001     1052822
005     20260128204143.0
024 7 _ |a 10.25493/MCV8-9T7
|2 doi
037 _ _ |a FZJ-2026-01179
100 1 _ |a Kuckertz, Anika
|0 P:(DE-Juel1)178766
|b 0
|u fzj
245 _ _ |a Parcellation scheme of rat iso- and proisocortical areas in Waxholm space (v3)
260 _ _ |c 2026
|b EBRAINS
336 7 _ |a MISC
|2 BibTeX
336 7 _ |a Dataset
|b dataset
|m dataset
|0 PUB:(DE-HGF)32
|s 1769600034_31423
|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 The present dataset provides a three-dimensional (3D) map of the rat iso- and proisocortex anchored in the standardized coordinate system of the Waxholm rat brain space. The parcellation encompasses 53 distinct areas and is the result of a multimodal analysis based on the heterogeneous regional and laminar distribution patterns of cell bodies and of muscarinic acetylcholine M2 receptors visualized in 2D sections. The receptor autoradiographs of a rat brain serially sectioned in the coronal plane were 3D reconstructed and anchored in Waxholm space. The ensuing transformation matrices were then applied to the delineations of the identified areas on the corresponding 2D autoradiographs, resulting in the registration of the location and extent of each area to the 3D reference Waxholm Space of the rat brain. This novel parcellation scheme of the rat iso- and proisocortical areas provides a high-resolution reference resource for the architectonically informed analysis of in vivo data and computational modelling approaches of the rat brain. As a dynamic framework, the Waxholm Rat Brain Atlas can be expanded by data of e.g., further neurotransmitter receptor types and brain regions.
536 _ _ |a 5251 - Multilevel Brain Organization and Variability (POF4-525)
|0 G:(DE-HGF)POF4-5251
|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 HIBALL - Helmholtz International BigBrain Analytics and Learning Laboratory (HIBALL) (InterLabs-0015)
|0 G:(DE-HGF)InterLabs-0015
|c InterLabs-0015
|x 2
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 3
588 _ _ |a Dataset connected to DataCite
650 _ 7 |a Neuroscience
|2 Other
700 1 _ |a Haghir, Hossein
|0 P:(DE-HGF)0
|b 1
700 1 _ |a Palomero-Gallagher, Nicola
|0 P:(DE-Juel1)131701
|b 2
|u fzj
700 1 _ |a Funck, Thomas
|0 P:(DE-Juel1)181092
|b 3
|u fzj
773 _ _ |a 10.25493/MCV8-9T7
909 C O |o oai:juser.fz-juelich.de:1052822
|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)178766
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)131701
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 3
|6 P:(DE-Juel1)181092
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)POF4-5251
|x 0
914 1 _ |y 2026
920 1 _ |0 I:(DE-Juel1)INM-1-20090406
|k INM-1
|l Strukturelle und funktionelle Organisation des Gehirns
|x 0
980 _ _ |a dataset
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)INM-1-20090406
980 _ _ |a UNRESTRICTED


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21