001     1034519
005     20241218210705.0
024 7 _ |a 10.25493/D8NF-B83
|2 doi
037 _ _ |a FZJ-2024-07282
100 1 _ |a Zhao, Ling
|0 P:(DE-Juel1)173031
|b 0
|u fzj
245 _ _ |a Regional and laminar distribution of silver stained cell bodies in the rat brain (v2)
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 1734524680_24844
|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 Classical mapping studies relied on the analysis of histologically processed sections from formalin-fixed brains for the identification of borders between cortical areas or of the boundaries of subcortical nuclei. Differences in the regional and laminar distribution patterns of neurotransmitter receptors are known to complement and extend the insights into the structural organization of the brain, which are provided by cytoarchitectonic observations alone. Since the method of quantitative in vitro receptor autoradiography requires processing of unfixed, shock frozen brains, we here present a modification of a silver cell body histological staining which can be applied to cryosections neighbouring those destined to labelling of receptors. The histological staining resembles a Nissl staining, but yields a higher contrast between cell bodies and neuropil, and can also be used for quantitative approaches to cytoarchitectonic mapping. The present dataset provides high-resolution digitized images of coronal sections through the rat brain that were processed for the visualization of cell bodies, and which complement a series processed for the visualization of 19 different receptor binding sites from multiple neurotransmitter systems. We also provide information about image data registration to the Waxholm Sprague Dawley rat brain atlas.
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 HBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907)
|0 G:(EU-Grant)785907
|c 785907
|f H2020-SGA-FETFLAG-HBP-2017
|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 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 3
588 _ _ |a Dataset connected to DataCite
650 _ 7 |a Neuroscience
|2 Other
700 1 _ |a Zilles, Karl
|b 1
700 1 _ |a Palomero-Gallagher, Nicola
|0 P:(DE-Juel1)131701
|b 2
|e Corresponding author
|u fzj
700 1 _ |a Puchades, Maja A.
|0 P:(DE-HGF)0
|b 3
|e Corresponding author
773 _ _ |a 10.25493/D8NF-B83
909 C O |o oai:juser.fz-juelich.de:1034519
|p openaire
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|p ec_fundedresources
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
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|6 P:(DE-Juel1)173031
910 1 _ |a Forschungszentrum Jülich
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913 1 _ |a DE-HGF
|b Key Technologies
|l Natural, Artificial and Cognitive Information Processing
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|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 2024
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


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