White matter growth as a mechanism of cognitive development in children

NeuroImage ◽  
2006 ◽  
Vol 33 (3) ◽  
pp. 936-946 ◽  
Author(s):  
Donald J. Mabbott ◽  
Michael Noseworthy ◽  
Eric Bouffet ◽  
Suzanne Laughlin ◽  
Conrad Rockel
2018 ◽  
Author(s):  
Elizabeth Huber ◽  
Rafael Neto Henriques ◽  
Julia P. Owen ◽  
Ariel Rokem ◽  
Jason D. Yeatman

AbstractDiffusion MRI (dMRI) holds great promise for illuminating the biological changes that underpin cognitive development. The diffusion of water molecules probes the cellular structure of brain tissue, and biophysical modeling of the diffusion signal can be used to make inferences about specific tissue properties that vary over development or predict cognitive performance. However, applying these models to study development requires that the parameters can be reliably estimated given the constraints of data collection with children. Here we collect repeated scans using a multi-shell diffusion MRI protocol in a group of children (ages 7-12) and use two popular biophysical models to characterize axonal properties. We first assess the scan-rescan reliability of model parameters and show that axon water faction can be reliably estimated from a relatively fast acquisition, without applying spatial smoothing or de-noising. We then investigate developmental changes in the white matter, and individual differences in white matter that correlate with reading skill. Specifically, we test the hypothesis that previously reported correlations between reading skill and diffusion anisotropy in the corpus callosum reflect increased axon density in poor readers. Both models support this interpretation, highlighting the utility of biophysical models for testing specific hypotheses about cognitive development.


2019 ◽  
Vol 36 ◽  
pp. 100624 ◽  
Author(s):  
Elizabeth Huber ◽  
Rafael Neto Henriques ◽  
Julia P. Owen ◽  
Ariel Rokem ◽  
Jason D. Yeatman

2019 ◽  
Vol 4 (5) ◽  
pp. 423-433 ◽  
Author(s):  
Catherine E. Hegarty ◽  
Dietsje D. Jolles ◽  
Eva Mennigen ◽  
Maria Jalbrzikowski ◽  
Carrie E. Bearden ◽  
...  

NeuroImage ◽  
2019 ◽  
Vol 185 ◽  
pp. 825-835 ◽  
Author(s):  
Jerod M. Rasmussen ◽  
Alice M. Graham ◽  
Sonja Entringer ◽  
John H. Gilmore ◽  
Martin Styner ◽  
...  

2019 ◽  
Vol 40 (14) ◽  
pp. 4130-4145 ◽  
Author(s):  
Xiongtao Dai ◽  
Pantelis Hadjipantelis ◽  
Jane‐Ling Wang ◽  
Sean C. L. Deoni ◽  
Hans‐Georg Müller

2016 ◽  
Vol 37 (8) ◽  
pp. 2943-2958 ◽  
Author(s):  
Jia Fan ◽  
Sandra W. Jacobson ◽  
Paul A. Taylor ◽  
Christopher D. Molteno ◽  
Neil C. Dodge ◽  
...  

2016 ◽  
Vol 114 (1) ◽  
pp. 148-153 ◽  
Author(s):  
Seung Jae Lee ◽  
Rachel J. Steiner ◽  
Yang Yu ◽  
Sarah J. Short ◽  
Michael C. Neale ◽  
...  

Previous studies indicate that the microstructure of individual white matter (WM) tracts is related to cognitive function. More recent studies indicate that the microstructure of individual tracts is highly correlated and that a property common across WM is related to overall cognitive function in adults. However, little is known about whether these common WM properties exist in early childhood development or how they are related to cognitive development. In this study, we used diffusion tensor imaging (DTI) to investigate common underlying factors in 12 fiber tracts, their relationship with cognitive function, and their heritability in a longitudinal sample of healthy children at birth (n = 535), 1 y (n = 322), and 2 y (n = 244) of age. Our data show that, in neonates, there is a highly significant correlation between major WM tracts that decreases from birth to 2 y of age. Over the same period, the factor structure increases in complexity, from one factor at birth to three factors at age 2 y, which explain 50% of variance. The identified common factors of DTI metrics in each age group are significantly correlated with general cognitive scores and predict cognitive ability in later childhood. These factors are moderately heritable. These findings illustrate the anatomical differentiation of WM fiber from birth to 2 y of age that correlate with cognitive development. Our results also suggest that the common factor approach is an informative way to study WM development and its relationship with cognition and is a useful approach for future imaging genetic studies.


NeuroImage ◽  
2020 ◽  
Vol 222 ◽  
pp. 117243
Author(s):  
Justin Remer ◽  
Douglas C. Dean ◽  
Kewei Chen ◽  
Rebecca A. Reiman ◽  
Matthew J. Huentelman ◽  
...  

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