001033963 001__ 1033963
001033963 005__ 20241212210728.0
001033963 0247_ $$2doi$$a10.25493/JYK2-17T
001033963 037__ $$aFZJ-2024-06799
001033963 1001_ $$0P:(DE-Juel1)190831$$aStacho, Martin$$b0$$eCorresponding author$$ufzj
001033963 245__ $$aProbabilistic cytoarchitectonic map of NRp (Midbrain, Nucleus Ruber, parvocellular part) (v2.0)
001033963 260__ $$bEBRAINS$$c2024
001033963 3367_ $$2BibTeX$$aMISC
001033963 3367_ $$0PUB:(DE-HGF)32$$2PUB:(DE-HGF)$$aDataset$$bdataset$$mdataset$$s1734016984_31367
001033963 3367_ $$026$$2EndNote$$aChart or Table
001033963 3367_ $$2DataCite$$aDataset
001033963 3367_ $$2ORCID$$aDATA_SET
001033963 3367_ $$2DINI$$aResearchData
001033963 520__ $$aThis dataset contains the probabilistic map (PM) of Nucleus Ruber, parvocellular part (NRp (Midbrain, Nucleus Ruber, parvocellular part)) of the midbrain of the human brain. As part of the Julich-Brain Atlas (JBA), the nucleus was identified using cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. The results of the cytoarchitectonic analysis were then mapped to common brain reference spaces, where each voxel was assigned the probability to belong to NRp (Midbrain, Nucleus Ruber, parvocellular part). The PM of NRp (Midbrain, Nucleus Ruber, parvocellular part) is provided in NifTi-1 format for each brain reference space and hemisphere. The JBA relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures that was described by [Amunts et al. in 2020](www.doi.org/10.1126/science.abb4588). Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.
001033963 536__ $$0G:(DE-HGF)POF4-5254$$a5254 - Neuroscientific Data Analytics and AI (POF4-525)$$cPOF4-525$$fPOF IV$$x0
001033963 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$$x1
001033963 536__ $$0G:(EU-Grant)945539$$aHBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539)$$c945539$$fH2020-SGA-FETFLAG-HBP-2019$$x2
001033963 536__ $$0G:(DE-Juel1)JL SMHB-2021-2027$$aJL SMHB - Joint Lab Supercomputing and Modeling for the Human Brain (JL SMHB-2021-2027)$$cJL SMHB-2021-2027$$x3
001033963 536__ $$0G:(DE-HGF)InterLabs-0015$$aHIBALL - Helmholtz International BigBrain Analytics and Learning Laboratory (HIBALL) (InterLabs-0015)$$cInterLabs-0015$$x4
001033963 588__ $$aDataset connected to DataCite
001033963 650_7 $$2Other$$aNeuroscience
001033963 7001_ $$0P:(DE-HGF)0$$aHäusler, A. Niklas$$b1
001033963 7001_ $$0P:(DE-Juel1)169263$$aBrandstetter, Andrea$$b2$$ufzj
001033963 7001_ $$0P:(DE-Juel1)169165$$aIannilli, Francesca$$b3
001033963 7001_ $$0P:(DE-Juel1)170068$$aSchiffer, Christian$$b4$$ufzj
001033963 7001_ $$0P:(DE-HGF)0$$aSmaers, Jeroen B.$$b5
001033963 7001_ $$0P:(DE-Juel1)131660$$aMohlberg, Hartmut$$b6$$ufzj
001033963 7001_ $$0P:(DE-Juel1)131636$$aBludau, Sebastian$$b7$$eCorresponding author$$ufzj
001033963 7001_ $$0P:(DE-Juel1)131631$$aAmunts, Katrin$$b8
001033963 773__ $$a10.25493/JYK2-17T
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001033963 9131_ $$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
001033963 9141_ $$y2024
001033963 9201_ $$0I:(DE-Juel1)INM-1-20090406$$kINM-1$$lStrukturelle und funktionelle Organisation des Gehirns$$x0
001033963 980__ $$adataset
001033963 980__ $$aVDB
001033963 980__ $$aI:(DE-Juel1)INM-1-20090406
001033963 980__ $$aUNRESTRICTED