Joshua M. Kuperman

Family income, parental education and brain structure in children and adolescents

Socioeconomic disparities are associated with differences in cognitive development. The extent to which this translates to disparities in brain structure is unclear. We investigated relationships between socioeconomic factors and brain morphometry, independently of genetic ancestry, among a cohort of 1,099 typically developing individuals between 3 and 20 years of age. Income was logarithmically associated with brain surface area. Among children from lower income families, small differences in income were associated with relatively large differences in surface area, whereas, among children from higher income families, similar income increments were associated with smaller differences in surface area. These relationships were most prominent in regions supporting language, reading, executive functions and spatial skills; surface area mediated socioeconomic differences in certain neurocognitive abilities. These data imply that income relates most strongly to brain structure among the most disadvantaged children.

Neuroanatomical assessment of biological maturity

Structural MRI allows unparalleled in vivo study of the anatomy of the developing human brain. For more than two decades, MRI research has revealed many new aspects of this multifaceted maturation process, significantly augmenting scientific knowledge gathered from postmortem studies. Postnatal brain development is notably protracted and involves considerable changes in cerebral cortical, subcortical, and cerebellar structures, as well as significant architectural changes in white matter fiber tracts (see [12]). Although much work has described isolated features of neuroanatomical development, it remains a critical challenge to characterize the multidimensional nature of brain anatomy, capturing different phases of development among individuals. Capitalizing on key advances in multisite, multimodal MRI, and using cross-validated nonlinear modeling, we demonstrate that developmental brain phase can be assessed with much greater precision than has been possible using other biological measures, accounting for more than 92% of the variance in age. Further, our composite metric of morphology, diffusivity, and signal intensity shows that the average difference in phase among children of the same age is only about 1 year, revealing for the first time a latent phenotype in the human brain for which maturation timing is tightly controlled.

Multimodal imaging of the self-regulating developing brain

Self-regulation refers to the ability to control behavior, cognition, and emotions, and self-regulation failure is related to a range of neuropsychiatric problems. It is poorly understood how structural maturation of the brain brings about the gradual improvement in self-regulation during childhood. In a large-scale multicenter effort, 735 children (4–21 y) underwent structural MRI for quantification of cortical thickness and surface area and diffusion tensor imaging for quantification of the quality of major fiber connections. Brain development was related to a standardized measure of cognitive control (the flanker task from the National Institutes of Health Toolbox), a critical component of self-regulation. Ability to inhibit responses and impose cognitive control increased rapidly during preteen years. Surface area of the anterior cingulate cortex accounted for a significant proportion of the variance in cognitive performance. This finding is intriguing, because characteristics of the anterior cingulum are shown to be related to impulse, attention, and executive problems in neurodevelopmental disorders, indicating a neural foundation for self-regulation abilities along a continuum from normality to pathology. The relationship was strongest in the younger children. Properties of large-fiber connections added to the picture by explaining additional variance in cognitive control. Although cognitive control was related to surface area of the anterior cingulate independently of basic processes of mental speed, the relationship between white matter quality and cognitive control could be fully accounted for by speed. The results underscore the need for integration of different aspects of brain maturation to understand the foundations of cognitive development.

Automated white-matter tractography using a probabilistic diffusion tensor atlas: Application to temporal lobe epilepsy

Diffusion‐weighted magnetic resonance imaging allows researchers and clinicians to identify individual white matter fiber tracts and map their trajectories. The reliability and interpretability of fiber‐tracking procedures is improved when a priori anatomical information is used as a guide. We have developed an automated method for labeling white matter fiber tracts in individual subjects based on a probabilistic atlas of fiber tract locations and orientations. The probabilistic fiber atlas contains 23 fiber tracts and was constructed by manually identifying fiber tracts in 21 healthy controls and 21 patients with temporal lobe epilepsy (TLE). The manual tract identification method required ∼40 h of manual editing by a trained image analyst using multiple regions of interest to select or exclude streamline fibers. Identification of fiber tracts with the atlas does not require human intervention, but nonetheless benefits from the a priori anatomical information that was used to manually identify the tracts included in the atlas. We applied this method to compare fractional anisotropy—thought to be a measure of white matter integrity—in individual fiber tracts between control subjects and patients with TLE. We found that the atlas‐based and manual fiber selection methods produced a similar pattern of results. However, the between‐group effect sizes using the atlas‐derived fibers were generally as large or larger than those obtained with manually selected fiber tracks. Hum Brain Mapp, 2009.

Long-term influence of normal variation in neonatal characteristics on human brain development

It is now recognized that a number of cognitive, behavioral, and mental health outcomes across the lifespan can be traced to fetal development. Although the direct mediation is unknown, the substantial variance in fetal growth, most commonly indexed by birth weight, may affect lifespan brain development. We investigated effects of normal variance in birth weight on MRI-derived measures of brain development in 628 healthy children, adolescents, and young adults in the large-scale multicenter Pediatric Imaging, Neurocognition, and Genetics study. This heterogeneous sample was recruited through geographically dispersed sites in the United States. The influence of birth weight on cortical thickness, surface area, and striatal and total brain volumes was investigated, controlling for variance in age, sex, household income, and genetic ancestry factors. Birth weight was found to exert robust positive effects on regional cortical surface area in multiple regions as well as total brain and caudate volumes. These effects were continuous across birth weight ranges and ages and were not confined to subsets of the sample. The findings show that (i) aspects of later child and adolescent brain development are influenced at birth and (ii) relatively small differences in birth weight across groups and conditions typically compared in neuropsychiatric research (e.g., Attention Deficit Hyperactivity Disorder, schizophrenia, and personality disorders) may influence group differences observed in brain parameters of interest at a later stage in life. These findings should serve to increase our attention to early influences.

Prospective motion correction of high-resolution magnetic resonance imaging data in children

Motion artifacts pose significant problems for the acquisition and analysis of high-resolution magnetic resonance imaging data. These artifacts can be particularly severe when studying pediatric populations, where greater patient movement reduces the ability to clearly view and reliably measure anatomy. In this study, we tested the effectiveness of a new prospective motion correction technique, called PROMO, as applied to making neuroanatomical measures in typically developing school-age children. This method attempts to address the problem of motion at its source by keeping the measurement coordinate system fixed with respect to the subject throughout image acquisition. The technique also performs automatic rescanning of images that were acquired during intervals of particularly severe motion. Unlike many previous techniques, this approach adjusts for both in-plane and through-plane movement, greatly reducing image artifacts without the need for additional equipment. Results show that the use of PROMO notably enhances subjective image quality, reduces errors in Freesurfer cortical surface reconstructions, and significantly improves the subcortical volumetric segmentation of brain structures. Further applications of PROMO for clinical and cognitive neuroscience are discussed.

Contrasting gray and white matter changes in preclinical Huntington disease An MRI study

Background: In Huntington disease (HD), substantial striatal atrophy precedes clinical motor symptoms. Accordingly, neuroprotection should prevent major cell loss before such symptoms arise. To evaluate neuroprotection, biomarkers such as MRI measures are needed. This requires first establishing the best imaging approach. Methods: Using a cross-sectional design, we acquired T1-weighted and diffusion-weighted scans in 39 preclinical (pre-HD) individuals and 25 age-matched controls. T1-weighted scans were analyzed with gross whole-brain segmentation and voxel-based morphometry. Analysis of diffusion-weighted scans used skeleton-based tractography. For all imaging measures, we compared pre-HD and control groups and within the pre-HD group we examined correlations with estimated years to clinical onset. Results: Pre-HD individuals had lower gross gray matter (GM) and white matter (WM) volume. Voxel-wise analysis demonstrated local GM volume loss, most notably in regions consistent with basal ganglia–thalamocortical pathways. By contrast, pre-HD individuals showed widespread reductions in WM integrity, probably due to a loss of axonal barriers. Both GM and WM imaging measures correlated with estimated years to onset. Conclusions: Using automated, observer-independent methods, we found that GM loss in pre-HD was regionally specific, while WM deterioration was much more general and probably the result of demyelination rather then axonal degeneration. These findings provide important information about the nature, relative staging, and topographic specificity of brain changes in pre-HD and suggest that combining GM and WM imaging may be the best biomarker approach. The empirically derived group difference images from this study are provided as regions-of-interest masks for improved sensitivity in future longitudinal studies.

White Matter Tracts Associated with Set-Shifting in Healthy Aging

Attentional set-shifting ability, commonly assessed with the Trail Making Test (TMT), decreases with increasing age in adults. Since set-shifting performance relies on activity in widespread brain regions, deterioration of the white matter tracts that connect these regions may underlie the age-related decrease in performance. We used an automated fiber tracking method to investigate the relationship between white matter integrity in several cortical association tracts and TMT performance in a sample of 24 healthy adults, 21-80 years. Diffusion tensor images were used to compute average fractional anisotropy (FA) for five cortical association tracts, the corpus callosum (CC), and the corticospinal tract (CST), which served as a control. Results showed that advancing age was associated with declines in set-shifting performance and with decreased FA in the CC and in association tracts that connect frontal cortex to more posterior brain regions, including the inferior fronto-occipital fasciculus (IFOF), uncinate fasciculus (UF), and superior longitudinal fasciculus (SLF). Declines in average FA in these tracts, and in average FA of the right inferior longitudinal fasciculus (ILF), were associated with increased time to completion on the set-shifting subtask of the TMT but not with the simple sequencing subtask. FA values in these tracts were strong mediators of the effect of age on set-shifting performance. Automated tractography methods can enhance our understanding of the fiber systems involved in performance of specific cognitive tasks and of the functional consequences of age-related changes in those systems.

The Pediatric Imaging, Neurocognition, and Genetics (PING) Data Repository

The main objective of the multi-site Pediatric Imaging, Neurocognition, and Genetics (PING) study was to create a large repository of standardized measurements of behavioral and imaging phenotypes accompanied by whole genome genotyping acquired from typically-developing children varying widely in age (3 to 20 years). This cross-sectional study produced sharable data from 1493 children, and these data have been described in several publications focusing on brain and cognitive development. Researchers may gain access to these data by applying for an account on the PING portal and filing a data use agreement. Here we describe the recruiting and screening of the children and give a brief overview of the assessments performed, the imaging methods applied, the genetic data produced, and the numbers of cases for whom different data types are available. We also cite sources of more detailed information about the methods and data. Finally we describe the procedures for accessing the data and for using the PING data exploration portal.

Structural Growth Trajectories and Rates of Change in the First 3 Months of Infant Brain Development

IMPORTANCE The very early postnatal period witnesses extraordinary rates of growth, but structural brain development in this period has largely not been explored longitudinally. Such assessment may be key in detecting and treating the earliest signs of neurodevelopmental disorders. OBJECTIVE To assess structural growth trajectories and rates of change in the whole brain and regions of interest in infants during the first 3 months after birth. DESIGN, SETTING, AND PARTICIPANTS Serial structural T1-weighted and/or T2-weighted magnetic resonance images were obtained for 211 time points from 87 healthy term-born or term-equivalent preterm-born infants, aged 2 to 90 days, between October 5, 2007, and June 12, 2013. MAIN OUTCOMES AND MEASURES We segmented whole-brain and multiple subcortical regions of interest using a novel application of Bayesian-based methods. We modeled growth and rate of growth trajectories nonparametrically and assessed left-right asymmetries and sexual dimorphisms. RESULTS Whole-brain volume at birth was approximately one-third of healthy elderly brain volume, and did not differ significantly between male and female infants (347 388 mm3 and 335 509 mm3, respectively, P = .12). The growth rate was approximately 1%/d, slowing to 0.4%/d by the end of the first 3 months, when the brain reached just more than half of elderly adult brain volume. Overall growth in the first 90 days was 64%. There was a significant age-by-sex effect leading to widening separation in brain sizes with age between male and female infants (with male infants growing faster than females by 200.4 mm3/d, SE = 67.2, P = .003). Longer gestation was associated with larger brain size (2215 mm3/d, SE = 284, P = 4×10-13). The expected brain size of an infant born one week earlier than average was 5% smaller than average; at 90 days it will not have caught up, being 2% smaller than average. The cerebellum grew at the highest rate, more than doubling in 90 days, and the hippocampus grew at the slowest rate, increasing by 47% in 90 days. There was left-right asymmetry in multiple regions of interest, particularly the lateral ventricles where the left was larger than the right by 462 mm3 on average (approximately 5% of lateral ventricular volume at 2 months). We calculated volume-by-age percentile plots for assessing individual development. CONCLUSIONS AND RELEVANCE Normative trajectories for early postnatal brain structural development can be determined from magnetic resonance imaging and could be used to improve the detection of deviant maturational patterns indicative of neurodevelopmental disorders.