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The advantage of brief fMRI acquisition runs for multi-voxel pattern detection across runs

机译:FMRI采集运行的优势在运行中为多体素图案检测运行

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摘要

Functional magnetic resonance imaging (fMRI) studies are broken up into runs (or ‘sessions’), frequently selected to be long to minimize across-run signal variations. For investigations that use multi-voxel pattern analysis (MVPA), however, employing many short runs might improve a classifier's ability to generalize across irrelevant pattern variations and detect condition-related activity patterns. We directly tested this hypothesis by scanning participants with both long and short runs and comparing MVPA performance using data from each set of runs. Every run included presentations of faces, places, man-made objects and fruit in a blocked 1-back design. MVPA performance significantly improved from using a large number of short runs, compared to several long runs, in across-run classifications with identical amounts of data. Superior classification was found across variations in the classifier employed, feature selection procedure and region of interest. Performance improvements also extended to an information brain mapping ‘searchlight’ procedure. These results suggest that investigators looking to maximize the detection of subtle multi-voxel patterns across runs might consider employing short fMRI runs.
机译:功能性磁共振成像(FMRI)研究被分解为运行(或“会话”),经常选择长度以最小化跨越信号变化。然而,对于使用多体素图案分析(MVPA)的调查,然而,采用许多短路可能会改善分类器横跨无关模式变化和检测条件相关的活动模式的能力。我们通过扫描参与者与长期和短期的参与者直接测试了这一假设,并使用来自每组运行的数据进行比较MVPA性能。每次运行都包括面部,地方,人造物体和果实的陈述,在一个封锁的1背面设计中。与多个长期运行相比,MVPA性能显着改善,与几个长期运行相比,在运行数量的数据中。在所采用的分类器的变化中发现了卓越的分类,特征选择程序和感兴趣的区域。性能改进还扩展到信息大脑映射'探照灯'程序。这些结果表明,寻求最大限度地检测跨运行的微妙多体素模式的调查人员可能考虑使用短FMRI运行。

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