001033954 001__ 1033954
001033954 005__ 20241213210711.0
001033954 0247_ $$2doi$$a10.25493/KNSN-XB4
001033954 037__ $$aFZJ-2024-06792
001033954 1001_ $$0P:(DE-Juel1)131631$$aAmunts, Katrin$$b0$$eCorresponding author
001033954 245__ $$aJulich-Brain Atlas, cytoarchitectonic maps
001033954 260__ $$bEBRAINS$$c2024
001033954 3367_ $$2BibTeX$$aMISC
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001033954 520__ $$aThe Julich-Brain Atlas (RRID:SCR_023277) presents in this dataset cytoarchitectonic maps in several coordinate spaces, such as MNI Colin 27, MNI ICBM 152, and Free Surfer FsAverage-7. These maps originate from peer-reviewed probability maps (PMs) that define both cortical and subcortical brain regions. Notably, these probability maps account for the brain's inter-individual variability by analyzing data from ten post-mortem samples. For a whole-brain parcellation, the available probability maps are combined into a maximum probability map (MPM) by considering for each voxel the probability of all cytoarchitectonic brain regions, and determining the most probable assignment. The atlas was used as a reference atlas for the Human Brain Project and is deeply embedded within the European research infrastructure platform, EBRAINS. Furthermore, the atlas is continuously evolving and regularly updated with new areas. The [siibra toolsuite](https://siibra-python.readthedocs.io) provides an automated access to the Atlas, to speed up your work.
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001033954 536__ $$0G:(EU-Grant)101147319$$aEBRAINS 2.0 - EBRAINS 2.0: A Research Infrastructure to Advance Neuroscience and Brain Health (101147319)$$c101147319$$fHORIZON-INFRA-2022-SERV-B-01$$x1
001033954 588__ $$aDataset connected to DataCite
001033954 650_7 $$2Other$$aNeuroscience
001033954 7001_ $$0P:(DE-Juel1)131660$$aMohlberg, Hartmut$$b1
001033954 7001_ $$0P:(DE-Juel1)131636$$aBludau, Sebastian$$b2
001033954 7001_ $$0P:(DE-Juel1)131675$$aCaspers, Svenja$$b3
001033954 7001_ $$0P:(DE-HGF)0$$aLewis, L. B.$$b4
001033954 7001_ $$0P:(DE-Juel1)131678$$aEickhoff, Simon$$b5
001033954 7001_ $$0P:(DE-Juel1)131666$$aPieperhoff, Peter$$b6
001033954 773__ $$a10.25493/KNSN-XB4
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001033954 9141_ $$y2024
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