001     891996
005     20230418142414.0
024 7 _ |a 10.1007/s10548-021-00837-1
|2 doi
024 7 _ |a 0896-0267
|2 ISSN
024 7 _ |a 1573-6792
|2 ISSN
024 7 _ |a 2128/30191
|2 Handle
024 7 _ |a 33866460
|2 pmid
024 7 _ |a WOS:000640947100001
|2 WOS
037 _ _ |a FZJ-2021-01868
082 _ _ |a 610
100 1 _ |a Myznikov, A.
|0 P:(DE-HGF)0
|b 0
|e Corresponding author
245 _ _ |a Neuroanatomical Correlates of Social Intelligence Measured by the Guilford Test
260 _ _ |a Dordrecht [u.a.]
|c 2021
|b Springer Science + Business Media B.V
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1642082489_5828
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a Social interactions are a crucial aspect of human behaviour. Numerous neurophysiological studies have focused on socio-cognitive processes associated with the so-called theory of mind—the ability to attribute mental states to oneself and others. Theory of mind is closely related to social intelligence defined as a set of abilities that facilitate effective social interactions. Social intelligence encompasses multiple theory of mind components and can be measured by the Four Factor Test of Social Intelligence (the Guilford-Sullivan test). However, it is unclear whether the differences in social intelligence are reflected in structural brain differences. During the experiment, 48 healthy right-handed individuals completed the Guilford-Sullivan test. T1-weighted structural MRI images were obtained for all participants. Voxel-based morphometry analysis was performed to reveal grey matter volume differences between the two groups (24 subjects in each)—with high social intelligence scores and with low social intelligence scores, respectively. Participants with high social intelligence scores had larger grey matter volumes of the bilateral caudate. The obtained results suggest the caudate nucleus involvement in the neural system of socio-cognitive processes, reflected by its structural characteristics.
536 _ _ |a 5252 - Brain Dysfunction and Plasticity (POF4-525)
|0 G:(DE-HGF)POF4-5252
|c POF4-525
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de
700 1 _ |a Zheltyakova, M.
|0 P:(DE-HGF)0
|b 1
700 1 _ |a Korotkov, A.
|0 P:(DE-HGF)0
|b 2
700 1 _ |a Kireev, M.
|0 P:(DE-Juel1)159559
|b 3
700 1 _ |a Masharipov, R.
|0 P:(DE-HGF)0
|b 4
700 1 _ |a Jagmurov, O. Dz.
|0 P:(DE-HGF)0
|b 5
700 1 _ |a Habel, U.
|0 P:(DE-Juel1)172840
|b 6
|u fzj
700 1 _ |a Votinov, M.
|0 P:(DE-Juel1)166584
|b 7
773 _ _ |a 10.1007/s10548-021-00837-1
|g Vol. 34, no. 3, p. 337 - 347
|0 PERI:(DE-600)2015003-9
|n 3
|p 337 - 347
|t Brain topography
|v 34
|y 2021
|x 1573-6792
856 4 _ |u https://juser.fz-juelich.de/record/891996/files/Myznikov2021_Article_NeuroanatomicalCorrelatesOfSoc.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:891996
|p openaire
|p open_access
|p OpenAPC_DEAL
|p driver
|p VDB
|p openCost
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 6
|6 P:(DE-Juel1)172840
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 7
|6 P:(DE-Juel1)166584
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)POF4-5252
|x 0
914 1 _ |y 2021
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2021-01-31
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2021-01-31
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
|d 2021-01-31
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1190
|2 StatID
|b Biological Abstracts
|d 2021-01-31
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b BRAIN TOPOGR : 2019
|d 2021-01-31
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
|d 2021-01-31
915 _ _ |a DEAL Springer
|0 StatID:(DE-HGF)3002
|2 StatID
|d 2021-01-31
|w ger
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2021-01-31
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2021-01-31
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2021-01-31
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2021-01-31
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
|d 2021-01-31
|w ger
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2021-01-31
915 p c |a APC keys set
|2 APC
|0 PC:(DE-HGF)0000
915 p c |a DEAL: Springer Nature 2020
|2 APC
|0 PC:(DE-HGF)0113
920 1 _ |0 I:(DE-Juel1)INM-10-20170113
|k INM-10
|l Jara-Institut Brain structure-function relationships
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)INM-10-20170113
980 _ _ |a APC
980 1 _ |a APC
980 1 _ |a FullTexts


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21