Neuropsychological development in adolescents: Longitudinal associations with white matter microstructure

• Main Authors: Ines M. Mürner-Lavanchy, Julian Koenig, Ayaka Ando, Romy Henze, Susanne Schell, Franz Resch, Romuald Brunner, Michael Kaess
• Format: Article
• Language: English
• Published: Elsevier 2020-10-01
• Series: Developmental Cognitive Neuroscience
• Subjects: Cognition; Adolescent; Development; Longitudinal; Diffusion tensor imaging; White matter microstructure
• Online Access: http://www.sciencedirect.com/science/article/pii/S1878929320300608

Important neuropsychological changes during adolescence coincide with the maturation of white matter microstructure. Few studies have investigated the association between neuropsychological development and white matter maturation longitudinally. We aimed to characterize developmental trajectories of inhibition, planning, emotion recognition and risk-taking and examine whether white matter microstructural characteristics were associated with neuropsychological development above and beyond age. In an accelerated longitudinal cohort design, n = 112 healthy adolescents between ages 9 and 16 underwent cognitive assessment and diffusion MRI over three years. Fractional anisotropy (FA) and mean diffusivity (MD) were extracted for major white matter pathways using an automatic probabilistic reconstruction technique and mixed models were used for statistical analyses. Inhibition, planning and emotion recognition performance improved linearly across adolescence. Risk-taking developed in a quadratic fashion, with stable performance between 9 and 12 and an increase between ages 12 and 16. Including cingulum and superior longitudinal fasciculus FA slightly improved model fit for emotion recognition across age. We found no evidence that FA or MD were related to inhibition, planning or risk-taking across age. Our results challenge the additional value of white matter microstructure to explain neuropsychological development in healthy adolescents, but more longitudinal research with large datasets is needed to identify the potential role of white matter microstructure in cognitive development.