Neural basis of interindividual variability in social perception in typically developing children and adolescents using diffusion tensor imaging - Archive ouverte HAL Access content directly
Journal Articles Scientific Reports Year : 2020

Neural basis of interindividual variability in social perception in typically developing children and adolescents using diffusion tensor imaging

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Abstract

Humans show great interindividual variability in the degree they engage in social relationship. The neural basis of this variability is still poorly understood, particularly in children. In this study, we aimed to investigate the neural basis of interindividual variability in the first step of social behavior, that is social perception, in typically developing children. For that purpose, we first used eye-tracking to objectively measure eye-gaze processing during passive visualization of social movie clips in 24 children and adolescents (10.5 ± 2.9 y). Secondly, we correlated eye-tracking data with measures of fractional anisotropy, an index of white matter microstructure, obtained using diffusion tensor imaging MRI. The results showed a large interindividual variability in the number of fixations to the eyes of characters during visualization of social scenes. In addition, whole-brain analysis showed a significant positive correlation between FA and number of fixations to the eyes,mainly in the temporal part of the superior longitudinal fasciculi bilaterally, adjacent to the posterior superior temporal cortex. Our results indicate the existence of a neural signature associated with the interindividual variability in social perception in children, contributing for better understanding the neural basis of typical and atypical development of a broader social expertise.
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Dates and versions

inserm-02875026 , version 1 (19-06-2020)

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Alice Vinçon-Leite, Ana Saitovitch, Hervé Lemaitre, Elza Rechtman, Ludovic Fillon, et al.. Neural basis of interindividual variability in social perception in typically developing children and adolescents using diffusion tensor imaging. Scientific Reports, 2020, 10 (1), pp.6379. ⟨10.1038/s41598-020-63273-4⟩. ⟨inserm-02875026⟩
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