Many researchers in the field of cognitive neuroscience increasingly appreciate the importance of conducting formal syntheses of cognitive neuroscience literature. In this section we summarize relevant history and discuss several recently developed tools and platforms designed to facilitate the sharing and integration of neuroimaging data. Our review is by no means exhaustive; it mainly emphasizes what we view as some of the more promising recent developments.

Data aggregation, atlasing and sharing

12 Costafreda S. Pooling FMRI data: meta-analysis, mega-analysis and multi-center studies. 13 Huerta M.F.

et al. The human brain project: an international resource. One way to increase the power and generalizability of neuroimaging studies is to aggregate data across multiple sites and studies []. This entails bringing data from different studies into a common spatial framework (an atlas) and a common data format, and also making the data readily available. Over the past two decades, there have been important advances on all three fronts. Many of these advances were fueled by the Human Brain Project [], Biomedical Informatics Research Network (BIRN; http://www.birncommunity.org/ ), and other targeted funding mechanisms in the USA and other countries.

14 Talairach J.

Tournoux P. Co-Planar Stereotaxic Atlas of the Human Brain: 3-Dimensional Proportional System: An Approach to Cerebral Imaging. 15 Fox P.T.

et al. A stereotactic method of anatomical localization for positron emission tomography. 16 Devlin J.T.

Poldrack R.A. In praise of tedious anatomy. 17 Van Essen D.

Dierker D. Surface-based and probabilistic atlases of primate cerebral cortex. 18 Van Essen D.C.

Dierker D. On navigating the human cerebral cortex: Response to ‘in praise of tedious anatomy’. 17 Van Essen D.

Dierker D. Surface-based and probabilistic atlases of primate cerebral cortex. 19 Van Horn J.

Toga A. Is it time to re-prioritize neuroimaging databases and digital repositories?. 20 Van Essen D. Windows on the brain: the emerging role of atlases and databases in neuroscience. 21 Laird A.R.

et al. The Social Evolution of a Human Brain Mapping Database. 22 Fox P.T.

et al. BrainMap: a database of human functional brain mapping. 23 Van Essen D.C. Lost in localization–But found with foci?!. 24 Dickson J.

et al. ‘The surface management system’ (SuMS) database: a surface-based database to aid cortical surface reconstruction, visualization and analysis. 25 Eickhoff S.

et al. Coordinate-based activation likelihood estimation meta-analysis of neuroimaging data: A random-effects approach based on empirical estimates of spatial uncertainty. 23 Van Essen D.C. Lost in localization–But found with foci?!. 26 Van Essen D.

et al. An integrated software suite for surface-based analyses of cerebral cortex. The Talairach atlas and its associated stereotaxic space, which allows for the reporting of stereotaxic coordinates (foci) describing the centers of brain activations or deactivations associated with various tasks, were introduced to neuroimaging in the 1980s [] as a way to compensate for individual variability in brain size, shape and patterns of cortical folding. Efforts to improve alignment and better compensate for variability have yielded a plethora of magnetic resonance (MR)-based atlases (both single-subject and probabilistic) and stereotaxic spaces, thereby posing a fresh set of challenges for comparing results across studies []. A crucial factor supporting the shift toward greater integration of the cognitive neuroscience literature has been the development of large-scale online databases [] that provide support for rapid data mining, visualization, and analysis of stereotaxic coordinates from many studies. Two of the most prominent such databases are the BrainMap database ( http://www.brainmap.org ) [] and SumsDB ( http://sumsdb.wustl.edu/sums ) [], each of which contains study metadata and activation coordinates for a sizable proportion of the neuroimaging literature. Both databases contain extensive functionality for searching, retrieving and analyzing neuroimaging data, although they also have somewhat different emphases (e.g. BrainMap interoperates closely with Activation Likelihood Estimate (ALE) meta-analysis software [], whereas SumsDB has greater support for online and offline visualization []). The emergence of such databases has greatly lowered the barrier to formal integration of the research literature, giving rise to a proliferation of studies focusing on synthesis of previous findings rather than generation of primary data.

27 Van Horn J.D.

et al. The Functional Magnetic Resonance Imaging Data Center (fMRIDC): the challenges and rewards of largeñscale databasing of neuroimaging studies. 28 Van Horn J.

et al. Sharing neuroimaging studies of human cognition. 19 Van Horn J.

Toga A. Is it time to re-prioritize neuroimaging databases and digital repositories?. 28 Van Horn J.

et al. Sharing neuroimaging studies of human cognition. 29 Marcus D.

et al. The extensible neuroimaging archive toolkit. 30 Luo X.

et al. Neuroimaging informatics tools and resources clearinghouse (NITRC) resource announcement. 31 Gardner D.

et al. The neuroscience information framework: a data and knowledge environment for neuroscience. Although stereotaxic coordinates are easy to report and communicate, they constitute a compact but impoverished distillation that belies the spatial complexity and richness of neuroimaging data. An early database infrastructure that could handle the full complexity of imaging data was developed in the 1990s by the fMRI Data Center (fMRIDC), which was devoted to storing and sharing large repositories of primary as well as processed neuroimaging data []. The fMRIDC faced significant challenges, including infrastructure limitations, the use of seemingly incommensurable experimental paradigms and data formats, and a reluctance on the part of many researchers to freely share their data []. Although it no longer accepts new contributions, the fMRIDC has inspired other recent developments designed to facilitate multi-site collaboration and data sharing of full image information. These include the XNAT (eXtensible Neuroimaging Archive Toolkit) software platform for the storage and dissemination of neuroimaging data [], as well as web-based resources such as the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) for neuroimaging tools [] and the Neuroscience Information Framework (NIF, http://www.neuinfo.org/ ; []), which provides easy access to a rapidly growing set of databases, neuroimaging tools and other online resources.