Home > Publications database > Probabilistic cytoarchitectonic map of Area PirT.Tu (PiriformCortexMesial, Piriform temporal Area, Uncus) (v5.0) > print |
001 | 1033961 | ||
005 | 20241212210728.0 | ||
024 | 7 | _ | |a 10.25493/FEDE-Y69 |2 doi |
037 | _ | _ | |a FZJ-2024-06797 |
100 | 1 | _ | |a Kedo, Olga |0 P:(DE-Juel1)131650 |b 0 |e Corresponding author |u fzj |
245 | _ | _ | |a Probabilistic cytoarchitectonic map of Area PirT.Tu (PiriformCortexMesial, Piriform temporal Area, Uncus) (v5.0) |
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 1734014580_5342 |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 the probabilistic map (PM) of Piriform temporal area, Uncus (Area PirT.Tu (PiriformCortexMesial, Piriform temporal Area, Uncus)) of the piriform cortex of the human brain. As part of the Julich-Brain Atlas (JBA), the area was identified using 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 common brain reference spaces, where each voxel was assigned the probability to belong to Area PirT.Tu (PiriformCortexMesial, Piriform temporal Area, Uncus). The PM of Area PirT.Tu (PiriformCortexMesial, Piriform temporal Area, Uncus) is provided in NifTi-1 format for each brain reference space and hemisphere. The JBA relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures that was described by [Amunts et al. in 2020](https://doi.org/10.1126/science.abb4588). Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets. |
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 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 1 |
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 2 |
536 | _ | _ | |a HIBALL - Helmholtz International BigBrain Analytics and Learning Laboratory (HIBALL) (InterLabs-0015) |0 G:(DE-HGF)InterLabs-0015 |c InterLabs-0015 |x 3 |
588 | _ | _ | |a Dataset connected to DataCite |
650 | _ | 7 | |a Neuroscience |2 Other |
700 | 1 | _ | |a Mohlberg, Hartmut |0 P:(DE-Juel1)131660 |b 1 |u fzj |
700 | 1 | _ | |a Bludau, Sebastian |0 P:(DE-Juel1)131636 |b 2 |e Corresponding author |u fzj |
700 | 1 | _ | |a Amunts, Katrin |0 P:(DE-Juel1)131631 |b 3 |
773 | _ | _ | |a 10.25493/FEDE-Y69 |
909 | C | O | |o oai:juser.fz-juelich.de:1033961 |p openaire |p VDB |p ec_fundedresources |
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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 |
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980 | _ | _ | |a UNRESTRICTED |
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