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Characterizing longitudinal white matter development during early childhood.

Dean DC, O'Muircheartaigh J, Dirks H, Waskiewicz N, Walker L, Doernberg E, Piryatinsky I, Deoni SC - Brain Struct Funct (2014)

Bottom Line: Using nonlinear mixed effects modeling, we provide the first in vivo longitudinal description of myelin water fraction development.Moreover, we show distinct male and female developmental patterns, and demonstrate significant relationships between myelin content and measures of cognitive function.These findings advance a new understanding of healthy brain development and provide a foundation from which to assess atypical development.

View Article: PubMed Central - PubMed

Affiliation: Advanced Baby Imaging Laboratory, School of Engineering, Brown University, Providence, RI, 02912, USA, douglas_dean_iii@brown.edu.

ABSTRACT
Post-mortem studies have shown the maturation of the brain's myelinated white matter, crucial for efficient and coordinated brain communication, follows a nonlinear spatio-temporal pattern that corresponds with the onset and refinement of cognitive functions and behaviors. Unfortunately, investigation of myelination in vivo is challenging and, thus, little is known about the normative pattern of myelination, or its association with functional development. Using a novel quantitative magnetic resonance imaging technique sensitive to myelin we examined longitudinal white matter development in 108 typically developing children ranging in age from 2.5 months to 5.5 years. Using nonlinear mixed effects modeling, we provide the first in vivo longitudinal description of myelin water fraction development. Moreover, we show distinct male and female developmental patterns, and demonstrate significant relationships between myelin content and measures of cognitive function. These findings advance a new understanding of healthy brain development and provide a foundation from which to assess atypical development.

No MeSH data available.


TopRow: 95 % confidence intervals for the frontal white matter and body of the corpus callosum. Using the standard error estimates from the nonlinear mixed effects modeling, confidence intervals of the population trajectory can be estimated. Bottom row: representative VFM growth rate curves. These curves were reconstructed by taking the time derivative of the modified Gompertz function (Eq. 2) and using the overall population estimates of the modified Gompertz parameters. Such curves are informative of the rate of change of the VFM with respect to age (time) and highlight the posterior–anterior developmental gradient of VFM
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Fig4: TopRow: 95 % confidence intervals for the frontal white matter and body of the corpus callosum. Using the standard error estimates from the nonlinear mixed effects modeling, confidence intervals of the population trajectory can be estimated. Bottom row: representative VFM growth rate curves. These curves were reconstructed by taking the time derivative of the modified Gompertz function (Eq. 2) and using the overall population estimates of the modified Gompertz parameters. Such curves are informative of the rate of change of the VFM with respect to age (time) and highlight the posterior–anterior developmental gradient of VFM

Mentions: The mixed effect modeling framework was applied to the 28 regional VFM trajectories to obtain Gompertz growth curve parameter estimates of both population fixed and subject-specific random effects. Representative modeled developmental trajectories are shown in Fig. 3, with overall population curves overlaid on top of subject-specific developmental trajectories. Additional trajectories are provided in Supplementary Figure 4. These plots illustrate both the degree of individual variability of VFM development, as well as the ability of the modeling framework to capture the population’s overall growth pattern. Moreover, mixed effects modeling provides standard error estimates of the fixed parameters, allowing derivation of confidence intervals of the developmental trajectory (Fig. 4).Fig. 3


Characterizing longitudinal white matter development during early childhood.

Dean DC, O'Muircheartaigh J, Dirks H, Waskiewicz N, Walker L, Doernberg E, Piryatinsky I, Deoni SC - Brain Struct Funct (2014)

TopRow: 95 % confidence intervals for the frontal white matter and body of the corpus callosum. Using the standard error estimates from the nonlinear mixed effects modeling, confidence intervals of the population trajectory can be estimated. Bottom row: representative VFM growth rate curves. These curves were reconstructed by taking the time derivative of the modified Gompertz function (Eq. 2) and using the overall population estimates of the modified Gompertz parameters. Such curves are informative of the rate of change of the VFM with respect to age (time) and highlight the posterior–anterior developmental gradient of VFM
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4481335&req=5

Fig4: TopRow: 95 % confidence intervals for the frontal white matter and body of the corpus callosum. Using the standard error estimates from the nonlinear mixed effects modeling, confidence intervals of the population trajectory can be estimated. Bottom row: representative VFM growth rate curves. These curves were reconstructed by taking the time derivative of the modified Gompertz function (Eq. 2) and using the overall population estimates of the modified Gompertz parameters. Such curves are informative of the rate of change of the VFM with respect to age (time) and highlight the posterior–anterior developmental gradient of VFM
Mentions: The mixed effect modeling framework was applied to the 28 regional VFM trajectories to obtain Gompertz growth curve parameter estimates of both population fixed and subject-specific random effects. Representative modeled developmental trajectories are shown in Fig. 3, with overall population curves overlaid on top of subject-specific developmental trajectories. Additional trajectories are provided in Supplementary Figure 4. These plots illustrate both the degree of individual variability of VFM development, as well as the ability of the modeling framework to capture the population’s overall growth pattern. Moreover, mixed effects modeling provides standard error estimates of the fixed parameters, allowing derivation of confidence intervals of the developmental trajectory (Fig. 4).Fig. 3

Bottom Line: Using nonlinear mixed effects modeling, we provide the first in vivo longitudinal description of myelin water fraction development.Moreover, we show distinct male and female developmental patterns, and demonstrate significant relationships between myelin content and measures of cognitive function.These findings advance a new understanding of healthy brain development and provide a foundation from which to assess atypical development.

View Article: PubMed Central - PubMed

Affiliation: Advanced Baby Imaging Laboratory, School of Engineering, Brown University, Providence, RI, 02912, USA, douglas_dean_iii@brown.edu.

ABSTRACT
Post-mortem studies have shown the maturation of the brain's myelinated white matter, crucial for efficient and coordinated brain communication, follows a nonlinear spatio-temporal pattern that corresponds with the onset and refinement of cognitive functions and behaviors. Unfortunately, investigation of myelination in vivo is challenging and, thus, little is known about the normative pattern of myelination, or its association with functional development. Using a novel quantitative magnetic resonance imaging technique sensitive to myelin we examined longitudinal white matter development in 108 typically developing children ranging in age from 2.5 months to 5.5 years. Using nonlinear mixed effects modeling, we provide the first in vivo longitudinal description of myelin water fraction development. Moreover, we show distinct male and female developmental patterns, and demonstrate significant relationships between myelin content and measures of cognitive function. These findings advance a new understanding of healthy brain development and provide a foundation from which to assess atypical development.

No MeSH data available.