Data for: A principled approach to synthesize neuroimaging data for replication and exploration

The synthetic predictor tables and fully synthetic neuroimaging data produced for the analysis of fully synthetic data in the current study are available as Research Data available from Mendeley Data. Ten fully synthetic datasets include synthetic gray matter images (nifti files) that were generated for analysis with simulated participant data (text files). An archive file predictor_tables.tar.gz contains ten fully synthetic predictor tables with information for 264 simulated subjects. Due to large file sizes, a separate archive was created for each set of synthetic gray matter image data: RBS001.tar.gz, …, RBS010.tar.gz. Regression analyses were performed for each synthetic dataset, then average statistic maps were made for each contrast, which were then smoothed (see accompanying paper for additional information).

The supplementary materials also include commented MATLAB and R code to implement the current neuroimaging data synthesis methods (SKexample.zip). The example data were selected from an earlier fMRI study (Kuchinsky et al., 2012) to demonstrate that the current approach can be used with other types of neuroimaging data. The example code can also be adapted to produce fully synthetic group-level datasets based on observed neuroimaging data from other sources. The zip archive includes a document with important information for performing the example analyses, and details that should be communicated with recipients of a synthetic neuroimaging dataset.

Kuchinsky, S.E., Vaden, K.I., Keren, N.I., Harris, K.C., Ahlstrom, J.B., Dubno, J.R., Eckert, M.A., 2012. Word intelligibility and age predict visual cortex activity during word listening. Cerebral Cortex 22, 1360–71. https://doi.org/10.1093/cercor/bhr211

本研究中为分析全合成数据所生成的合成预测表和全合成神经影像数据，均可作为研究数据从Mendeley Data获取。包含合成灰质图像（nifti文件）的十个全合成数据集中，这些图像是针对模拟参与者的数据（文本文件）生成的。包含264个模拟受试者信息的十个全合成预测表存于名为predictor_tables.tar.gz的归档文件中。鉴于文件体积庞大，为每套合成灰质图像数据创建了单独的归档：RBS001.tar.gz，……，RBS010.tar.gz。对每个合成数据集进行了回归分析，随后针对每个对比度制作了平均统计图，并对这些图像进行了平滑处理（有关更多信息，请参阅随附论文）。补充材料还包括注释过的MATLAB和R代码，用于实现当前的神经影像数据合成方法（SKexample.zip）。示例数据选自早期的fMRI研究（Kuchinsky等，2012），以证明当前方法可用于其他类型的神经影像数据。该示例代码亦可根据其他来源观察到的神经影像数据进行调整，以生成基于观察数据的全合成组级数据集。zip归档文件中包含了一份执行示例分析的重要信息文档，以及应与合成神经影像数据集接收者沟通的详细信息。

Kuchinsky, S.E., Vaden, K.I., Keren, N.I., Harris, K.C., Ahlstrom, J.B., Dubno, J.R., Eckert, M.A., 2012. Word intelligibility and age predict visual cortex activity during word listening. Cerebral Cortex 22, 1360–71. https://doi.org/10.1093/cercor/bhr211