摘要
功能磁共振技术在表象研究中得到广泛应用是表象研究追求客观化精确性的必然趋势。本文介绍了功能磁共振多变量模式分析方法及其演变历程,探讨了借助该方法实现"视觉表象可视化"的理论依据与亟待解决的关键问题。分析指出"视觉表象可视化"将为表象研究提供全新的研究视角与方法途径。
Over the past decade, fMRI researchers have developed increasingly aen,sitive techniques for analyzing the information repre- sented in BOLD activity. The current understanding of the goal of many fMRI studies has been achieved by extracting representational information from analyzing fMRI data in some specific region 4 the brain rather than just comparing the activation difference among experiment conditions. Multivariate pattern analysis is one of methods which have recently emerged as a promising computational technique m neurolmaging, studies. Recently, the multivariate pattern analysis method based of fMRI technology has been widely used in the field of the neuroscienee, which is significantly changing the related question and methods of the. studies of cognition. Specifically, the multivariate pattern analysis method will be applied to the study of mental imagery with the aim to improve the research of the essence and its related function of mental imagery processing. In this study. we introduced the principle and the history of the multivariate pattern analysis method; we showed the advantage of the mutlvariate pattern analysis method when compared with thai of the traditional method such as the fMRI analysis based on a general linear model. Then. we introduced the different stages of the multivariate pattern analysis in the neuroimaging studies including the classification, identification, and reconstruction. In the aspect of the classification ; the researchers focused on analyzing data from the decoding perspective and a ttemod to determine how much could be learned about the sensory stimuli, cognitive state, movement and： so on：, where the linear classifier such as the support vector machine and linear fisher classifier was widely used. In the aspect, of the stimuli identffication, the researchers were interested in underanng how activity varies in different brain regions when there is concurrent variation in the world by analyzing fMRI data with the encoding model such as the general linear model.
出处
《心理科学》
CSSCI
CSCD
北大核心
2014年第3期573-580,共8页
Journal of Psychological Science
基金
国家自然科学基金项目(31371049)
国家自然科学基金专项基金项目(31140052)
国家社科基金"十二五"规划2011年度教育学一般课题(BBA110411)
省部共建人文社科重点研究基地项目(11JJD190003)的资助
关键词
表象
FMRI
多变量模式分析
解码模型编码模型
mental imagery,fMri,multivariate pattern analysis ,decoding model,encoding model
