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基于感兴趣区域的功能成像数据分析。

Region of interest based analysis of functional imaging data.

作者信息

Nieto-Castanon Alfonso, Ghosh Satrajit S, Tourville Jason A, Guenther Frank H

机构信息

Department of Cognitive and Neural Systems, Boston University, 677 Beacon Street, Boston, MA 02215, USA.

出版信息

Neuroimage. 2003 Aug;19(4):1303-16. doi: 10.1016/s1053-8119(03)00188-5.

Abstract

fMRI analysis techniques are presented that test functional hypotheses at the region of interest (ROI) level. An SPM-compatible Matlab toolbox has been developed that allows the creation of subject-specific ROI masks based on anatomical markers and the testing of functional hypotheses on the regional response using multivariate time-series analysis techniques. The combined application of subject-specific ROI definition and region-level functional analysis is shown to appropriately compensate for intersubject anatomical variability, offering finer localization and increased sensitivity to task-related effects than standard techniques based on whole-brain normalization and voxel or cluster-level functional analysis, while providing a more direct link between discrete brain region hypotheses and the statistical analyses used to test them.

摘要

本文介绍了在感兴趣区域(ROI)水平上测试功能假设的功能磁共振成像(fMRI)分析技术。已开发出一个与统计参数映射(SPM)兼容的Matlab工具箱,该工具箱允许基于解剖学标记创建特定于个体的ROI掩码,并使用多变量时间序列分析技术对区域反应的功能假设进行测试。结果表明,特定于个体的ROI定义和区域水平功能分析的联合应用能够适当补偿个体间的解剖变异性,与基于全脑归一化以及体素或簇水平功能分析的标准技术相比,提供了更精确的定位以及对任务相关效应更高的敏感性,同时在离散脑区假设与用于检验这些假设的统计分析之间建立了更直接的联系。

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