Sharing the wealth: Neuroimaging data repositories

Eickhoff, Simon; Turner, J. A.; Nichols, T. E.; Van Horn, J. D.

doi:10.1016/j.neuroimage.2015.10.079

Journal Article

FZJ-2015-06893

Sharing the wealth: Neuroimaging data repositories

Eickhoff, S.FZJ* ; Nichols, T. E. ; Van Horn, J. D. ; Turner, J. A.

2016
Academic Press Orlando, Fla.

NeuroImage 124(B), 1065–1068 (2016) [10.1016/j.neuroimage.2015.10.079]

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Please use a persistent id in citations: http://hdl.handle.net/2128/15821 doi:10.1016/j.neuroimage.2015.10.079

Abstract: Neuroimaging by means of functional and structural magnetic resonance imaging (MRI) has become the by far most widely used tool to study human brain organization in vivo. Since the 1990s, applications of MRI in neuroimaging have been almost exclusively devoted to the assessment of task-evoked changes in neuronal activity in the context of cognitive neuroscience experiments. These studies usually involved no more than a dozen subjects, represented a logical extension of experimental psychology, with differential brain responses to different tasks or stimuli serving as markers for differential processing modules. Over the last decade, however, the landscape has changed dramatically through three closely related developments. The first was the rapid advancements in high-resolution structural neuroimaging, i.e., methods and approaches that allowed studying detailed aspects of brain structure, function and connectivity outside of the context of experimental task paradigms. Using voxel-based morphometry, cortical thickness analysis or related techniques, morphological information derived from T1-weighted anatomical scans may be computed, compared across groups or in relation to phenotypic variability. Methods for the analysis of diffusion-weighted imaging (DWI) have also been the focus of considerable development allowing the characterization of fiber pathways in the brain and the detailed quantification of white-matter architecture. Finally, resting-state functional MRI (rs-fMRI) has provided many new and exciting avenues for exploring the brain's functional connectivity and network architecture.

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