Search

BACKGROUND: Parenting behavior is thought to affect child brain development, with implications for mental health. However, longitudinal studies that use whole-brain approaches are lacking. In this study, we investigated associations between parenting behavior, age-related changes in whole-brain functional connectivity, and psychopathology symptoms in children and adolescents. METHODS: Two hundred forty (126 female) children underwent resting-state functional magnetic resonance imaging at up to two time points, providing a total of 398 scans covering the age range 8 to 13 years. Parenting behavior was self-reported at baseline. Parenting factors (positive parenting, inattentive parenting, and harsh and inconsistent discipline) were identified based on a factor analysis of self-report parenting questionnaires. Longitudinal measures of child internalizing and externalizing symptoms were collected. Network-based R-statistics was used to identify associations between parenting and age-related changes in functional connectivity. RESULTS: Higher maternal inattentive behavior was associated with lower decreases in connectivity over time, particularly between regions of the ventral attention and default mode networks and frontoparietal and default mode networks. However, this association was not significant after strict correction for multiple comparisons. CONCLUSIONS: While results should be considered preliminary, they suggest that inattentive parenting may be associated with a reduction in the normative pattern of increased network specialization that occurs with age. This may reflect a delayed development of functional connectivity.

The negative impact of adverse experiences in childhood on neurodevelopment is well documented. Less attention however has been given to the impact of variations in "normative" parenting behaviors. The influence of these parenting behaviors is likely to be marked during periods of rapid brain reorganization, such as late childhood. The aim of the current study was to investigate associations between normative parenting behaviors and the development of structural brain networks across late childhood. Data were collected from a longitudinal sample of 114 mother-child dyads (54% female children, M age 8.41 years, SD = 0.32 years), recruited from low socioeconomic areas of Melbourne, Australia. At the first assessment parenting behaviors were coded from two lab-based interaction tasks and structural magnetic resonance imaging (MRI) scans of the children were performed. At the second assessment, approximately 18 months later (M age 9.97 years, SD = 0.37 years) MRI scans were repeated. Cortical thickness (CT) was extracted from T1-weighted images using FreeSurfer. Structural covariance (SC) networks were constructed from partial correlations of CT estimates between brain regions and estimates of network efficiency and modularity were obtained for each time point. The change in these network measures, from Time 1 to Time 2, was also calculated. At Time 2, less positive maternal affective behavior was associated with higher modularity (more segregated networks), while negative maternal affective behavior was not related. No support was found for an association between local or global efficacy and maternal affective behaviors at Time 2. Similarly, no support was demonstrated for associations between maternal affective behaviors and change in network efficiency and modularity, from Time 1 to Time 2. These results indicate that normative variations in parenting may influence the development of structural brain networks in late childhood and extend current knowledge about envir

Typical brain development follows a protracted trajectory throughout childhood and adolescence. Deviations from typical growth trajectories have been implicated in neurodevelopmental and psychiatric disorders. Recently, the use of machine learning algorithms to model age as a function of structural or functional brain properties has been used to examine advanced or delayed brain maturation in healthy and clinical populations. Termed 'brain age', this approach often relies on complex, nonlinear models that can be difficult to interpret. In this study, we use model explanation methods to examine the cortical features that contribute to brain age modelling on an individual basis. In a large cohort of n = 768 typically-developing children (aged 3-21 years), we build models of brain development using three different machine learning approaches. We employ SHAP, a model-agnostic technique to identify sample-specific feature importance, to identify regional cortical metrics that explain errors in brain age prediction. We find that, on average, brain age prediction and the cortical features that explain model predictions are consistent across model types and reflect previously reported patterns of regions brain development. However, while several regions are found to contribute to brain age prediction error, we find little spatial correspondence between individual estimates of feature importance, even when matched for age, sex and brain age prediction error. We also find no association between brain age error and cognitive performance in this typically-developing sample. Overall, this study shows that, while brain age estimates based on cortical development are relatively robust and consistent across model types and preprocessing strategies, significant between-subject variation exists in the features that explain erroneous brain age predictions on an individual level.

IMPORTANCE: Neurofibromatosis type 1 (NF1) affects hearing through disruption of central auditory processing. The mechanisms, functional severity, and management implications are unclear. OBJECTIVE: To investigate auditory neural dysfunction and its perceptual consequences in individuals with NF1. DESIGN, SETTING, AND PARTICIPANTS: This case-control study included children and adults with NF1 and control participants matched on age, sex, and hearing level. Patients were recruited through specialist neurofibromatosis and neurogenetic outpatient clinics between April and September 2019. An evaluation of auditory neural activity, monaural/binaural processing, and functional hearing was conducted. Diffusion-weighted magnetic resonance imaging (MRI) data were collected from a subset of participants (10 children with NF1 and 10 matched control participants) and evaluated using a fixel-based analysis of apparent fiber density. MAIN OUTCOMES AND MEASURES: Type and severity of auditory dysfunction evaluated via laboratory testing and questionnaire data. RESULTS: A total of 44 participants (18 [41%] female individuals) with NF1 with a mean (SD) age of 16.9 (10.7) years and 44 control participants (18 [41%] female individuals) with a mean (SD) age of 17.2 (10.2) years were included in the study. Overall, 11 participants (25%) with NF1 presented with evidence of auditory neural dysfunction, including absent, delayed, or low amplitude electrophysiological responses from the auditory nerve and/or brainstem, compared with 1 participant (2%) in the control group (odds ratio [OR], 13.03; 95% CI, 1.59-106.95). Furthermore, 14 participants (32%) with NF1 showed clinically abnormal speech perception in background noise compared with 1 participant (2%) in the control group (OR, 20.07; 95% CI, 2.50-160.89). Analysis of diffusion-weighted MRI data of participants with NF1 showed significantly lower apparent fiber density within the ascending auditory brainstem pathways. The regions identi

Children born extremely preterm (EP, <28 weeks' gestation) or extremely low birth weight (ELBW, <1,000 g) are a vulnerable population at high risk of working memory impairments. We aimed to examine changes in the brain structural connectivity networks thought to underlie working memory performance, after completion of a working memory training program (Cogmed) compared with a placebo program in EP/ELBW children. This was a double-blind, placebo-controlled randomized trial (the Improving Memory in a Preterm Randomised Intervention Trial). Children born EP/ELBW received either the Cogmed or placebo program at 7 years of age (n = 91). A subset of children had magnetic resonance imaging of the brain immediately pre- and 2 weeks post-training (Cogmed n = 28; placebo n = 27). T1 -weighted and diffusion-weighted images were used to perform graph theoretical analysis of structural connectivity networks. Changes from pre-training to post-training in structural connectivity metrics were generally similar between randomized groups. There was little evidence that changes in structural connectivity metrics were related to changes in working memory performance from pre- to post-training. Overall, our results provide little evidence that the Cogmed working memory training program has training-specific effects on structural connectivity networks in EP/ELBW children.

The brain undergoes extensive structural changes during adolescence, concurrent to puberty-related physical and hormonal changes. While animal research suggests these biological processes are related to one another, our knowledge of brain development in humans is largely based on age-related processes. Thus, the current study characterized puberty-related changes in human brain structure, by combining data from two longitudinal neuroimaging cohorts. Beyond normative changes in cortical thickness, we examined whether individual differences in the rate of pubertal maturation (or "pubertal tempo") was associated with variations in cortical trajectories. Participants (N = 192; scans = 366) completed up to three waves of MRI assessments between 8.5 and 14.5 years of age, as well as questionnaire assessments of pubertal stage at each wave. Generalized additive mixture models were used to characterize trajectories of cortical development. Results revealed widespread linear puberty-related changes across much of the cortex. Many of these changes, particularly within the frontal and parietal cortices, were independent of age-related development. Males exhibiting faster pubertal tempo demonstrated greater thinning in the precuneus and frontal cortices than same-aged and -sex peers. Findings suggest that the unique influence of puberty on cortical development may be more extensive than previously identified, and also emphasize important individual differences in the coupling of these developmental processes.

A substantial body of knowledge suggests that exposure to adverse family environments - including violence and neglect - influences many aspects of brain development. Relatively less attention has been directed toward the influence of "normative" differences in parenting behaviors. Given the rapid brain reorganization during late childhood, parenting behaviors are particularly likely to impact the structure of the brain during this time. This study investigated associations between maternal parenting behaviors and the organization of structural brain networks in late childhood, as measured by structural covariance. One hundred and forty-five typically developing 8-year-olds and their mothers completed questionnaire measures and two observed interaction tasks; magnetic resonance imaging (MRI) scans were obtained from the children. Measures of maternal negative, positive, and communicative behavior were derived from the interaction tasks. Structural covariance networks based on partial correlations between cortical thickness estimates were constructed and estimates of modularity were obtained using graph theoretical analysis. High levels of negative maternal behavior were associated with low modularity. Minimal support was found for an association between positive maternal behaviors and modularity and between maternal communicative behaviors and modularity. Our findings suggest that variation in negative maternal behavior is associated with the structural organization of brain networks in children.

BACKGROUND: Research on monogenic forms of autism spectrum disorder (autism) can inform our understanding of genetic contributions to the autism phenotype; yet, there is much to be learned about the pathways from gene to brain structure to behavior. This systematic review summarizes and evaluates research on brain magnetic resonance imaging (MRI) findings in monogenic conditions that have strong association with autism. This will improve understanding of the impact of genetic variability on brain structure and related behavioral traits in autism. METHODS: The search strategy for this systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Risk of bias (ROB) assessment was completed on included studies using the Newcastle-Ottawa Scales. RESULTS: Of 4,287 studies screened, 69 were included pertaining to 13 of the top 20 genes with the strongest association with autism. The greatest number of studies related to individuals with PTEN variants and autism. Brain MRI abnormalities were reported for 12 of the 13 genes studied, and in 51.7% of participants across all 13 genes, including 100% of participants with ARID1B variants. Specific MRI findings were highly variable, with no clear patterns emerging within or between the 13 genes, although white matter abnormalities were the most common. Few studies reported specific details about methods for acquisition and processing of brain MRI, and descriptors for brain abnormalities were variable. ROB assessment indicated high ROB for all studies, largely due to small sample sizes and lack of comparison groups. CONCLUSIONS: Brain abnormalities are common in this population of individuals, in particular, children; however, a range of different brain abnormalities were reported within and between genes. Directions for future neuroimaging research in monogenic autism are suggested.

Structural covariance conceptualizes how morphologic properties of brain regions are related to one another (across individuals). It can provide unique information to cortical structure (e.g., thickness) about the development of functionally meaningful networks. The current study investigated how structural covariance networks develop during the transition from childhood to adolescence, a period characterized by marked structural re-organization. Participants (N = 192; scans = 366) completed MRI assessments between 8.5 and 14.5 years of age. A sliding window approach was used to create "age-bins", and structural covariance networks (based on cortical thickness) were created for each bin. Next, generalized additive models were used to characterize trajectories of age-related changes in network properties. Results revealed nonlinear trajectories with "peaks" in mean correlation and global density that are suggestive of a period of convergence in anatomical properties across the cortex during early adolescence, prior to regional specialization. "Hub" regions in sensorimotor cortices were present by late childhood, but the extent and strength of association cortices as "hubs" increased into mid-adolescence. Moreover, these regional changes were found to be related to rates of thinning across the cortex. In the context of neurocognitive networks, the frontoparietal, default mode, and attention systems exhibited age-related increases in within-network and between-network covariance. These regional and modular developmental patterns are consistent with continued refinement of socioemotional and other complex executive functions that are supported by higher-order cognitive networks during early adolescence.

Serial regional brain growth from the newborn period to adolescence has not been described. Here, we measured regional brain growth in 216 very preterm (VP) and 45 full-term (FT) children. Brain MRI was performed at term-equivalent age, 7 and 13 years in 82 regions. Brain volumes increased between term-equivalent and 7 years, with faster growth in the FT than VP group. Perinatal brain abnormality was associated with less increase in brain volume between term-equivalent and 7 years in the VP group. Between 7 and 13 years, volumes were relatively stable, with some subcortical and cortical regions increasing while others reduced. Notably, VP infants continued to lag, with overall brain size generally less than that of FT peers at 13 years. Parieto-frontal growth, mainly between 7 and 13 years in FT children, was associated with higher intelligence at 13 years. This study improves understanding of typical and atypical regional brain growth.

The pubertal period involves dynamic white matter development. This period also corresponds with rapid gains in higher cognitive functions including attention, as well as increased risk of developing mental health difficulties. This longitudinal study comprised children aged 9-13 years (n = 130). Diffusion magnetic resonance imaging (dMRI) data were acquired (b = 2800s/mm2, 60 directions) at two time-points. We derived measures of fibre density and morphology using the fixel-based analysis framework and performed a tract-based mixed-effects modelling analysis to understand patterns of white matter development with respect to age, sex, pubertal stage, and the change in pubertal stage. We observed significant increases in apparent fibre density across a large number of white matter pathways, including major association and commissural pathways. We observed a linear relationship between pubertal stage and fibre density and morphology in the right superior longitudinal fasciculus, and fibre morphology in the right inferior longitudinal fasciculus. Finally, we report a significant interaction between the change in pubertal stage and age in the development of fibre density, for left-lateralised association tracts. Overall, white matter development across ages 9-13 years involves the expansion of major white matter fibre pathways, with key association pathways linked with pubertal stage.

This study in children born extremely preterm (EP; <28 weeks' gestational age) or extremely low birth weight (ELBW; <1,000 g) investigated whether adaptive working memory training using Cogmed® is associated with structural and/or functional brain changes compared with a placebo program. Ninety-one EP/ELBW children were recruited at a mean (standard deviation) age of 7.8 (0.4) years. Children were randomly allocated to Cogmed or placebo (45-min sessions, 5 days a week over 5-7 weeks). A subset had usable magnetic resonance imaging (MRI) data pretraining and 2 weeks posttraining (structural, n = 48; diffusion, n = 43; task-based functional, n = 18). Statistical analyses examined whether cortical morphometry, white matter microstructure and blood oxygenation level-dependent (BOLD) signal during an n-back working memory task changed from pretraining to posttraining in the Cogmed and placebo groups separately. Interaction analyses between time point and group were then performed. There was a significant increase in neurite density in several white matter regions from pretraining to posttraining in both the Cogmed and placebo groups. BOLD signal in the posterior cingulate and precuneus cortices during the n-back task increased from pretraining to posttraining in the Cogmed but not placebo group. Evidence for group-by-time interactions for the MRI measures was weak, suggesting that brain changes generally did not differ between Cogmed and placebo groups. Overall, while some structural and functional MRI changes between the pretraining and posttraining period in EP/ELBW children were observed, there was little evidence of training-induced neuroplasticity, with changes generally identified in both groups. Trial registration Australian New Zealand Clinical Trials Registry, anzctr.org.au; ACTRN12612000124831.

Magnetic Resonance Imaging (MRI) in paediatric cohorts is often complicated by reluctance to enter the scanner and head motion-related imaging artefacts. The process is particularly challenging for children with neurodevelopmental disorders where coping with novel task demands in an unfamiliar setting may be more difficult due to symptom-related deficits or distress. These issues often give rise to excessive head motion that can significantly reduce the quality of images acquired, or render data unusable. Here we report an individualised MRI training procedure that enables children with Autism Spectrum Disorders (ASD) to better tolerate the MRI scanner environment based on a child-focused approach and individualised familiarisation strategies, including a pre-visit interview, familiarisation package, and personalised rewards. A medical imaging mobile application was utilised to familiarise participants to multi-sensory aspects of the neuroimaging experience through a variety of themed mini-games and activities. The MRI training procedure was implemented for monozygotic twins (n = 12; 6 twin pairs; age range 7.1-12.9 years) concordant or discordant for ASD. MRI image quality indices were better or comparable to images acquired from a large independent multi-centre ASD cohort. Present findings are promising and suggest that child-focused strategies could improve the quality of paediatric neuroimaging in clinical populations.

Brain atlases providing standardised identification of neonatal brain regions are key in investigating neurological disorders of early childhood. Our previously developed Melbourne Children's Regional Infant Brain (M-CRIB) and M-CRIB 2.0 neonatal brain atlases provide standardised parcellation of 100 brain regions including cortical, subcortical, and cerebellar regions. The aim of this study was to extend M-CRIB atlas coverage to include 54 white matter (WM) regions. Participants were 10 healthy term-born neonates that were used to create the initial M-CRIB atlas. WM regions were manually segmented based on T2 images and co-registered diffusion tensor imaging-based, direction-encoded colour maps. Our labelled regions imitate the Johns Hopkins University neonatal atlas, with minor anatomical modifications. All segmentations were reviewed and approved by a paediatric radiologist and a neurosurgery research fellow for anatomical accuracy. The resulting neonatal WM atlas comprises 54 WM regions: 24 paired regions, and six unpaired regions comprising five corpus callosum subdivisions, and one pontine crossing tract. Detailed protocols for manual WM parcellations are provided, and the M-CRIB-WM atlas is presented together with the existing M-CRIB cortical, subcortical, and cerebellar parcellations in 10 individual neonatal MRI data sets. The novel M-CRIB-WM atlas, along with the M-CRIB cortical and subcortical atlases, provide neonatal whole brain MRI coverage in the first multi-subject manually parcellated neonatal atlas compatible with atlases commonly used at older time points. The M-CRIB-WM atlas is publicly available, providing a valuable tool that will help facilitate neuroimaging research into neonatal brain development in both healthy and diseased states.

Longitudinal studies measuring changes in cortical morphology over time are best facilitated by parcellation schemes compatible across all life stages. The Melbourne Children's Regional Infant Brain (M-CRIB) and M-CRIB 2.0 atlases provide voxel-based parcellations of the cerebral cortex compatible with the Desikan-Killiany (DK) and the Desikan-Killiany-Tourville (DKT) cortical labelling schemes. This study introduces surface-based versions of the M-CRIB and M-CRIB 2.0 atlases, termed M-CRIB-S(DK) and M-CRIB-S(DKT), with a pipeline for automated parcellation utilizing FreeSurfer and developing Human Connectome Project (dHCP) tools. Using T2-weighted magnetic resonance images of healthy neonates (n = 58), we created average spherical templates of cortical curvature and sulcal depth. Manually labelled regions in a subset (n = 10) were encoded into the spherical template space to construct M-CRIB-S(DK) and M-CRIB-S(DKT) atlases. Labelling accuracy was assessed using Dice overlap and boundary discrepancy measures with leave-one-out cross-validation. Cross-validated labelling accuracy was high for both atlases (average regional Dice = 0.79-0.83). Worst-case boundary discrepancy instances ranged from 9.96-10.22 mm, which appeared to be driven by variability in anatomy for some cases. The M-CRIB-S atlas data and automatic pipeline allow extraction of neonatal cortical surfaces labelled according to the DK or DKT parcellation schemes.

AIM: To examine: (1) relationships between brain structure, and concurrently assessed neurological and behavioural functioning, in infants born preterm at term-equivalent age (TEA; approximately 38-44wks); and (2) whether brain structure-function relationships differ between infants born very (24-29wks) and moderate-late (32-36wks) preterm. METHOD: A total of 257 infants (91 very preterm, 166 moderate-late preterm; 120 males, 137 females) had structural magnetic resonance imaging (MRI) and neurological and behavioural assessments (Prechtl's general movements assessment, Neonatal Intensive Care Unit Network Neurobehavioral Scale [NNNS] and Hammersmith Neonatal Neurological Examination [HNNE]). Two hundred and sixty-three infants (90 very preterm, 173 moderate-late preterm; 131 males, 132 females) had diffusion MRI and assessments. Associations were investigated between assessment scores and global brain volumes using linear regressions, regional brain volumes using Voxel-Based Morphometry, and white matter microstructure using Tract-Based Spatial Statistics. RESULTS: Suboptimal scores on some assessments were associated with lower fractional anisotropy and/or higher axial, radial, and mean diffusivities in some tracts: NNNS attention and reflexes, and HNNE total score and tone, were associated with the corpus callosum and optic radiation; NNNS quality of movement with the corona radiata; HNNE abnormal signs with several major tracts. Brain structure-function associations generally did not differ between the very and moderate-late preterm groups. INTERPRETATION: White matter microstructural alterations may be associated with suboptimal neurological and behavioural performance in some domains at TEA in infants born preterm. Brain structure-function relationships are similar for infants born very preterm and moderate-late preterm. WHAT THIS PAPER ADDS: Brain volume is not related to neurological/behavioural function in infants born preterm at term. White matter microstr

BACKGROUND: Risk of morbidity differs between very preterm (VP; <32 weeks' gestational age (GA)), moderate preterm (MP; 32-33 weeks' GA), late preterm (LP; 34-36 weeks' GA), and full-term (FT; ≥37 weeks' GA) infants. However, brain structure at term-equivalent age (TEA; 38-44 weeks) remains to be characterised in all clinically important GA groups. We aimed to compare global and regional brain volumes, and regional white matter microstructure, between VP, MP, LP and FT groups at TEA, in order to establish the magnitude and anatomical locations of between-group differences. METHODS: Structural images from 328 infants (91 VP, 63 MP, 104 LP and 70 FT) were segmented into white matter, cortical grey matter, cerebrospinal fluid (CSF), subcortical grey matter, brainstem and cerebellum. Global tissue volumes were analysed, and additionally, cortical grey matter and white matter volumes were analysed at the regional level using voxel-based morphometry. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) images from 361 infants (92 VP, 69 MP, 120 LP and 80 FT) were analysed using Tract-Based Spatial Statistics. Statistical analyses involved examining the overall effect of GA group on global volumes (using linear regressions) and regional volumes and microstructure (using non-parametric permutation testing), as well performing post-hoc comparisons between the GA sub-groups. RESULTS: On global analysis, cerebrospinal fluid (CSF) volume was larger in all preterm sub-groups compared with the FT group. On regional analysis, volume was smaller in parts of the temporal cortical grey matter, and parts of the temporal white matter and corpus callosum, in all preterm sub-groups compared with the FT group. FA was lower, and RD and MD were higher in voxels located in much of the white matter in all preterm sub-groups compared with the FT group. The anatomical locations of group differences were similar for each preterm vs. FT comparison

The neurobiology of heterogeneous neurodevelopmental disorders such as autism spectrum disorders (ASD) are still unclear. Despite extensive efforts, most findings are difficult to reproduce due to high levels of individual variance in phenotypic expression. To quantify individual differences in brain morphometry in ASD, we implemented a novel subject-level, distance-based method on subject-specific attributes. In a large multi-cohort sample, each subject with ASD (n = 100; n = 84 males; mean age: 11.43 years; mean IQ: 110.58) was strictly matched to a control participant (n = 100; n = 84 males; mean age: 11.43 years; mean IQ: 110.70). Intrapair Euclidean distance of MRI brain morphometry and symptom severity measures (Social Responsiveness Scale) were entered into a regularised machine learning pipeline for feature selection, with rigorous out-of-sample validation and permutation testing. Subject-specific structural morphometry features significantly predicted individual variation in ASD symptom severity (19 cortical thickness features, p = 0.01, n = 5000 permutations; 10 surface area features, p = 0.006, n = 5000 permutations). Findings remained robust across subjects and were replicated in validation samples. Identified cortical regions implicate key hubs of the salience and default mode networks as neuroanatomical features of social impairment in ASD. Present results highlight the importance of subject-level markers in ASD, and offer an important step forward in understanding the neurobiology of heterogeneous disorders.

Our recently published M-CRIB atlas comprises 100 neonatal brain regions including 68 compatible with the widely-used Desikan-Killiany adult cortical atlas. A successor to the Desikan-Killiany atlas is the Desikan-Killiany-Tourville atlas, in which some regions with unclear boundaries were removed, and many existing boundaries were revised to conform to clearer landmarks in sulcal fundi. Our first aim here was to modify cortical M-CRIB regions to comply with the Desikan-Killiany-Tourville protocol, in order to offer: (a) compatibility with this adult cortical atlas, (b) greater labeling accuracy due to clearer landmarks, and (c) optimisation of cortical regions for integration with surface-based infant parcellation pipelines. Secondly, we aimed to update subcortical regions in order to offer greater compatibility with subcortical segmentations produced in FreeSurfer. Data utilized were the T2-weighted MRI scans in our M-CRIB atlas, for 10 healthy neonates (post-menstrual age at MRI 40-43 weeks, four female), and corresponding parcellated images. Edits were performed on the parcellated images in volume space using ITK-SNAP. Cortical updates included deletion of frontal and temporal poles and 'Banks STS,' and modification of boundaries of many other regions. Changes to subcortical regions included the addition of 'ventral diencephalon,' and deletion of 'subcortical matter' labels. A detailed updated parcellation protocol was produced. The resulting whole-brain M-CRIB 2.0 atlas comprises 94 regions altogether. This atlas provides comparability with adult Desikan-Killiany-Tourville-labeled cortical data and FreeSurfer-labeed subcortical data, and is more readily adaptable for incorporation into surface-based neonatal parcellation pipelines. As such, it offers the ability to help facilitate a broad range of investigations into brain structure and function both at the neonatal time point and developmentally across the lifespan.

Levels of the adrenal hormones dehydroepiandrosterone (DHEA), its sulfate (DHEAS), and testosterone, have all been linked to behavior and mental health during adrenarche, and preclinical studies suggest that these hormones influence brain development. However, little is known about how variation in these hormones is associated with white matter structure during this period of life. The current study aimed to examine associations between DHEA, DHEAS, and testosterone, and white matter microstructure during adrenarche. To avoid the confounding effect of age on hormone levels, we tested these associations in 87 children within a narrow age range (mean age 9.56 years, SD=0.34) but varying in hormone levels. All children provided saliva samples directly after waking and completed a diffusion-weighted MRI scan. Higher levels of DHEA were associated with higher mean diffusivity (MD) in a widespread cluster of white matter tracts, which was partially explained by higher radial diffusivity (RD) and partially by higher axial diffusivity (AD). In addition, there was an interaction between DHEA and testosterone, with higher levels of testosterone being associated with higher fractional anisotropy (FA) and lower MD and RD when DHEA levels were relatively high, but with lower FA and higher MD and RD when DHEA levels were low. These findings suggest that relatively early exposure to DHEA, as well as an imbalance between the adrenal hormones, may be associated with alterations in white matter microstructure. These findings highlight the potential relevance of adrenarcheal hormones for structural brain development.

The regional distribution of white matter (WM) abnormalities in schizophrenia remains poorly understood, and reported disease effects on the brain vary widely between studies. In an effort to identify commonalities across studies, we perform what we believe is the first ever large-scale coordinated study of WM microstructural differences in schizophrenia. Our analysis consisted of 2359 healthy controls and 1963 schizophrenia patients from 29 independent international studies; we harmonized the processing and statistical analyses of diffusion tensor imaging (DTI) data across sites and meta-analyzed effects across studies. Significant reductions in fractional anisotropy (FA) in schizophrenia patients were widespread, and detected in 20 of 25 regions of interest within a WM skeleton representing all major WM fasciculi. Effect sizes varied by region, peaking at (d=0.42) for the entire WM skeleton, driven more by peripheral areas as opposed to the core WM where regions of interest were defined. The anterior corona radiata (d=0.40) and corpus callosum (d=0.39), specifically its body (d=0.39) and genu (d=0.37), showed greatest effects. Significant decreases, to lesser degrees, were observed in almost all regions analyzed. Larger effect sizes were observed for FA than diffusivity measures; significantly higher mean and radial diffusivity was observed for schizophrenia patients compared with controls. No significant effects of age at onset of schizophrenia or medication dosage were detected. As the largest coordinated analysis of WM differences in a psychiatric disorder to date, the present study provides a robust profile of widespread WM abnormalities in schizophrenia patients worldwide. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.

OBJECTIVE: The transition from childhood to adolescence is a vulnerable period for the development of anxiety symptoms. There is some evidence that hormonal changes occurring during adrenarche, an early pubertal phase, might play a role in this increased vulnerability. Little is known about underlying brain mechanisms. Given the role of the amygdala-based fear circuit in anxiety, the current study aimed to investigate whether children's adrenarcheal hormone levels were associated with functional connectivity of the amygdala while processing fearful facial expressions, and how this in turn related to anxiety symptoms. METHOD: Participants were 83 children (M age 9.53 years) who completed two morning saliva collections to measure levels of dehydroepiandrosterone (DHEA), its sulphate (DHEAS), and testosterone. They also completed the Spence Children's Anxiety Scale (SCAS), and viewed fearful and calm facial expressions while undergoing a functional MRI scan. Psychophysiological interaction (PPI) analyses were performed to examine amygdala connectivity and significant clusters were fed into a bootstrapping mediation model. RESULTS: In boys, mediation analyses showed an indirect positive effect of testosterone on anxiety symptoms, which was mediated by amygdala-secondary visual cortex connectivity as well as amygdala-anterior cingulate connectivity. In girls, DHEAS showed a negative indirect association with anxiety symptoms mediated by amygdala connectivity to the fusiform face area and insula. CONCLUSION: The results indicate unique roles for adrenarcheal hormones in anxiety and suggest that amygdala connectivity may represent an important neural mechanism in these associations. Importantly, results reveal prominent sex differences in the biological mechanisms associated with anxiety in children undergoing adrenarche.

Executive functions (EFs), such as inhibition and cognitive flexibility, are essential for everyday functioning, including regulation of socially appropriate emotional responses. These skills develop during childhood and continue maturing into early adulthood. The current study aimed to investigate the very long-term impact of childhood traumatic brain injury (TBI) on inhibition and cognitive flexibility, and to examine whether global white matter is associated with these abilities. Twenty-eight young adult survivors of childhood TBI (mean age at 16-year follow-up = 21.67 years, SD = 2.70) and 16 typically developing controls (TDCs), group-matched for age, sex, and socioeconomic status, completed tests of inhibition and cognitive flexibility and underwent structural MRI. Survivors of childhood TBI did not significantly differ from TDCs on EF or white matter volume. However, the relationship between EF and white matter volume differed between survivors of TBI and TDCs. Survivors of TBI did not mimic the brain behavior relationship that characterized EF in TDCs. The inverse brain behavior relationship, exhibited by childhood TBI survivors, suggests disruptions in the whole brain underpinning EF following childhood TBI.

Variations in symptom trajectories within a population may represent distinct groups with different etiologies and outcomes. This study aimed to identify subgroups of depression symptom trajectories in a sample of adolescents, and to describe psychosocial attributes of the different groups. In a longitudinal study, 243 adolescents (121 males and 122 females), were assessed using a battery of measures of temperament, psychopathology, and psychological and behavioral functioning. Four phases of data collection over 7 years spanned average ages of the participants from 12 to 18 years old. Depressive symptoms from each phase were used to model latent class growth trajectories. A 4-group solution was selected as the best-fitting model: (1) ongoing stable low levels of depression; (2) very high depressive symptoms initially, but a steep decrease in symptoms over time; (3) moderately high depressive symptoms initially, but symptoms decreased over time; and (4) initially low levels of symptoms that increased over time. Trajectory group membership was associated with a range of psychosocial variables including temperament, childhood maltreatment, and young adult quality of life. Characterising these subgroups allows for a better understanding of how the interaction of risk factors increases the likelihood of depression and other poor outcomes, and highlights the importance of early interventions to prevent and treat adolescent depression.

BACKGROUND: Extant research has demonstrated that parenting behaviour can be a significant contributor to the development of brain structure and mental health during adolescence. Nonetheless, there is limited research examining these relationships during late childhood, and particularly in the critical period of brain development occurring between 8 and 10 years of age. The effects of the family environment on the brain during late childhood may have significant implications for later functioning, and particularly mental health. The Families and Childhood Transitions Study (FACTS) is a multidisciplinary longitudinal cohort study of brain development and mental health, with two waves of data collection currently funded, occurring 18-months apart, when child participants are aged approximately 8- and 10-years old. METHODS/DESIGN: Participants are 163 children (M age [SD] = 8.44 [0.34] years, 76 males) and their mothers (M age [SD] = 40.34 [5.43] years). Of the 163 families who consented to participate, 156 completed a video-recorded and observer-coded dyadic interaction task and 153 completed a child magnetic resonance imaging brain scan at baseline. Families were recruited from lower socioeconomic status (SES) areas to maximise rates of social disadvantage and variation in parenting behaviours. All experimental measures and tasks completed at baseline are repeated at an 18-month follow-up, excluding the observer coded family interaction tasks. The baseline assessment was completed in October 2015, and the 18-month follow up will be completed May 2017. DISCUSSION: This study, by examining the neurobiological and mental health consequences of variations in parenting, has the potential to significantly advance our understanding of child development and risk processes. Recruitment of lower SES families will also allow assessment of resilience factors given the poorer outcomes often associated with this population.

Brain development is a dynamic process with tissue-specific alterations that reflect complex and ongoing biological processes taking place during childhood and adolescence. Accurate identification and modelling of these anatomical processes in vivo with MRI may provide clinically useful imaging markers of individual variability in development. In this study, we use manifold learning to build a model of age- and sex-related anatomical variation using multiple magnetic resonance imaging metrics. Using publicly available data from a large paediatric cohort (n = 768), we apply a multi-metric machine learning approach combining measures of tissue volume, cortical area and cortical thickness into a low-dimensional data representation. We find that neuroanatomical variation due to age and sex can be captured by two orthogonal patterns of brain development and we use this model to simultaneously predict age with a mean error of 1.5-1.6 years and sex with an accuracy of 81%. We validate this model in an independent developmental cohort. We present a framework for modelling anatomical development during childhood using manifold embedding. This model accurately predicts age and sex based on image-derived markers of cerebral morphology and generalises well to independent populations.

Measuring the distribution of brain tissue types (tissue classification) in neonates is necessary for studying typical and atypical brain development, such as that associated with preterm birth, and may provide biomarkers for neurodevelopmental outcomes. Compared with magnetic resonance images of adults, neonatal images present specific challenges that require the development of specialized, population-specific methods. This paper introduces MANTiS (Morphologically Adaptive Neonatal Tissue Segmentation), which extends the unified segmentation approach to tissue classification implemented in Statistical Parametric Mapping (SPM) software to neonates. MANTiS utilizes a combination of unified segmentation, template adaptation via morphological segmentation tools and topological filtering, to segment the neonatal brain into eight tissue classes: cortical gray matter, white matter, deep nuclear gray matter, cerebellum, brainstem, cerebrospinal fluid (CSF), hippocampus and amygdala. We evaluated the performance of MANTiS using two independent datasets. The first dataset, provided by the NeoBrainS12 challenge, consisted of coronal T 2-weighted images of preterm infants (born ≤30 weeks' gestation) acquired at 30 weeks' corrected gestational age (n = 5), coronal T 2-weighted images of preterm infants acquired at 40 weeks' corrected gestational age (n = 5) and axial T 2-weighted images of preterm infants acquired at 40 weeks' corrected gestational age (n = 5). The second dataset, provided by the Washington University NeuroDevelopmental Research (WUNDeR) group, consisted of T 2-weighted images of preterm infants (born <30 weeks' gestation) acquired shortly after birth (n = 12), preterm infants acquired at term-equivalent age (n = 12), and healthy term-born infants (born ≥38 weeks' gestation) acquired within the first 9 days of life (n = 12). For the NeoBrainS12 dataset, mean Dice scores comparing MANTiS with manual segmentations were all above 0.7, except for the cortical gray

Early timing of adrenarche, associated with relatively high levels of dehydroepiandrosterone (DHEA) and its sulphate (DHEA-S) in children, has been linked with mental health problems, particularly anxiety. However, little is known about possible neurobiological mechanisms underlying this association. The pituitary gland is a key component of the hypothalamic-pituitary-adrenal (HPA) axis, the activation of which triggers the onset of adrenarche. The purpose of this study was to examine the extent to which pituitary gland volume mediated the relationship between levels of DHEA/DHEA-S relative to age (i.e., adrenarcheal timing) and symptoms of anxiety in 95 children (50 female, M age 9.50 years, SD 0.34 years). Relatively high DHEA and DHEA-S (DHEA/S) levels were found to be associated with larger pituitary gland volumes. There was no significant direct effect of relative DHEA/S levels on overall symptoms of anxiety. However, results supported an indirect link between relatively high DHEA/S levels and symptoms of social anxiety, mediated by pituitary gland volume. No sex differences were observed for any relationship. Our findings suggest that neurobiological mechanisms may be partly responsible for the link between relatively early adrenarche and anxiety symptoms in children. One possible mechanism for this finding is that an enlarged pituitary gland in children experiencing relatively advanced adrenarche might be associated with hyper-activity/reactivity of the HPA axis. Further research is needed to understand the role of stress in the link between adrenarcheal timing and HPA-axis function, especially in relation to the development of anxiety symptoms in children and adolescents.

The identification of individuals at high risk of developing psychosis is entirely based on clinical assessment, associated with limited predictive potential. There is, therefore, increasing interest in the development of biological markers that could be used in clinical practice for this purpose. We studied 25 individuals with an at-risk mental state for psychosis and 25 healthy controls using structural MRI, and functional MRI in conjunction with a verbal memory task. Data were analyzed using a standard univariate analysis, and with support vector machine (SVM), a multivariate pattern recognition technique that enables statistical inferences to be made at the level of the individual, yielding results with high translational potential. The application of SVM to structural MRI data permitted the identification of individuals at high risk of psychosis with a sensitivity of 68% and a specificity of 76%, resulting in an accuracy of 72% (p < 0.001). Univariate volumetric between-group differences did not reach statistical significance. By contrast, the univariate fMRI analysis identified between-group differences (p < 0.05 corrected), while the application of SVM to the same data did not. Since SVM is well suited at identifying the pattern of abnormality that distinguishes two groups, whereas univariate methods are more likely to identify regions that individually are most different between two groups, our results suggest the presence of focal functional abnormalities in the context of a diffuse pattern of structural abnormalities in individuals at high clinical risk of psychosis.

Despite being identified as a high risk cohort for psychosis, there has been relatively little research on the clinical presentation and assessment of Schizotypal Personality Disorder (SPD) in childhood. The current study aimed to develop a measure of childhood SPD (Melbourne Assessment of Schizotypy in Kids (MASK)) and assess discriminant validity against another neurodevelopmental disorder, autism spectrum disorder (ASD). Sixty-eight children aged between 5 and 12 (21 SPD, 15 ASD, and 32 typically developing) and their parents were administered the MASK. The MASK is a 57-item semistructured interview that obtains information from the child, their parents, and the clinician. The results showed high internal consistency for the MASK and higher scores in the SPD group. A factor analysis revealed two MASK factors: social/pragmatic symptoms and positive schizotypal symptoms. Both factors were associated with SPD, while only the social/pragmatic factor was associated with ASD. Within the two clinical groups, a receiver operating characteristic curve showed that the MASK (cut-off score: 132 out of 228) was a good indicator of SPD diagnosis. These preliminary MASK findings were reliable and consistent and suggest that childhood SPD is characterised by complex symptomology distinguishable from ASD.

Early timing of adrenarche, associated with relatively high levels of Dehydroepiandrosterone (DHEA) in children, has been associated with mental health and behavioral problems. However, little is known about effects of adreneracheal timing on brain function. The aim of this study was to investigate the effects of early adrenarche (defined by high DHEA levels independent of age) on affective brain function and symptoms of psychopathology in late childhood (N = 83, 43 females, M age 9.53 years, s.d. 0.34 years). Results showed that higher DHEA levels were associated with decreased affect-related brain activity (i) in the mid-cingulate cortex in the whole sample, and (ii) in a number of cortical and subcortical regions in female but not male children. Higher DHEA levels were also associated with increased externalizing symptoms in females, an association that was partly mediated by posterior insula activation to happy facial expressions. These results suggest that timing of adrenarche is an important moderator of affect-related brain function, and that this may be one mechanism linking early adrenarche to psychopathology.

BACKGROUND: Puberty is a critical developmental phase in physical, reproductive and socio-emotional maturation that is associated with the period of peak onset for psychopathology. Puberty also drives significant changes in brain development and function. Research to date has focused on gonadarche, driven by the hypothalamic-pituitary-gonadal axis, and yet increasing evidence suggests that the earlier pubertal stage of adrenarche, driven by the hypothalamic-pituitary-adrenal axis, may play a critical role in both brain development and increased risk for disorder. We have established a unique cohort of children who differ in their exposure to adrenarcheal hormones. This presents a unique opportunity to examine the influence of adrenarcheal timing on brain structural and functional development, and subsequent health outcomes. The primary objective of the study is to explore the hypothesis that patterns of structural and functional brain development will mediate the relationship between adrenarcheal timing and indices of affect, self-regulation, and mental health symptoms collected across time (and therefore years of development). METHODS/DESIGN: Children were recruited based upon earlier or later timing of adrenarche, from a larger cohort, with 128 children (68 female; M age 9.51 years) and one of their parents taking part. Children completed brain MRI structural and functional sequences, provided saliva samples for adrenarcheal hormones and immune biomarkers, hair for long-term cortisol levels, and completed questionnaires, anthropometric measures and an IQ test. Parents completed questionnaires reporting on child behaviour, development, health, traumatic events, and parental report of family environment and parenting style. DISCUSSION: This study, by examining the neurobiological and behavioural consequences of relatively early and late exposure to adrenarche, has the potential to significantly impact our understanding of pubertal risk processes.

OBJECTIVES: Extremely preterm (EP) survivors have smaller brains, lower IQ, and worse educational achievement than their term-born peers. The contribution of smaller brain size to the IQ and educational disadvantages of EP is unknown. This study aimed (i) to compare brain volumes from multiple brain tissues and structures between EP-born (< 28 weeks) and term-born (≥ 37 weeks) control adolescents, (ii) to explore the relationships of brain tissue volumes with IQ and basic educational skills and whether this differed by group, and (iii) to explore how much total brain tissue volume explains the underperformance of EP adolescents compared with controls. METHODS: Longitudinal cohort study of 148 EP and 132 term controls born in Victoria, Australia in 1991-92. At age 18, magnetic resonance imaging-determined brain volumes of multiple tissues and structures were calculated. IQ and educational skills were measured using the Wechsler Abbreviated Scale of Intelligence (WASI) and the Wide Range Achievement Test(WRAT-4), respectively. RESULTS: Brain volumes were smaller in EP adolescents compared with controls (mean difference [95% confidence interval] of -5.9% [-8.0, -3.7%] for total brain tissue volume). The largest relative differences were noted in the thalamus and hippocampus. The EP group had lower IQs(-11.9 [-15.4, -8.5]), spelling(-8.0 [-11.5, -4.6]), math computation(-10.3 [-13.7, -6.9]) and word reading(-5.6 [-8.8, -2.4]) scores than controls; all p-values<0.001. Volumes of total brain tissue and other brain tissues and structures correlated positively with IQ and educational skills, a relationship that was similar for both the EP and controls. Total brain tissue volume explained between 20-40% of the IQ and educational outcome differences between EP and controls. CONCLUSIONS: EP adolescents had smaller brain volumes, lower IQs and poorer educational performance than controls. Brain volumes of multiple tissues and structures are related to IQ and educational outcome

BACKGROUND: Very preterm children exhibit difficulties in working memory, a key cognitive ability vital to learning information and the development of academic skills. Previous research suggests that an adaptive working memory training intervention (Cogmed) may improve working memory and other cognitive and behavioural domains, although further randomised controlled trials employing long-term outcomes are needed, and with populations at risk for working memory deficits, such as children born preterm.In a cohort of extremely preterm (<28 weeks' gestation)/extremely low birthweight (<1000 g) 7-year-olds, we will assess the effectiveness of Cogmed in improving academic functioning 2 years' post-intervention. Secondary objectives are to assess the effectiveness of Cogmed in improving working memory and attention 2 weeks', 12 months' and 24 months' post-intervention, and to investigate training related neuroplasticity in working memory neural networks 2 weeks' post-intervention. METHODS/DESIGN: This double-blind, placebo-controlled, randomised controlled trial aims to recruit 126 extremely preterm/extremely low birthweight 7-year-old children. Children attending mainstream school without major intellectual, sensory or physical impairments will be eligible. Participating children will undergo an extensive baseline cognitive assessment before being randomised to either an adaptive or placebo (non-adaptive) version of Cogmed. Cogmed is a computerised working memory training program consisting of 25 sessions completed over a 5 to 7 week period. Each training session takes approximately 35 minutes and will be completed in the child's home. Structural, diffusion and functional Magnetic Resonance Imaging, which is optional for participants, will be completed prior to and 2 weeks following the training period. Follow-up assessments focusing on academic skills (primary outcome), working memory and attention (secondary outcomes) will be conducted at 2 weeks', 12 months' and 24 mon

Isolation of the brain from other tissue types in magnetic resonance (MR) images is an important step in many types of neuro-imaging research using both humans and animal subjects. The importance of brain extraction is well appreciated-numerous approaches have been published and the benefits of good extraction methods to subsequent processing are well known. We describe a tool-the marker based watershed scalper (MBWSS)-for isolating the brain in T1-weighted MR images built using filtering and segmentation components from the Insight Toolkit (ITK) framework. The key elements of MBWSS-the watershed transform from markers and aggressive filtering with large kernels-are techniques that have rarely been used in neuroimaging segmentation applications. MBWSS is able to reliably isolate the brain without expensive preprocessing steps, such as registration to an atlas, and is therefore useful as the first stage of processing pipelines. It is an informative example of the level of accuracy achievable without using priors in the form of atlases, shape models or libraries of examples. We validate the MBWSS using a publicly available dataset, a paediatric cohort, an adolescent cohort, intra-surgical scans and demonstrate flexibility of the approach by modifying the method to extract macaque brains.

The long-term effect of regular cannabis use on brain function underlying cognitive control remains equivocal. Cognitive control abilities are thought to have a major role in everyday functioning, and their dysfunction has been implicated in the maintenance of maladaptive drug-taking patterns. In this study, the Multi-Source Interference Task was employed alongside functional magnetic resonance imaging and psychophysiological interaction methods to investigate functional interactions between brain regions underlying cognitive control. Current cannabis users with a history of greater than 10 years of daily or near-daily cannabis smoking (n=21) were compared with age, gender, and IQ-matched non-using controls (n=21). No differences in behavioral performance or magnitude of task-related brain activations were evident between the groups. However, greater connectivity between the prefrontal cortex and the occipitoparietal cortex was evident in cannabis users, as compared with controls, as cognitive control demands increased. The magnitude of this connectivity was positively associated with age of onset and lifetime exposure to cannabis. These findings suggest that brain regions responsible for coordinating behavioral control have an increased influence on the direction and switching of attention in cannabis users, and that these changes may have a compensatory role in mitigating cannabis-related impairments in cognitive control or perceptual processes.

BACKGROUND: Patients with depression demonstrate cognitive impairment on a wide range of cognitive tasks, particularly putative tasks of frontal lobe function. Recent models of frontal lobe function have argued that the frontal pole region is involved in cognitive branching, a process requiring holding in mind one goal while performing sub-goal processes. Evidence for this model comes from functional neuroimaging and frontal-pole lesion patients. We have utilised these new concepts to investigate the possibility that patients with depression are impaired at cognitive 'branching'. METHODS: 11 non-medicated patients with major depression were compared to 11 matched controls in a behavioural study on a task of cognitive 'branching'. In the version employed here, we recorded participant's performance as they learnt to perform the task. This involved participants completing a control condition, followed by a working memory condition, a dual-task condition and finally the branching condition, which integrates processes in the working memory and dual-task conditions. We also measured participants on a number of other cognitive tasks as well as mood-state before and after the branching experiment. RESULTS: Patients took longer to learn the first condition, but performed comparably to controls after six runs of the task. Overall, reaction times decreased with repeated exposure on the task conditions in controls, with this effect attenuated in patients. Importantly, no differences were found between patients and controls on the branching condition. There was, however, a significant change in mood-state with patients increasing in positive affect and decreasing in negative affect after the experiment. CONCLUSION: We found no clear evidence of a fundamental impairment in anterior prefrontal 'branching processes' in patients with depression. Rather our data argue for a contextual learning impairment underlying cognitive dysfunction in this disorder. Our data suggest that MDD pat