丛丰裕

个人信息Personal Information

教授

博士生导师

硕士生导师

主要任职:人力资源处处长(党委教师工作部部长、党委人才办公室主任)【兼党委组织部副部长】

性别:男

毕业院校:上海交通大学

学位:博士

所在单位:人力资源处(党委教师工作部、党委人才办公室)

学科:生物医学工程. 信号与信息处理. 模式识别与智能系统

电子邮箱:cong@dlut.edu.cn

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Combining PCA and Multiset CCA for Dimension Reduction when Group ICA is Applied to Decompose Naturalistic fMRI Data

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论文类型:会议论文

发表时间:2015-07-12

收录刊物:EI、CPCI-S、Scopus

卷号:2015-September

关键字:Group ICA; temporal concatenation; naturalistic fMRI; dimension reduction; Multiset CCA; PCA

摘要:An extension of group independent component analysis (GICA) is introduced, where multi-set canonical correlation analysis (MCCA) is combined with principal component analysis (PCA) for three-stage dimension reduction. The method is applied on naturalistic functional MRI (fMRI) images acquired during task-free continuous music listening experiment, and the results are compared with the outcome of the conventional GICA. The extended GICA resulted slightly faster ICA convergence and, more interestingly, extracted more stimulus-related components than its conventional counterpart. Therefore, we think the extension is beneficial enhancement for GICA, especially when applied to challenging fMRI data.