001034406 001__ 1034406
001034406 005__ 20241218210703.0
001034406 0247_ $$2doi$$a10.25493/EJBW-G5D
001034406 037__ $$aFZJ-2024-07187
001034406 1001_ $$0P:(DE-Juel1)144196$$aRuland, Sabine Helene$$b0$$eCorresponding author$$ufzj
001034406 245__ $$aProbabilistic cytoarchitectonic map of Area 6v3 (PreCG) (v11.0)
001034406 260__ $$bEBRAINS$$c2024
001034406 3367_ $$2BibTeX$$aMISC
001034406 3367_ $$0PUB:(DE-HGF)32$$2PUB:(DE-HGF)$$aDataset$$bdataset$$mdataset$$s1734518222_15483
001034406 3367_ $$026$$2EndNote$$aChart or Table
001034406 3367_ $$2DataCite$$aDataset
001034406 3367_ $$2ORCID$$aDATA_SET
001034406 3367_ $$2DINI$$aResearchData
001034406 520__ $$aThis dataset contains the probabilistic map (PM) of the ventral premotor area (Area 6v3 (PreCG)) of the ventral precentral gyrus of the human brain. As part of the Julich-Brain Atlas (JBA), the area was identified using cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. The results of the cytoarchitectonic analysis were then mapped to common brain reference spaces, where each voxel was assigned the probability to belong to Area 6v3 (PreCG). The PM of Area 6v3 (PreCG) is provided in NifTi-1 format for each brain reference space and hemisphere. The JBA relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures that was described by [Amunts et al. in 2020](https://doi.org/10.1126/science.abb4588). Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.
001034406 536__ $$0G:(DE-HGF)POF4-5254$$a5254 - Neuroscientific Data Analytics and AI (POF4-525)$$cPOF4-525$$fPOF IV$$x0
001034406 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$$x1
001034406 536__ $$0G:(EU-Grant)945539$$aHBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539)$$c945539$$fH2020-SGA-FETFLAG-HBP-2019$$x2
001034406 536__ $$0G:(DE-HGF)InterLabs-0015$$aHIBALL - Helmholtz International BigBrain Analytics and Learning Laboratory (HIBALL) (InterLabs-0015)$$cInterLabs-0015$$x3
001034406 588__ $$aDataset connected to DataCite
001034406 650_7 $$2Other$$aNeuroscience
001034406 7001_ $$aSigl, Benjamin$$b1
001034406 7001_ $$aStangier, Jeanette$$b2
001034406 7001_ $$0P:(DE-Juel1)131675$$aCaspers, Svenja$$b3$$ufzj
001034406 7001_ $$0P:(DE-Juel1)131660$$aMohlberg, Hartmut$$b4$$ufzj
001034406 7001_ $$0P:(DE-Juel1)131636$$aBludau, Sebastian$$b5$$eCorresponding author$$ufzj
001034406 7001_ $$0P:(DE-Juel1)131631$$aAmunts, Katrin$$b6$$ufzj
001034406 773__ $$a10.25493/EJBW-G5D
001034406 909CO $$ooai:juser.fz-juelich.de:1034406$$popenaire$$pVDB$$pec_fundedresources
001034406 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)144196$$aForschungszentrum Jülich$$b0$$kFZJ
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001034406 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131660$$aForschungszentrum Jülich$$b4$$kFZJ
001034406 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131636$$aForschungszentrum Jülich$$b5$$kFZJ
001034406 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131631$$aForschungszentrum Jülich$$b6$$kFZJ
001034406 9131_ $$0G:(DE-HGF)POF4-525$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5254$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vDecoding Brain Organization and Dysfunction$$x0
001034406 9141_ $$y2024
001034406 9201_ $$0I:(DE-Juel1)INM-1-20090406$$kINM-1$$lStrukturelle und funktionelle Organisation des Gehirns$$x0
001034406 980__ $$adataset
001034406 980__ $$aVDB
001034406 980__ $$aI:(DE-Juel1)INM-1-20090406
001034406 980__ $$aUNRESTRICTED