001     1033983
005     20241212210728.0
024 7 _ |a 10.25493/YCEZ-0H1
|2 doi
037 _ _ |a FZJ-2024-06819
100 1 _ |a Vogt, Brent A.
|0 P:(DE-599)DNB931807816
|b 0
|e Corresponding author
245 _ _ |a Probabilistic cytoarchitectonic map of Area a30 (retrosplenial) (v11.0)
260 _ _ |c 2024
|b EBRAINS
336 7 _ |a MISC
|2 BibTeX
336 7 _ |a Dataset
|b dataset
|m dataset
|0 PUB:(DE-HGF)32
|s 1734014652_5342
|2 PUB:(DE-HGF)
336 7 _ |a Chart or Table
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|2 EndNote
336 7 _ |a Dataset
|2 DataCite
336 7 _ |a DATA_SET
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336 7 _ |a ResearchData
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520 _ _ |a This dataset contains the distinct probabilistic cytoarchitectonic map of Area a30 (retrosplenial) in the individual, single subject template of the MNI Colin 27 reference space. As part of the Julich-Brain cytoarchitectonic atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. The results of the cytoarchitectonic analysis were then mapped to the reference space, where each voxel was assigned the probability to belong to Area a30 (retrosplenial). The probability map of Area a30 (retrosplenial) is provided in NifTi format for each hemisphere in the reference space. The Julich-Brain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and updated probability estimates for new brain structures may in some cases lead to measurable but negligible deviations of existing probability maps, as compared to earlier released datasets. The most probable delineation of Area a30 (retrosplenial) derived from the calculation of a maximum probability map of all currently released Julich-Brain brain structures can be found here: Amunts et al. (2020) [Data set, v2.2] [DOI: 10.25493/TAKY-64D](https://doi.org/10.25493/TAKY-64D)
536 _ _ |a 5254 - Neuroscientific Data Analytics and AI (POF4-525)
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536 _ _ |a EBRAINS 2.0 - EBRAINS 2.0: A Research Infrastructure to Advance Neuroscience and Brain Health (101147319)
|0 G:(EU-Grant)101147319
|c 101147319
|f HORIZON-INFRA-2022-SERV-B-01
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588 _ _ |a Dataset connected to DataCite
650 _ 7 |a Neuroscience
|2 Other
700 1 _ |a Mohlberg, Hartmut
|0 P:(DE-Juel1)131660
|b 1
700 1 _ |a Zilles, Karl
|0 P:(DE-Juel1)131714
|b 2
700 1 _ |a Palomero-Gallagher, Nicola
|0 P:(DE-Juel1)131701
|b 3
700 1 _ |a Amunts, Katrin
|0 P:(DE-Juel1)131631
|b 4
|e Corresponding author
773 _ _ |a 10.25493/YCEZ-0H1
909 C O |o oai:juser.fz-juelich.de:1033983
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910 1 _ |a Forschungszentrum Jülich
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913 1 _ |a DE-HGF
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|v Decoding Brain Organization and Dysfunction
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914 1 _ |y 2024
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980 _ _ |a dataset
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980 _ _ |a I:(DE-Juel1)INM-1-20090406
980 _ _ |a UNRESTRICTED


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