001     857706
005     20210129235636.0
024 7 _ |a 10.1093/cercor/bhy249
|2 doi
024 7 _ |a 1047-3211
|2 ISSN
024 7 _ |a 1460-2199
|2 ISSN
024 7 _ |a 2128/21901
|2 Handle
024 7 _ |a pmid:30357321
|2 pmid
024 7 _ |a WOS:000459518500028
|2 WOS
024 7 _ |a altmetric:58153212
|2 altmetric
037 _ _ |a FZJ-2018-06678
082 _ _ |a 610
100 1 _ |0 0000-0002-3886-2226
|a James, Gregory M
|b 0
245 _ _ |a Parcellation of the Human Cerebral Cortex Based on Molecular Targets in the Serotonin System Quantified by Positron Emission Tomography In vivo
260 _ _ |a Oxford
|b Oxford Univ. Press
|c 2019
336 7 _ |2 DRIVER
|a article
336 7 _ |2 DataCite
|a Output Types/Journal article
336 7 _ |0 PUB:(DE-HGF)16
|2 PUB:(DE-HGF)
|a Journal Article
|b journal
|m journal
|s 1553606197_27369
336 7 _ |2 BibTeX
|a ARTICLE
336 7 _ |2 ORCID
|a JOURNAL_ARTICLE
336 7 _ |0 0
|2 EndNote
|a Journal Article
520 _ _ |a Parcellation of distinct areas in the cerebral cortex has a long history in neuroscience and is of great value for the study of brain function, specialization, and alterations in neuropsychiatric disorders. Analysis of cytoarchitectonical features has revealed their close association with molecular profiles based on protein density. This provides a rationale for the use of in vivo molecular imaging data for parcellation of the cortex with the advantage of whole-brain coverage. In the current work, parcellation was based on expression of key players of the serotonin neurotransmitter system. Positron emission tomography was carried out for the quantification of serotonin 1A (5-HT1A, n = 30) and 5-HT2A receptors (n = 22), the serotonin-degrading enzyme monoamine oxidase A (MAO-A, n = 32) and the serotonin transporter (5-HTT, n = 24) in healthy participants. Cortical protein distribution maps were obtained using surface-based quantification. Based on k-means clustering, silhouette criterion and bootstrapping, five distinct clusters were identified as the optimal solution. The defined clusters proved of high explanatory value for the effects of psychotropic drugs acting on the serotonin system, such as antidepressants and psychedelics. Therefore, the proposed method constitutes a sensible approach towards integration of multimodal imaging data for research and development in neuropharmacology and psychiatry. Key words: cortex, cortical reconstruction, molecular imaging, parcellation, PET, serotonin
536 _ _ |0 G:(DE-HGF)POF3-573
|a 573 - Neuroimaging (POF3-573)
|c POF3-573
|f POF III
|x 0
588 _ _ |a Dataset connected to CrossRef
700 1 _ |0 0000-0002-7344-8071
|a Gryglewski, Gregor
|b 1
700 1 _ |0 P:(DE-HGF)0
|a Vanicek, Thomas
|b 2
700 1 _ |0 0000-0002-9247-6457
|a Berroterán-Infante, Neydher
|b 3
700 1 _ |0 P:(DE-HGF)0
|a Philippe, Cécile
|b 4
700 1 _ |0 P:(DE-HGF)0
|a Kautzky, Alexander
|b 5
700 1 _ |0 P:(DE-HGF)0
|a Nics, Lukas
|b 6
700 1 _ |0 P:(DE-HGF)0
|a Vraka, Chrysoula
|b 7
700 1 _ |0 P:(DE-HGF)0
|a Godbersen, Godber M
|b 8
700 1 _ |0 P:(DE-HGF)0
|a Unterholzner, Jakob
|b 9
700 1 _ |0 P:(DE-HGF)0
|a Sigurdardottir, Helen L
|b 10
700 1 _ |0 P:(DE-HGF)0
|a Spies, Marie
|b 11
700 1 _ |0 P:(DE-HGF)0
|a Seiger, René
|b 12
700 1 _ |0 P:(DE-HGF)0
|a Kranz, Georg S
|b 13
700 1 _ |0 P:(DE-HGF)0
|a Hahn, Andreas
|b 14
700 1 _ |0 P:(DE-HGF)0
|a Mitterhauser, Markus
|b 15
700 1 _ |0 P:(DE-HGF)0
|a Wadsak, Wolfgang
|b 16
700 1 _ |0 P:(DE-Juel1)131672
|a Bauer, Andreas
|b 17
|u fzj
700 1 _ |0 P:(DE-HGF)0
|a Hacker, Marcus
|b 18
700 1 _ |0 P:(DE-HGF)0
|a Kasper, Siegfried
|b 19
700 1 _ |0 0000-0003-4641-9539
|a Lanzenberger, Rupert
|b 20
|e Corresponding author
773 _ _ |0 PERI:(DE-600)1483485-6
|a 10.1093/cercor/bhy249
|p 11
|t Cerebral cortex
|v 1-11
|x 1460-2199
|y 2019
856 4 _ |u https://juser.fz-juelich.de/record/857706/files/bhy249.pdf
|y OpenAccess
856 4 _ |u https://juser.fz-juelich.de/record/857706/files/bhy249.pdf?subformat=pdfa
|x pdfa
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:857706
|p openaire
|p open_access
|p VDB
|p driver
|p dnbdelivery
910 1 _ |0 I:(DE-HGF)0
|6 0000-0002-3886-2226
|a Medical University of Vienna, Vienna 1090, Austria
|b 0
910 1 _ |0 I:(DE-HGF)0
|6 0000-0002-7344-8071
|a Medical University of Vienna, Vienna 1090, Austria
|b 1
910 1 _ |0 I:(DE-HGF)0
|6 P:(DE-HGF)0
|a Medical University of Vienna, Vienna 1090, Austria
|b 2
910 1 _ |0 I:(DE-HGF)0
|6 0000-0002-9247-6457
|a Medical University of Vienna, Vienna 1090, Austria
|b 3
910 1 _ |0 I:(DE-HGF)0
|6 P:(DE-HGF)0
|a Medical University of Vienna, Vienna 1090, Austria
|b 4
910 1 _ |0 I:(DE-HGF)0
|6 P:(DE-HGF)0
|a Medical University of Vienna, Vienna 1090, Austria
|b 5
910 1 _ |0 I:(DE-HGF)0
|6 P:(DE-HGF)0
|a Medical University of Vienna, Vienna 1090, Austria
|b 6
910 1 _ |0 I:(DE-HGF)0
|6 P:(DE-HGF)0
|a Medical University of Vienna, Vienna 1090, Austria
|b 7
910 1 _ |0 I:(DE-HGF)0
|6 P:(DE-HGF)0
|a Medical University of Vienna, Vienna 1090, Austria
|b 8
910 1 _ |0 I:(DE-HGF)0
|6 P:(DE-HGF)0
|a Medical University of Vienna, Vienna 1090, Austria
|b 9
910 1 _ |0 I:(DE-HGF)0
|6 P:(DE-HGF)0
|a Medical University of Vienna, Vienna 1090, Austria
|b 10
910 1 _ |0 I:(DE-HGF)0
|6 P:(DE-HGF)0
|a Medical University of Vienna, Vienna 1090, Austria
|b 11
910 1 _ |0 I:(DE-HGF)0
|6 P:(DE-HGF)0
|a Medical University of Vienna, Vienna 1090, Austria
|b 12
910 1 _ |0 I:(DE-HGF)0
|6 P:(DE-HGF)0
|a Medical University of Vienna, Vienna 1090, Austria
|b 13
910 1 _ |0 I:(DE-HGF)0
|6 P:(DE-HGF)0
|a The Hong Kong Polytechnic University Hong Kong 999077, China
|b 13
910 1 _ |0 I:(DE-HGF)0
|6 P:(DE-HGF)0
|a Medical University of Vienna, Vienna 1090, Austria
|b 14
910 1 _ |0 I:(DE-HGF)0
|6 P:(DE-HGF)0
|a Ludwig Boltzmann Institute Applied Diagnostics, Vienna 1090, Austria
|b 15
910 1 _ |0 I:(DE-HGF)0
|6 P:(DE-HGF)0
|a Medical University of Vienna, Vienna 1090, Austria
|b 15
910 1 _ |0 I:(DE-HGF)0
|6 P:(DE-HGF)0
|a Medical University of Vienna, Vienna 1090, Austria
|b 16
910 1 _ |0 I:(DE-HGF)0
|6 P:(DE-HGF)0
|a Center for Biomarker Research in Medicine (CBmed), Graz 8010, Austria
|b 16
910 1 _ |0 I:(DE-588b)5008462-8
|6 P:(DE-Juel1)131672
|a Forschungszentrum Jülich
|b 17
|k FZJ
910 1 _ |0 I:(DE-HGF)0
|6 P:(DE-HGF)0
|a Medical University of Vienna, Vienna 1090, Austria
|b 18
910 1 _ |0 I:(DE-HGF)0
|6 P:(DE-HGF)0
|a Medical University of Vienna, Vienna 1090, Austria
|b 19
910 1 _ |0 I:(DE-HGF)0
|6 0000-0003-4641-9539
|a Medical University of Vienna, Vienna 1090, Austria
|b 20
913 1 _ |0 G:(DE-HGF)POF3-573
|1 G:(DE-HGF)POF3-570
|2 G:(DE-HGF)POF3-500
|a DE-HGF
|b Key Technologies
|l Decoding the Human Brain
|v Neuroimaging
|x 0
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF3
914 1 _ |y 2018
915 _ _ |0 StatID:(DE-HGF)0200
|2 StatID
|a DBCoverage
|b SCOPUS
915 _ _ |0 StatID:(DE-HGF)1030
|2 StatID
|a DBCoverage
|b Current Contents - Life Sciences
915 _ _ |0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
|a Creative Commons Attribution CC BY 4.0
915 _ _ |0 StatID:(DE-HGF)0100
|2 StatID
|a JCR
|b CEREB CORTEX : 2017
915 _ _ |0 StatID:(DE-HGF)0150
|2 StatID
|a DBCoverage
|b Web of Science Core Collection
915 _ _ |0 StatID:(DE-HGF)0110
|2 StatID
|a WoS
|b Science Citation Index
915 _ _ |0 StatID:(DE-HGF)0111
|2 StatID
|a WoS
|b Science Citation Index Expanded
915 _ _ |0 StatID:(DE-HGF)0510
|2 StatID
|a OpenAccess
915 _ _ |0 StatID:(DE-HGF)9905
|2 StatID
|a IF >= 5
|b CEREB CORTEX : 2017
915 _ _ |0 StatID:(DE-HGF)0310
|2 StatID
|a DBCoverage
|b NCBI Molecular Biology Database
915 _ _ |0 StatID:(DE-HGF)1050
|2 StatID
|a DBCoverage
|b BIOSIS Previews
915 _ _ |0 StatID:(DE-HGF)0300
|2 StatID
|a DBCoverage
|b Medline
915 _ _ |0 StatID:(DE-HGF)0320
|2 StatID
|a DBCoverage
|b PubMed Central
915 _ _ |0 StatID:(DE-HGF)0420
|2 StatID
|a Nationallizenz
915 _ _ |0 StatID:(DE-HGF)0199
|2 StatID
|a DBCoverage
|b Clarivate Analytics Master Journal List
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)INM-2-20090406
|k INM-2
|l Molekulare Organisation des Gehirns
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)INM-2-20090406
980 1 _ |a FullTexts


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21