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| 001 | 1034448 | ||
| 005 | 20241218210704.0 | ||
| 024 | 7 | _ | |a 10.25493/NQWJ-2EM |2 doi |
| 037 | _ | _ | |a FZJ-2024-07214 |
| 100 | 1 | _ | |a Schiffer, Christian |0 P:(DE-Juel1)170068 |b 0 |e Corresponding author |u fzj |
| 245 | _ | _ | |a 3D cytoarchitectonic map of the human mesial piriform region of the BigBrain (v2.0) |
| 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 1734522489_24846 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a Chart or Table |0 26 |2 EndNote |
| 336 | 7 | _ | |a Dataset |2 DataCite |
| 336 | 7 | _ | |a DATA_SET |2 ORCID |
| 336 | 7 | _ | |a ResearchData |2 DINI |
| 520 | _ | _ | |a This dataset contains cytoarchitectonic maps of four areas of the mesial piriform region in the BigBrain dataset. The maps are based on reference delineations in serial histological sections of the BigBrain at 1 micron resolution in-plane, with a distance of sections typically not lower than 300 micrometers. The 3 D cytoarchitectonic maps were created in two different approaches: (1) As first version, a 3D map of the area was created by interpolation of the respective reference delineations. (2) As a more advanced version, a 3D map was created using deep convolutional neural networks trained on the respective reference delineations. As a result, the latter version also includes delineations of the area in the sections in-between reference delineations. The 3D maps were transformed to the 3D reconstructed BigBrain space and are integrated into the Julich-Brain Cytoarchitectonic Atlas. |
| 536 | _ | _ | |a 5254 - Neuroscientific Data Analytics and AI (POF4-525) |0 G:(DE-HGF)POF4-5254 |c POF4-525 |f POF IV |x 0 |
| 536 | _ | _ | |a HBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539) |0 G:(EU-Grant)945539 |c 945539 |f H2020-SGA-FETFLAG-HBP-2019 |x 1 |
| 536 | _ | _ | |a HIBALL - Helmholtz International BigBrain Analytics and Learning Laboratory (HIBALL) (InterLabs-0015) |0 G:(DE-HGF)InterLabs-0015 |c InterLabs-0015 |x 2 |
| 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 |x 3 |
| 588 | _ | _ | |a Dataset connected to DataCite |
| 650 | _ | 7 | |a Neuroscience |2 Other |
| 700 | 1 | _ | |a Kedo, Olga |0 P:(DE-Juel1)131650 |b 1 |u fzj |
| 700 | 1 | _ | |a Amunts, Katrin |0 P:(DE-Juel1)131631 |b 2 |u fzj |
| 700 | 1 | _ | |a Dickscheid, Timo |0 P:(DE-Juel1)165746 |b 3 |u fzj |
| 773 | _ | _ | |a 10.25493/NQWJ-2EM |
| 909 | C | O | |o oai:juser.fz-juelich.de:1034448 |p openaire |p VDB |p ec_fundedresources |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)170068 |
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| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 2 |6 P:(DE-Juel1)131631 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 3 |6 P:(DE-Juel1)165746 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Natural, Artificial and Cognitive Information Processing |1 G:(DE-HGF)POF4-520 |0 G:(DE-HGF)POF4-525 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Decoding Brain Organization and Dysfunction |9 G:(DE-HGF)POF4-5254 |x 0 |
| 914 | 1 | _ | |y 2024 |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-1-20090406 |k INM-1 |l Strukturelle und funktionelle Organisation des Gehirns |x 0 |
| 980 | _ | _ | |a dataset |
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| 980 | _ | _ | |a I:(DE-Juel1)INM-1-20090406 |
| 980 | _ | _ | |a UNRESTRICTED |
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