Biology subjects

Seal, M.

Publications and source records attributed to Seal, M..

5 recordsLinked to original sources

bioRxiv2018

Quantifying individual differences in brain morphometry underlying symptom severity in Autism Spectrum Disorders

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 were entered into a regularised machine learning pipeline for feature selection, with rigorous out-of-sample validation and bootstrapped 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.

neuroscience↗

bioRxiv2018

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

PurposeWhite 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.\n\nMethodsDiffusion-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 {+/-} 0.4 years, time-point 2: 11.7 {+/-} 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 affected by 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.\n\nResultsThere 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.\n\nConclusionUsing 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.

neuroscience↗

bioRxiv2017

Age, sex, and puberty related development of the corpus callosum: a multi-technique diffusion MRI study

PurposeThe corpus callosum is integral to the central nervous system, and continually develops with age by virtue of increasing axon diameter and ongoing myelination. Magnetic resonance imaging (MRI) techniques offer a means to disentangle these two aspects of white matter development. We investigate the profile of microstructural metrics across the corpus callosum, and assess the impact of age, sex and pubertal development on these processes.\n\nMethodsThis study made use of two independent paediatric populations. Multi-shell diffusion MRI data were analysed to produce a suite of diffusion tensor imaging (DTI), neurite orientation density and dispersion imaging (NODDI), and apparent fibre density (AFD) metrics. A multivariate profile analysis was performed for each diffusion metric across 10 subdivisions of the corpus callosum.\n\nResultsAll diffusion metrics significantly varied across the length of the corpus callosum. AFD exhibited a strong relationship with age across the corpus callosum (partial{eta} 2 = .65), particularly in the posterior body of the corpus callosum (partial{eta} 2 = .72). In addition, females had significantly higher AFD compared with males, most markedly in the anterior splenium (partial{eta} 2 = .14) and posterior genu (partial{eta} 2 = .13). Age-matched pubertal group differences were localised to the splenium.\n\nConclusionWe present evidence of a strong relationship between apparent fibre density and age, sex, and puberty during development. These results are consistent with ex vivo studies of fibre morphology, providing insights into the dynamics of axonal development in childhood and adolescence using diffusion MRI.\n\nTarget journalsBrain Structure & Function; HBM; NeuroImage; Developmental Cognitive Neuroscience

neuroscience↗

bioRxiv2017

Different Brain Networks Underlying Intelligence In Autism Spectrum Disorders And Typically Developing Children

BackgroundThere has been sustained clinical and cognitive neuroscience research interest in how network correlates of brain-behaviour relationships might be altered in Autism Spectrum Disorders (ASD) and other neurodevelopmental disorders. As previous work has mostly focused on adults, the nature of whole-brain connectivity networks underlying intelligence in pediatric cohorts with abnormal neurodevelopment requires further investigation.\n\nMethodsWe used network-based statistics (NBS) to examine the association between resting-state functional Magnetic Resonance Imaging (fMRI) connectivity and fluid intelligence ability in male children (n=50) with Autism Spectrum Disorders (ASD; M=10.45, SD=1.58 years and in controls (M=10.38, SD=0.96 years) matched on fluid intelligence performance, age and sex. Repeat analyses were performed in independent sites for validation and replication.\n\nResultsDespite being equivalent on fluid intelligence ability to strictly matched neurotypical controls, boys with ASD displayed a subnetwork of significantly increased associations between functional connectivity and fluid intelligence. Between-group differences remained significant at higher edge thresholding, and results were validated in independent-site replication analyses in an equivalent age and sex-matched cohort with ASD. Regions consistently implicated in atypical connectivity correlates of fluid intelligence in ASD were the angular gyrus, posterior middle temporal gyrus, occipital and temporo-occipital regions.\n\nConclusionDevelopment of fluid intelligence neural correlates in young ASD males is aberrant, with an increased strength in intrinsic connectivity association during childhood. Alterations in whole-brain network correlates of fluid intelligence in ASD may be a compensatory mechanism that allows equal task performance to neurotypical peers.

neuroscience↗

bioRxiv2017

Network component analysis reveals developmental trajectories of structural connectivity and specific alterations in autism spectrum disorder

The structural organisation of the brain can be characterised as a hierarchical ensemble of segregated modules linked by densely interconnected hub regions that facilitate distributed functional interactions. Disturbances to this network may be an important marker of abnormal development. Recently, several neurodevelopmental disorders, including autism spectrum disorder (ASD), have been framed as disorders of connectivity but the full nature and timing of these disturbances remain unclear.\n\nIn this study, we use non-negative matrix factorisation, a data-driven, multivariate approach, to model the structural network architecture of the brain as a set of superposed subnetworks, or network components.\n\nIn an openly available dataset of 196 subjects scanned between 5 to 85 years we identify a set of robust and reliable subnetworks that develop in tandem with age and reflect both anatomically local and long-range, network hub connections. In a second experiment, we compare network components in a cohort of 51 high-functioning ASD adolescents to a group of age-matched controls. We identify a specific subnetwork representing an increase in local connection strength in the cingulate cortex in ASD (t=3.44, p<0.001).\n\nThis work highlights possible long-term implications of alterations to the developmental trajectories of specific cortical subnetworks.

neuroscience↗