多空间尺度多变量模式分析方法的验证

J. Bulthé, J. V. D. Hurk, Nicky Daniels, B. Smedt, H. O. D. Beeck
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引用次数: 6

摘要

大多数使用多体素模式分析(MVPA)的fMRI研究将这些分析限制在一个空间尺度上。然而,最近[1]使用了一种多空间尺度方法,将三个层次的MVPA分析结合了16名受试者的fMRI数据,这些受试者执行了数字比较任务:全脑MVPA,基于感兴趣区域(ROI)的MVPA和小半径探照灯。[1]的结果清楚地证明了在MVPA分析中纳入不同空间尺度的必要性,以得出关于效应的神经表征如何在大脑中分布的结论。我们通过使用三个模拟fMRI数据集来测试本实证研究中使用的方法的有效性。模拟数据和实际数据[1]都证实了分析数据在不同空间尺度上与MVPA的相关性。
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A validation of a multi-spatialscale method for multivariate pattern analysis
Most fMRI studies using Multi-Voxel Pattern Analysis (MVPA) restrict these analyses to merely one spatial scale. However, recently [1] used a multi-spatial scale method combining three levels of MVPA analysis on fMRI data from 16 subjects who performed a number comparison task: whole-brain MVPA, Regions Of Interest (ROI) based MVPA, and a small radius searchlight. The results of [1] clearly demonstrated the necessity of incorporating different spatial scales in MVPA analysis to draw conclusions on how the neural representations of the effects are distributed across the brain. We tested the validity of the method used in this empirical study by using three simulated fMRI datasets. Both simulated data and the real data [1] confirmed the relevance of analyzing data with MVPA on different spatial scales.
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