The NIH MRI study of normal brain development (Objective-2): newborns, infants, toddlers, and preschoolers

Primatologist: A modular segmentation pipeline for macaque brain morphometry

Because they bridge the genetic gap between rodents and humans, non-human primates (NHPs) play a major role in therapy development and evaluation for neurological disorders. However, translational research success from NHPs to patients requires an accurate phenotyping of the models. In patients, magnetic resonance imaging (MRI) combined with automated segmentation methods has offered the unique opportunity to assess in vivo brain morphological changes. Meanwhile, specific challenges caused by brain size and high field contrasts make existing algorithms hard to use routinely in NHPs. To tackle this issue, we propose a complete pipeline, Primatologist, for multi-region segmentation. Tissue segmentation is based on a modular statistical model that includes random field regularization, bias correction and denoising and is optimized by expectation-maximization. To deal with the broad variety of structures with different relaxing times at 7 T, images are segmented into 17 anatomical classes, including subcortical regions. Pre-processing steps insure a good initialization of the parameters and thus the robustness of the pipeline. It is validated on 10 T2-weighted MRIs of healthy macaque brains. Classification scores are compared with those of a non-linear atlas registration, and the impact of each module on classification scores is thoroughly evaluated.

Macroanatomical Landmarks Featuring Junctions of Major Sulci and Fissures and Scalp Landmarks Based on the International 10-10 System for Analyzing Lateral Cortical Development of Infants

The topographic relationships between the macroanatomical structure of the lateral cortex, including sulci and fissures, and anatomical landmarks on the external surface of the head are known to be consistent. This allows the coregistration of EEG electrodes or functional near-infrared spectroscopy over the scalp with underlying cortical regions. However, limited information is available as to whether the topographic relationships are maintained in rapidly developing infants, whose brains and heads exhibit drastic growth. We used MRIs of infants ranging in age from 3 to 22 months old, and identified 20 macroanatomical landmarks, featuring the junctions of major sulci and fissures, as well as cranial landmarks and virtually determined positions of the international 10-20 and 10-10 systems. A Procrustes analysis revealed developmental trends in changes of shape in both the cortex and head. An analysis of Euclidian distances between selected pairs of cortical landmarks at standard stereotactic coordinates showed anterior shifts of the relative positions of the premotor and parietal cortices with age. Finally, cortical landmark positions and their spatial variability were compared with 10-10 landmark positions. The results indicate that variability in the distribution of each macroanatomical landmark was much smaller than the pitch of the 10-10 landmarks. This study demonstrates that the scalp-based 10-10 system serves as a good frame of reference in infants not only for assessing the development of the macroanatomy of the lateral cortical structure, but also for functional studies of cortical development using transcranial modalities such as EEG and fNIRS.

Using clinically acquired MRI to construct age-specific ADC atlases: Quantifying spatiotemporal ADC changes from birth to 6-year old

Diffusion imaging is critical for detecting acute brain injury. However, normal apparent diffusion coefficient (ADC) maps change rapidly in early childhood, making abnormality detection difficult. In this article, we explored clinical PACS and electronic healthcare records (EHR) to create age-specific ADC atlases for clinical radiology reference. Using the EHR and three rounds of multiexpert reviews, we found ADC maps from 201 children 0-6 years of age scanned between 2006 and 2013 who had brain MRIs with no reported abnormalities and normal clinical evaluations 2+ years later. These images were grouped in 10 age bins, densely sampling the first 1 year of life (5 bins, including neonates and 4 quarters) and representing the 1-6 year age range (an age bin per year). Unbiased group-wise registration was used to construct ADC atlases for 10 age bins. We used the atlases to quantify (a) cross-sectional normative ADC variations; (b) spatiotemporal heterogeneous ADC changes; and (c) spatiotemporal heterogeneous volumetric changes. The quantified age-specific whole-brain and region-wise ADC values were compared to those from age-matched individual subjects in our study and in multiple existing independent studies. The significance of this study is that we have shown that clinically acquired images can be used to construct normative age-specific atlases. These first of their kind age-specific normative ADC atlases quantitatively characterize changes of myelination-related water diffusion in the first 6 years of life. The quantified voxel-wise spatiotemporal ADC variations provide standard references to assist radiologists toward more objective interpretation of abnormalities in clinical images. Our atlases are available at https://www.nitrc.org/projects/mgh_adcatlases. Hum Brain Mapp 38:3052-3068, 2017. © 2017 Wiley Periodicals, Inc.

Scalable Joint Segmentation and Registration Framework for Infant Brain Images

The first year of life is the most dynamic and perhaps the most critical phase of postnatal brain development. The ability to accurately measure structure changes is critical in early brain development study, which highly relies on the performances of image segmentation and registration techniques. However, either infant image segmentation or registration, if deployed independently, encounters much more challenges than segmentation/registration of adult brains due to dynamic appearance change with rapid brain development. In fact, image segmentation and registration of infant images can assists each other to overcome the above challenges by using the growth trajectories (i.e., temporal correspondences) learned from a large set of training subjects with complete longitudinal data. Specifically, a one-year-old image with ground-truth tissue segmentation can be first set as the reference domain. Then, to register the infant image of a new subject at earlier age, we can estimate its tissue probability maps, i.e., with sparse patch-based multi-atlas label fusion technique, where only the training images at the respective age are considered as atlases since they have similar image appearance. Next, these probability maps can be fused as a good initialization to guide the level set segmentation. Thus, image registration between the new infant image and the reference image is free of difficulty of appearance changes, by establishing correspondences upon the reasonably segmented images. Importantly, the segmentation of new infant image can be further enhanced by propagating the much more reliable label fusion heuristics at the reference domain to the corresponding location of the new infant image via the learned growth trajectories, which brings image segmentation and registration to assist each other. It is worth noting that our joint segmentation and registration framework is also flexible to handle the registration of any two infant images even with significant age gap in the first year of life, by linking their joint segmentation and registration through the reference domain. Thus, our proposed joint segmentation and registration method is scalable to various registration tasks in early brain development studies. Promising segmentation and registration results have been achieved for infant brain MR images aged from 2-week-old to 1-year-old, indicating the applicability of our method in early brain development study.

Workshops of the Sixth International Brain-Computer Interface Meeting: brain-computer interfaces past, present, and future

The Sixth International Brain-Computer Interface (BCI) Meeting was held 30 May-3 June 2016 at the Asilomar Conference Grounds, Pacific Grove, California, USA. The conference included 28 workshops covering topics in BCI and brain-machine interface research. Topics included BCI for specific populations or applications, advancing BCI research through use of specific signals or technological advances, and translational and commercial issues to bring both implanted and non-invasive BCIs to market. BCI research is growing and expanding in the breadth of its applications, the depth of knowledge it can produce, and the practical benefit it can provide both for those with physical impairments and the general public. Here we provide summaries of each workshop, illustrating the breadth and depth of BCI research and highlighting important issues and calls for action to support future research and development.

Early-Life Nutrition and Neurodevelopment: Use of the Piglet as a Translational Model

Optimal nutrition early in life is critical to ensure proper structural and functional development of infant organ systems. Although pediatric nutrition historically has emphasized research on the relation between nutrition, growth rates, and gastrointestinal maturation, efforts increasingly have focused on how nutrition influences neurodevelopment. The provision of human milk is considered the gold standard in pediatric nutrition; thus, there is interest in understanding how functional nutrients and bioactive components in milk may modulate developmental processes. The piglet has emerged as an important translational model for studying neurodevelopmental outcomes influenced by pediatric nutrition. Given the comparable nutritional requirements and strikingly similar brain developmental patterns between young pigs and humans, the piglet is being used increasingly in developmental nutritional neuroscience studies. The piglet primarily has been used to assess the effects of dietary fatty acids and their accretion in the brain throughout neurodevelopment. However, recent research indicates that other dietary components, including choline, iron, cholesterol, gangliosides, and sialic acid, among other compounds, also affect neurodevelopment in the pig model. Moreover, novel analytical techniques, including but not limited to MRI, behavioral assessments, and molecular quantification, allow for a more holistic understanding of how nutrition affects neurodevelopmental patterns. By combining early-life nutritional interventions with innovative analytical approaches, opportunities abound to quantify factors affecting neurodevelopmental trajectories in the neonate. This review discusses research using the translational pig model with primary emphasis on early-life nutrition interventions assessing neurodevelopment outcomes, while also discussing nutritionally-sensitive methods to characterize brain maturation.

STGP: Spatio-temporal Gaussian process models for longitudinal neuroimaging data

Longitudinal neuroimaging data plays an important role in mapping the neural developmental profile of major neuropsychiatric and neurodegenerative disorders and normal brain. The development of such developmental maps is critical for the prevention, diagnosis, and treatment of many brain-related diseases. The aim of this paper is to develop a spatio-temporal Gaussian process (STGP) framework to accurately delineate the developmental trajectories of brain structure and function, while achieving better prediction by explicitly incorporating the spatial and temporal features of longitudinal neuroimaging data. Our STGP integrates a functional principal component model (FPCA) and a partition parametric space-time covariance model to capture the medium-to-large and small-to-medium spatio-temporal dependence structures, respectively. We develop a three-stage efficient estimation procedure as well as a predictive method based on a kriging technique. Two key novelties of STGP are that it can efficiently use a small number of parameters to capture complex non-stationary and non-separable spatio-temporal dependence structures and that it can accurately predict spatio-temporal changes. We illustrate STGP using simulated data sets and two real data analyses including longitudinal positron emission tomography data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and longitudinal lateral ventricle surface data from a longitudinal study of early brain development.

Handedness in Children With Autism Spectrum Disorder

The left hemisphere is usually predominant in manual skills and language, suggesting a link between hand dominance and language. Studies of autism spectrum disorder show atypical handedness; however, few have examined language-handedness associations. Handedness, assessed by task performance, and standardized receptive and expressive language tests were completed in 110 autism spectrum disorder children (96 boys; M age = 8.3 years, SD = 3.8) and 45 typically developing children (37 boys; M age = 8.6 years, SD = 4.3), 3 to 17 years of age. The autism spectrum disorder group had a lower handedness score (was less strongly lateralized) than the control group. In the autism spectrum disorder group, there was a small effect of handedness on language; right-handers had better language than non-right-handers. Results suggest poorer language prognosis may be associated with left- or mixed-handedness in autism spectrum disorder.

Fat Imaging via Magnetic Resonance Imaging (MRI) in Young Children (Ages 1-4 Years) without Sedation

Introduction

This pilot study developed techniques to perform Magnetic Resonance Imaging (MRI) of specific fat deposition in 18 children (age 18 months to 4 years).

Methods

The children engaged in a series of practice tests to become acclimated to the scanner noises, reduce claustrophobia, and rehearse holding still for a set time. The practice tests assessed if the child could remain still for two minutes while watching a video, first while lying on a blanket, second, on the blanket with headphones, and third, in the mock scanner. The children who passed the three practice tests were then scanned with a 3T Siemens Skyra magnet. Abdominal fat distribution (region of interest (ROI) from the top of the ileac crest to the bottom of the ribcage) volume was measured using 2-point DIXON technique. This region was chosen to give an indication of the body composition around the liver.

Results

Twelve out of eighteen participants successfully completed the actual MRI scan. Chi-squared test showed no significant difference between male and female pass-fail rates. The median age of completed scans was 36 months, whereas the median age for children unable to complete a scan was 28 months. The average total trunk fat was 240.9±85.2mL and the average total VAT was 37.7±25.9mLand liver fat was not quantifiable due to physiological motion. Several strategies (modeling, videos, and incentives) were identified to improve pediatric imaging in different age ranges.

Conclusion

Using an age-specific and tailored protocol, we were able to successfully use MRI for fat imaging in a majority of young children. Development of such protocols enables researchers to better understand the etiology of fat deposition in young children, which can be used to aid in the prevention and treatment of adiposity.

Imaging the "At-Risk" Brain: Future Directions

OBJECTIVES

Clinical neuroscience is increasingly turning to imaging the human brain for answers to a range of questions and challenges. To date, the majority of studies have focused on the neural basis of current psychiatric symptoms, which can facilitate the identification of neurobiological markers for diagnosis. However, the increasing availability and feasibility of using imaging modalities, such as diffusion imaging and resting-state fMRI, enable longitudinal mapping of brain development. This shift in the field is opening the possibility of identifying predictive markers of risk or prognosis, and also represents a critical missing element for efforts to promote personalized or individualized medicine in psychiatry (i.e., stratified psychiatry).

METHODS

The present work provides a selective review of potentially high-yield populations for longitudinal examination with MRI, based upon our understanding of risk from epidemiologic studies and initial MRI findings.

RESULTS

Our discussion is organized into three topic areas: (1) practical considerations for establishing temporal precedence in psychiatric research; (2) readiness of the field for conducting longitudinal MRI, particularly for neurodevelopmental questions; and (3) illustrations of high-yield populations and time windows for examination that can be used to rapidly generate meaningful and useful data. Particular emphasis is placed on the implementation of time-appropriate, developmentally informed longitudinal designs, capable of facilitating the identification of biomarkers predictive of risk and prognosis.

CONCLUSIONS

Strategic longitudinal examination of the brain at-risk has the potential to bring the concepts of early intervention and prevention to psychiatry.

Altered Gray Matter in Adolescents with d-Transposition of the Great Arteries

OBJECTIVE

To investigate the structural brain characteristics of adolescent patients with d-transposition of the great arteries (d-TGA), repaired with the arterial switch operation in early infancy, using quantitative volumetric magnetic resonance imaging.

STUDY DESIGN

Ninety-two patients with d-TGA from the Boston Circulatory Arrest Study (76% male; median age at scan 16.1 years) and 49 control subjects (41% male; median age at scan 15.7 years) were scanned using a 1.5-Tesla magnetic resonance imaging system. Subcortical and cortical gyral volumes and cortical gyral thicknesses were measured using surface-based morphometry. Group differences were assessed with linear regression.

RESULTS

Compared with controls, patients with d-TGA demonstrated significantly reduced subcortical volumes bilaterally in the striatum and pallidum. Cortical regions that showed significant volume and thickness differences between groups were distributed throughout parietal, medial frontoparietal, cingulate, and temporal gyri. Among adolescents with d-TGA, volumes and thicknesses correlated with several perioperative variables, including age at surgery, cooling duration, total support time, and days in the cardiac intensive care unit.

CONCLUSIONS

Adolescents with d-TGA repaired early in life exhibit widespread differences from control adolescents in gray matter volumes and thicknesses, particularly in parietal, midline, and subcortical brain regions, corresponding to white matter regions already known to demonstrate altered microstructure. These findings complement observations made in white matter in this group and suggest that the adolescent d-TGA cognitive profile derives from altered brain development involving both white and gray matter.

Spectral and source structural development of mu and alpha rhythms from infancy through adulthood

OBJECTIVE

To assess the developmental trajectory of spectral, topographic, and source structural properties of functional mu desynchronization (characterized during voluntary reaching/grasping movement), and investigate its spectral/topographic relation to spontaneous EEG in the developing alpha band.

METHODS

Event related desynchronization (ERD) and power spectral density spectra/topography are analyzed in 12 month-old infants, 4 year-old children, and adults. Age-matched head models derived from structural MRI are used to obtain current density reconstructions of mu desynchronization across the cortical surface.

RESULTS

Infant/child EEG contains spectral peaks evident in both the upper and lower developing alpha band, and spectral/topographic properties of functionally identified mu rhythm strongly reflect those of upper alpha in all subject groups. Source reconstructions show distributed frontoparietal patterns of cortical mu desynchronization concentrated in specific central and parietal regions which are consistent across age groups.

CONCLUSIONS

Peak frequencies of mu desynchronization and spontaneous alpha band EEG increase with age, and characteristic mu topography/source-structure is evident in development at least as early as 12 months.

SIGNIFICANCE

Results provide evidence for a cortically distributed functional mu network, with spontaneous activity measurable in the upper alpha band throughout development.

Effect of socioeconomic status disparity on child language and neural outcome: how early is early?

It is not news that poverty adversely affects child outcome. The literature is replete with reports of deleterious effects on developmental outcome, cognitive function, and school performance in children and youth. Causative factors include poor nutrition, exposure to toxins, inadequate parenting, lack of cognitive stimulation, unstable social support, genetics, and toxic environments. Less is known regarding how early in life adverse effects may be detected. This review proposes to elucidate "how early is early" through discussion of seminal articles related to the effect of socioeconomic status on language outcome and a discussion of the emerging literature on effects of socioeconomic status disparity on brain structure in very young children. Given the young ages at which such outcomes are detected, the critical need for early targeted interventions for our youngest is underscored. Further, the fiscal reasonableness of initiating quality interventions supports these initiatives. As early life adversity produces lasting and deleterious effects on developmental outcome and brain structure, increased focus on programs and policies directed to reducing the impact of socioeconomic disparities is essential.

Hindbrain regional growth in preterm newborns and its impairment in relation to brain injury

Premature birth globally affects about 11.1% of all newborns and is a risk factor for neurodevelopmental disability in surviving infants. Histology has suggested that hindbrain subdivisions grow differentially, especially in the third trimester. Prematurity-related brain injuries occurring in this period may selectively affect more rapidly developing areas of hindbrain, thus accompanying region-specific impairments in growth and ultimately neurodevelopmental deficits. The current study aimed to quantify regional growth of the cerebellum and the brainstem in preterm neonates (n = 65 with individually multiple scans). We probed associations of the regional volumes with severity of brain injury. In neonates with no imaging evidence of injury, our analysis using a mixed-effect linear model showed faster growth in the pons and the lateral convexity of anterior/posterior cerebellar lobes. Different patterns of growth impairment were found in relation to early cerebral intraventricular hemorrhage and cerebellar hemorrhage (P < 0.05), likely explaining different mechanisms through which neurogenesis is disrupted. The pattern of cerebellar growth identified in our study agreed excellently with details of cerebellar morphogenesis in perinatal development, which has only been observed in histological data. Our proposed analytic framework may provide predictive imaging biomarkers for neurodevelopmental outcome, enabling early identification and treatment of high-risk patients. Hum Brain Mapp 37:678-688, 2016. © 2015 Wiley Periodicals, Inc.

Effect of socioeconomic status (SES) disparity on neural development in female African-American infants at age 1 month

There is increasing interest in both the cumulative and long-term impact of early life adversity on brain structure and function, especially as the brain is both highly vulnerable and highly adaptive during childhood. Relationships between SES and neural development have been shown in children older than age 2 years. Less is known regarding the impact of SES on neural development in children before age 2. This paper examines the effect of SES, indexed by income-to-needs (ITN) and maternal education, on cortical gray, deep gray, and white matter volumes in term, healthy, appropriate for gestational age, African-American, female infants. At 5 weeks postnatal age, unsedated infants underwent MRI (3.0T Siemens Verio scanner, 32-channel head coil). Images were segmented based on a locally constructed template. Utilizing hierarchical linear regression, SES effects on MRI volumes were examined. In this cohort of healthy African-American female infants of varying SES, lower SES was associated with smaller cortical gray and deep gray matter volumes. These SES effects on neural outcome at such a young age build on similar studies of older children, suggesting that the biological embedding of adversity may occur very early in development.

Stereotaxic Magnetic Resonance Imaging Brain Atlases for Infants from 3 to 12 Months

BACKGROUND

Accurate labeling of brain structures within an individual or group is a key issue in neuroimaging. Methods for labeling infant brains have depended on the labels done on adult brains or average magnetic resonance imaging (MRI) templates based on adult brains. However, the features of adult brains differ in several ways from infant brains, so the creation of a labeled stereotaxic atlas based on infants would be helpful. The current work builds on the recent creation of age-appropriate average MRI templates during the first year (3, 4.5, 6, 7.5, 9, and 12 months) by creating anatomical label sets for each template.

METHODS

We created stereotaxic atlases for the age-specific average MRI templates. Manual delineation of cortical and subcortical areas was done on the average templates based on infants during the first year. We also applied a procedure for automatic computation of macroanatomical atlases for individual infant participants using two manually segmented adult atlases (Hammers, LONI Probabilistic Brain Atlas-LPBA40). To evaluate our methods, we did manual delineation of several cortical areas on selected individuals from each age. Linear and nonlinear registration of the individual and average template was used to transform the average atlas into the individual participant's space, and the average-transformed atlas was compared to the individual manually delineated brain areas. We also applied these methods to an external data set - not used in the atlas creation - to test generalizability of the atlases.

RESULTS

Age-appropriate manual atlases were the best fit to the individual manually delineated regions, with more error seen at greater age discrepancy. There was a close fit between the manually delineated and the automatically labeled regions for individual participants and for the age-appropriate template-based atlas transformed into participant space. There was close correspondence between automatic labeling of individual brain regions and those from the age-appropriate template. These relationships held even when tested on an external set of images.

CONCLUSION

We have created age-appropriate labeled templates for use in the study of infant development at 6 ages (3, 4.5, 6, 7.5, 9, and 12 months). Comparison with manual methods was quite good. We developed three stereotaxic atlases (one manual, two automatic) for each infant age, which should allow more fine-grained analysis of brain structure for these populations than was previously possible with existing tools. The template-based atlases constructed in the current study are available online (http://jerlab.psych.sc.edu/NeurodevelopmentalMRIDatabase).

Abnormal surface morphology of the central sulcus in children with attention-deficit/hyperactivity disorder

The central sulcus (CS) divides the primary motor and somatosensory areas, and its three-dimensional (3D) anatomy reveals the structural changes of the sensorimotor regions. Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that is associated with sensorimotor and executive function deficits. However, it is largely unknown whether the morphology of the CS alters due to inappropriate development in the ADHD brain. Here, we employed the sulcus-based morphometry approach to investigate the 3D morphology of the CS in 42 children whose ages spanned from 8.8 to 13.5 years (21 with ADHD and 21 controls). After automatic labeling of each CS, we computed seven regional shape metrics for each CS, including the global average length, average depth, maximum depth, average span, surface area, average cortical thickness, and local sulcal profile. We found that the average depth and maximum depth of the left CS as well as the average cortical thickness of bilateral CS in the ADHD group were significantly larger than those in the healthy children. Moreover, significant between-group differences in the sulcal profile had been found in middle sections of the CSs bilaterally, and these changes were positively correlated with the hyperactivity-impulsivity scores in the children with ADHD. Altogether, our results provide evidence for the abnormity of the CS anatomical morphology in children with ADHD due to the structural changes in the motor cortex, which significantly contribute to the clinical symptomatology of the disorder.

The diffusion tensor imaging (DTI) component of the NIH MRI study of normal brain development (PedsDTI)

The NIH MRI Study of normal brain development sought to characterize typical brain development in a population of infants, toddlers, children and adolescents/young adults, covering the socio-economic and ethnic diversity of the population of the United States. The study began in 1999 with data collection commencing in 2001 and concluding in 2007. The study was designed with the final goal of providing a controlled-access database; open to qualified researchers and clinicians, which could serve as a powerful tool for elucidating typical brain development and identifying deviations associated with brain-based disorders and diseases, and as a resource for developing computational methods and image processing tools. This paper focuses on the DTI component of the NIH MRI study of normal brain development. In this work, we describe the DTI data acquisition protocols, data processing steps, quality assessment procedures, and data included in the database, along with database access requirements. For more details, visit http://www.pediatricmri.nih.gov. This longitudinal DTI dataset includes raw and processed diffusion data from 498 low resolution (3 mm) DTI datasets from 274 unique subjects, and 193 high resolution (2.5 mm) DTI datasets from 152 unique subjects. Subjects range in age from 10 days (from date of birth) through 22 years. Additionally, a set of age-specific DTI templates are included. This forms one component of the larger NIH MRI study of normal brain development which also includes T1-, T2-, proton density-weighted, and proton magnetic resonance spectroscopy (MRS) imaging data, and demographic, clinical and behavioral data.

A database of age-appropriate average MRI templates

This article summarizes a life-span neurodevelopmental MRI database. The study of neurostructural development or neurofunctional development has been hampered by the lack of age-appropriate MRI reference volumes. This causes misspecification of segmented data, irregular registrations, and the absence of appropriate stereotaxic volumes. We have created the "Neurodevelopmental MRI Database" that provides age-specific reference data from 2 weeks through 89 years of age. The data are presented in fine-grained ages (e.g., 3 months intervals through 1 year; 6 months intervals through 19.5 years; 5 year intervals from 20 through 89 years). The base component of the database at each age is an age-specific average MRI template. The average MRI templates are accompanied by segmented partial volume estimates for segmenting priors, and a common stereotaxic atlas for infant, pediatric, and adult participants. The database is available online (http://jerlab.psych.sc.edu/NeurodevelopmentalMRIDatabase/).

Age-specific MRI brain and head templates for healthy adults from 20 through 89 years of age

This study created and tested a database of adult, age-specific MRI brain and head templates. The participants included healthy adults from 20 through 89 years of age. The templates were done in five-year, 10-year, and multi-year intervals from 20 through 89 years, and consist of average T1W for the head and brain, and segmenting priors for gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). It was found that age-appropriate templates provided less biased tissue classification estimates than age-inappropriate reference data and reference data based on young adult templates. This database is available for use by other investigators and clinicians for their MRI studies, as well as other types of neuroimaging and electrophysiological research.¹

The potential of infant fMRI research and the study of early life stress as a promising exemplar

Functional magnetic resonance imaging (fMRI) research with infants and toddlers has increased rapidly over the past decade, and provided a unique window into early brain development. In the current report, we review the state of the literature, which has established the feasibility and utility of task-based fMRI and resting state functional connectivity MRI (rs-fcMRI) during early periods of brain maturation. These methodologies have been successfully applied beginning in the neonatal period to increase understanding of how the brain both responds to environmental stimuli, and becomes organized into large-scale functional systems that support complex behaviors. We discuss the methodological challenges posed by this promising area of research. We also highlight that despite these challenges, early work indicates a strong potential for these methods to influence multiple research domains. As an example, we focus on the study of early life stress and its influence on brain development and mental health outcomes. We illustrate the promise of these methodologies for building on, and making important contributions to, the existing literature in this field.

MRI evaluation and safety in the developing brain

Magnetic resonance imaging (MRI) evaluation of the developing brain has dramatically increased over the last decade. Faster acquisitions and the development of advanced MRI sequences, such as magnetic resonance spectroscopy (MRS), diffusion tensor imaging (DTI), perfusion imaging, functional MR imaging (fMRI), and susceptibility-weighted imaging (SWI), as well as the use of higher magnetic field strengths has made MRI an invaluable tool for detailed evaluation of the developing brain. This article will provide an overview of the use and challenges associated with 1.5-T and 3-T static magnetic fields for evaluation of the developing brain. This review will also summarize the advantages, clinical challenges, and safety concerns specifically related to MRI in the fetus and newborn, including the implications of increased magnetic field strength, logistics related to transporting and monitoring of neonates during scanning, and sedation considerations, and a discussion of current technologies such as MRI conditional neonatal incubators and dedicated small-foot print neonatal intensive care unit (NICU) scanners.

Observation and modeling of deep brain stimulation electrode depth in the pallidal target of the developing brain

OBJECTIVE

It is unclear how brain growth with age affects electrode position in relation to target for children undergoing deep brain stimulation surgery. We aimed to model projected change in the distance between the entry point of the electrode into the brain and target during growth to adulthood.

METHODS

Modeling was performed using a neurodevelopmental magnetic resonance imaging database of age-specific templates in 6-month increments from 4 to 18 years of age. Coordinates were chosen for a set of entry points into both cerebral hemispheres and target positions within the globus pallidus internus on the youngest magnetic resonance imaging template. The youngest template was nonlinearly registered to the older templates, and the transformations generated by these registrations were applied to the original coordinates of entry and target positions, mapping these positions with increasing age. Euclidean geometry was used to calculate the distance between projected electrode entry and target with increasing age.

RESULTS

A projected increase in distance between entry point and target of 5-10 mm was found from age 4 to 18 years. Most change appeared to occur before 7 years of age, after which minimal change in distance was found.

CONCLUSIONS

Electrodes inserted during deep brain stimulation surgery are tethered at the point of entry to the skull. Brain growth, which could result in a relative retraction with respect to the original target position, appears to occur before 7 years of age, suggesting careful monitoring is needed for children undergoing implantation before this age. Reengineering of electrode design could avoid reimplantation surgery in young children undergoing deep brain stimulation.

Volumetric brain analysis in neurosurgery: Part 2. Brain and CSF volumes discriminate neurocognitive outcomes in hydrocephalus

OBJECT

The evaluation of hydrocephalus remains focused on ventricular size, yet the goal of treatment is to allow for healthy brain development. It is likely that brain volume is more related to cognitive development than is fluid volume in children with hydrocephalus. This study tests this hypothesis by comparing brain and fluid volumes with neurocognitive outcome in pediatric patients with hydrocephalus.

METHODS

Warf and colleagues previously acquired CT scans for pediatric patients in Uganda with myelomeningocele, measured frontal-occipital horn ratio (FOHR), and administered the modified Bayley Scales of Infant Development, third edition (BSID-III) to measure neurocognitive outcome that did not correlate with FOHR. In this present study, brain and fluid volumes were measured in 33 of these patients, 26 of whom required surgical treatment for hydrocephalus. Linear discrimination analysis (LDA) was used to test whether age-normalized brain and fluid volumes can discriminate neurocognitive outcome.

RESULTS

Hydrocephalic patients show normal to small brain volumes and substantially larger fluid volumes compared with normal values. FOHR correlates highly with fluid volume (r=0.84, p<0.001) and substantially less with brain volume (r=-0.37, p=0.03), while brain and fluid volumes do not correlate with each other (p=0.99). Brain and CSF volumes correlated best with fine motor (p=0.03, p=0.01), cognitive (p=0.05, p=0.09), and expressive communication (p=0.08, p=0.08) scores. A combination of these 3 scores was used as a multivariate measure of neurocognitive outcome. Brain volume alone, unlike fluid volume, could discriminate high from low cognitive outcome (by t-test and ANOVA). It was shown that a combination of age-normalized brain and fluid volumes can discriminate neurocognitive outcome by 2-way LDA (p<0.01) and 3-way LDA (p<0.01). The multivariate LDA demonstrated the contribution of large fluid volume to a decrement in cognition.

CONCLUSIONS

Hydrocephalus is treated by normalizing CSF, but normal brain development depends on brain growth. A combination of brain and CSF volumes appears to be significantly more powerful at predicting good versus poor neurocognitive outcomes in patients with hydrocephalus than either volume alone.

Volumetric brain analysis in neurosurgery: Part 1. Particle filter segmentation of brain and cerebrospinal fluid growth dynamics from MRI and CT images

OBJECT

Accurate edge tracing segmentation remains an incompletely solved problem in brain image analysis. The authors propose a novel algorithm using a particle filter to follow the boundary of the brain in the style often used in autonomous air and ground vehicle navigation. Their goals were to create a versatile tool to segment brain and fluid in MRI and CT images of the developing brain, lay the foundation for an intelligent automated edge tracker that is modality independent, and segment normative data from MRI that can be applied to both MRI and CT.

METHODS

Simulated MRI data sets were used to train and evaluate the particle filter segmentation algorithm. The method was then applied to produce normative growth curves for children and adolescents from 0 to 18 years of age for brain and fluid from MR images from the National Institutes of Health pediatric database and these data were compared to historical results. The authors further adapted this method for use with CT images of pediatric hydrocephalus and compared the results with hand-segmented data.

RESULTS

Segmentation of simulated MRI data with varied levels of noise (0%-9%) and spatial inhomogeneity (0%-40%) resulted in percent errors ranging from 0.06% to 5.38% for brain volume and 2.45% to 22.3% for fluid volume. The authors used this tool to create normal brain and CSF growth curves from MR images. The calculated growth curves showed excellent consistency with historical data. Additionally, compared with manual segmentation the particle filter accurately segmented brain and fluid volumes from CT scans of 5 pediatric patients with hydrocephalus (p<0.001).

CONCLUSIONS

The authors have produced the first normative brain and CSF growth curves for children and adolescents 0-18 years of age. In addition, this study includes the first use of a particle filter as an edge tracker in image segmentation and offers a semiautomatic method to segment both pediatric and adult brain data from MR and CT images. The particle filter has the potential to be further automated toward a clinical rather than research tool with both of these modalities. Because of its modality independence, it has the capability to allow CT to be a more effective diagnostic tool for neurological disorders, a task of substantial importance in emergency settings and in developing countries where CT is often the only available method of brain imaging.

Volumetric brain analysis in neurosurgery: Part 3. Volumetric CT analysis as a predictor of seizure outcome following temporal lobectomy

OBJECT

The incidence of temporal lobe epilepsy (TLE) due to mesial temporal sclerosis (MTS) can be high in developing countries. Current diagnosis of MTS relies on structural MRI, which is generally unavailable in developing world settings. Given widespread effects on temporal lobe structure beyond hippocampal atrophy in TLE, the authors propose that CT volumetric analysis can be used in patient selection to help predict outcomes following resection.

METHODS

Ten pediatric patients received preoperative CT scans and temporal resections at the CURE Children's Hospital of Uganda. Engel classification of seizure control was determined 12 months postoperatively. Temporal lobe volumes were measured from CT and from normative MR images using the Cavalieri method. Whole brain and fluid volumes were measured using particle filter segmentation. Linear discrimination analysis (LDA) was used to classify seizure outcome by temporal lobe volumes and normalized brain volume.

RESULTS

Epilepsy patients showed normal to small brain volumes and small temporal lobes bilaterally. A multivariate measure of the volume of each temporal lobe separated patients who were seizure free (Engel Class IA) from those with incomplete seizure control (Engel Class IB/IIB) with LDA (p<0.01). Temporal lobe volumes also separate normal subjects, patients with Engel Class IA outcomes, and patients with Class IB/IIB outcomes (p<0.01). Additionally, the authors demonstrated that age-normalized whole brain volume, in combination with temporal lobe volumes, may further improve outcome prediction (p<0.01).

CONCLUSIONS

This study shows strong evidence that temporal lobe and brain volume can be predictive of seizure outcome following temporal lobe resection, and that volumetric CT analysis of the temporal lobe may be feasible in lieu of structural MRI when the latter is unavailable. Furthermore, since the authors' methods are modality independent, these findings suggest that temporal lobe and normative brain volumes may further be useful in the selection of patients for temporal lobe resection when structural MRI is available.

Brains for all the ages: structural neurodevelopment in infants and children from a life-span perspective

Magnetic resonance imaging (MRI) is a noninvasive method to measure brain structure and function that may be applied to human participants of all ages. This chapter reviews our recent work creating a life-span Neurodevelopmental MRI Database. It provides age-specific reference data in fine-grained age intervals from 2 weeks through 89 years. The reference data include average MRI templates, segmented tissue priors, and a common stereotaxic atlas for pediatric and adult participants. The database will be useful for neuroimaging research over a wide range of ages and may be used to make life-span comparisons. The chapter reviews the application of this database to the study of neurostructural development, including a new volumetric study of segmented brain tissue over the life span. We also show how this database could be used to create "study-specific" MRI templates for special groups and apply this to the MRIs of Chinese children. Finally, we review recent use of the database in the study of brain activity in pediatric populations.

Human neuroimaging as a "Big Data" science

The maturation of in vivo neuroimaging has led to incredible quantities of digital information about the human brain. While much is made of the data deluge in science, neuroimaging represents the leading edge of this onslaught of "big data". A range of neuroimaging databasing approaches has streamlined the transmission, storage, and dissemination of data from such brain imaging studies. Yet few, if any, common solutions exist to support the science of neuroimaging. In this article, we discuss how modern neuroimaging research represents a multifactorial and broad ranging data challenge, involving the growing size of the data being acquired; sociological and logistical sharing issues; infrastructural challenges for multi-site, multi-datatype archiving; and the means by which to explore and mine these data. As neuroimaging advances further, e.g. aging, genetics, and age-related disease, new vision is needed to manage and process this information while marshalling of these resources into novel results. Thus, "big data" can become "big" brain science.

Simultaneous and consistent labeling of longitudinal dynamic developing cortical surfaces in infants

The human cerebral cortex develops extremely dynamically in the first 2years of life. Accurate and consistent parcellation of longitudinal dynamic cortical surfaces during this critical stage is essential to understand the early development of cortical structure and function in both normal and high-risk infant brains. However, directly applying the existing methods developed for the cross-sectional studies often generates longitudinally-inconsistent results, thus leading to inaccurate measurements of the cortex development. In this paper, we propose a new method for accurate, consistent, and simultaneous labeling of longitudinal cortical surfaces in the serial infant brain MR images. The proposed method is explicitly formulated as a minimization problem with an energy function that includes a data fitting term, a spatial smoothness term, and a temporal consistency term. Specifically, inspired by multi-atlas based label fusion, the data fitting term is designed to integrate the contributions from multi-atlas surfaces adaptively, according to the similarities of their local cortical folding with that of the subject cortical surface. The spatial smoothness term is then designed to adaptively encourage label smoothness based on the local cortical folding geometries, i.e., allowing label discontinuity at sulcal bottoms (which often are the boundaries of cytoarchitecturally and functionally distinct regions). The temporal consistency term is to adaptively encourage the label consistency among the temporally-corresponding vertices, based on their similarity of local cortical folding. Finally, the entire energy function is efficiently minimized by a graph cuts method. The proposed method has been applied to the parcellation of longitudinal cortical surfaces of 13 healthy infants, each with 6 serial MRI scans acquired at 0, 3, 6, 9, 12 and 18months of age. Qualitative and quantitative evaluations demonstrated both accuracy and longitudinal consistency of the proposed method. By using our method, for the first time, we reveal several hitherto unseen properties of the dynamic and regionally heterogeneous development of the cortical surface area in the first 18months of life.

Annual research review: Current limitations and future directions in MRI studies of child- and adult-onset developmental psychopathologies

BACKGROUND

The widespread use of Magnetic Resonance Imaging (MRI) in the study of child- and adult-onset developmental psychopathologies has generated many investigations that have measured brain structure and function in vivo throughout development, often generating great excitement over our ability to visualize the living, developing brain using the attractive, even seductive images that these studies produce. Often lost in this excitement is the recognition that brain imaging generally, and MRI in particular, is simply a technology, one that does not fundamentally differ from any other technology, be it a blood test, a genotyping assay, a biochemical assay, or behavioral test. No technology alone can generate valid scientific findings. Rather, it is only technology coupled with a strong experimental design that can generate valid and reproducible findings that lead to new insights into the mechanisms of disease and therapeutic response.

METHODS

In this review we discuss selected studies to illustrate the most common and important limitations of MRI study designs as most commonly implemented thus far, as well as the misunderstanding that the interpretations of findings from those studies can create for our theories of developmental psychopathologies.

RESULTS

Common limitations of MRI study designs are in large part responsible thus far for the generally poor reproducibility of findings across studies, poor generalizability to the larger population, failure to identify developmental trajectories, inability to distinguish causes from effects of illness, and poor ability to infer causal mechanisms in most MRI studies of developmental psychopathologies. For each of these limitations in study design and the difficulties they entail for the interpretation of findings, we discuss various approaches that numerous laboratories are now taking to address those difficulties, which have in common the yoking of brain imaging technologies to studies with inherently stronger designs that permit more valid and more powerful causal inferences. Those study designs include epidemiological, longitudinal, high-risk, clinical trials, and multimodal imaging studies.

CONCLUSIONS

We highlight several studies that have yoked brain imaging technologies to these stronger designs to illustrate how doing so can aid our understanding of disease mechanisms and in the foreseeable future can improve clinical diagnosis, prevention, and treatment planning for developmental psychopathologies.

Movement-related neuromagnetic fields in preschool age children

We examined sensorimotor brain activity associated with voluntary movements in preschool children using a customized pediatric magnetoencephalographic system. A videogame-like task was used to generate self-initiated right or left index finger movements in 17 healthy right-handed subjects (8 females, ages 3.2-4.8 years). We successfully identified spatiotemporal patterns of movement-related brain activity in 15/17 children using beamformer source analysis and surrogate MRI spatial normalization. Readiness fields in the contralateral sensorimotor cortex began ∼0.5 s prior to movement onset (motor field, MF), followed by transient movement-evoked fields (MEFs), similar to that observed during self-paced movements in adults, but slightly delayed and with inverted source polarities. We also observed modulation of mu (8-12 Hz) and beta (15-30 Hz) oscillations in sensorimotor cortex with movement, but with different timing and a stronger frequency band coupling compared to that observed in adults. Adult-like high-frequency (70-80 Hz) gamma bursts were detected at movement onset. All children showed activation of the right superior temporal gyrus that was independent of the side of movement, a response that has not been reported in adults. These results provide new insights into the development of movement-related brain function, for an age group in which no previous data exist. The results show that children under 5 years of age have markedly different patterns of movement-related brain activity in comparison to older children and adults, and indicate that significant maturational changes occur in the sensorimotor system between the preschool years and later childhood.

Reprint of "Quantitative evaluation of brain development using anatomical MRI and diffusion tensor imaging"

The development of the brain is structure-specific, and the growth rate of each structure differs depending on the age of the subject. Magnetic resonance imaging (MRI) is often used to evaluate brain development because of the high spatial resolution and contrast that enable the observation of structure-specific developmental status. Currently, most clinical MRIs are evaluated qualitatively to assist in the clinical decision-making and diagnosis. The clinical MRI report usually does not provide quantitative values that can be used to monitor developmental status. Recently, the importance of image quantification to detect and evaluate mild-to-moderate anatomical abnormalities has been emphasized because these alterations are possibly related to several psychiatric disorders and learning disabilities. In the research arena, structural MRI and diffusion tensor imaging (DTI) have been widely applied to quantify brain development of the pediatric population. To interpret the values from these MR modalities, a "growth percentile chart," which describes the mean and standard deviation of the normal developmental curve for each anatomical structure, is required. Although efforts have been made to create such a growth percentile chart based on MRI and DTI, one of the greatest challenges is to standardize the anatomical boundaries of the measured anatomical structures. To avoid inter- and intra-reader variability about the anatomical boundary definition, and hence, to increase the precision of quantitative measurements, an automated structure parcellation method, customized for the neonatal and pediatric population, has been developed. This method enables quantification of multiple MR modalities using a common analytic framework. In this paper, the attempt to create an MRI- and a DTI-based growth percentile chart, followed by an application to investigate developmental abnormalities related to cerebral palsy, Williams syndrome, and Rett syndrome, have been introduced. Future directions include multimodal image analysis and personalization for clinical application.

Referential framework for transcranial anatomical correspondence for fNIRS based on manually traced sulci and gyri of an infant brain

Functional near infrared spectroscopy (fNIRS), which is compact, portable, and tolerant of body movement, is suitable for monitoring infant brain functions. Nevertheless, fNIRS also poses a technical problem in that it cannot provide structural information. Supplementation with structural magnetic resonance images (MRI) is not always feasible for infants who undergo fNIRS measurement. Probabilistic registration methods using an MRI database instead of subjects' own MRIs are optimized for adult studies and offer only limited resources for infant studies. To overcome this, we used high-quality infant MRI data for a 12-month-old infant and manually delineated segmented gyri from among the highly visible macroanatomies on the lateral cortical surface. These macroanatomical regions are primarily linked to the spherical coordinate system based on external cranial landmarks, and further to traditional 10-20-based head-surface positioning systems. While macroanatomical structures were generally comparable between adult and infant atlases, differences were found in the parietal lobe, which was positioned posteriorly at the vertex in the infant brain. The present study provides a referential framework for macroanatomical analyses in infant fNIRS studies. With this resource, multichannel fNIRS functional data could be analyzed in reference to macroanatomical structures through virtual and probabilistic registrations without acquiring subject-specific MRIs.

Measuring the dynamic longitudinal cortex development in infants by reconstruction of temporally consistent cortical surfaces

Quantitative measurement of the dynamic longitudinal cortex development during early postnatal stages is of great importance to understand the early cortical structural and functional development. Conventional methods usually reconstruct the cortical surfaces of longitudinal images from the same subject independently, which often generate longitudinally-inconsistent cortical surfaces and thus lead to inaccurate measurement of cortical changes, especially for vertex-wise mapping of cortical development. This paper aims to address this problem by presenting a method to reconstruct temporally-consistent cortical surfaces from longitudinal infant brain MR images, for accurate and consistent measurement of the dynamic cortex development in infants. Specifically, the longitudinal development of the inner cortical surface is first modeled by a deformable growth sheet with elasto-plasticity property to establish longitudinally smooth correspondences of the inner cortical surfaces. Then, the modeled longitudinal inner cortical surfaces are jointly deformed to locate both inner and outer cortical surfaces with a spatial-temporal deformable surface method. The method has been applied to 13 healthy infants, each with 6 serial MR scans acquired at 2 weeks, 3 months, 6 months, 9 months, 12 months and 18 months of age. Experimental results showed that our method with the incorporated longitudinal constraints can reconstruct the longitudinally-dynamic cortical surfaces from serial infant MR images more consistently and accurately than the previously published methods. By using our method, for the first time, we can characterize the vertex-wise longitudinal cortical thickness development trajectory at multiple time points in the first 18 months of life. Specifically, we found the highly age-related and regionally-heterogeneous developmental trajectories of the cortical thickness during this period, with the cortical thickness increased most from 3 to 6 months (16.2%) and least from 9 to 12 months (less than 0.1%). Specifically, the central sulcus only underwent significant increase of cortical thickness from 6 to 9 months and the occipital cortex underwent significant increase from 0 to 9 months, while the frontal, temporal and parietal cortices grew continuously in this first 18 months of life. The adult-like spatial patterns of cortical thickness were generally present at 18 months of age. These results provided detailed insights into the dynamic trajectory of the cortical thickness development in infants.

Family poverty affects the rate of human infant brain growth

Living in poverty places children at very high risk for problems across a variety of domains, including schooling, behavioral regulation, and health. Aspects of cognitive functioning, such as information processing, may underlie these kinds of problems. How might poverty affect the brain functions underlying these cognitive processes? Here, we address this question by observing and analyzing repeated measures of brain development of young children between five months and four years of age from economically diverse backgrounds (n = 77). In doing so, we have the opportunity to observe changes in brain growth as children begin to experience the effects of poverty. These children underwent MRI scanning, with subjects completing between 1 and 7 scans longitudinally. Two hundred and three MRI scans were divided into different tissue types using a novel image processing algorithm specifically designed to analyze brain data from young infants. Total gray, white, and cerebral (summation of total gray and white matter) volumes were examined along with volumes of the frontal, parietal, temporal, and occipital lobes. Infants from low-income families had lower volumes of gray matter, tissue critical for processing of information and execution of actions. These differences were found for both the frontal and parietal lobes. No differences were detected in white matter, temporal lobe volumes, or occipital lobe volumes. In addition, differences in brain growth were found to vary with socioeconomic status (SES), with children from lower-income households having slower trajectories of growth during infancy and early childhood. Volumetric differences were associated with the emergence of disruptive behavioral problems.

Prenatal maternal depression associates with microstructure of right amygdala in neonates at birth

BACKGROUND

Antenatal maternal cortisol levels associate with alterations in the amygdala, a structure associated with emotion regulation, in the offspring. However, because offspring brain and behavior are commonly assessed years after birth, the timing of such maternal influences is unclear. This study aimed to examine the association between antenatal maternal depressive symptomatology and neonatal amygdala volume and microstructure and thus establish evidence for the transgenerational transmission of vulnerability for affective disorders during prenatal development.

METHODS

Our study recruited Asian mothers at 10 to 13 weeks pregnancy and assessed maternal depression at 26 weeks gestation using the Edinburgh Postnatal Depression Scale. Structural magnetic resonance imaging and diffusion tensor imaging were performed with 157 nonsedated, 6- to 14-day-old newborns and then analyzed to extract the volume, fractional anisotropy, and axial diffusivity values of the amygdala.

RESULTS

Adjusting for household income, maternal age, and smoking exposure, postconceptual age at magnetic resonance imaging, and birth weight, we found significantly lower fractional anisotropy (p = .009) and axial diffusivity (p = .028), but not volume (p = .993), in the right amygdala in the infants of mothers with high compared with those with low-normal Edinburgh Postnatal Depression Scale scores.

CONCLUSIONS

The results reveal a significant relation between antenatal maternal depression and the neonatal microstructure of the right amygdala, a brain region closely associated with stress reactivity and vulnerability for mood anxiety disorders. These findings suggest the prenatal transmission of vulnerability for depression from mother to child and that interventions targeting maternal depression should begin early in pregnancy.

Quantitative evaluation of brain development using anatomical MRI and diffusion tensor imaging

The development of the brain is structure-specific, and the growth rate of each structure differs depending on the age of the subject. Magnetic resonance imaging (MRI) is often used to evaluate brain development because of the high spatial resolution and contrast that enable the observation of structure-specific developmental status. Currently, most clinical MRIs are evaluated qualitatively to assist in the clinical decision-making and diagnosis. The clinical MRI report usually does not provide quantitative values that can be used to monitor developmental status. Recently, the importance of image quantification to detect and evaluate mild-to-moderate anatomical abnormalities has been emphasized because these alterations are possibly related to several psychiatric disorders and learning disabilities. In the research arena, structural MRI and diffusion tensor imaging (DTI) have been widely applied to quantify brain development of the pediatric population. To interpret the values from these MR modalities, a "growth percentile chart," which describes the mean and standard deviation of the normal developmental curve for each anatomical structure, is required. Although efforts have been made to create such a growth percentile chart based on MRI and DTI, one of the greatest challenges is to standardize the anatomical boundaries of the measured anatomical structures. To avoid inter- and intra-reader variability about the anatomical boundary definition, and hence, to increase the precision of quantitative measurements, an automated structure parcellation method, customized for the neonatal and pediatric population, has been developed. This method enables quantification of multiple MR modalities using a common analytic framework. In this paper, the attempt to create an MRI- and a DTI-based growth percentile chart, followed by an application to investigate developmental abnormalities related to cerebral palsy, Williams syndrome, and Rett syndrome, have been introduced. Future directions include multimodal image analysis and personalization for clinical application.

Age-specific average head template for typically developing 6-month-old infants

Due to the rapid anatomical changes that occur within the brain structure in early human development and the significant differences between infant brains and the widely used standard adult templates, it becomes increasingly important to utilize appropriate age- and population-specific average templates when analyzing infant neuroimaging data. In this study we created a new and highly detailed age-specific unbiased average head template in a standard MNI152-like infant coordinate system for healthy, typically developing 6-month-old infants by performing linear normalization, diffeomorphic normalization and iterative averaging processing on 60 subjects' structural images. The resulting age-specific average templates in a standard MNI152-like infant coordinate system demonstrate sharper anatomical detail and clarity compared to existing infant average templates and successfully retains the average head size of the 6-month-old infant. An example usage of the average infant templates transforms magnetoencephalography (MEG) estimated activity locations from MEG's subject-specific head coordinate space to the standard MNI152-like infant coordinate space. We also created a new atlas that reflects the true 6-month-old infant brain anatomy. Average templates and atlas are publicly available on our website (http://ilabs.washington.edu/6-m-templates-atlas).

A brain of two halves: insights into interhemispheric organization provided by near-infrared spectroscopy

The discovery of functional lateralization and localization of the brain marked the beginning of a new era in neuroscience. While the past 150 years of research have provided a great deal of knowledge of hemispheric differences and functional relationships, the precise organization of functional laterality remains a topic of intense debate. Here I will shed light on the functional organization of the two hemispheres by reviewing some of the most recent functional near-infrared spectroscopy (NIRS) studies that have reported hemispheric differences in activation patterns. Most NIRS studies using visual stimuli, which revealed functional differentiation between the hemispheres, have reported unilateral activation, i.e., significant levels of activation in only one hemisphere. Auditory stimuli, including speech sounds, elicited bilateral activation, while the limited number of studies on young infants revealed primarily unilateral activation. The stimulus modality and the age of the participants therefore determine whether the resulting cortical activation is unilateral or bilateral. By combining a review of the existing literature with NIRS results regarding homologous connectivity across hemispheres, I hypothesized that the origin of functional lateralization changes from the independence of each hemispheric region, to mutual inhibition between homologous regions during development. Future studies applying multi-modal measurements along with NIRS and spatiotemporal analyses will further deepen our understanding of the interhemispheric organization of brain function.

Age-related changes in tissue signal properties within cortical areas important for word understanding in 12- to 19-month-old infants

Recently, our laboratory has shown that the neural mechanisms for encoding lexico-semantic information in adults operate functionally by 12-18 months of age within left frontotemporal cortices (Travis et al., 2011. Spatiotemporal neural dynamics of word understanding in 12- to 18-month-old-infants. Cereb Cortex. 8:1832-1839). However, there is minimal knowledge of the structural changes that occur within these and other cortical regions important for language development. To identify regional structural changes taking place during this important period in infant development, we examined age-related changes in tissue signal properties of gray matter (GM) and white matter (WM) intensity and contrast. T1-weighted surface-based measures were acquired from 12- to 19-month-old infants and analyzed using a general linear model. Significant age effects were observed for GM and WM intensity and contrast within bilateral inferior lateral and anterovental temporal regions, dorsomedial frontal, and superior parietal cortices. Region of interest (ROI) analyses revealed that GM and WM intensity and contrast significantly increased with age within the same left lateral temporal regions shown to generate lexico-semantic activity in infants and adults. These findings suggest that neurophysiological processes supporting linguistic and cognitive behaviors may develop before cellular and structural maturation is complete within associative cortices. These results have important implications for understanding the neurobiological mechanisms relating structural to functional brain development.

Multiscale adaptive generalized estimating equations for longitudinal neuroimaging data

Many large-scale longitudinal imaging studies have been or are being widely conducted to better understand the progress of neuropsychiatric and neurodegenerative disorders and normal brain development. The goal of this article is to develop a multiscale adaptive generalized estimation equation (MAGEE) method for spatial and adaptive analysis of neuroimaging data from longitudinal studies. MAGEE is applicable to making statistical inference on regression coefficients in both balanced and unbalanced longitudinal designs and even in twin and familial studies, whereas standard software platforms have several major limitations in handling these complex studies. Specifically, conventional voxel-based analyses in these software platforms involve Gaussian smoothing imaging data and then independently fitting a statistical model at each voxel. However, the conventional smoothing methods suffer from the lack of spatial adaptivity to the shape and spatial extent of region of interest and the arbitrary choice of smoothing extent, while independently fitting statistical models across voxels does not account for the spatial properties of imaging observations and noise distribution. To address such drawbacks, we adapt a powerful propagation-separation (PS) procedure to sequentially incorporate the neighboring information of each voxel and develop a new novel strategy to solely update a set of parameters of interest, while fixing other nuisance parameters at their initial estimators. Simulation studies and real data analysis show that MAGEE significantly outperforms voxel-based analysis.

Tracking cerebral white matter changes across the lifespan: insights from diffusion tensor imaging studies

Delineating the normal development of brain white matter (WM) over the human lifespan is crucial to improved understanding of underlying WM pathology in neuropsychiatric and neurological conditions. We review the extant literature concerning diffusion tensor imaging studies of brain WM development in healthy individuals available until October 2012, summarise trends of normal development of human brain WM and suggest possible future research directions. Temporally, brain WM maturation follows a curvilinear pattern with an increase in fractional anisotropy (FA) from newborn to adolescence, decelerating in adulthood till a plateau around mid-adulthood, and a more rapid decrease of FA from old age onwards. Spatially, brain WM tracts develop from central to peripheral regions, with evidence of anterior-to-posterior maturation in commissural and projection fibres. The corpus callosum and fornix develop first and decline earlier, whilst fronto-temporal WM tracts like cingulum and uncinate fasciculus have protracted maturation and decline later. Prefrontal WM is most vulnerable with greater age-related FA reduction compared with posterior WM. Future large scale studies adopting longitudinal design will better clarify human brain WM changes over time.

Age-specific MRI templates for pediatric neuroimaging

This study created a database of pediatric age-specific magnetic resonance imaging (MRI) brain templates for normalization and segmentation. Participants included children from 4.5 through 19.5 years, totaling 823 scans from 494 subjects. Open-source processing programs (FMRIB Software Library, Statistical Parametric Mapping, Advanced Normalization Tools [ANTS]) constructed head, brain, and segmentation templates in 6-month intervals. The tissue classification (white matter [WM], gray matter [GM], cerebrospinal fluid) showed changes over age similar to previous reports. A volumetric analysis of age-related changes in WM and GM based on these templates showed expected increase/decrease pattern in GM and an increase in WM over the sampled ages. This database is available for use for neuroimaging studies (http://jerlab.psych.sc.edu/neurodevelopmentalmridatabase).