同大小的图形时所诱发的ERP在成分上存在差异.

The study of the dynamic process of social decision - making plays an important role in understanding the cognitive and neural mechanisms of social decision - making, especially the accuracy of prediction. By decomposing the key components of the decision process, the measurement of the time （starting point） and amplitude of these components in the decision making process is the key problem to solve the cognitive and neural mechanisms of social decision problem. In this paper, functional data clustering method is used to identify matching test conditions in the frontal lobe and occipital lobe induced the early ERP components whether there are differences, the results show that the differences between the subjects in the observation of different size induced graphics ERP in composition.