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Neuroimage. 2016 Jan 1;124(Pt B):1245-53. doi: 10.1016/j.neuroimage.2015.07.060. Epub 2015 Jul 29.

ANIMA: A data-sharing initiative for neuroimaging meta-analyses.

Author information

1
Institute of Neuroscience and Medicine 1, Research Centre Jülich, Jülich, Germany. Electronic address: a.reid@fz-juelich.de.
2
Institute of Neuroscience and Medicine 1, Research Centre Jülich, Jülich, Germany; Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University, Düsseldorf, Germany; INRIA, Neurospin, bat 145, CEA Saclay, 91191 Gif-sur-Yvette, France.
3
Institute of Neuroscience and Medicine 1, Research Centre Jülich, Jülich, Germany; Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University, Düsseldorf, Germany.
4
Institute of Neuroscience and Medicine 1, Research Centre Jülich, Jülich, Germany; Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital Aachen, Aachen, Germany.
5
University of Texas Health Sciences Center at San Antonio, San Antonio, TX, USA.
6
Florida International University, Miami, FL, USA.
7
Institute of Neuroscience and Medicine 1, Research Centre Jülich, Jülich, Germany; C. & O. Vogt Institute for Brain Research, Heinrich Heine University, Düsseldorf, Germany.
8
Institute of Neuroscience and Medicine (INM-2), Research Centre Jülich, 52425 Jülich, Germany; JARA-BRAIN, Jülich-Aachen Research Alliance, 52425 Jülich, Germany.

Abstract

Meta-analytic techniques allow cognitive neuroscientists to pool large amounts of data across many individual task-based functional neuroimaging experiments. These methods have been aided by the introduction of online databases such as Brainmap.org or Neurosynth.org, which collate peak activation coordinates obtained from thousands of published studies. Findings from meta-analytic studies typically include brain regions which are consistently activated across studies for specific contrasts, investigating cognitive or clinical hypotheses. These regions can be subsequently used as the basis for seed-based connectivity analysis, or formally compared to neuroimaging data in order to help interpret new findings. To facilitate such approaches, we have developed a new online repository of meta-analytic neuroimaging results, named the Archive of Neuroimaging Meta-analyses (ANIMA). The ANIMA platform consists of an intuitive online interface for querying, downloading, and contributing data from published meta-analytic studies. Additionally, to aid the process of organizing, visualizing, and working with these data, we present an open-source desktop application called Volume Viewer. Volume Viewer allows users to easily arrange imaging data into composite stacks, and save these sessions as individual files, which can also be uploaded to the ANIMA database. The application also allows users to perform basic functions, such as computing conjunctions between images, or extracting regions-of-interest or peak coordinates for further analysis. The introduction of this new resource will enhance the ability of researchers to both share their findings and incorporate existing meta-analytic results into their own research.

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