Timing of White Matter Development Determines Cognitive Abilities at School Entry but Not in Late Adolescence

Ullman, Henrik; Klingberg, Torkel

doi:10.1093/cercor/bhw256

Cited by 2 publications

(3 citation statements)

References 44 publications

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“…In other words, having advanced brain maturation, which may be considered to be a type of "deviation," is associated with positive outcomes. Previous studies have reported increased cognitive performance for individuals with high brain age, in normative samples [39,108]. Here we found higher brain age is related to reduced ASD severity.…”

Section: Multivariate Brain Maturationsupporting

confidence: 65%

Deviation from normative brain development is associated with symptom severity in autism spectrum disorder

et al. 2019

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Background: Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition. The degree to which the brain development in ASD deviates from typical brain development, and how this deviation relates to observed behavioral outcomes at the individual level are not well-studied. We hypothesize that the degree of deviation from typical brain development of an individual with ASD would relate to observed symptom severity. Methods: The developmental changes in anatomical (cortical thickness, surface area, and volume) and diffusion metrics (fractional anisotropy and apparent diffusion coefficient) were compared between a sample of ASD (n = 247) and typically developing children (TDC) (n = 220) aged 6-25. Machine learning was used to predict age (brain age) from these metrics in the TDC sample, to define a normative model of brain development. This model was then used to compute brain age in the ASD sample. The difference between chronological age and brain age was considered a developmental deviation index (DDI), which was then correlated with ASD symptom severity.Results: Machine learning model trained on all five metrics accurately predicted age in the TDC (r = 0.88) and the ASD (r = 0.85) samples, with dominant contributions to the model from the diffusion metrics. Within the ASD group, the DDI derived from fractional anisotropy was correlated with ASD symptom severity (r = − 0.2), such that individuals with the most advanced brain age showing the lowest severity, and individuals with the most delayed brain age showing the highest severity. Limitations: This work investigated only linear relationships between five specific brain metrics and only one measure of ASD symptom severity in a limited age range. Reported effect sizes are moderate. Further work is needed to investigate developmental differences in other age ranges, other aspects of behavior, other neurobiological measures, and in an independent sample before results can be clinically applicable. Conclusions: Findings demonstrate that the degree of deviation from typical brain development relates to ASD symptom severity, partially accounting for the observed heterogeneity in ASD. Our approach enables characterization of each individual with reference to normative brain development and identification of distinct developmental subtypes, facilitating a better understanding of developmental heterogeneity in ASD.

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Section: Multivariate Brain Maturationsupporting

confidence: 65%

Deviation from normative brain development is associated with symptom severity in autism spectrum disorder

et al. 2019

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“…For example, whole‐brain FA from DTI was associated with visuospatial ability, independent of age, in a large sample of primary school‐aged children ( n = 778, age range = 6–10 years; Muetzel et al, ). In another study, DTI indices were used to calculate an estimate of the variability in white matter development—deemed brain age in a cohort of typically developing children, adolescents, and young adults ( n = 82, age range = 6–20 years) (Ullman & Klingberg, ). Brain age predicted working memory and numerical ability in younger children, but not in adolescents and young adults, suggesting that variability in individual developmental timing strongly affects cognition in younger ages (6–11 years), but does not predict adolescent cognitive functioning (Ullman & Klingberg, ).…”

Section: Introductionmentioning

confidence: 99%

“…In another study, DTI indices were used to calculate an estimate of the variability in white matter development—deemed brain age in a cohort of typically developing children, adolescents, and young adults ( n = 82, age range = 6–20 years) (Ullman & Klingberg, ). Brain age predicted working memory and numerical ability in younger children, but not in adolescents and young adults, suggesting that variability in individual developmental timing strongly affects cognition in younger ages (6–11 years), but does not predict adolescent cognitive functioning (Ullman & Klingberg, ). Finally, a recent MCR study showed that voxel‐wise MWF from within frontal and temporal areas predicted language abilities and that relations became more strongly associated with increasing age in infants and preschool children ( n = 183, age range = 3 months–4 years; O'Muircheartaigh et al, ).…”

Section: Introductionmentioning

confidence: 99%

White matter plasticity and maturation in human cognition

Bells

Lefebvre

Longoni

et al. 2019

Glia

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White matter plasticity likely plays a critical role in supporting cognitive development. However, few studies have used the imaging methods specific to white matter tissue structure or experimental designs sensitive to change in white matter necessary to elucidate these relations. Here we briefly review novel imaging approaches that provide more specific information regarding white matter microstructure. Furthermore, we highlight recent studies that provide greater clarity regarding the relations between changes in white matter and cognition maturation in both healthy children and adolescents and those with white matter insult. Finally, we examine the hypothesis that white matter is linked to cognitive function via its impact on neural synchronization. We test this hypothesis in a population of children and adolescents with recurrent demyelinating syndromes. Specifically, we evaluate group differences in white matter microstructure within the optic radiation; and neural phase synchrony in visual cortex during a visual task between 25 patients and 28 typically developing age‐matched controls. Children and adolescents with demyelinating syndromes show evidence of myelin and axonal compromise and this compromise predicts reduced phase synchrony during a visual task compared to typically developing controls. We investigate one plausible mechanism at play in this relationship using a computational model of gamma generation in early visual cortical areas. Overall, our findings show a fundamental connection between white matter microstructure and neural synchronization that may be critical for cognitive processing. In the future, longitudinal or interventional studies can build upon our knowledge of these exciting relations between white matter, neural communication, and cognition.

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Timing of White Matter Development Determines Cognitive Abilities at School Entry but Not in Late Adolescence

Cited by 2 publications

References 44 publications

Deviation from normative brain development is associated with symptom severity in autism spectrum disorder

Deviation from normative brain development is associated with symptom severity in autism spectrum disorder

White matter plasticity and maturation in human cognition

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