Applying FSL to the FIAC data: model-based and model-free analysis of voice and sentence repetition priming.

Applying FSL to the FIAC data: model-based and model-free analysis of voice and sentence repetition priming.
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DOI:
10.1002/hbm.20246
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发表时间:
2006-05
影响因子:
4.8
通讯作者:
Smith, SM
Smith, SM
中科院分区:
医学2区
文献类型:
--
作者:
Beckmann, CF;Jenkinson, M;Woolrich, MW;Behrens, TEJ;Flitney, DE;Devlin, JT;Smith, SM

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本文介绍了将FSL(FMRIB软件库)中的各种工具应用于HBM‘05功能图像分析竞赛的重复启动实验所获得的结果。我们提供了基于模型的通用线性模型(GLM)工具(FEAT)和无模型独立分量分析工具(Meloic)的分析。我们还讨论了在统计分析之前用于校正图像失真的工具的应用,以及功能磁共振成像(FMRI)时间序列建模和推理的最新进展的应用,例如使用最优约束HRF基函数建模和混合建模推理。特别是血流动力学反应函数(HRF)和混合体模型的结合,揭示了句子内容和说话人的语音启动效应都发生在双侧上颞沟(STS)的长度上。这些结果表明,这两者都是在一个基础系统中处理的,在内容和语音处理方面没有任何明显的不对称。
This article presents results obtained from applying various tools from FSL (FMRIB Software Library) to data from the repetition priming experiment used for the HBM’05 Functional Image Analysis Contest. We present analyses from the model-based General Linear Model (GLM) tool (FEAT) and from the model-free independent component analysis tool (MELODIC). We also discuss the application of tools for the correction of image distortions prior to the statistical analysis and the utility of recent advances in functional magnetic resonance imaging (FMRI) time series modeling and inference such as the use of optimal constrained HRF basis function modeling and mixture modeling inference. The combination of hemodynamic response function (HRF) and mixture modeling, in particular, revealed that both sentence content and speaker voice priming effects occurred bilaterally along the length of the superior temporal sulcus (STS). These results suggest that both are processed in a single underlying system without any significant asymmetries for content vs. voice processing.
DOI: 10.1006/nimg.2002.1132
发表时间: 2002-10-01
期刊: NEUROIMAGE
影响因子: 5.7
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期刊: NEUROIMAGE
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