Social dominance and rainfall predict telomere dynamics in a cooperative arid-zone bird.

In many vertebrate societies dominant individuals breed at substantially higher rates than subordinates, but whether this hastens ageing remains poorly understood. While frequent reproduction may trade off against somatic maintenance, the extraordinary fecundity and longevity of some social insect queens highlight that breeders need not always suffer more rapid somatic deterioration than their nonbreeding subordinates. Here, we used extensive longitudinal assessments of telomere dynamics to investigate the impact of dominance status on within-individual age-related changes in somatic integrity in a wild social bird, the white-browed sparrow-weaver (Plocepasser mahali). Dominant birds, who monopolise reproduction, had neither shorter telomeres nor faster telomere attrition rates over the long-term (1-5 years) than their subordinates. However, over shorter (half-year) time intervals dominants with shorter telomeres showed lower rates of telomere attrition (and evidence suggestive of telomere lengthening), while the same was not true among subordinates. Dominants may therefore invest more heavily in telomere length regulation (and/or somatic maintenance more broadly); a strategy that could mitigate the long-term costs of reproductive effort, leaving their long-term telomere dynamics comparable to those of subordinates. Consistent with the expectation that reproduction entails short-term costs to somatic integrity, telomere attrition rates were most severe for all birds during the breeding seasons of wetter years (rainfall is the key driver of reproductive activity in this arid-zone species). Our findings suggest that, even in vertebrate societies in which dominants monopolise reproduction, dominants may experience long-term somatic integrity trajectories indistinguishable from those of their nonreproductive subordinates.

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.

Analysis of the contribution of experimental bias, experimental noise, and inter-subject biological variability on the assessment of developmental trajectories in diffusion MRI studies of the brain.

Metrics derived from the diffusion tensor, such as fractional anisotropy (FA) and mean diffusivity (MD) have been used in many studies of postnatal brain development. A common finding of previous studies is that these tensor-derived measures vary widely even in healthy populations. This variability can be due to inherent inter-individual biological differences as well as experimental noise. Moreover, when comparing different studies, additional variability can be introduced by different acquisition protocols. In this study we examined scans of 61 individuals (aged 4-22 years) from the NIH MRI study of normal brain development. Two scans were collected with different protocols (low and high resolution). Our goal was to separate the contributions of biological variability and experimental noise to the overall measured variance, as well as to assess potential systematic effects related to the use of different protocols. We analyzed FA and MD in seventeen regions of interest. We found that biological variability for both FA and MD varies widely across brain regions; biological variability is highest for FA in the lateral part of the splenium and body of the corpus callosum along with the cingulum and the superior longitudinal fasciculus, and for MD in the optic radiations and the lateral part of the splenium. These regions with high inter-individual biological variability are the most likely candidates for assessing genetic and environmental effects in the developing brain. With respect to protocol-related effects, the lower resolution acquisition resulted in higher MD and lower FA values for the majority of regions compared with the higher resolution protocol. However, the majority of the regions did not show any age-protocol interaction, indicating similar trajectories were obtained irrespective of the protocol used.

Investigation of vibration-induced artifact in clinical diffusion-weighted imaging of pediatric subjects.

It has been reported that mechanical vibrations of the magnetic resonance imaging scanner could produce spurious signal dropouts in diffusion-weighted images resulting in artifactual anisotropy in certain regions of the brain with red appearance in the Directionally Encoded Color maps. We performed a review of the frequency of this artifact across pediatric studies, noting differences by scanner manufacturer, acquisition protocol, as well as weight and position of the subject. We also evaluated the ability of automated and quantitative methods to detect this artifact. We found that the artifact may be present in over 50% of data in certain protocols and is not limited to one scanner manufacturer. While a specific scanner had the highest incidence, low body weight and positioning were also associated with appearance of the artifact for both scanner types evaluated, making children potentially more susceptible than adults. Visual inspection remains the best method for artifact identification. Software for automated detection showed very low sensitivity (10%). The artifact may present inconsistently in longitudinal studies. We discuss a published case report that has been widely cited and used as evidence to set policy about diagnostic criteria for determining vegetative state. That report attributed longitudinal changes in anisotropy to white matter plasticity without considering the possibility that the changes were caused by this artifact. Our study underscores the need to check for the presence of this artifact in clinical studies, analyzes circumstances for when it may be more likely to occur, and suggests simple strategies to identify and potentially avoid its effects.

Estimating the age of healthy infants from quantitative myelin water fraction maps.

The trajectory of the developing brain is characterized by a sequence of complex, nonlinear patterns that occur at systematic stages of maturation. Although significant prior neuroimaging research has shed light on these patterns, the challenge of accurately characterizing brain maturation, and identifying areas of accelerated or delayed development, remains. Altered brain development, particularly during the earliest stages of life, is believed to be associated with many neurological and neuropsychiatric disorders. In this work, we develop a framework to construct voxel-wise estimates of brain age based on magnetic resonance imaging measures sensitive to myelin content. 198 myelin water fraction (VF(M) ) maps were acquired from healthy male and female infants and toddlers, 3 to 48 months of age, and used to train a sigmoidal-based maturational model. The validity of the approach was then established by testing the model on 129 different VF(M) datasets. Results revealed the approach to have high accuracy, with a mean absolute percent error of 13% in males and 14% in females, and high predictive ability, with correlation coefficients between estimated and true ages of 0.945 in males and 0.94 in females. This work represents a new approach toward mapping brain maturity, and may provide a more faithful staging of brain maturation in infants beyond chronological or gestation-corrected age, allowing earlier identification of atypical regional brain development.

Group B Streptococcus ß-hemolysin/cytolysin breaches maternal-fetal barriers to cause preterm birth and intrauterine fetal demise in vivo.

BACKGROUND: Maternal vaginal colonization with Streptococcus agalactiae (Group B Streptococcus [GBS]) is a precursor to chorioamnionitis, fetal infection, and neonatal sepsis, but the understanding of specific factors in the pathogenesis of ascending infection remains limited. METHODS: We used a new murine model to evaluate the contribution of the pore-forming GBS ß-hemolysin/cytolysin (ßH/C) to vaginal colonization, ascension, and fetal infection. RESULTS: Competition assays demonstrated a marked advantage to ßH/C-expressing GBS during colonization. Intrauterine fetal demise and/or preterm birth were observed in 54% of pregnant mice colonized with wild-type (WT) GBS and 0% of those colonized with the toxin-deficient cylE knockout strain, despite efficient colonization and ascension by both strains. Robust placental inflammation, disruption of maternal-fetal barriers, and fetal infection were more frequent in animals colonized with WT bacteria. Histopathologic examination revealed bacterial tropism for fetal lung and liver. CONCLUSIONS: Preterm birth and fetal demise are likely the direct result of toxin-induced damage and inflammation rather than differences in efficiency of ascension into the upper genital tract. These data demonstrate a distinct contribution of ßH/C to GBS chorioamnionitis and subsequent fetal infection in vivo and showcase a model for this most proximal step in GBS pathogenesis.

Nutritional influences on early white matter development: response to Anderson and Burggren.

Does breastfeeding alter early brain development? In a recent retrospective study, our group examined the cross-sectional relationship between early infant feeding practice and white matter maturation and cognitive development. In groups matched for child and mother age, gestation duration, birth weight, gender distribution, and socio-economic status; we observed that children who were breastfed exclusively for at least 3 months showed, on average, increased white matter myelin development compared to children who either were exclusively formula-fed, or received a mixture of breast milk and formula. In secondary analysis on sub-sets of these children, again matched for important confounding variables, we found improved cognitive test scores of receptive language in the exclusively breast-fed children compared to formula or formula+breast-fed children; and that prolonged breastfeeding was associated with increased motor, language, and visual functioning in exclusively breast-fed children. In response to this work, Anderson and Burggren have questioned our methodology and, by association, our findings. Further, they use their critique as a platform for advancing an alternative interpretation of our findings: that observed results were not associated with prolonged breast-feeding, but rather delayed the introduction of cow's milk. In this response, we address and clarify some of the misconceptions presented by Anderson and Burggren.

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

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

White matter development and early cognition in babies and toddlers.

The normal myelination of neuronal axons is essential to neurodevelopment, allowing fast inter-neuronal communication. The most dynamic period of myelination occurs in the first few years of life, in concert with a dramatic increase in cognitive abilities. How these processes relate, however, is still unclear. Here we aimed to use a data-driven technique to parcellate developing white matter into regions with consistent white matter growth trajectories and investigate how these regions related to cognitive development. In a large sample of 183 children aged 3 months to 4 years, we calculated whole brain myelin volume fraction (VFM ) maps using quantitative multicomponent relaxometry. We used spatial independent component analysis (ICA) to blindly segment these quantitative VFM images into anatomically meaningful parcels with distinct developmental trajectories. We further investigated the relationship of these trajectories with standardized cognitive scores in the same children. The resulting components represented a mix of unilateral and bilateral white matter regions (e.g., cortico-spinal tract, genu and splenium of the corpus callosum, white matter underlying the inferior frontal gyrus) as well as structured noise (misregistration, image artifact). The trajectories of these regions were associated with individual differences in cognitive abilities. Specifically, components in white matter underlying frontal and temporal cortices showed significant relationships to expressive and receptive language abilities. Many of these relationships had a significant interaction with age, with VFM becoming more strongly associated with language skills with age. These data provide evidence for a changing coupling between developing myelin and cognitive development.

Pediatric neuroimaging using magnetic resonance imaging during non-sedated sleep.

BACKGROUND: Etiological studies of many neurological and psychiatric disorders are increasingly turning toward longitudinal investigations of infant brain development in order to discern predisposing structural and/or functional differences prior to the onset of overt clinical symptoms. While MRI provides a noninvasive window into the developing brain, MRI of infants and toddlers is challenging due to the modality's extreme motion sensitivity and children's difficulty in remaining still during image acquisition. OBJECTIVE: Here, we outline a broad research protocol for successful MRI of children under 4 years of age during natural, non-sedated sleep. MATERIALS AND METHODS: All children were imaged during natural, non-sedated sleep. Active and passive measures to reduce acoustic noise were implemented to reduce the likelihood of the children waking up during acquisition. Foam cushions and vacuum immobilizers were used to limit intra-scan motion artifacts. RESULTS: More than 380 MRI datasets have been successfully acquired from 220 children younger than 4 years of age within the past 39 months. Implemented measures permitted children to remain asleep for the duration of the scan and allowed the data to be acquired with an overall 97% success rate. CONCLUSION: The proposed method greatly advances current pediatric imaging techniques and may be readily implemented in other research and clinical settings to facilitate and further improve pediatric neuroimaging.

SMIM1 absence is associated with reduced energy expenditure and excess weight.

BACKGROUND: Obesity rates have nearly tripled in the past 50 years, and by 2030 more than 1 billion individuals worldwide are projected to be obese. This creates a significant economic strain due to the associated non-communicable diseases. The root cause is an energy expenditure imbalance, owing to an interplay of lifestyle, environmental, and genetic factors. Obesity has a polygenic genetic architecture; however, single genetic variants with large effect size are etiological in a minority of cases. These variants allowed the discovery of novel genes and biology relevant to weight regulation and ultimately led to the development of novel specific treatments. METHODS: We used a case-control approach to determine metabolic differences between individuals homozygous for a loss-of-function genetic variant in the small integral membrane protein 1 (SMIM1) and the general population, leveraging data from five cohorts. Metabolic characterization of SMIM1-/- individuals was performed using plasma biochemistry, calorimetric chamber, and DXA scan. FINDINGS: We found that individuals homozygous for a loss-of-function genetic variant in SMIM1 gene, underlying the blood group Vel, display excess body weight, dyslipidemia, altered leptin to adiponectin ratio, increased liver enzymes, and lower thyroid hormone levels. This was accompanied by a reduction in resting energy expenditure. CONCLUSION: This research identified a novel genetic predisposition to being overweight or obese. It highlights the need to investigate the genetic causes of obesity to select the most appropriate treatment given the large cost disparity between them. FUNDING: This work was funded by the National Institute of Health Research, British Heart Foundation, and NHS Blood and Transplant.

A framework for the analysis of phantom data in multicenter diffusion tensor imaging studies.

Diffusion tensor imaging (DTI) is commonly used for studies of the human brain due to its inherent sensitivity to the microstructural architecture of white matter. To increase sampling diversity, it is often desirable to perform multicenter studies. However, it is likely that the variability of acquired data will be greater in multicenter studies than in single-center studies due to the added confound of differences between sites. Therefore, careful characterization of the contributions to variance in a multicenter study is extremely important for meaningful pooling of data from multiple sites. We propose a two-step analysis framework for first identifying outlier datasets, followed by a parametric variance analysis for identification of intersite and intrasite contributions to total variance. This framework is then applied to phantom data from the NIH MRI study of normal brain development (PedsMRI). Our results suggest that initial outlier identification is extremely important for accurate assessment of intersite and intrasite variability, as well as for early identification of problems with data acquisition. We recommend the use of the presented framework at frequent intervals during the data acquisition phase of multicenter DTI studies, which will allow investigators to identify and solve problems as they occur.

Effects of image distortions originating from susceptibility variations and concomitant fields on diffusion MRI tractography results.

In this work we investigate the effects of echo planar imaging (EPI) distortions on diffusion tensor imaging (DTI) based fiber tractography results. We propose a simple experimental framework that would enable assessing the effects of EPI distortions on the accuracy and reproducibility of fiber tractography from a pilot study on a few subjects. We compare trajectories computed from two diffusion datasets collected on each subject that are identical except for the orientation of phase encode direction, either right-left (RL) or anterior-posterior (AP). We define metrics to assess potential discrepancies between RL and AP trajectories in association, commissural, and projection pathways. Results from measurements on a 3 Tesla clinical scanner indicated that the effects of EPI distortions on computed fiber trajectories are statistically significant and large in magnitude, potentially leading to erroneous inferences about brain connectivity. The correction of EPI distortion using an image-based registration approach showed a significant improvement in tract consistency and accuracy. Although obtained in the context of a DTI experiment, our findings are generally applicable to all EPI-based diffusion MRI tractography investigations, including high angular resolution (HARDI) methods. On the basis of our findings, we recommend adding an EPI distortion correction step to the diffusion MRI processing pipeline if the output is to be used for fiber tractography.

Informed RESTORE: A method for robust estimation of diffusion tensor from low redundancy datasets in the presence of physiological noise artifacts.

Physiological noise artifacts, especially those originating from cardiac pulsation and subject motion, are common in clinical Diffusion tensor-MRI acquisitions. Previous works show that signal perturbations produced by artifacts can be severe and neglecting to account for their contribution can result in erroneous diffusion tensor values. The Robust Estimation of Tensors by Outlier Rejection (RESTORE) method has been shown to be an effective strategy for improving tensor estimation on a voxel-by-voxel basis in the presence of artifactual data points in diffusion-weighted images. In this article, we address potential instabilities that may arise when using RESTORE and propose practical constraints to improve its usability. Moreover, we introduce a method, called informed RESTORE designed to remove physiological noise artifacts in datasets acquired with low redundancy (less than 30-40 diffusion-weighted image volumes)--a condition in which the original RESTORE algorithm may converge to an incorrect solution. This new method is based on the notion that physiological noise is more likely to result in signal dropouts than signal increases. Results from both Monte Carlo simulation and clinical diffusion data indicate that informed RESTORE performs very well in removing physiological noise artifacts for low redundancy diffusion-weighted image datasets.

Effects of physiological noise in population analysis of diffusion tensor MRI data.

The goal of this study is to characterize the potential effect of artifacts originating from physiological noise on statistical analysis of diffusion tensor MRI (DTI) data in a population. DTI derived quantities including mean diffusivity (Trace(D)), fractional anisotropy (FA), and principal eigenvector (ε(1)) are computed in the brain of 40 healthy subjects from tensors estimated using two different methods: conventional nonlinear least-squares, and robust fitting (RESTORE). RESTORE identifies artifactual data points as outliers and excludes them on a voxel-by-voxel basis. We found that outlier data points are localized in specific spatial clusters in the population, indicating a consistency in brain regions affected across subjects. In brain parenchyma RESTORE slightly reduces inter-subject variance of FA and Trace(D). The dominant effect of artifacts, however, is bias. Voxel-wise analysis indicates that inclusion of outlier data points results in clusters of under- and over-estimation of FA, while Trace(D) is always over-estimated. Removing outliers affects ε(1) mostly in low anisotropy regions. It was found that brain regions known to be affected by cardiac pulsation - cerebellum and genu of the corpus callosum, as well as regions not previously reported, splenium of the corpus callosum-show significant effects in the population analysis. It is generally assumed that statistical properties of DTI data are homogenous across the brain. This assumption does not appear to be valid based on these results. The use of RESTORE can lead to a more accurate evaluation of a population, and help reduce spurious findings that may occur due to artifacts in DTI data.

The cultural evolution and ecology of institutions.

Human societies are structured by what we refer to as 'institutions', which are socially created and culturally inherited proscriptions on behaviour that define roles and set expectations about social interactions. The study of institutions in several social science fields has provided many important insights that have not been fully appreciated in the evolutionary human sciences. However, such research has often lacked a shared understanding of general processes of change that shape institutional diversity across space and time. We argue that evolutionary theory can provide a useful framework for synthesizing information from different disciplines to address issues such as how and why institutions change over time, how institutional rules co-evolve with other culturally inherited traits, and the role that ecological factors might play in shaping institutional diversity. We argue that we can gain important insights by applying cultural evolutionary thinking to the study of institutions, but that we also need to expand and adapt our approaches to better handle the ways that institutions work, and how they might change over time. In this paper, we illustrate our approach by describing macro-scale empirical comparative analyses that demonstrate how evolutionary theory can be used to generate and test hypotheses about the processes that have shaped some of the major patterns we see in institutional diversity over time and across the world today. We then go on to discuss how we might usefully develop micro-scale models of institutional change by adapting concepts from game theory and agent-based modelling. We end by considering current challenges and areas for future research, and the potential implications for other areas of study and real-world applications. This article is part of the theme issue 'Foundations of cultural evolution'.

Age-related differences in white matter diffusion measures in autism spectrum condition.

BACKGROUND: Autism spectrum condition (ASC) is accompanied by developmental differences in brain anatomy and connectivity. White matter differences in ASC have been widely studied with diffusion imaging but results are heterogeneous and vary across the age range of study participants and varying methodological approaches. To characterize the neurodevelopmental trajectory of white matter maturation, it is necessary to examine a broad age range of individuals on the autism spectrum and typically developing controls, and investigate age × group interactions. METHODS: Here, we employed a spatially unbiased tract-based spatial statistics (TBSS) approach to examine age-related differences in white matter connectivity in a sample of 41 individuals with ASC, and 41 matched controls between 7-17 years of age. RESULTS: We found significant age-related differences between the ASC and control group in widespread brain regions. This included age-related differences in the uncinate fasciculus, corticospinal tract, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, anterior thalamic radiation, superior longitudinal fasciculus and forceps major. Measures of fractional anisotropy (FA) were significantly positively associated with age in both groups. However, this relationship was significantly stronger in the ASC group relative to controls. Measures of radial diffusivity (RD) were significantly negatively associated with age in both groups, but this relationship was significantly stronger in the ASC group relative to controls. LIMITATIONS: The generalisability of our findings is limited by the restriction of the sample to right-handed males with an IQ > 70. Furthermore, a longitudinal design would be required to fully investigate maturational processes across this age group. CONCLUSIONS: Taken together, our findings suggest that autistic males have an altered trajectory of white matter maturation relative to controls. Future longitudinal analyses are required to further characterize the extent and time course of these differences.

Cognitive and environmental interventions to encourage healthy eating: evidence-based recommendations for public health policy.

Policymakers are focused on reducing the public health burden of obesity. The UK average percentage of adults classified as obese is 26%, which is double that of the global average. Over a third of UK adults report using at least one weight management aid. Yet, many people still struggle to change their diet-related behaviour, despite having the awareness, intention and capability to do so. This 'intention-behaviour gap' may be because most existing dietary-choice interventions focus on individual decision-making, ignoring the effects of environmental cues on human behaviour. Behaviour change interventions that 'nudge' people into making healthier choices by modifying the food environment have been shown to be effective. However, this type of intervention is typically challenging for policymakers to implement for economic, ethical and public accessibility reasons. To overcome these concerns, policymakers should consider 'boosting' interventions. Boosting involves enhancing competences that help people make decisions consistent with their goals. Here, we outline cognitive training as a boosting intervention to tackle obesity. We synthesize the evidence for one type of cognitive training (go/no-go training) that may be effective at modifying food-related decisions and reducing body weight. We offer evidence-based recommendations for an obesity-focused Public Health Wales behaviour change programme.

Supporting evidence-informed policy and scrutiny: A consultation of UK research professionals.

Access to reliable and timely information ensures that decision-makers can operate effectively. The motivations and challenges of parliamentarians and policy-makers in accessing evidence have been well documented in the policy literature. However, there has been little focus on research-providers. Understanding both the demand- and the supply-side of research engagement is imperative to enhancing impactful interactions. Here, we examine the broader experiences, motivations and challenges of UK-based research professionals engaging with research-users relevant to policy-making and scrutiny in the UK using a nationwide online questionnaire. The context of the survey partly involved contributing to the UK Evidence Information Service (EIS), a proposed rapid match-making service to facilitate interaction between parliamentary arenas that use evidence and research-providers. Our findings reveal, at least for this sub-sample who responded, that there are gender-related differences in policy-related experience, motivations, incentives and challenges for research professionals to contribute to evidence-informed decision-making through initiatives such as the EIS. Male and female participants were equally likely to have policy experience; however, males reported both significantly broader engagement with the research-users included in the survey and significantly higher levels of engagement with each research-user. Reported incentives for engagement included understanding what the evidence will be used for, guidance on style and content of contribution, and acknowledgement of contributions by the policymaker or elected official. Female participants were significantly more likely to select the guidance-related options. The main reported barrier was workload. We discuss how academia-policy engagement initiatives can best address these issues in ways that enhance the integration of research evidence with policy and practice across the UK.

Brain diffusion abnormalities in children with fetal alcohol spectrum disorder.

BACKGROUND: Children with fetal alcohol spectrum disorder (FASD) have a variety of cognitive, behavioral, and neurological impairments, including structural brain damage. Despite the importance of white matter connections for proper brain function, little is known about how these connections, and the deep gray matter structures that act as relay stations, are affected in children with FASD. The purpose of this study was to use diffusion tensor imaging, an advanced magnetic resonance imaging technique, to examine microstructural differences of white and deep gray matter in children with FASD. METHODS: Subjects were 24 children aged 5-13 years previously diagnosed with FASD and 95 healthy children over the same age range. Diffusion tractography was used to delineate 10 major white matter tracts in each individual, and region-of-interest analysis was used to assess 4 deep gray matter structures. Fractional anisotropy, an indicator of white matter integrity, and mean diffusivity, a measure of the average water diffusion, were assessed in all 14 brain structures. RESULTS: Diffusion tensor imaging revealed significant differences of diffusion parameters in several areas of the brain, including the genu and splenium of the corpus callosum, cingulum, corticospinal tracts, inferior fronto-occipital fasciculus, inferior and superior longitudinal fasciculi, globus pallidus, putamen, and thalamus. Reduced white and gray matter volumes, as well as total brain volume, were observed in the FASD group. CONCLUSIONS: These results demonstrate diffusion abnormalities in FASD beyond the corpus callosum and suggest that several specific white matter regions, particularly commissural and temporal connections, and deep gray matter areas of the brain are sensitive to prenatal alcohol exposure.