Subtle changes in hippocampal volumes may occur during both physiological and pathophysiological processes in the human brain. Assessing hippocampal volumes manually is a time-consuming procedure, however, creating a need for automated segmentation methods that are both fast and reliable over time. Segmentation algorithms that employ deep convolutional neural networks (CNN) have emerged as a promising solution for large longitudinal neuroimaging studies. However, for these novel algorithms to be useful in clinical studies, the accuracy and reproducibility should be established on independent datasets. Here, we evaluate the performance of a CNN-based hippocampal segmentation algorithm that was developed by Thyreau and colleagues - Hippodeep. We compared its segmentation outputs to manual segmentation and FreeSurfer 6.0 in a sample of 200 healthy participants scanned repeatedly at seven sites across Canada, as part of the Canadian Biomarker Integration Network in Depression consortium. The algorithm demonstrated high levels of stability and reproducibility of volumetric measures across all time points compared to the other two techniques. Although more rigorous testing in clinical populations is necessary, this approach holds promise as a viable option for tracking volumetric changes in longitudinal neuroimaging studies.

White matter development continues throughout childhood and into early adulthood, but few studies have examined early childhood, and the specific trajectories and regional variation in this age range remain unclear. The aim of this study was to characterize developmental trajectories and sex differences of white matter in typically developing young children. Three hundred and ninety-six diffusion tensor imaging datasets from 120 children (57 male) aged 2-8 years were analyzed using tractography. Fractional anisotropy (FA) increased and mean diffusivity (MD) decreased in all white matter tracts by 5-15% over the 6-year period, likely reflecting increases in myelination and axonal packing. Males showed steeper slopes in a number of brain areas. Overall, early childhood is associated with substantial development of all white matter and appears to be an important period for the development of occipital and limbic connections, which showed the largest changes. This study provides a detailed characterization of age-related white matter changes in early childhood, offering baseline data that can be used to understand cognitive and behavioural development, as well as to identify deviations from normal development in children with various diseases, disorders, or brain injuries.

The preschool period is a time of significant physical and behavioral growth, including the improvement of gross and fine motor skills. Although motor development has been comprehensively mapped from infancy to adulthood, the neural correlates associated with motor advancements during early childhood remain unclear. The current study used diffusion tensor imaging (DTI) to delineate key motor pathways and characterize their relationships with motor performance in 80 typically developing preschool children, aged 3-6 years. The Movement Assessment Battery for Children-2nd edition (MABC-II) was used to assess motor functioning. Partial correlations between DTI parameters and motor performance, controlling for sex and age, revealed a positive correlation between motor performance and fractional anisotropy of corpus callosum motor fibers, as well as negative correlations of motor performance with mean and radial diffusivity. These results appear to be driven by females, as correlations were significant in girls but not boys when analyzed separately. Mean corticospinal tract (CST) diffusion parameters were not significantly related to motor performance, but relationships were observed at regionally specific locations along the bilateral CST. These findings suggest preschool-aged children with better motor performance show more mature white matter patterns within motor pathways, and that the structural variation in these pathways may partially account for the natural variability in motor performance.

Adequate cerebral blood flow (CBF) is essential to proper brain development and function. Detailed characterization of CBF developmental trajectories will lead to better understanding of the development of cognitive, motor, and sensory functions, as well as behaviour in children. Previous studies have shown CBF increases during infancy and decreases during adolescence; however, the trajectories during childhood, and in particular the timing of peak CBF, remain unclear. Here, we used arterial spin labeling to map age-related changes of CBF across a large longitudinal sample that included 279 scans on 96 participants (46 girls and 50 boys) aged 2-7 years. CBF maps were analyzed using hierarchical linear regression for every voxel inside the grey matter mask, controlling for multiple comparisons. The results revealed a significant positive linear association between CBF and age in distributed brain regions including prefrontal, temporal, parietal, and occipital cortex, and in the cerebellum. There were no differences in developmental trajectories between males and females. Our findings show that CBF continues to increase until the age of 7 years, likely supporting ongoing improvements in behaviour, cognition, motor, and sensory functions in early childhood.

Intra-individual transient temporal fluctuations in brain signal, as measured by fMRI blood oxygenation level dependent (BOLD) variability, is increasingly considered an important signal rather than measurement noise. Evidence from computational and cognitive neuroscience suggests that signal variability is a good proxy-measure of brain functional integrity and information processing capacity. Here, we sought to explore across-participant and longitudinal relationships between BOLD variability, age, and white matter structure in early childhood. We measured standard deviation of BOLD signal, total white matter volume, global fractional anisotropy (FA) and mean diffusivity (MD) during passive movie viewing in a sample of healthy children (aged 2-8 years; N = 83). We investigated how age and white matter development related to changes in BOLD variability both across- and within-participants. Our across-participant analyses using behavioural partial least squares (bPLS) revealed that the influence of age and white matter maturation on BOLD variability was highly interrelated. BOLD variability increased in widespread frontal, temporal and parietal regions, and decreased in the hippocampus and parahippocampal gyrus with age and white matter development. Our longitudinal analyses using linear mixed effects modelling revealed significant associations between BOLD variability, age and white matter microstructure. Analyses using artificial neural networks demonstrated that BOLD variability and white matter micro and macro-structure at earlier ages were strong predictors of BOLD variability at later ages. By characterizing the across-participant and longitudinal features of the association between BOLD variability and white matter micro- and macrostructure in early childhood, our results provide a novel perspective to understand structure-function relationships in the developing brain.

Early childhood is an important period for cognitive and brain development, though white matter changes specific to this period remain understudied. Here we utilize a novel analytic approach to quantify and track developmental changes in white matter micro- and macro-structure, calculated from individually oriented fiber-bundle populations, termed "fixels". Fixel-based analysis and mixed-effects models were used to assess tract-wise changes in fiber density and bundle morphology in 73 girls scanned at baseline (ages 4.09-7.02, mean ​= ​5.47, SD ​= ​0.81), 6-month (N ​= ​7), and one-year follow-up (N ​= ​42). For comparison, we also assessed changes in commonly utilized diffusion tensor metrics: fractional anisotropy (FA), and mean, radial and axial diffusivity (MD, RD, AD). Maturational increases in fixel-metrics were seen in most major white matter tracts, with the most rapid increases in the corticospinal tract and slowest or non-significant increases in the genu of the corpus callosum and uncinate fasciculi. As expected, we observed developmental increases in FA and decreases in MD, RD and AD, though percent changes were smaller relative to fixel-metrics. The majority of tracts showed more substantial morphological than microstructural changes. These findings highlight early childhood as a period of dynamic white matter maturation, characterized by large increases in macroscopic fiber bundle size, mild changes in axonal density, and parallel, albeit less substantial, changes in diffusion tensor metrics.

Sensitive and specific biomarkers of myelin can help define baseline brain health and development, identify and monitor disease pathology, and evaluate response to treatment where myelin content is affected. Diffusion measures such as radial diffusivity (RD) are commonly used to assess myelin content, but are not specific to myelin. Inhomogeneous magnetization transfer (ihMT) and multicomponent driven equilibrium single-pulse observation of T1 and T2 (mcDESPOT) offer quantitative parameters (qihMT and myelin volume fraction/VFm, respectively) which are suggested to have improved sensitivity to myelin. We compared RD, qihMT, and VFm in a cohort of 23 healthy children aged 8-13 years to evaluate the similarities and differences across these measures. All 3 measures were significantly related across brain voxels, but VFm and qihMT were significantly more strongly correlated (qihMT-VFm r = 0.89) than either measure was with RD (RD-qihMT r = -0.66, RD-VFm r = -0.74; all p < 0.001). Mean parameters differed in several regions, especially in subcortical gray matter. These differences can likely be explained by unique sensitivities of each measure to non-myelin factors, such as crossing fiber geometry, axonal packing, fiber orientation, glial density, or magnetization transfer effects in a voxel. We also observed an orientation dependence of qihMT in white matter, such that qihMT decreased as fiber orientation went from parallel to perpendicular to B0. All measures appear to be sensitive to myelin content, though qihMT and VFm appear to be more specific to it than RD. Scan time, noise tolerance, and resolution requirements may inform researchers of the appropriate measure to choose for a specific application.

Age-related thinning of the cortical mantle varies regionally, leading to hemispheric asymmetries in cortical thickness that may emerge at various stages of development and aging. Cortical asymmetry may play a role in modulating the functional maturation (or degradation) of language and cognition in humans, but its evolution over the lifespan is unknown. Here cortical thickness was negatively correlated with age in 274 5-59 year old, right-handed healthy participants. Pre-adolescents showed limited regions of cortical asymmetry focused on medial occipital lobe (R>L) and inferior frontal gyrus (R>L), namely vision and language relevant areas. More extensive frontal (lateral R>L, medial L>R) and parietal lobe (lateral L>R, medial R>L) asymmetries emerged after adolescence, and increased during aging. Changes of cortical asymmetry in these regions may be linked to specialization of the brain with maturity.

White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process.