Modeling healthy male white matter and myelin development: 3 through 60months of age

Abstract

An emerging hypothesis in developmental and behavioral disorders is that they arise from disorganized brain messaging or reduced connectivity. Given the importance of myelin to efficient brain communication, characterization of myelin development in infancy and childhood may provide salient information related to early connectivity deficits. In this work, we investigate regional and whole brain growth trajectories of the myelin water fraction, a quantitative magnetic resonance imaging measure sensitive and specific to myelin content, in data acquired from 122 healthy male children from 3 to 60months of age. We examine common growth functions to find the most representative model of myelin maturation and subsequently use the best of these models to develop a continuous population-averaged, four-dimensional model of normative myelination. Through comparisons with an independent sample of 63 male children across the same age span, we show that the developed model is representative of this population. This work contributes to understanding the trajectory of myelination in healthy infants and toddlers, furthering our knowledge of early brain development, and provides a model that may be useful for identifying developmental abnormalities.

Keywords: Brain development; Infant imaging; Myelin maturation; Myelin water fraction; White matter development.

Fig. 1

(A) Properties of a sigmoid function. Although many functional forms exist, each shares three similar characteristics: 1) an initial lag or period of slow growth, 2) a period of rapid exponential growth, and 3) a period of reduced growth-rate. These properties and shape of the overall curve are governed by the free parameters of the model. (B) Modified Gompertz model is described by 4 free parameters, each contributing to the characteristics of the curve. These parameters may be useful for describing biologically relevant metrics such as a developmental transitionary period (α), developmental lag, or (β) growth rates (γ, δ).

Fig. 2

Derived myelination trajectories for the left and right hemisphere frontal, temporal, occipital, parietal and cerebellar white matter, as well as body, genu, and splenium of the corpus callosum from 122 healthy male infants under 5 years of age. Right and left hemisphere measurements are denoted with black squares and gray circles, respectively. Error bars represent the standard deviation of the measurement. These developmental trajectories exhibit the characteristic ‘S’-shaped curve of a sigmoid, suggesting this class of models might be best to characterize the underlying pattern.

Fig. 3

Plot comparing representative native-space and template-space mean MWF values. High correlation between the native-space and template-space illustrate that MWF values were not significantly altered through the normalization process.

Fig. 4

Representative fitting of the mean myelination trajectory for the body of corpus callosum. Blue points represent mean MWF values from the 122 male infants, while the red curve represents the best-fit curve for each investigated model. In total, 8 sigmoid models were examined. BIC metric values indicate that the modified Gompertz growth model provided the best fit.

Fig. 5

Mean, acquired, model-derived MWF maps, and difference maps for 9 separate age groups (Table 3). Comparison of acquired and model derived MWF maps was done using a paired t-test for each age group. Few significant differences (p < 0.05, uncorrected) were detected between the in vivo and model-derived maps.

Fig. 6

Repeated individual MWF maps at three different time points. Atlas derived MWF maps were derived for each corresponding age and compared to the longitudinal data using Z-statistics. Few areas of significant differences (|Z| < 1.96) between the repeated data and corresponding model-derived MWF maps were found.

Fig. 7

Bootstrapped mean Gompertz fit with 95% confidence interval for mean MWF values obtained from the genu, body and splenium of the corpus callosum.