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Correction: Global genetic variations predict brain response to faces

Authors :
Dickie, Erin W.
Tahmasebi, Amir
French, Leon
Kovacevic, Natasa
Banaschewski, Tobias
Barker, Gareth J.
Bokde, Arun
Büchel, Christian
Conrod, Patricia J.
Flor, Herta
Garavan, Hugh
Gallinat, Jürgen
Gowland, Penny
Heinz, Andreas
Ittermann, Bernd
Lawrence, Claire
Mann, Karl
Martinot, Jean-Luc
Nees, Frauke
Nichols, Thomas E.
Lathrop, Mark
Loth, Eva
Pausova, Zdenka
Rietschel, Marcela
Smolka, Michal N.
Ströhle, Andreas
Toro, Roberto
Schumann, Gunter
Paus, Tomáš
HASH(0x5651ca074060)
Publication Year :
2014
Publisher :
Public Library of Science, 2014.

Abstract

Face expressions are a rich source of social signals. Here we estimated the proportion of phenotypic variance in the brain response to facial expressions explained by common genetic variance captured by ~500,000 single nucleotide polymorphisms. Using genomic-relationship-matrix restricted maximum likelihood (GREML), we related this global genetic variance to that in the brain response to facial expressions, as assessed with functional magnetic resonance imaging (fMRI) in a community-based sample of adolescents (n = 1,620). Brain response to facial expressions was measured in 25 regions constituting a face network, as defined previously. In 9 out of these 25 regions, common genetic variance explained a significant proportion of phenotypic variance (40–50%) in their response to ambiguous facial expressions; this was not the case for angry facial expressions. Across the network, the strength of the genotype-phenotype relationship varied as a function of the inter-individual variability in the number of functional connections possessed by a given region (R2 = 0.38, p

Details

Language :
English
ISSN :
15537390
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....4d4ee0c549f31a719da50ae9f4d5355d