CoordsFinder - software tool for systematic search for brain coordinates of interest for area-based meta-analyses
Neuroimaging studies are accumulating fast. A significant number of these studies use functional magnetic resonance imaging (fMRI) and report stereotactic brain coordinates. In the last 15 years meta-analytic software tools have been developed to identify over-arching data agreement across studies (e.g., http://www.brainmap.org/). Meta-analytic studies help establish statistical concordance and quantitatively summarize large amounts of evidence. To date there are 944 papers on fMRI meta-analyses, as indexed by Web of Science (WOS; 28/04/18). Before analyzing coordinates researchers have to compile, systematically review relevant literature and extract stereotaxic coordinates. One process of pooling information from the articles requires manual search of the articles and manual extraction the relevant data, such as coordinates (i.e., foci), contrasts (i.e., experiments) and types of analyses (whole-brain or region of interest). Another available approach is offered by software with pre-extracted information, such as Sleuth (http://brainmap.org/sleuth/), Neurosynth (http://neurosynth.org/) and other open-source programs. Critically, these methods do not have up to date datasets covering only a limited number of studies (e.g., 11406 papers in the Neurosynth and 3294 papers in the Sleuth 2.4 at the 28/04/2018), whereas, a WOS search for the keyword (“fMRI”) yields 61976 papers.
To improve the quality of the manual search for area-based meta-analyses and increase the speed of the identification of the foci of interest, we developed CoordsFinder - standalone graphical interface software for addressing the challenge of processing multiple fMRI articles reporting data in coordinate space. The software is written using WPF (C# and XAML), based on .NET Framework 4.5.2, and it supports Microsoft Windows 7 operating system or higher. The CoordsFinder estimates the foci uploaded in the software manually and searches for it inside the specified folder, which contains the pdf files of the papers, as this is the most common file format for articles. Foci coordinates can be found both in tables and in a plain text of the articles. The foci file uploaded could contain MNI or TAL space coordinates, and the software can indicate each type. In the current version, CoordsFinder can explore only files stored at the user’s computer, and process 274 papers per minute for a typical computer. Practically this software provides a solution for automatically extracting coordinates from multiple articles for effectively organizing and further analyzing data already available in the literature.