001034530 001__ 1034530
001034530 005__ 20241218210705.0
001034530 0247_ $$2doi$$a10.25493/3E5S-9QK
001034530 037__ $$aFZJ-2024-07293
001034530 1001_ $$0P:(DE-Juel1)173031$$aZhao, Ling$$b0$$ufzj
001034530 245__ $$aRegional and laminar distribution of receptors for GABA in the rat brain (v2)
001034530 260__ $$bEBRAINS$$c2024
001034530 3367_ $$2BibTeX$$aMISC
001034530 3367_ $$0PUB:(DE-HGF)32$$2PUB:(DE-HGF)$$aDataset$$bdataset$$mdataset$$s1734524545_24847
001034530 3367_ $$026$$2EndNote$$aChart or Table
001034530 3367_ $$2DataCite$$aDataset
001034530 3367_ $$2ORCID$$aDATA_SET
001034530 3367_ $$2DINI$$aResearchData
001034530 520__ $$aThe present dataset provides the quantitative regional and laminar distribution of key molecules of inhibitory neurotransmission, namely the γ-aminobutyric acid (GABA) receptors GABA A and GABA B as well as the peripheral benzodiazepine (perBZ) receptors and the GABA A associated benzodiazepine (GABA A /BZ) binding sites, in five selected rostrocaudal levels of the rat brain. The receptors were visualized by means of quantitative *in vitro* receptor autoradiography and the selective tritiated ligands muscimol, CGP 54626 and flumazenil. The high spatial resolution of this method enables quantification of receptor densities in anatomically identifiable cortical structures as detailed as the hippocampal regions and layers, or subcortical structures such as amygdalar nuclei. We also provide information about image data registration to the Waxholm Sprague Dawley rat brain atlas.
001034530 536__ $$0G:(DE-HGF)POF4-5251$$a5251 - Multilevel Brain Organization and Variability (POF4-525)$$cPOF4-525$$fPOF IV$$x0
001034530 536__ $$0G:(EU-Grant)785907$$aHBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907)$$c785907$$fH2020-SGA-FETFLAG-HBP-2017$$x1
001034530 536__ $$0G:(EU-Grant)945539$$aHBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539)$$c945539$$fH2020-SGA-FETFLAG-HBP-2019$$x2
001034530 536__ $$0G:(EU-Grant)101147319$$aEBRAINS 2.0 - EBRAINS 2.0: A Research Infrastructure to Advance Neuroscience and Brain Health (101147319)$$c101147319$$fHORIZON-INFRA-2022-SERV-B-01$$x3
001034530 588__ $$aDataset connected to DataCite
001034530 650_7 $$2Other$$aNeuroscience
001034530 7001_ $$aZilles, Karl$$b1
001034530 7001_ $$0P:(DE-Juel1)131701$$aPalomero-Gallagher, Nicola$$b2$$eCorresponding author$$ufzj
001034530 7001_ $$0P:(DE-HGF)0$$aPuchades, Maja A.$$b3$$eCorresponding author
001034530 773__ $$a10.25493/3E5S-9QK
001034530 909CO $$ooai:juser.fz-juelich.de:1034530$$popenaire$$pVDB$$pec_fundedresources
001034530 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)173031$$aForschungszentrum Jülich$$b0$$kFZJ
001034530 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131701$$aForschungszentrum Jülich$$b2$$kFZJ
001034530 9131_ $$0G:(DE-HGF)POF4-525$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5251$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vDecoding Brain Organization and Dysfunction$$x0
001034530 9141_ $$y2024
001034530 9201_ $$0I:(DE-Juel1)INM-1-20090406$$kINM-1$$lStrukturelle und funktionelle Organisation des Gehirns$$x0
001034530 980__ $$adataset
001034530 980__ $$aVDB
001034530 980__ $$aI:(DE-Juel1)INM-1-20090406
001034530 980__ $$aUNRESTRICTED