期刊
NEUROIMAGE
卷 38, 期 3, 页码 422-438出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2007.07.026
关键词
magnetoencephalography; inverse problem; restricted maximum likelihood
资金
- Medical Research Council [MC_U105579226] Funding Source: Medline
- Wellcome Trust Funding Source: Medline
- MRC [MC_U105579226] Funding Source: UKRI
- Medical Research Council [MC_U105579226] Funding Source: researchfish
We address some key issues entailed by population inference about responses evoked in distributed brain systems using magnetoencephalography (MEG). In particular, we look at model selection issues at the within-subject level and feature selection issues at the between-subject level, using responses evoked by intact and scrambled faces around 170 ms (M170). We compared the face validity of subject-specific forward models and their summary statistics in terms of how estimated responses reproduced over subjects. At the within-subject level, we focused on the use of multiple constraints, or priors, for inverting distributed source models. We used restricted maximum likelihood (ReML) estimates of prior covariance components (in both sensor and source space) and show that their relative importance is conserved over subjects. At the between-subject level, we used standard anatomical normalization methods to create posterior probability maps that furnish inference about regionally specific population responses. We used these to compare different summary statistics, namely; (i) whether to test for differences between condition-specific source estimates, or whether to test the source estimate of differences between conditions, and (ii) whether to accommodate differences in source orientation by using signed or unsigned (absolute) estimates of source activity. Crown Copyright (c) 2007 Published by Elsevier Inc. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据