Data for: Fully synthetic neuroimaging data for replication and exploration.

Published: 26 August 2020| Version 1 | DOI: 10.17632/jtts2d7dtg.1
Contributors:
Kenneth Vaden,
Mulugeta Gebregziabher,
DDC Dyslexia Data Consortium,
Mark Eckert

Description

The fully synthetic neuroimaging dataset generated for analysis of fully synthetic data in the current study are available as Research Data from Mendeley Data. Ten fully synthetic datasets are included, with synthetic gray matter images (nifti files) that were generated based on simulated participant data (text files). The file Synthetic_predictors.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

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