Indra Kraft1, Jan Schreiber2, Riccardo Cafiero2, Riccardo Metere3, Gesa Schaadt4, Jens Brauer2, Nicole E Neef2, Bent Müller5, Holger Kirsten6, Arndt Wilcke5, Johannes Boltze7, Angela D Friederici2, Michael A Skeide2. 1. Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany. Electronic address: ikraft@cbs.mpg.de. 2. Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany. 3. Nuclear Magnetic Resonance Unit, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany. 4. Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany; Department of Psychology, Humboldt-Universität zu Berlin, Rudower Chaussee 18, 12489 Berlin, Germany. 5. Cognitive Genetics Unit, Department of Cell Therapy, Fraunhofer Institute for Cell Therapy and Immunology, Perlickstraße 1, 04103 Leipzig, Germany. 6. Cognitive Genetics Unit, Department of Cell Therapy, Fraunhofer Institute for Cell Therapy and Immunology, Perlickstraße 1, 04103 Leipzig, Germany; Institute for Medical Informatics, Statistics and Epidemiology, and LIFE - Leipzig Research Center for Civilization Diseases, Universität Leipzig, Härtelstraße 16 - 18, 04107 Leipzig, Germany. 7. Cognitive Genetics Unit, Department of Cell Therapy, Fraunhofer Institute for Cell Therapy and Immunology, Perlickstraße 1, 04103 Leipzig, Germany; Fraunhofer Research Institution for Marine Biotechnology, Department of Medical Cell Technology, and Institute for Medical and Marine Biotechnology, Universität Lübeck, Mönkhofer Weg 239a, 23562 Lübeck, Germany.
Abstract
BACKGROUND: Recent studies suggest that neurobiological anomalies are already detectable in pre-school children with a family history of developmental dyslexia (DD). However, there is a lack of longitudinal studies showing a direct link between those differences at a preliterate age and the subsequent literacy difficulties seen in school. It is also not clear whether the prediction of DD in pre-school children can be significantly improved when considering neurobiological predictors, compared to models based on behavioral literacy precursors only. METHODS: We recruited 53 pre-reading children either with (N=25) or without a family risk of DD (N=28). Quantitative T1 MNI data and literacy precursor abilities were assessed at kindergarten age. A subsample of 35 children was tested for literacy skills either one or two years later, that is, either in first or second grade. RESULTS: The group comparison of quantitative T1 measures revealed significantly higher T1 intensities in the left anterior arcuate fascicle (AF), suggesting reduced myelin concentration in preliterate children at risk of DD. A logistic regression showed that DD can be predicted significantly better (p=.024) when neuroanatomical differences between groups are used as predictors (80%) compared to a model based on behavioral predictors only (63%). The Wald statistic confirmed that the T1 intensity of the left AF is a statistically significant predictor of DD (p<.05). CONCLUSIONS: Our longitudinal results provide evidence for the hypothesis that neuroanatomical anomalies in children with a family risk of DD are related to subsequent problems in acquiring literacy. Particularly, solid white matter organization in the left anterior arcuate fascicle seems to play a pivotal role. Copyright Â
BACKGROUND: Recent studies suggest that neurobiological anomalies are already detectable in pre-school children with a family history of developmental dyslexia (DD). However, there is a lack of longitudinal studies showing a direct link between those differences at a preliterate age and the subsequent literacy difficulties seen in school. It is also not clear whether the prediction of DD in pre-school children can be significantly improved when considering neurobiological predictors, compared to models based on behavioral literacy precursors only. METHODS: We recruited 53 pre-reading children either with (N=25) or without a family risk of DD (N=28). Quantitative T1 MNI data and literacy precursor abilities were assessed at kindergarten age. A subsample of 35 children was tested for literacy skills either one or two years later, that is, either in first or second grade. RESULTS: The group comparison of quantitative T1 measures revealed significantly higher T1 intensities in the left anterior arcuate fascicle (AF), suggesting reduced myelin concentration in preliterate children at risk of DD. A logistic regression showed that DD can be predicted significantly better (p=.024) when neuroanatomical differences between groups are used as predictors (80%) compared to a model based on behavioral predictors only (63%). The Wald statistic confirmed that the T1 intensity of the left AF is a statistically significant predictor of DD (p<.05). CONCLUSIONS: Our longitudinal results provide evidence for the hypothesis that neuroanatomical anomalies in children with a family risk of DD are related to subsequent problems in acquiring literacy. Particularly, solid white matter organization in the left anterior arcuate fascicle seems to play a pivotal role. Copyright Â
Authors: Lauren R Borchers; Lisa Bruckert; Cory K Dodson; Katherine E Travis; Virginia A Marchman; Michal Ben-Shachar; Heidi M Feldman Journal: Brain Struct Funct Date: 2018-12-11 Impact factor: 3.270
Authors: Edith Brignoni-Pérez; Sarah E Dubner; Michal Ben-Shachar; Shai Berman; Aviv A Mezer; Heidi M Feldman; Katherine E Travis Journal: Neuroimage Date: 2022-04-28 Impact factor: 7.400