Eyes-Open/Eyes-Closed Dataset Sharing for Reproducibility Evaluation of Resting State fMRI Data Analysis Methods
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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.
KeywordsResting state fMRI measures Reproducibility Data sharing Eyes open Eyes closed
This work was supported by the National Natural Science Foundation of China (Grant No. 30770594) and the National High Technology Program of China (863) (Grant No. 2008AA02Z405).
Conflict of Interest
The authors declare that they have no conflict of interest.
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