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睁眼/闭眼数据集共享用于重现性评估静息态 fMRI 数据分析方法。

Eyes-open/eyes-closed dataset sharing for reproducibility evaluation of resting state fMRI data analysis methods.

机构信息

Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, 310015, China,

出版信息

Neuroinformatics. 2013 Oct;11(4):469-76. doi: 10.1007/s12021-013-9187-0.

Abstract

The multi-scan resting state fMRI (rs-fMRI) dataset was recently released; thus the test-retest (TRT) reliability of rs-fMRI measures can be assessed. However, because this dataset was acquired only from a single group under a single condition, we cannot directly evaluate whether the rs-fMRI measures can generate reproducible between-condition or between-group results. Because the modulation of resting state activity has gained increasing attention, it is important to know whether one rs-fMRI metric can reliably detect the alteration of the resting activity. Here, we shared a public Eyes-Open (EO)/Eyes-Closed (EC) dataset for evaluating the split-half reproducibility of the rs-fMRI measures in detecting changes of the resting state activity between EO and EC. As examples, we assessed the split-half reproducibility of three widely applied rs-fMRI metrics: amplitude of low frequency fluctuation, regional homogeneity, and seed-based correlation analysis. Our results demonstrated that reproducible patterns of EO-EC differences can be detected by all three measures, suggesting the feasibility of the EO/EC dataset for performing reproducibility assessment for other rs-fMRI measures.

摘要

多扫描静息态功能磁共振成像 (rs-fMRI) 数据集最近发布;因此,可以评估 rs-fMRI 测量的测试-重测 (TRT) 可靠性。然而,由于该数据集仅从单个组在单个条件下获得,我们不能直接评估 rs-fMRI 测量是否可以产生可重复的条件间或组间结果。由于静息状态活动的调制引起了越来越多的关注,因此了解一个 rs-fMRI 指标是否可以可靠地检测到静息活动的改变是很重要的。在这里,我们共享了一个公共的睁眼 (EO)/闭眼 (EC) 数据集,用于评估 rs-fMRI 测量在检测 EO 和 EC 之间静息状态活动变化方面的半分割重现性。例如,我们评估了三种广泛应用的 rs-fMRI 指标的半分割重现性:低频波动幅度、局部一致性和基于种子的相关分析。我们的结果表明,所有三种测量方法都可以检测到可重复的 EO-EC 差异模式,这表明 EO/EC 数据集可用于评估其他 rs-fMRI 测量的重现性。

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