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Hum Brain Mapp. 2017 Jan;38(1):7-11. doi: 10.1002/hbm.23342. Epub 2016 Aug 11.

Implementation errors in the GingerALE Software: Description and recommendations.

Author information

Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Germany.
Institute of Clinical Neuroscience and Medical Psychology, Heinrich-Heine University Düsseldorf, Germany.
Department of Physics, Florida International University, Miami, Florida.
Research Imaging Institute, University of Texas Health Science Center at San Antonio, Texas.
Department of Radiology, University of Texas Health Science Center at San Antonio, Florida.
South Texas Veterans Health Care System, San Antonio, Texas.


Neuroscience imaging is a burgeoning, highly sophisticated field the growth of which has been fostered by grant-funded, freely distributed software libraries that perform voxel-wise analyses in anatomically standardized three-dimensional space on multi-subject, whole-brain, primary datasets. Despite the ongoing advances made using these non-commercial computational tools, the replicability of individual studies is an acknowledged limitation. Coordinate-based meta-analysis offers a practical solution to this limitation and, consequently, plays an important role in filtering and consolidating the enormous corpus of functional and structural neuroimaging results reported in the peer-reviewed literature. In both primary data and meta-analytic neuroimaging analyses, correction for multiple comparisons is a complex but critical step for ensuring statistical rigor. Reports of errors in multiple-comparison corrections in primary-data analyses have recently appeared. Here, we report two such errors in GingerALE, a widely used, US National Institutes of Health (NIH)-funded, freely distributed software package for coordinate-based meta-analysis. These errors have given rise to published reports with more liberal statistical inferences than were specified by the authors. The intent of this technical report is threefold. First, we inform authors who used GingerALE of these errors so that they can take appropriate actions including re-analyses and corrective publications. Second, we seek to exemplify and promote an open approach to error management. Third, we discuss the implications of these and similar errors in a scientific environment dependent on third-party software. Hum Brain Mapp 38:7-11, 2017.


cluster inference; fMRI; false positives; meta-analysis; statistics

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