The purpose of the present study was to detail the childhood developmental course of different white matter (WM) characteristics. In a longitudinal diffusion tensor imaging (DTI) study of 159 healthy children between 4 and 11years scanned twice, we used tract-based spatial statistics as well as delineation of 15 major WM tracts to characterize the regional pattern of change in fractional anisotropy (FA), mean (MD), radial (RD) and axial diffusivity (AD). We tested whether there were decelerations of change with increasing age globally and tract-wise, and also illustrated change along medial-to-lateral, posterior-to-anterior and inferior-to-superior gradients. We found a significant linear increase in global FA, and decrease in MD and RD over time. For mean AD, a weak decrease was observed. The developmental changes in specific WM tracts showed regional differences. Eight WM tracts showed non-linear development patterns for one or several DTI metrics, with a deceleration in change with age. Sex did not affect change in any DTI metric. Overall, greater rate of change was found in the left hemisphere. Spatially, there was a posterior-to-anterior gradient of change with greater change in frontal regions for all metrics. The current study provides a comprehensive characterization of the regional patters of change in WM microstructure across pre-adolescence childhood.

Variations in levels of processing affect memory encoding and subsequent retrieval performance, but it is unknown how processing depth affects communication patterns within the network of interconnected brain regions involved in episodic memory encoding. In 113 healthy adults scanned with functional MRI, we used graph theory to calculate centrality indices representing the brain regions' relative importance in the memory network. We tested how communication patterns in 42 brain regions involved in episodic memory encoding changed as a function of processing depth, and how these changes were related to episodic memory ability. Centrality changes in right middle frontal gyrus, right inferior parietal lobule and left superior frontal gyrus were positively related to semantic elaboration during encoding. In the same regions, centrality during successful episodic memory encoding was related to performance on the episodic memory task, indicating that these centrality changes reflect processes that support memory encoding through deep elaborative processing. Similar analyses were performed for congruent trials, i.e. events that fit into existing knowledge structures, but no relationship between centrality changes and congruity were found. The results demonstrate that while elaboration and congruity have similar beneficial effects on source memory performance, the cortical signatures of these processes are probably not identical.

Differential functional specialization of the left and right hemispheres for linguistic and emotional functions, respectively, suggest that interhemispheric communication via the corpus callosum is critical for emotional awareness. Accordingly, it has been hypothesized that the age-related decline in callosal connectivity mediates the frequently demonstrated reduction in emotional awareness in older age. The present study tests this hypothesis in a sample of 307 healthy individuals between 20-89 years using combined structural and diffusion-tensor magnetic resonance imaging (MRI) of the corpus callosum. As assumed, inter-hemispheric connectivity (midsagittal callosal area and thickness, as well as fractional anisotropy, FA) and emotional awareness (i.e., increase in externally-oriented thinking, EOT; assessed with the Toronto Alexithymia Scale, TAS-20) were found to be reduced in older (> 60 years) compared to younger participants. Furthermore, relating callosal measures to emotional awareness, FA in the genu of the corpus callosum was found to be negatively correlated with EOT in male participants. Thus, "stronger" structural connectivity (higher FA) was related with higher emotional awareness (lower EOT). However, a formal mediation analysis did not support the notion that age-related decline in emotional awareness is mediated by the corpus callosum. Thus, the observed reduction of emotional awareness and callosal connectivity in older age likely reflects parallel but not inter-dependent processes.

The onset of adolescence in humans is marked by hormonal changes that give rise to secondary sexual characteristics, noted as puberty. It has, however, proven challenging to unravel to what extent pubertal changes may have organizing effects on the brain beyond chronological age, as reported in animal studies. The present longitudinal study aimed to characterize the unique effects of age and puberty on subcortical brain volumes and included three waves of data collection at two-year intervals and 680 T1-weighted MRI scans of 271 participants (54% females) aged between 8 and 29 years old. Generalized additive mixed model procedures were used to assess the effects of age, self-report pubertal status and testosterone level on basal ganglia, thalamus, hippocampus, amygdala and cerebellum gray matter volumes. We observed age-related increases in putamen and pallidum volumes, and decreases in accumbens and thalamus volumes, all show larger volumes in boys than girls. Only the cerebellum showed an interaction effect of age by sex, such that males showed prolonged increases in cerebellar volume than females. Next, we showed that changes in self-report puberty status better described developmental change than chronological age for most structures in males, and for caudate, pallidum and hippocampal volumes in females. Furthermore, changes in testosterone level were related to development of pallidum, accumbens, hippocampus and amygdala volumes in males and caudate and hippocampal volumes in females. The modeling approach of the present study allowed us to characterize the complex interactions between chronological age and pubertal maturational changes, and the findings indicate puberty unique changes in brain structure that are sex specific.

We hypothesized that higher levels of omega-3 fatty acids, vitamin D, and physical activity relate to cortical sparing, whereas higher levels of cholesterol, systolic blood pressure, and body mass index (BMI) relate to increased atrophy in the adult lifespan. Longitudinal measures of cortical thickness were derived from magnetic resonance imaging scans acquired (mean interval 3.6 years) from 203 healthy persons aged 23-87 years. At follow-up, measures of BMI, blood pressure, and physical activity were obtained. Blood levels of docosahexaenoic acid, eicosapentaenoic acid, vitamin D, and cholesterol were measured in a subsample (n = 92). Effects were tested in cortical surface-based analyses, with sex, age, follow-up interval, and the interactions between each included as covariates. Higher levels of docosahexaenoic acid, vitamin D, and physical activity related to cortical sparing. Higher cholesterol and BMI related to increased cortical thinning. Effects were independent, did not interact with age, and the cholesterol effect was restricted to males. Eicosapentaenoic acid and blood pressure showed no effects. The observed effects show promise for potential factors to reduce cortical atrophy in normal aging.

Age-related changes in brain structure result from a complex interplay among various neurobiological processes, which may contribute to more complex trajectories than what can be described by simple linear or quadratic models. We used a nonparametric smoothing spline approach to delineate cross-sectionally estimated age trajectories of the volume of 17 neuroanatomic structures in 1100 healthy adults (18-94 years). Accelerated estimated decline in advanced age characterized some structures, for example hippocampus, but was not the norm. For most areas, 1 or 2 critical ages were identified, characterized by changes in the estimated rate of change. One-year follow-up data from 142 healthy older adults (60-91 years) confirmed the existence of estimated change from the cross-sectional analyses for all areas except 1 (caudate). The cross-sectional and the longitudinal analyses agreed well on the rank order of age effects on specific brain structures (Spearman ρ = 0.91). The main conclusions are that most brain structures do not follow a simple path throughout adult life and that accelerated decline in high age is not the norm of healthy brain aging.

It is suggested that reductions in a medial temporo-parietal episodic memory network characterize Alzheimer's disease (AD), while changes in a fronto-striatal executive network characterize healthy aging. In the present study, magnetic resonance imaging (MRI) was used to test this directly. MRI scans of 372 participants from two samples were analyzed: Sample 1 consisted of 96 very mild to moderate AD patients, 93 healthy elderly (HE), and 137 young (HY), all with available MR scans, while Sample 2 consisted of 46 MCI patients, with available MR scans and measures of CSF biomarkers Abeta42 and tau protein. Substantial morphometric reductions of the medial temporo-parietal network were found in AD, while the fronto-striatal network was less affected. Both networks were affected by healthy aging, but the fronto-striatal to a greater degree than the medial temporo-parietal. Further exploratory analyses of 49 cortical and subcortical structures indicated no overlap between predictors of AD vs. HE and predictors of HE vs. HY. CSF biomarker pathology correlated with the medial temporo-parietal but not fronto-striatal network. Likewise, the AD-prone structures from the exploratory analyses were related to CSF biomarkers, while the aging-prone structures were not. It is concluded that the pattern of macrostructural brain changes in very mild to moderate AD can be clearly delineated from that of healthy aging.

MRI-based estimates of cerebral morphometric properties, e.g. cortical thickness, are pivotal to studies of normal and pathological brain changes. These measures are based on automated or manual segmentation procedures, which utilize the tissue contrast between gray and white matter on T(1)-weighted MR images. Tissue contrast is unlikely to remain a constant property across groups of different age and health. An important question is therefore how the sensitivity of cortical thickness estimates is influenced by variability in WM/GM contrast. The effect of adjusting for variability in WM/GM contrast on age sensitivity of cortical thickness was tested in 1189 healthy subjects from six different samples, enabling evaluation of consistency of effects within and between sites and scanners. Further, the influence of Alzheimer's disease (AD) diagnosis on cortical thickness with and without correction for contrast was tested in an additional sample of 96 patients. In healthy controls, regional increases in the sensitivity of the cortical thickness measure to age were found after correcting for contrast. Across samples, the strongest effects were observed in frontal, lateral temporal and parietal areas. Controlling for contrast variability also increased the cortical thickness estimates' sensitivity to AD, thus replicating the finding in an independent clinical sample. The results showed increased sensitivity of cortical estimates to AD in areas earlier reported to be compromised in AD, including medial temporal, inferior and superior parietal regions. In sum, the findings indicate that adjusting for contrast can increase the sensitivity of MR morphometry to variables of interest.

The developmental patterns of subcortical brain volumes in males and females observed in previous studies have been inconsistent. To help resolve these discrepancies, we examined developmental trajectories using three independent longitudinal samples of participants in the age-span of 8-22 years (total 216 participants and 467 scans). These datasets, including Pittsburgh (PIT; University of Pittsburgh, USA), NeuroCognitive Development (NCD; University of Oslo, Norway), and Orygen Adolescent Development Study (OADS; The University of Melbourne, Australia), span three countries and were analyzed together and in parallel using mixed-effects modeling with both generalized additive models and general linear models. For all regions and across all samples, males were found to have significantly larger volumes as compared to females, and significant sex differences were seen in age trajectories over time. However, direct comparison of sample trajectories and sex differences identified within samples were not consistent. The trajectories for the amygdala, putamen, and nucleus accumbens were most consistent between the three samples. Our results suggest that even after using similar preprocessing and analytic techniques, additional factors, such as image acquisition or sample composition may contribute to some of the discrepancies in sex specific patterns in subcortical brain changes across adolescence, and highlight region-specific variations in congruency of developmental trajectories.

Continued advances in neuroimaging technologies and statistical modelling capabilities have improved our knowledge of structural brain development in children and adolescents. While this has provided an increasingly nuanced understanding of brain development, the field is still plagued by inconsistent findings. This review highlights the methodological diversity in existing longitudinal magnetic resonance imaging (MRI) studies on structural brain development during childhood and adolescence, and addresses how such variation might contribute to inconsistencies in the literature. We discuss the impact of method choices at multiple decision points across the research process, from study design and sample selection, to image processing and statistical analysis. We also highlight the extent to which different methodological considerations have been empirically examined, drawing attention to specific areas that would benefit from future investigation. Where appropriate, we recommend certain best practices that would be beneficial for the field to adopt, including greater completeness and transparency in reporting methods, in order to ultimately develop an accurate and detailed understanding of normative child and adolescent brain development.

Cerebral myeloarchitecture shows substantial development across childhood and adolescence, and aberrations in these trajectories are relevant for a range of mental disorders. Differential myelination between intracortical and subjacent white matter can be approximated using signal intensities in T1-weighted magnetic resonance imaging.

It is well documented that some brain regions, such as association cortices, caudate, and hippocampus, are particularly prone to age-related atrophy, but it has been hypothesized that there are individual differences in atrophy profiles. Here, we document heterogeneity in regional-atrophy patterns using latent-profile analysis of 1,482 longitudinal magnetic resonance imaging observations. The results supported a 2-group solution reflecting differences in atrophy rates in cortical regions and hippocampus along with comparable caudate atrophy. The higher-atrophy group had the most marked atrophy in hippocampus and also lower episodic memory, and their normal caudate atrophy rate was accompanied by larger baseline volumes. Our findings support and refine models of heterogeneity in brain aging and suggest distinct mechanisms of atrophy in striatal versus hippocampal-cortical systems.

It has been suggested that specific forms of cognition in older age rely largely on late-life specific mechanisms. Here instead, we tested using task-fMRI (n = 540, age 6-82 years) whether the functional foundations of successful episodic memory encoding adhere to a principle of lifespan continuity, shaped by developmental, structural, and evolutionary influences. We clustered regions of the cerebral cortex according to the shape of the lifespan trajectory of memory activity in each region so that regions showing the same pattern were clustered together. The results revealed that lifespan trajectories of memory encoding function showed a continuity through life but no evidence of age-specific mechanisms such as compensatory patterns. Encoding activity was related to general cognitive abilities and variations of grey matter as captured by a multi-modal independent component analysis, variables reflecting core aspects of cognitive and structural change throughout the lifespan. Furthermore, memory encoding activity aligned to fundamental aspects of brain organization, such as large-scale connectivity and evolutionary cortical expansion gradients. Altogether, we provide novel support for a perspective on memory aging in which maintenance and decay of episodic memory in older age needs to be understood from a comprehensive life-long perspective rather than as a late-life phenomenon only.

Memory performance results from plasticity, the ability to change with experience. We show that benefit from practice over a few trials, learning slope, is predictive of long-term recall and hippocampal volume across a broad age range and a long period of time, relates to memory training benefit, and is heritable. First, in a healthy lifespan sample (n = 1825, age 4-93 years), comprising 3483 occasions of combined magnetic resonance imaging (MRI) scans and memory tests over a period of up to 11 years, learning slope across 5 trials was uniquely related to performance on a delayed free recall test, as well as hippocampal volume, independent from first trial memory or total memory performance across the five learning trials. Second, learning slope was predictive of benefit from memory training across ten weeks in an experimental subsample of adults (n = 155). Finally, in an independent sample of male twins (n = 1240, age 51-50 years), learning slope showed significant heritability. Within-session learning slope may be a useful marker beyond performance per se, being heritable and having unique predictive value for long-term memory function, hippocampal volume and training benefit across the human lifespan.

Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers-the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.

Many workflows and tools that aim to increase the reproducibility and replicability of research findings have been suggested. In this review, we discuss the opportunities that these efforts offer for the field of developmental cognitive neuroscience, in particular developmental neuroimaging. We focus on issues broadly related to statistical power and to flexibility and transparency in data analyses. Critical considerations relating to statistical power include challenges in recruitment and testing of young populations, how to increase the value of studies with small samples, and the opportunities and challenges related to working with large-scale datasets. Developmental studies involve challenges such as choices about age groupings, lifespan modelling, analyses of longitudinal changes, and data that can be processed and analyzed in a multitude of ways. Flexibility in data acquisition, analyses and description may thereby greatly impact results. We discuss methods for improving transparency in developmental neuroimaging, and how preregistration can improve methodological rigor. While outlining challenges and issues that may arise before, during, and after data collection, solutions and resources are highlighted aiding to overcome some of these. Since the number of useful tools and techniques is ever-growing, we highlight the fact that many practices can be implemented stepwise.

Human brain development involves spatially and temporally heterogeneous changes, detectable across a wide range of magnetic resonance imaging (MRI) measures. Investigating the interplay between multimodal MRI and polygenic scores (PGS) for personality traits associated with mental disorders in youth may provide new knowledge about typical and atypical neurodevelopment. We derived independent components across cortical thickness, cortical surface area, and grey/white matter contrast (GWC) (n = 2596, 3-23 years), and tested for associations between these components and age, sex and-, in a subsample (n = 878), PGS for neuroticism. Age was negatively associated with a single-modality component reflecting higher global GWC, and additionally with components capturing common variance between global thickness and GWC, and several multimodal regional patterns. Sex differences were found for components primarily capturing global and regional surface area (boys > girls), but also regional cortical thickness. For PGS for neuroticism, we found weak and bidirectional associations with a component reflecting right prefrontal surface area. These results indicate that multimodal fusion is sensitive to age and sex differences in brain structure in youth, but only weakly to polygenic load for neuroticism.

Cortical asymmetry is a ubiquitous feature of brain organization that is subtly altered in some neurodevelopmental disorders, yet we lack knowledge of how its development proceeds across life in health. Achieving consensus on the precise cortical asymmetries in humans is necessary to uncover the developmental timing of asymmetry and the extent to which it arises through genetic and later influences in childhood. Here, we delineate population-level asymmetry in cortical thickness and surface area vertex-wise in seven datasets and chart asymmetry trajectories longitudinally across life (4-89 years; observations = 3937; 70% longitudinal). We find replicable asymmetry interrelationships, heritability maps, and test asymmetry associations in large-scale data. Cortical asymmetry was robust across datasets. Whereas areal asymmetry is predominantly stable across life, thickness asymmetry grows in childhood and peaks in early adulthood. Areal asymmetry is low-moderately heritable (max h2SNP ~19%) and correlates phenotypically and genetically in specific regions, indicating coordinated development of asymmetries partly through genes. In contrast, thickness asymmetry is globally interrelated across the cortex in a pattern suggesting highly left-lateralized individuals tend towards left-lateralization also in population-level right-asymmetric regions (and vice versa), and exhibits low or absent heritability. We find less areal asymmetry in the most consistently lateralized region in humans associates with subtly lower cognitive ability, and confirm small handedness and sex effects. Results suggest areal asymmetry is developmentally stable and arises early in life through genetic but mainly subject-specific stochastic effects, whereas childhood developmental growth shapes thickness asymmetry and may lead to directional variability of global thickness lateralization in the population.

Establishing an efficient functional and structural connectivity between the two cerebral hemispheres is an important developmental task during childhood, and alterations in this development have accordingly been linked to a series of neurodevelopmental and pediatric disorders. The corpus callosum, the major white-matter structure connecting the hemispheres, has been shown to increase in size throughout the three first decades of life. However, behavioral studies indicate that adult-like performance levels of functional hemispheric interaction are already reached during middle and late childhood. Thus, here we specifically examine the structural development of the corpus callosum during the functionally relevant time period by for the first time (a) selectively addressing prospective childhood development and (b) analyzing a sample in which also younger children are well represented. Corpus callosum anatomy was assessed from 732 T1-weighted MRI datasets acquired from 428 children (213 boys, 215 girls) aged of 4.1 and 10.9years, of which 304 were scanned at two time points. Regional callosal thickness was determined from an outline-based segmentation of the mid-sagittal cross-sectional surface area. Linear-mixed model analyses revealed a significant increase in thickness with age (effect size: up to 15% explained variance) equivalent to a growth in callosal thickness of up to 0.19mm per year in the posterior corpus callosum. The age effect was found to be stronger in posterior segments (i.e., splenium) than in other callosal subregions. Also, the age effect was found to be comparable between boys and girls, and was detected irrespective of whether developmental or individual differences in overall brain size where accounted for or not. Our results demonstrate a selective increase in posterior corpus-callosum thickness during middle and late childhood. Since axons crossing the midline in the splenium mainly connect occipital and parietal cortices, the accentuated posterior growth might reflect the onset of a posterior-to-anterior moving maturation wave in cortical development known to take place in the same time period.

A causal link between decreases in white matter (WM) integrity and cortical degeneration is assumed, but there is scarce knowledge on the relationship between these changes across the adult human lifespan. We investigated changes in thickness throughout the cortical mantle and WM tract integrity derived from T1 and diffusion weighted magnetic resonance imaging (MRI) scans in 201 healthy adults aged 23-87 years over a mean interval of 3.6 years. Fractional anisotropy (FA), mean (MD), radial (RD) and axial (AD) diffusivity changes were calculated for forceps minor and major and eight major white matter tracts in each hemisphere by use of a novel automated longitudinal tractography constrained by underlying anatomy (TRACULA) approach. We hypothesized that increasing MD and decreasing FA across tracts would relate to cortical thinning, with some anatomical specificity. WM integrity decreased across tracts non-uniformly, with mean annual percentage decreases ranging from 0.20 in the Inferior Longitudinal Fasciculus to 0.65 in the Superior Longitudinal Fasciculus. For most tracts, greater MD increases and FA decreases related to more cortical thinning, in areas in part overlapping with but also outside the projected tract endings. The findings indicate a combination of global and tract-specific relationships between WM integrity and cortical thinning.