In vivo evidence of microstructural hypo-connectivity of brain white matter in 22q11.2 deletion syndrome.

22q11.2 deletion syndrome, or 22q11.2DS, is a genetic syndrome associated with high rates of schizophrenia and autism spectrum disorders, in addition to widespread structural and functional abnormalities throughout the brain. Experimental animal models have identified neuronal connectivity deficits, e.g., decreased axonal length and complexity of axonal branching, as a primary mechanism underlying atypical brain development in 22q11.2DS. However, it is still unclear whether deficits in axonal morphology can also be observed in people with 22q11.2DS. Here, we provide an unparalleled in vivo characterization of white matter microstructure in participants with 22q11.2DS (12-15 years) and those undergoing typical development (8-18 years) using a customized magnetic resonance imaging scanner which is sensitive to axonal morphology. A rich array of diffusion MRI metrics are extracted to present microstructural profiles of typical and atypical white matter development, and provide new evidence of connectivity differences in individuals with 22q11.2DS. A recent, large-scale consortium study of 22q11.2DS identified higher diffusion anisotropy and reduced overall diffusion mobility of water as hallmark microstructural alterations of white matter in individuals across a wide age range (6-52 years). We observed similar findings across the white matter tracts included in this study, in addition to identifying deficits in axonal morphology. This, in combination with reduced tract volume measurements, supports the hypothesis that abnormal microstructural connectivity in 22q11.2DS may be mediated by densely packed axons with disproportionately small diameters. Our findings provide insight into the in vivo white matter phenotype of 22q11.2DS, and promote the continued investigation of shared features in neurodevelopmental and psychiatric disorders.

Novel insights into axon diameter and myelin content in late childhood and adolescence.

White matter microstructural development in late childhood and adolescence is driven predominantly by increasing axon density and myelin thickness. Ex vivo studies suggest that the increase in axon diameter drives developmental increases in axon density observed with pubertal onset. In this cross-sectional study, 50 typically developing participants aged 8-18 years were scanned using an ultra-strong gradient magnetic resonance imaging scanner. Microstructural properties, including apparent axon diameter $({d}_a)$, myelin content, and g-ratio, were estimated in regions of the corpus callosum. We observed age-related differences in ${d}_a$, myelin content, and g-ratio. In early puberty, males had larger ${d}_a$ in the splenium and lower myelin content in the genu and body of the corpus callosum, compared with females. Overall, this work provides novel insights into developmental, pubertal, and cognitive correlates of individual differences in apparent axon diameter and myelin content in the developing human brain.

Surface-based tracking for short association fibre tractography.

It is estimated that in the human brain, short association fibres (SAF) represent more than half of the total white matter volume and their involvement has been implicated in a range of neurological and psychiatric conditions. This population of fibres, however, remains relatively understudied in the neuroimaging literature. Some of the challenges pertinent to the mapping of SAF include their variable anatomical course and proximity to the cortical mantle, leading to partial volume effects and potentially affecting streamline trajectory estimation. This work considers the impact of seeding and filtering strategies and choice of scanner, acquisition, data resampling to propose a whole-brain, surface-based short (≤30-40 mm) SAF tractography approach. The framework is shown to produce longer streamlines with a predilection for connecting gyri as well as high cortical coverage. We further demonstrate that certain areas of subcortical white matter become disproportionally underrepresented in diffusion-weighted MRI data with lower angular and spatial resolution and weaker diffusion weighting; however, collecting data with stronger gradients than are usually available clinically has minimal impact, making our framework translatable to data collected on commonly available hardware. Finally, the tractograms are examined using voxel- and surface-based measures of consistency, demonstrating moderate reliability, low repeatability and high between-subject variability, urging caution when streamline count-based analyses of SAF are performed.

Fixel-based Analysis of Diffusion MRI: Methods, Applications, Challenges and Opportunities.

Diffusion MRI has provided the neuroimaging community with a powerful tool to acquire in-vivo data sensitive to microstructural features of white matter, up to 3 orders of magnitude smaller than typical voxel sizes. The key to extracting such valuable information lies in complex modelling techniques, which form the link between the rich diffusion MRI data and various metrics related to the microstructural organization. Over time, increasingly advanced techniques have been developed, up to the point where some diffusion MRI models can now provide access to properties specific to individual fibre populations in each voxel in the presence of multiple "crossing" fibre pathways. While highly valuable, such fibre-specific information poses unique challenges for typical image processing pipelines and statistical analysis. In this work, we review the "Fixel-Based Analysis" (FBA) framework, which implements bespoke solutions to this end. It has recently seen a stark increase in adoption for studies of both typical (healthy) populations as well as a wide range of clinical populations. We describe the main concepts related to Fixel-Based Analyses, as well as the methods and specific steps involved in a state-of-the-art FBA pipeline, with a focus on providing researchers with practical advice on how to interpret results. We also include an overview of the scope of all current FBA studies, categorized across a broad range of neuro-scientific domains, listing key design choices and summarizing their main results and conclusions. Finally, we critically discuss several aspects and challenges involved with the FBA framework, and outline some directions and future opportunities.

Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?

White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process.

Long-term development of white matter fibre density and morphology up to 13 years after preterm birth: A fixel-based analysis.

BACKGROUND: It is well documented that infants born very preterm (VP) are at risk of brain injury and altered brain development in the neonatal period, however there is a lack of long-term, longitudinal studies on the effects of VP birth on white matter development over childhood. Most previous studies were based on voxel-averaged, non-fibre-specific diffusion magnetic resonance imaging (MRI) measures, such as fractional anisotropy. In contrast, the novel diffusion MRI analysis framework, fixel-based analysis (FBA), enables whole-brain analysis of microstructural and macrostructural properties of individual fibre populations at a sub-voxel level. We applied FBA to investigate the long-term implications of VP birth and associated perinatal risk factors on fibre development in childhood and adolescence. METHODS: Diffusion images were acquired for a cohort of VP (born <30 weeks' gestation) and full-term (FT, ≥37 weeks' gestation) children at two timepoints: mean (SD) 7.6 (0.2) years (n â€‹= â€‹138 VP and 32 FT children) and 13.3 (0.4) years (n â€‹= â€‹130 VP and 45 FT children). 103 VP and 21 FT children had images at both ages for longitudinal analysis. At every fixel (individual fibre population within an image voxel) across the white matter, we compared FBA metrics (fibre density (FD), cross-section (FC) and a combination of these properties (FDC)) between VP and FT groups cross-sectionally at each timepoint, and longitudinally between timepoints. We also examined associations between known perinatal risk factors and FBA metrics in the VP group. RESULTS: Compared with FT children, VP children had lower FD, FC and FDC throughout the white matter, particularly in the corpus callosum, tapetum, inferior fronto-occipital fasciculus, fornix and cingulum at ages 7 and 13 years, as well as the corticospinal tract and anterior limb of the internal capsule at age 13 years. VP children also had slower FDC development in the corpus callosum and corticospinal tract between ages 7 and 13 years compared with FT children. Within VP children, earlier gestational age at birth, lower birth weight z-score, and neonatal brain abnormalities were associated with lower FD, FC and FDC throughout the white matter at both ages. CONCLUSIONS: VP birth and concomitant perinatal risk factors are associated with fibre tract-specific alterations to axonal development in childhood and adolescence.

Impact of b-value on estimates of apparent fibre density.

Recent advances in diffusion magnetic resonance imaging (dMRI) analysis techniques have improved our understanding of fibre-specific variations in white matter microstructure. Increasingly, studies are adopting multi-shell dMRI acquisitions to improve the robustness of dMRI-based inferences. However, the impact of b-value choice on the estimation of dMRI measures such as apparent fibre density (AFD) derived from spherical deconvolution is not known. Here, we investigate the impact of b-value sampling scheme on estimates of AFD. First, we performed simulations to assess the correspondence between AFD and simulated intra-axonal signal fraction across multiple b-value sampling schemes. We then studied the impact of sampling scheme on the relationship between AFD and age in a developmental population (n = 78) aged 8-18 (mean = 12.4, SD = 2.9 years) using hierarchical clustering and whole brain fixel-based analyses. Multi-shell dMRI data were collected at 3.0T using ultra-strong gradients (300 mT/m), using 6 diffusion-weighted shells ranging from b = 0 to 6,000 s/mm2 . Simulations revealed that the correspondence between estimated AFD and simulated intra-axonal signal fraction was improved with high b-value shells due to increased suppression of the extra-axonal signal. These results were supported by in vivo data, as sensitivity to developmental age-relationships was improved with increasing b-value (b = 6,000 s/mm2 , median R2 = .34; b = 4,000 s/mm2 , median R2 = .29; b = 2,400 s/mm2 , median R2 = .21; b = 1,200 s/mm2 , median R2 = .17) in a tract-specific fashion. Overall, estimates of AFD and age-related microstructural development were better characterised at high diffusion-weightings due to improved correspondence with intra-axonal properties.

Dimensionality reduction of diffusion MRI measures for improved tractometry of the human brain.

Various diffusion MRI (dMRI) measures have been proposed for characterising tissue microstructure over the last 15 years. Despite the growing number of experiments using different dMRI measures in assessments of white matter, there has been limited work on: 1) examining their covariance along specific pathways; and on 2) combining these different measures to study tissue microstructure. Indeed, it quickly becomes intractable for existing analysis pipelines to process multiple measurements at each voxel and at each vertex forming a streamline, highlighting the need for new ways to visualise or analyse such high-dimensional data. In a sample of 36 typically developing children aged 8-18 years, we profiled various commonly used dMRI measures across 22 brain pathways. Using a data-reduction approach, we identified two biologically-interpretable components that capture 80% of the variance in these dMRI measures. The first derived component captures properties related to hindrance and restriction in tissue microstructure, while the second component reflects characteristics related to tissue complexity and orientational dispersion. We then demonstrate that the components generated by this approach preserve the biological relevance of the original measurements by showing age-related effects across developmentally sensitive pathways. In summary, our findings demonstrate that dMRI analyses can benefit from dimensionality reduction techniques, to help disentangling the neurobiological underpinnings of white matter organisation.

Development of white matter fibre density and morphology over childhood: A longitudinal fixel-based analysis.

PURPOSE: White matter fibre development in childhood involves dynamic changes to microstructural organisation driven by increasing axon diameter, density, and myelination. However, there is a lack of longitudinal studies that have quantified advanced diffusion metrics to identify regions of accelerated fibre maturation, particularly across the early pubertal period. We applied a novel longitudinal fixel-based analysis (FBA) framework, in order to estimate microscopic and macroscopic white matter changes over time. METHODS: Diffusion-weighted imaging (DWI) data were acquired for 59 typically developing children (27 female) aged 9-13 years  at two time-points approximately 16 months apart (time-point 1: 10.4 ±â€¯0.4 years, time-point 2: 11.7 ±â€¯0.5 years). Whole brain FBA was performed using the connectivity-based fixel enhancement method, to assess longitudinal changes in fibre microscopic density and macroscopic morphological measures, and how these changes are related to sex, pubertal stage, and pubertal progression. Follow-up analyses were performed in sub-regions of the corpus callosum to confirm the main findings using a Bayesian repeated measures approach. RESULTS: There was a statistically significant increase in fibre density over time localised to medial and posterior commissural and association fibres, including the forceps major and bilateral superior longitudinal fasciculus. Increases in fibre cross-section were substantially more widespread. The rate of fibre development was not associated with age or sex. In addition, there was no significant relationship between pubertal stage or progression and longitudinal fibre development over time. Follow-up Bayesian analyses were performed to confirm the findings, which supported the null effect of the longitudinal pubertal comparison. CONCLUSION: Using a novel longitudinal fixel-based analysis framework, we demonstrate that white matter fibre density and fibre cross-section increased within a 16-month scan rescan period in specific regions. The observed increases might reflect increasing axonal diameter or axon count. Pubertal stage or progression did not influence the rate of fibre development in the early stages of puberty. Future work should focus on quantifying these measures across a wider age range to capture the full spectrum of fibre development across the pubertal period.

Neurite density index is sensitive to age related differences in the developing brain.

PURPOSE: White matter development during childhood and adolescence is characterised by increasing white matter coherence and organisation. Commonly used scalar metrics, such as fractional anisotropy (FA), are sensitive to multiple mechanisms of white matter change and therefore unable to distinguish between mechanisms that change during development. We investigate the relationship between age and neurite density index (NDI) from neurite orientation dispersion and density imaging (NODDI), and the age-classification accuracy of NDI compared with FA, in a developmental cohort. METHOD: Diffusion-weighted imaging data from 72 children and adolescents between the ages of 4-19 was collected (M=10.42, SD=3.99, 36 male). We compared NODDI metrics against conventional DTI metrics (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity [AD] and radial diffusivity [RD]) in terms of their relationship to age. An ROC analysis was also performed to assess the ability of each metric to classify older and younger participants. RESULTS: NDI exhibited a stronger relationship with age (median R2=.60) compared with MD (median R2=.39), FA (median R2=.27), AD (median R2=.14), and RD (median R2=.35) in a high proportion of white matter tracts. When participants were divided into an older and younger group, NDI achieved the best classification (median area under the curve [AUC]=.89), followed by MD (median AUC=.81), FA (median AUC=.80), RD (median AUC=.81), and AD (median AUC=.64). CONCLUSION: Our results demonstrate the sensitivity of NDI to age-related differences in white matter microstructural organisation over development. Importantly, NDI is more sensitive to such developmental changes compared to commonly used DTI metrics. This knowledge provides justification for implementing NODDI metrics in developmental studies.

White matter alterations at pubertal onset.

Recent neurodevelopmental research supports the contribution of pubertal stage to local and global grey and white matter remodelling. Little is known, however, about white matter microstructural alterations at pubertal onset. This study investigated differences in white matter properties between pre-pubertal and pubertal children using whole brain fixel-based analysis (FBA) of the microscopic density and macroscopic cross-section of fibre bundles. Diffusion-weighted imaging data were acquired for 74 typically developing children (M=10.4, SD=.43 years, 31 female) at 3.0T (60 diffusion gradient directions, b-value=2800s/mm2). Group comparisons of fibre density (FD) and fibre cross-section (FC) were made between age-matched pre-pubertal and pubertal groups, and post-hoc analyses were performed on regions of interest (ROIs) defined in the splenium, body and genu of the corpus callosum. Significant fixel-wise differences in FD were observed between the pubertal groups, where the pubertal group had significantly higher FD compared with age-matched pre-pubertal children, localised to the posterior corpus callosum. Post-hoc analyses on mean FD in the corpus callosum ROIs revealed group differences between the pubertal groups in the splenium, but not body or genu. The observed higher apparent fibre density in the splenium suggests that pubertal onset coincides with white matter differences explained by increasing axon diameter. This may be an important effect to account for over pubertal development, particularly for group studies where age-matched clinical and typical populations may be at various stages of puberty.

Short-term white matter alterations in Alzheimer's disease characterized by diffusion tensor imaging.

PURPOSE: To investigate whether there are any white matter changes in a 6-month follow-up of mild-moderate Alzheimer's patients using diffusion tensor imaging (DTI). MATERIALS AND METHODS: We recruited 18 mild-moderate Alzheimer's disease patients and they underwent magnetic resonance imaging (MRI) at recruitment and at 6-month follow-up. Diffusion MRI images were processed using DTI-ToolKit to create a population-based tensor template. This template was integrated with a voxel-wise and atlas-based analysis in FSL to determine the magnitude and location of change in diffusion metrics over the 6-month follow-up period. RESULTS: There were significant widespread changes in diffusion metrics across the entire white matter skeleton (P < 0.001), 95% confidence interval (CI) difference in fractional anisotropy: -0.007 (-0.011, -0.002), mean diffusivity: 0.040 (0.023, 0.058), axial diffusivity: 0.015 (0.008, 0.022), radial diffusivity: 0.012 (0.006, 0.019), as well as regions of interest in the splenium and superior longitudinal fasciculus. CONCLUSION: Our findings show that diffusion metrics are altered in a 6-month follow-up period of mild-moderate Alzheimer's patients, supporting the potential of DTI metrics to act as sensitive biomarkers for disease progression even over a relatively short time interval, and the potential utility to be applied to clinical trials of putative disease-modifying therapies.

Developmental brain trajectories in children with ADHD and controls: a longitudinal neuroimaging study.

BACKGROUND: The symptom profile and neuropsychological functioning of individuals with Attention Deficit/Hyperactivity Disorder (ADHD), change as they enter adolescence. It is unclear whether variation in brain structure and function parallels these changes, and also whether deviations from typical brain development trajectories are associated with differential outcomes. This paper describes the Neuroimaging of the Children's Attention Project (NICAP), a comprehensive longitudinal multimodal neuroimaging study. Primary aims are to determine how brain structure and function change with age in ADHD, and whether different trajectories of brain development are associated with variations in outcomes including diagnostic persistence, and academic, cognitive, social and mental health outcomes. METHODS/DESIGN: NICAP is a multimodal neuroimaging study in a community-based cohort of children with and without ADHD. Approximately 100 children with ADHD and 100 typically developing controls will be scanned at a mean age of 10 years (range; 9-11years) and will be re-scanned at two 18-month intervals (ages 11.5 and 13 years respectively). Assessments include a structured diagnostic interview, parent and teacher questionnaires, direct child cognitive/executive functioning assessment and magnetic resonance imaging (MRI). MRI acquisition techniques, collected at a single site, have been selected to provide optimized information concerning structural and functional brain development. DISCUSSION: This study will allow us to address the primary aims by describing the neurobiological development of ADHD and elucidating brain features associated with differential clinical/behavioral outcomes. NICAP data will also be explored to assess the impact of sex, ADHD presentation, ADHD severity, comorbidities and medication use on brain development trajectories. Establishing which brain regions are associated with differential clinical outcomes, may allow us to improve predictions about the course of ADHD.

Ultra-strong diffusion-weighted MRI reveals cerebellar grey matter abnormalities in movement disorders.

Structural brain MRI has proven invaluable in understanding movement disorder pathophysiology. However, most work has focused on grey/white matter volumetric (macrostructural) and white matter microstructural effects, limiting understanding of frequently implicated grey matter microstructural differences. Using ultra-strong spherical tensor encoding diffusion-weighted MRI, a persistent MRI signal was seen in healthy cerebellar grey matter even at high diffusion-weightings (b ​≥ 10,000 s/mm2). Quantifying the proportion of this signal (denoted fs), previously ascertained to originate from inside small spherical spaces, provides a potential proxy for cell body density. In this work, this approach was applied for the first time to a clinical cohort, including patients with diagnosed movement disorders in which the cerebellum has been implicated in symptom pathophysiology. Five control participants (control group 1, median age 24.5 years (20-39 years), imaged at two timepoints, demonstrated consistency in measurement of all three measures - MD (Mean Diffusivity) fs, and Ds (dot diffusivity)- with intraclass correlation coefficients (ICC) of 0.98, 0.86 and 0.76, respectively. Comparison with an older control group (control group 2 (n = 5), median age 51 years (43-58 years)) found no significant differences, neither with morphometric nor microstructural (MD (p = 0.36), fs (p = 0.17) and Ds (p = 0.22)) measures. The movement disorder cohort (Parkinson's Disease, n = 5, dystonia, n = 5. Spinocerebellar Ataxia 6, n = 5) when compared to the age-matched control cohort (Control Group 2) identified significantly lower MD (p < 0.0001 and p < 0.0001) and higher fs values (p < 0.0001 and p < 0.0001) in SCA6 and dystonia cohorts respectively. Lobar division of the cerebellum found these same differences in the superior and inferior posterior lobes, while no differences were seen in either the anterior lobes or with Ds measurements. In contrast to more conventional measures from diffusion tensor imaging, this framework provides enhanced specificity to differences in restricted spherical spaces in grey matter (including small cells) by eliminating signals from cerebrospinal fluid and axons. In the context of human and animal histopathology studies, these findings potentially implicate the cerebellar Purkinje and granule cells as contributors to the observed signal differences, with both cell types having been implicated in several neurological disorders through both postmortem and animal model studies. This novel microstructural imaging approach shows promise for improving movement disorder diagnosis, prognosis, and treatment.

Childhood conduct problems are associated with reduced white matter fibre density and morphology.

Childhood conduct problems are an important public health issue as these children are at-risk of adverse outcomes. Studies using diffusion Magnetic Resonance Imaging (dMRI) have found that conduct problems in adults are characterised by abnormal white-matter microstructure within a range of white matter pathways underpinning socio-emotional processing, while evidence within children and adolescents has been less conclusive based on non-specific diffusion tensor imaging metrics. Fixel-based analysis (FBA) provides measures of fibre density and morphology that are more sensitive to developmental changes in white matter microstructure. The current study used FBA to investigate whether childhood conduct problems were related both cross-sectionally and longitudinally to microstructural alterations within the fornix, inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus (SLF), and the uncinate fasciculus (UF). dMRI data was obtained for 130 children across two time-points in a community sample with high levels of externalising difficulties (age: time-point 1 = 9.47 - 11.86 years, time-point 2 = 10.67 -13.45 years). Conduct problems were indexed at each time-point using the Conduct Problems subscale of the parent-informant Strengths and Difficulties Questionnaire (SDQ). Conduct problems were related to lower fibre density in the fornix at both time-points, and in the ILF at time-point 2. We also observed lower fibre cross-section in the UF at time-point 1. The change in conduct problems did not predict longitudinal changes in white-matter microstructure across time-points. The current study suggests that childhood conduct problems are related to reduced fibre-specific microstructure within white matter fibre pathways implicated in socio-emotional functioning.

Detecting microstructural deviations in individuals with deep diffusion MRI tractometry.

Most diffusion magnetic resonance imaging studies of disease rely on statistical comparisons between large groups of patients and healthy participants to infer altered tissue states in the brain; however, clinical heterogeneity can greatly challenge their discriminative power. There is currently an unmet need to move away from the current approach of group-wise comparisons to methods with the sensitivity to detect altered tissue states at the individual level. This would ultimately enable the early detection and interpretation of microstructural abnormalities in individual patients, an important step towards personalized medicine in translational imaging. To this end, Detect was developed to advance diffusion magnetic resonance imaging tractometry towards single-patient analysis. By operating on the manifold of white-matter pathways and learning normative microstructural features, our framework captures idiosyncrasies in patterns along white-matter pathways. Our approach paves the way from traditional group-based comparisons to true personalized radiology, taking microstructural imaging from the bench to the bedside.

Longitudinal patterns of white matter fibre density and morphology in children are associated with age and pubertal stage.

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.

Evidence accumulation during perceptual decisions in humans varies as a function of dorsal frontoparietal organization.

Animal neurophysiological studies have identified neural signals within dorsal frontoparietal areas that trace a perceptual decision by accumulating sensory evidence over time and trigger action upon reaching a threshold. Although analogous accumulation-to-bound signals are identifiable on extracranial human electroencephalography, their cortical origins remain unknown. Here neural metrics of human evidence accumulation, predictive of the speed of perceptual reports, were isolated using electroencephalography and related to dorsal frontoparietal network (dFPN) connectivity using diffusion and resting-state functional magnetic resonance imaging. The build-up rate of evidence accumulation mediated the relationship between the white matter macrostructure of dFPN pathways and the efficiency of perceptual reports. This association between steeper build-up rates of evidence accumulation and the dFPN was recapitulated in the resting-state networks. Stronger connectivity between dFPN regions is thus associated with faster evidence accumulation and speeded perceptual decisions. Our findings identify an integrated network for perceptual decisions that may be targeted for neurorehabilitation in cognitive disorders.

Multimodal Structural Neuroimaging Markers of Brain Development and ADHD Symptoms.

OBJECTIVE: Attention deficit hyperactivity disorder (ADHD) is a multifactorial disorder with diverse associated risk factors and comorbidities. In this study, the authors sought to understand ADHD from a dimensional perspective and to identify neuroanatomical correlates of traits and behaviors that span diagnostic criteria. METHODS: Multimodal neuroimaging data and multi-informant cognitive and clinical data were collected in a densely phenotyped pediatric cohort (N=160; 70 with ADHD; age range, 9-12 years). Multivariate analysis identified associations between clinical and cognitive factors and multimodal neuroimaging markers (across tissue volume, cortical thickness, cortical area, and white matter microstructure). The resulting imaging markers were validated in an independent cohort (N=231; 132 with ADHD; age range, 7-18 years). RESULTS: Four novel patterns of neuroanatomical variation that related to phenotypic variation were identified. The first imaging pattern captured association of head size with sex, socioeconomic status, and mathematics and reading performance. The second pattern captured variation associated with development and showed that individuals with delayed development were more likely to be receiving ADHD medication. The third pattern was associated with hyperactivity, greater comorbidities, poorer cognition, lower parental education, and lower quality of life. The fourth pattern was associated with a particular profile of poorer cognition and irritability independent of ADHD. The authors further demonstrated that these imaging patterns could predict variation in age and ADHD symptoms in an independent cohort. CONCLUSIONS: The findings suggest that ADHD presentation may arise from a summation of several clinical, developmental, or cognitive factors, each with a distinct neuroanatomical foundation. This informs the neurobiological foundations of ADHD and highlights the value of detailed phenotypic data in understanding the neurobiology underlying neurodevelopmental disorders.

Supranutritional Sodium Selenate Supplementation Delivers Selenium to the Central Nervous System: Results from a Randomized Controlled Pilot Trial in Alzheimer's Disease.

Insufficient supply of selenium to antioxidant enzymes in the brain may contribute to Alzheimer's disease (AD) pathophysiology; therefore, oral supplementation may potentially slow neurodegeneration. We examined selenium and selenoproteins in serum and cerebrospinal fluid (CSF) from a dual-dose 24-week randomized controlled trial of sodium selenate in AD patients, to assess tolerability, and efficacy of selenate in modulating selenium concentration in the central nervous system (CNS). A pilot study of 40 AD cases was randomized to placebo, nutritional (0.32 mg sodium selenate, 3 times daily), or supranutritional (10 mg, 3 times daily) groups. We measured total selenium, selenoproteins, and inorganic selenium levels, in serum and CSF, and compared against cognitive outcomes. Supranutritional selenium supplementation was well tolerated and yielded a significant (p < 0.001) but variable (95% CI = 13.4-24.8 µg/L) increase in CSF selenium, distributed across selenoproteins and inorganic species. Reclassifying subjects as either responsive or non-responsive based on elevation in CSF selenium concentrations revealed that responsive group did not deteriorate in Mini-Mental Status Examination (MMSE) as non-responsive group (p = 0.03). Pooled analysis of all samples revealed that CSF selenium could predict change in MMSE performance (Spearman's rho = 0.403; p = 0.023). High-dose sodium selenate supplementation is well tolerated and can modulate CNS selenium concentration, although individual variation in selenium metabolism must be considered to optimize potential benefits in AD. The Vel002 study is listed on the Australian and New Zealand Clinical Trials Registry ( http://www.anzctr.org.au /), ID: ACTRN12611001200976.