An evaluation of the efficacy, reliability, and sensitivity of motion correction strategies for resting-state functional MRI

Code used to generate these data can be found at:<br>https://github.com/lindenmp/rs-fMRI<br>Details:These data are the fully processed and denoised time series from three of the four datasets presented in the manuscript listed below: 1) A healthy control cohort from the Beijing Zang dataset (http://fcon_1000.projects.nitrc.org/fcpClassic/FcpTable.html) 1) The healthy control and schizophrenia cohorts from the Consortium for Neuropsychiatric Phenomics dataset (https://openfmri.org/dataset/ds000030/).2) The three time points for the healthy control cohort from the Consortium for Reliability and Reproducibility (CoRR) NYU dataset (http://fcon_1000.projects.nitrc.org/indi/CoRR/html/).<br>For each participant, the results for each denoising pipeline are saved into separate, named, subdirectories. Within each of these subdirectories, the time series for each denoising pipeline are saved in cfg.mat.When loaded into matlab:cfg.roiTS{1} = Gordon parcellationcfg.roiTS{2} = Power parcellationThere are also additional parcellation time series not included in the manuscript (see run_prepro.m on GitHub for more details).<br>Also included for the CNP dataset are the Network Based Statistic (Zalesky et al. 2010. NeuroImage) outputs for each pipeline comparing healthy control and schizophrenia cohorts.<br>Together with the QC code (https://github.com/lindenmp/rs-fMRI), these data allow for the reproduction of the figures presented in the below manuscript.<br>if you use this code, please cite:<br>L. Parkes, B. D. Fulcher, M. Yucel, &amp; A. Fornito. An evaluation of the efficacy, reliability, and sensitivity of motion correction strategies for resting-state functional MRI. NeuroImage (2017).

生成本数据集的代码可于以下网址获取：https://github.com/lindenmp/rs-fMRI

【数据集说明】本数据集包含下述论文中提及的四项数据集里的三项的全处理及去噪时间序列：
1. 北京臧数据集（Beijing Zang dataset）中的健康对照组（数据来源：http://fcon_1000.projects.nitrc.org/fcpClassic/FcpTable.html）
2. 神经精神表型组联盟数据集（Consortium for Neuropsychiatric Phenomics dataset）中的健康对照与精神分裂症队列（数据来源：https://openfmri.org/dataset/ds000030/）
3. 可靠性与可重复性联盟（Consortium for Reliability and Reproducibility, CoRR）NYU数据集里健康对照组的三个时间点数据（数据来源：http://fcon_1000.projects.nitrc.org/indi/CoRR/html/）

针对每位被试，每种去噪流水线（denoising pipeline）的处理结果均保存至独立命名的子目录中。各子目录内，每种去噪流水线对应的时间序列均存储于cfg.mat文件中。在Matlab中加载该文件后：
cfg.roiTS{1} = Gordon脑区分割（Gordon parcellation）结果
cfg.roiTS{2} = Power脑区分割（Power parcellation）结果
此外还包含论文未提及的额外脑区分割时间序列（详见GitHub仓库中的run_prepro.m文件）

针对神经精神表型组联盟（CNP）数据集，还提供了每种去噪流水线的基于网络的统计量（Network Based Statistic, Zalesky等，2010年，《NeuroImage》）输出结果，用于对比健康对照组与精神分裂症队列

结合质量控制（QC）代码（https://github.com/lindenmp/rs-fMRI），本数据集可用于复现下述论文中的相关图表

若您使用本代码，请引用以下文献：
L. Parkes、B. D. Fulcher、M. Yucel与A. Fornito. 《静息态功能磁共振成像运动校正策略的有效性、可靠性与敏感性评估》，《NeuroImage》，2017年。