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Neuroimage. 2014 Oct 1;99:525-32. doi: 10.1016/j.neuroimage.2014.06.010. Epub 2014 Jun 15.

Interoperable atlases of the human brain.

Author information

1
Institute of Neuroscience and Medicine, INM-1, Research Centre Jülich, Germany; C. and O. Vogt Institute for Brain Research, Heinrich Heine University, Düsseldorf, Germany.
2
Allen Institute for Brain Science, Seattle, WA, USA.
3
Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, MO, USA.
4
The Institute for Neuroimaging and Informatics (INI) and Laboratory for Neuro Imaging (LONI), Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
5
Center for Magnetic Resonance Research, Departments of Radiology & Neurosurgery, University of Minnesota School of Medicine, Minneapolis, MN, USA.
6
Hellen Wills Neuroscience Institute, Brain Imaging Center, University of California at Berkeley, CA, USA.
7
Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.
8
Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.
9
INSERM, U992, Cognitive Neuroimaging Unit, F-91191 Gif/Yvette, France.
10
Cuban Neuroscience Center, Havana, Cuba; Key Laboratory for Neuroinformation, Chengudu, China.
11
Parietal Research Team, French Institute for Research in Computer Science and Automation (INRIA), Gif sur Yvette, France.
12
Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH University Aachen, Aachen, Germany; Jülich-Aachen Research Alliance (JARA), Translational Brain Medicine, Jülich, Germany.
13
International Neuroinformatics Coordinating Facility Secretariat (INCF), Stockholm, Sweden.
14
International Neuroinformatics Coordinating Facility Secretariat (INCF), Stockholm, Sweden. Electronic address: mathew.abrams@incf.org.
15
Institute of Neuroscience and Medicine, INM-1, Research Centre Jülich, Germany; Department of Neuromodulation, University of Cologne, Cologne, Germany; Department of Neurosurgery, Stanford University, Stanford, USA.
16
Department of Neurosciences, KU Leuven, Leuven, Belgium.
17
Montreal Neurological Institute, McGill University, Montreal, Canada.
18
Institute of Neuroscience and Medicine, INM-1, Research Centre Jülich, Germany; Institute for Clinical Neuroscience and Medical Psychology, Heinrich-Heine University, Düsseldorf, Germany.

Abstract

The last two decades have seen an unprecedented development of human brain mapping approaches at various spatial and temporal scales. Together, these have provided a large fundus of information on many different aspects of the human brain including micro- and macrostructural segregation, regional specialization of function, connectivity, and temporal dynamics. Atlases are central in order to integrate such diverse information in a topographically meaningful way. It is noteworthy, that the brain mapping field has been developed along several major lines such as structure vs. function, postmortem vs. in vivo, individual features of the brain vs. population-based aspects, or slow vs. fast dynamics. In order to understand human brain organization, however, it seems inevitable that these different lines are integrated and combined into a multimodal human brain model. To this aim, we held a workshop to determine the constraints of a multi-modal human brain model that are needed to enable (i) an integration of different spatial and temporal scales and data modalities into a common reference system, and (ii) efficient data exchange and analysis. As detailed in this report, to arrive at fully interoperable atlases of the human brain will still require much work at the frontiers of data acquisition, analysis, and representation. Among them, the latter may provide the most challenging task, in particular when it comes to representing features of vastly different scales of space, time and abstraction. The potential benefits of such endeavor, however, clearly outweigh the problems, as only such kind of multi-modal human brain atlas may provide a starting point from which the complex relationships between structure, function, and connectivity may be explored.

[Indexed for MEDLINE]

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