000903071 001__ 903071
000903071 005__ 20211209142054.0
000903071 0247_ $$2doi$$a10.25493/33MJ-0RM
000903071 037__ $$aFZJ-2021-04800
000903071 1001_ $$0P:(DE-Juel1)169263$$aBrandstetter, A.$$b0$$eCorresponding author$$ufzj
000903071 245__ $$aReference delineations of the LGB (lam 1-6, CGL, Metathalamus) in individual sections of the BigBrain
000903071 260__ $$c2021
000903071 3367_ $$2BibTeX$$aMISC
000903071 3367_ $$0PUB:(DE-HGF)32$$2PUB:(DE-HGF)$$aDataset$$bdataset$$mdataset$$s1639050044_4180
000903071 3367_ $$026$$2EndNote$$aChart or Table
000903071 3367_ $$2DataCite$$aDataset
000903071 3367_ $$2ORCID$$aDATA_SET
000903071 3367_ $$2DINI$$aResearchData
000903071 520__ $$aThis dataset contains cytoarchitectonic maps of the six distinct layers (lam 1-6) of the lateral geniculate body – LGB (CGL, Metathalamus) in the BigBrain (LGB is equivalent to CGL and can be used as synonyms). The mappings were created using cytoarchitectonic criteria applied on digitized histological sections of 1 μm resolution cut in coronal plane. Mappings are available on 15 sections of the diencephalon of the BigBrain and have been transformed to the 3D reconstructed BigBrain space. For this brain area, a highly detailed 3D map has been computed based on automatic delineations on every histological section from a novel Deep Learning algorithm. This ultrahigh resolution 3D cytoarchitectonic map of the LGB can be explored in the HBP interactive Atlas Viewer. This dataset can be accessed here: [Ultrahigh resolution 3D cytoarchitectonic map of LGB (CGL, Metathalamus) created by a Deep-Learning assisted workflow.](https://search.kg.ebrains.eu/instances/d0c36f4a-91a8-4885-880d-f2896f5c54cf)
000903071 536__ $$0G:(DE-HGF)POF4-5254$$a5254 - Neuroscientific Data Analytics and AI (POF4-525)$$cPOF4-525$$fPOF IV$$x0
000903071 536__ $$0G:(EU-Grant)945539$$aHBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539)$$c945539$$fH2020-SGA-FETFLAG-HBP-2019$$x1
000903071 588__ $$aDataset connected to DataCite
000903071 650_7 $$2Other$$aNeuroscience
000903071 7001_ $$0P:(DE-Juel1)180739$$aBolakhrif, N.$$b1$$ufzj
000903071 7001_ $$0P:(DE-Juel1)170068$$aSchiffer, C.$$b2$$ufzj
000903071 7001_ $$0P:(DE-Juel1)165746$$aDickscheid, T.$$b3$$ufzj
000903071 7001_ $$0P:(DE-Juel1)131660$$aMohlberg, H.$$b4$$ufzj
000903071 7001_ $$0P:(DE-Juel1)131631$$aAmunts, K.$$b5$$ufzj
000903071 773__ $$a10.25493/33MJ-0RM
000903071 909CO $$ooai:juser.fz-juelich.de:903071$$popenaire$$pVDB$$pec_fundedresources
000903071 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)169263$$aForschungszentrum Jülich$$b0$$kFZJ
000903071 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)180739$$aForschungszentrum Jülich$$b1$$kFZJ
000903071 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)170068$$aForschungszentrum Jülich$$b2$$kFZJ
000903071 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)165746$$aForschungszentrum Jülich$$b3$$kFZJ
000903071 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131660$$aForschungszentrum Jülich$$b4$$kFZJ
000903071 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131631$$aForschungszentrum Jülich$$b5$$kFZJ
000903071 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$$x0
000903071 9141_ $$y2021
000903071 9201_ $$0I:(DE-Juel1)INM-1-20090406$$kINM-1$$lStrukturelle und funktionelle Organisation des Gehirns$$x0
000903071 980__ $$adataset
000903071 980__ $$aVDB
000903071 980__ $$aI:(DE-Juel1)INM-1-20090406
000903071 980__ $$aUNRESTRICTED