Hauptseite > Publikationsdatenbank > Probabilistic cytoarchitectonic map of CA3 (Hippocampus) (v11.1) > print

001     887985
005     20210130010718.0
024 7 _ |a 10.25493/C546-GS0
|2 doi
037 _ _ |a FZJ-2020-04563
100 1 _ |a Palomero-Gallagher, Nicola
|0 P:(DE-Juel1)131701
|b 0
|e Corresponding author
|u fzj
245 _ _ |a Probabilistic cytoarchitectonic map of CA3 (Hippocampus) (v11.1)
260 _ _ |c 2020
|b EBRAINS
336 7 _ |a MISC
|2 BibTeX
336 7 _ |a Dataset
|b dataset
|m dataset
|0 PUB:(DE-HGF)32
|s 1605799786_29122
|2 PUB:(DE-HGF)
336 7 _ |a Chart or Table
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336 7 _ |a Dataset
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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 CA3 (Hippocampus) 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 CA3 (Hippocampus). The probability map of CA3 (Hippocampus) 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. Other available data versions of CA3 (Hippocampus): Amunts et al. (2020) [Data set, v11b.0] [DOI: 10.25493/MQ0Y-22E](https://doi.org/10.25493/MQ0Y-22E) The most probable delineation of CA3 (Hippocampus) derived from the calculation of a maximum probability map of all currently released Julich-Brain brain structures can be found here: Amunts et al. (2019) [Data set, v1.13] [DOI: 10.25493/Q3ZS-NV6](https://doi.org/10.25493%2FQ3ZS-NV6) Amunts et al. (2020) [Data set, v2.2] [DOI: 10.25493/TAKY-64D](https://doi.org/10.25493/TAKY-64D)
536 _ _ |a 574 - Theory, modelling and simulation (POF3-574)
|0 G:(DE-HGF)POF3-574
|c POF3-574
|f POF III
|x 0
536 _ _ |a HBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907)
|0 G:(EU-Grant)785907
|c 785907
|f H2020-SGA-FETFLAG-HBP-2017
|x 1
536 _ _ |a HBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539)
|0 G:(EU-Grant)945539
|c 945539
|x 2
588 _ _ |a Dataset connected to DataCite
700 1 _ |a Kedo, Olga
|0 P:(DE-Juel1)131650
|b 1
|u fzj
700 1 _ |a Mohlberg, Hartmut
|0 P:(DE-Juel1)131660
|b 2
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700 1 _ |a Zilles, Karl
|0 P:(DE-Juel1)131714
|b 3
|u fzj
700 1 _ |a Amunts, Katrin
|0 P:(DE-Juel1)131631
|b 4
|u fzj
773 _ _ |a 10.25493/C546-GS0
909 C O |o oai:juser.fz-juelich.de:887985
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910 1 _ |a Forschungszentrum Jülich
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913 1 _ |a DE-HGF
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|l Decoding the Human Brain
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|v Theory, modelling and simulation
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914 1 _ |y 2020
920 1 _ |0 I:(DE-Juel1)INM-1-20090406
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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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