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Smith, R. E.

Publications and source records attributed to Smith, R. E..

At least 19 recordsLinked to original sources
bioRxiv2026

Longitudinal quantitative streamline tractography: robust estimation of white matter connectivity differences

Longitudinal probing of structural connectivity via diffusion magnetic resonance imaging (dMRI) is experiencing uptake. However, the detection of biological effects is significantly hampered by the limitations of cross-sectional streamline tractography, where even small changes in the dMRI signal can produce drastically different trajectories and therefore quantitative parameterisation; if not properly dealt with, such effects will manifest as spurious longitudinal change, which can obscure subtle biological differences. To overcome this challenge, we here introduce a novel quantitative streamline tractography framework tailored for longitudinal analysis, wherein an individuals streamline trajectories remain fixed throughout the analysis, allowing only their ascribed density weights to vary between sessions. We present two strategies by which these quantitative streamline weights can be determined, both extensions of the widely adopted SIFT2 method. The performance of this framework is benchmarked against cross-sectional reconstruction with and without SIFT2 optimisation, in both in silico dMRI phantoms with known ground truths and three distinct human in vivo cohorts with clear a priori expectations of biological effects. We demonstrate that the proposed framework drastically reduces methodological imprecisions in synthetic dMRI phantoms and enhances statistical sensitivity and specificity to biological effects in human cohorts, enabling robust longitudinal quantification of structural connectivity.

neuroscience↗
bioRxiv2025

Reinterpretation of Bakiribu waridza from the Romualdo Formation (Lower Cretaceous) of Brazil: a fish not a pterosaur

Fragmentary remains of fossil vertebrates from the Romualdo Formation (Lower Cretaceous) of Brazil, preserved in association with two fish were interpreted as two individuals of a new genus and species of ctenochasmatine pterosaur, Bakiribu waridza Pegas et al., 2025. Comparison with a range of fossils from the same geological unit show that the remains represent the gill arch apparatus of a large actinopterygian fish. This reinterpretation, which mirrors a comparable event in the mid twentieth century when the remains of a supposed ctenochasmatine pterosaur, Belonochasma aenigmaticum, were reidentified as part of the gill apparatus of a fish, does not affect our current understanding of the evolutionary history of pterosaurs.

paleontology↗
bioRxiv2025

TRAMFIX: TRavelling Across Melbourne for FIXel-based analysis (a reproducibility study)

Fixel-based analysis (FBA) has gained substantial interest for its ability to probe fibre-specific changes in the brains white matter from diffusion-weighted imaging data. However, the reproducibility and reliability of fixel-based measures across different scanners remains largely unknown. In this work, we present TRAMFIX: a multisite dataset of travelling participants (n=10 healthy adults) scanned across four 3T MRI scanners using a harmonised multi-shell DWI protocol. DWI data were processed using two pipelines that can adopted when performing multi-site FBA studies (site-specific versus pooled processing). We extracted fixel-based measures of fibre density (FD), fibre cross-section (FC), and fibre density and cross-section (FDC), as well as diffusion tensor imaging (DTI)-based fractional anisotropy (FA) and mean diffusivity (MD) from the harmonised protocol. Within-subject coefficients of variation (CVws) and intraclass correlation coefficients (ICC) of FBA and DTI measures were computed at multiple resolutions of computation and analysis: (i) the whole-brain averaged level, (ii) tract-level, and (iii) fixel- or voxel-level. Fixel-based metrics demonstrated high reproducibility and reliability at the whole-brain level (CVws ranging between 0.51% to 1.57% and ICC between 0.93 and 0.996). While reproducibility and reliability remained high for tract-averaged FBA measures (particularly the FC and FDC metrics), some tracts exhibited lower ICC values < 0.8 for the FD measure. When examining fixel-level reliability and reproducibility clear spatial patterns emerged, with lower ICC across subcortical and cerebellar regions, and higher CVws at the cortical boundaries. Across all levels, tensor-based metrics demonstrated slightly lower reproducibility and reliability metrics than FBA measures, suggesting that FBA metrics are just as, if not more, reproducible than DTI metrics across scanners when using identical protocols. Our findings provide support for the reproducibility and reliability of fixel-based measures, highlighting their potential for use in multi-site FBA studies. Future work examining protocol-related differences, as well as appropriate harmonisation strategies when pooling data across sites and scanners, will be valuable.

neuroscience↗
bioRxiv2025

Robust-tedana: An automated denoising pipeline for multi-echo fMRI data

Multi-echo functional Magnetic Resonance Imaging (fMRI) data are acquired by recording image volumes at multiple echo times and can be used to improve the separation of neural activity from noise. TE-Dependent ANAlysis (tedana) is an open-source software tailored to denoising of multi-echo fMRI data. The efficacy of denoising can however be inconsistent, often necessitating manual inspection that precludes its application in large-scale studies where processing is ideally fully automated. Here, we introduce Robusttedana, an optimised denoising pipeline that achieves adequate results at both single-subject and group level. Robust-tedana incorporates Marchenko-Pastur Principal Component Analysis (MPPCA) for effective thermal noise reduction, robust independent component analysis for stabilised signal decomposition, and a modified component classification process. We evaluated its performance on Multi-Band Multi-Echo (MBME) language-task fMRI data from the Australian Epilepsy Project (AEP) using objective measures, comparing to conventional fMRI analysis with and without multi-echo-based denoising. Experts manual evaluation was undertaken on a subset of these data to validate the objective measures. The proposed pipeline both mitigates the prevalence of erroneous attenuation of genuine task activation due to instability of single-subject analysis, and increases the magnitude of group-wise effects. Robust-tedana therefore facilitates advanced analysis of MBME fMRI data in an automated pipeline, including for clinical research assessment of individuals.

bioengineering↗
bioRxiv2025

Beyond the Resection: Surgical White Matter Disruption alters Non-Resected Brain Anatomy

Resective neurosurgery is a cornerstone treatment for many neurological conditions. Although traditionally viewed as localised procedure, increasing evidence from advanced magnetic resonance imaging (MRI) shows that also non-resected anatomy can degenerate following surgery. The relationship between local tissue removal and these postoperative changes remains thus far speculative. Here, we investigate the hypothesis that degenerative changes to surgically preserved grey and white matter are mediated by transneuronal degeneration, a deterioration of intact neuronal populations due to lost axonal input. Using a robust structural and diffusion MRI framework, we first identify widespread postoperative atrophy: pronounced cortical thickness decreases near the resection, and extensive white matter impairments across the ipsilateral hemisphere. Importantly, we then link these alterations to surgical white matter disruption, revealing a sequential network atrophy following neurosurgery. Beyond degenerative effects, we also demonstrate often reported structural network reorganisations as an artefact of image processing, indicating limited capacity for macroscale plasticity post-resection. Key PointsO_LIResective neurosurgery can lead to postoperative atrophy of non-resected grey and white matter. Utilising a robust longitudinal neuroimaging framework, we evaluate these changes as consequences of transneuronal degeneration, demonstrating a sequential atrophy of brain anatomy following the loss of surgically disrupted white matter. C_LIO_LIThe majority of severed connections projected to atrophic cortices near the resection, indicating them to be short association fibers. Consecutive white matter atrophy however affected extensive ipsilateral pathways, highlighting a cascading network effect of resective brain surgery. C_LIO_LIWe did not find evidence to support often reported structural reorganisations of large-scale brain networks post-resection. Yet, we demonstrate that evidence typically interpreted as such can be replicated when using non-robust reconstruction methods. C_LI

neuroscience↗
bioRxiv2025

Testing the Vogt-Bailey Index using task-based fMRI across pulse sequence protocols

Local connectivity analyses in fMRI such as the Vogt-Bailey Index, investigate the prevalence of co-fluctuations in the time-series of adjacent voxels. While there have been in silico assessments of the VB Index, this technique has not yet been assessed in vivo. This study has two aims: first, to assess the VB Index using a task paradigm with well established a priori expectations on the brain region predominantly responsible for executing this task to determine whether the VB Index highlights this area. Second, we investigate if, and how, the spatial resolution of the sequence protocols employed, with their inherent effects on the signal-to-noise ratio, affect the resultant VB maps. A cohort of 10 research volunteers underwent fMRI acquisitions utilising a block design finger tapping experiment. Each volunteer was scanned with three sequence protocols, with all parameters equivalent except for the volume of the voxels. The resulting parametric maps derived using the VB Index were compared with those obtained from the conventional General Linear Model approach. Particular emphasis was placed on the identification of the hand portion of the motor homunculus. Across sequence protocols, the VB Index consistently identified elevated local connectivity in, qualitatively, the same portion of the motor cortex as that yielded by the General Linear Model based on the task paradigm. However, the VB Index also detected elevated local connectivity outside the motor cortex while the General Linear Model results were mostly restricted to the motor cortex. The consistently high VB Index, across sequence protocols, in the cortical region associated with an fMRI task paradigm, despite the approachs agnosticism to that task, provides support for the biological relevance of such local connectivity measures.

neuroscience↗
bioRxiv2024

Enterococcal cell wall remodelling underpins pathogenesis via the release of the Enteroccocal Polysaccharide Antigen (EPA)

Enterococci are opportunistic pathogens displaying a characteristic ovoid shape, typically forming pairs of cells (diplococci) and short chains. Control of cell chain length in Enterococcus faecalis relies on the activity of the major N-acetylglucosaminidase AtlA. The formation of short chains and diplococci is critical during pathogenesis for dissemination in the host and to limit recognition by innate immune effectors such as complement molecules and phagocytes. Here, we identify AtlE, an N-acetylmuramidase that contributes to septum cleavage during stationary phase in the absence of AtlA. AtlE is encoded by the locus required to produce the decoration subunits of the Enterococcal Polysaccharide Antigen (EPA), which mediate evasion of phagocytosis. We show that peptidoglycan hydrolysis by AtlE is essential for pathogenesis and demonstrate that soluble cell wall fragments containing EPA decorations increase the virulence of E. faecalis, suggesting that EPA plays a role as a decoy molecule to evade host defences. This research sheds light on the complex interplay between bacterial cell division, cell wall remodelling, and the host immune system, providing valuable insights into a novel mechanism underlying the virulence of E. faecalis. Author summaryThe major component of the bacterial cell envelope (peptidoglycan) undergoes partial hydrolysis during growth. This process, referred to as remodelling, is required for the incorporation of novel peptidoglycan building blocks, and cell separation at the end of division. In Enterococcus faecalis, only one ubiquitous peptidoglycan hydrolase, named AtlA, has been described so far. AtlA plays a prominent role in septum cleavage and is responsible for the characteristic formation of diplococci and short cell chains. The minimization of cell chain length by AtlA is critical for innate immune evasion and underpins pathogenesis. Here, we identify another ubiquitous peptidoglycan hydrolase named AtlE encoded by the Enterococcal Polysaccharide Antigen (EPA) biosynthetic locus. We show that AtlE displays N-acetylmuramidase activity and requires strain-specific EPA decorations to be active. Whilst AtlE only plays a marginal role in septum cleavage during growth, AtlE is essential for virulence in the zebrafish model of infection. We demonstrate that AtlE activity contributes to release cell wall fragments and promotes phagocyte evasion, indicating that EPA plays a role as a decoy molecule produced by enterococci to counteract host immune defenses.

microbiology↗
bioRxiv2024

Multiscale heterogeneity of white matter morphometry in psychiatric disorders

BackgroundInter-individual variability in neurobiological and clinical characteristics in mental illness is often overlooked by classical group-mean case-control studies. Studies using normative modelling to infer person-specific deviations of grey matter volume have indicated that group means are not representative of most individuals. The extent to which this variability is present in white matter morphometry, which is integral to brain function, remains unclear. MethodsWe applied Warped Bayesian Linear Regression normative models to T1- weighted magnetic resonance imaging data and mapped inter-individual variability in person-specific white matter volume deviations in 1,294 cases (58% male) diagnosed with one of six disorders (attention-deficit/hyperactivity, autism, bipolar, major depressive, obsessive-compulsive and schizophrenia) and 1,465 matched controls (54% male) recruited across 25 scan sites. We developed a framework to characterize deviation heterogeneity at multiple spatial scales, from individual voxels, through inter- regional connections, specific brain regions, and spatially extended brain networks. ResultsThe specific locations of white matter volume deviations were highly heterogeneous across participants, affecting the same voxel in fewer than 8% of individuals with the same diagnosis. For autism and schizophrenia, negative deviations (i.e., areas where volume is lower than normative expectations) aggregated into common tracts, regions and large-scale networks in up to 35% of individuals. ConclusionsThe prevalence of white matter volume deviations was lower than previously observed in grey matter, and the specific location of these deviations was highly heterogeneous when considering voxel-wise spatial resolution. Evidence of aggregation within common pathways and networks was apparent in schizophrenia and autism but not other disorders.

neuroscience↗
bioRxiv2024

The Enterococcal Polysaccharide Antigen: from structure to biosynthesis and function

L-Rhamnose-containing polysaccharides are produced by Streptococci and Enterococci. They define Lancefield serotypes and represent promising candidates for the design of glycoconjugate vaccines. The Enterococcal Polysaccharide Antigen produced by the opportunistic pathogen Enterococcus faecalis plays a critical role in normal growth, division, biofilm formation, antimicrobial resistance, phage susceptibility, and innate immune evasion. Despite the critical role of this polymer for E. faecalis physiology and host-pathogen interactions, little information is available on its structure and biosynthesis. Here, we elucidate the structure of the intact EPA produced by E. faecalis OG1RF. We report the structure of the linkage unit, revealing an unprecedented complexity of the rhamnose backbone and decorations. Finally, we explore the impact of several EPA structural modifications on innate immune evasion and recognition by bacteriophages. This work represents a first step towards the functional characterisation of EPA for the rational design of therapeutic strategies against a group of important pathogens.

microbiology↗
bioRxiv2024

Eigenmodes of the brain: revisiting connectomics and geometry

Eigenmodes can be derived from various structural brain properties, including cortical surface geometry1 and interareal axonal connections comprising an organisms connectome2. Pang and colleagues map geometric and connectome eigenmodes to spatial patterns of human brain activity, assessing whether brain connectivity or geometry provide greater explanatory power of brain function3. The authors find that geometric eigenmodes are superior predictors of cortical activity compared to connectome eigenmodes. They conclude that this supports the predictions of neural field theory (NFT)4, in that "brain activity is best represented in terms of eigenmodes derived directly from the shape of the cortex, thus emphasizing a fundamental role of geometry in constraining dynamics". The experimental comparisons favoring geometric eigenmodes over connectome eigenmodes, in conjunction with specific statements regarding the relative efficacy of geometry in representing brain activity, have been widely interpreted to mean that geometry imposes stronger constraints on cortical dynamics than connectivity5-9. Here, we reconsider the comparative experimental evidence focusing on the impact of connectome mapping methodology. Utilizing established methods to mitigate connectome construction limitations, we map new connectomes for the same dataset, finding that eigenmodes derived from these connectomes reach comparable accuracy in explaining brain activity to that of geometric eigenmodes. We conclude that the evidence presented to support the comparative proposition that "eigenmodes derived from brain geometry represent a more fundamental anatomical constraint on dynamics than the connectome" may require reconsideration in light of our findings. Pang and colleagues present compelling evidence for the important role of geometric constraints on brain function, but their findings should not be interpreted to mean that geometry has superior explanatory power over the connectome.

neuroscience↗
bioRxiv2024

Related PP2C phosphatases Pic3 and Pic12 negatively regulate immunity in tomato to Pseudomonas syringae

Type 2C protein phosphatases (PP2Cs) constitute a large family in most plant species but relatively few of them have been implicated in immunity. To identify and characterize PP2C phosphatases that affect tomato immunity, we used CRISPR/Cas9 to generate loss-of-function mutations in 11 PP2C-encoding genes whose expression is altered in response to immune elicitors or pathogens. We report that two closely related PP2C phosphatases, Pic3 and Pic12, are involved in regulating resistance to the bacterial pathogen Pseudomonas syringae pv. tomato (Pst). Loss-of-function mutations in Pic3 lead to enhanced resistance to Pst in older but not younger leaves, whereas such mutations in Pic12 resulted in enhanced resistance in both older and younger leaves. Overexpression of Pic3 and Pic12 proteins in leaves of Nicotiana benthamiana inhibited resistance to Pst and this effect was dependent on Pic3/12 phosphatase activity and an N-terminal palmitoylation motif associated with localization to the cell periphery. Pic3 but not Pic12 had a slight negative effect on flagellin-associated reactive oxygen species generation, although their involvement in the response to Pst appeared independent of flagellin. RNA-sequencing analysis of Rio Grande (RG)-PtoR wild-type plants and two independent RG-pic3 mutants revealed that the enhanced disease resistance in RG-pic3 older leaves is associated with increased transcript abundance of multiple defense related genes. RG-pic3/RG-pic12 double mutant plants exhibited stronger disease resistance than RG-pic3 or RG-pic12 single mutants. Together, our results reveal that Pic3 and Pic12 negatively regulate tomato immunity in an additive manner through flagellin-independent pathways.

plant biology↗
bioRxiv2023

An ancestral dual function of OmpM as outer membrane tether and nutrient uptake channel in diderm Firmicutes

The outer membrane (OM) in diderm, or Gram-negative, bacteria must be tethered to peptidoglycan (PG) for mechanical stability and to maintain cell morphology. Most diderm phyla from the Terrabacteria group lack well-characterised OM attachment systems such as Brauns lipoprotein, Pal and OmpA, but instead have the OmpM protein. OmpM has a periplasmic region containing an S-layer homology domain and a {beta}-barrel region that is embedded in the OM. Here, we have determined the structure of the most abundant OmpM protein from the diderm firmicute Veillonella parvula by single particle cryogenic electron microscopy (cryo-EM). We reveal an OM portion similar to well-characterised trimeric general porins and a mobile periplasmic PG-binding region. Combining the cryo-EM data with crystal structures, structure predictions and molecular dynamics simulations, we show that the periplasmic region of OmpM likely adopts multiple conformations. Single-channel electrophysiology demonstrates ion conductance properties similar to E. coli OmpF. Finally, we demonstrate via functional assays that the four OmpM paralogues are likely to be the only general porins in V. parvula. Together, our results show that OM tethering and nutrient acquisition are genetically linked in V. parvula (and other diderm Firmicutes), suggesting that concurrent loss of two key OM-related functions, tethering and nutrient uptake, promoted the multiple OM loss events that have been inferred in the Terrabacteria.

biochemistry↗
bioRxiv2023

Connectomes for 40,000 UK Biobank participants: A multi-modal, multi-scale brain network resource

We mapped functional and structural brain networks for more than 40,000 UK Biobank participants. Structural connectivity was estimated with tractography and diffusion MRI. Resting-state functional MRI was used to infer regional functional connectivity. We provide high-quality structural and functional connectomes for multiple parcellation granularities, several alternative measures of interregional connectivity, and a variety of common data pre-processing techniques, yielding more than one million connectomes in total and requiring more than 200,000 hours of compute time. For a single subject, we provide 28 out-of-the-box versions of structural and functional brain networks, allowing users to select, e.g., the parcellation and connectivity measure that best suit their research goals. Furthermore, we provide code and intermediate data for the time-efficient reconstruction of more than 1,000 different versions of a subjects connectome based on an array of methodological choices. All connectomes are available via the UK Biobank data sharing platform and our connectome mapping pipelines are openly available. In this report, we describe our connectome resource in detail for users, outline key considerations in developing an efficient pipeline to map an unprecedented number of connectomes, and report on the quality control procedures that were completed to ensure connectome reliability and accuracy. We demonstrate that our structural and functional connectivity matrices meet a number of quality control checks and replicate previously established findings in network neuroscience. We envisage that our resource will enable new studies of the human connectome in health, disease and aging at an unprecedented scale.

neuroscience↗
bioRxiv2021

Connectome-Based Smoothing (CBS): Concepts, methods, and evaluation

Structural connectomes are increasingly mapped at high spatial resolutions comprising many hundreds--if not thousands--of network nodes. However, high-resolution connectomes are particularly susceptible to image registration misalignment, tractography artifacts, and noise, all of which can lead to reductions in connectome accuracy and test-retest reliability. We investigate a network analogue of image smoothing to address these key challenges. Connectome Spatial Smoothing (CSS) involves jointly applying a carefully chosen smoothing kernel to the two endpoints of each tractography streamline, yielding a spatially smoothed connectivity matrix. We develop computationally efficient methods to perform CSS using a matrix congruence transformation and evaluate a range of different smoothing kernel choices on CSS performance. We find that smoothing substantially improves the identifiability, sensitivity, and test-retest reliability of high-resolution connectivity maps, though at a cost of increasing storage burden. For atlas-based connectomes (i.e. low-resolution connectivity maps), we show that CSS marginally improves the statistical power to detect associations between connectivity and cognitive performance, particularly for connectomes mapped using probabilistic tractography. CSS was also found to enable more reliable statistical inference compared to connectomes without any smoothing. We provide recommendations on optimal smoothing kernel parameters for connectomes mapped using both deterministic and probabilistic tractography. We conclude that spatial smoothing is particularly important for the reliability of high-resolution connectomes, but can also provide benefits at lower parcellation resolutions. We hope that our work enables computationally efficient integration of spatial smoothing into established structural connectome mapping pipelines. HighlightsO_LIWe establish a network equivalent of image smoothing for structural connectomes. C_LIO_LIConnectome Spatial Smoothing (CSS) improves connectome test-retest reliability, identifiability and sensitivity. C_LIO_LICSS also facilitates reliable inference and improves power to detect statistical associations. C_LIO_LIBoth high-resolution and atlas-based connectomes can benefit from CSS. C_LI

neuroscience↗
bioRxiv2020

The efficacy of different preprocessing steps in reducing motion-related confounds in diffusion MRI connectomics

Head motion is a major confounding factor in neuroimaging studies. While numerous studies have investigated how motion impacts estimates of functional connectivity, the effects of motion on structural connectivity measured using diffusion MRI have not received the same level of attention, despite the fact that, like functional MRI, diffusion MRI relies on elaborate preprocessing pipelines that require multiple choices at each step. Here, we report a comprehensive analysis of how these choices influence motion-related contamination of structural connectivity estimates. Using a healthy adult sample (N = 252), we evaluated 240 different preprocessing pipelines, devised using plausible combinations of different choices related to explicit head motion correction, tractography propagation algorithms, track seeding methods, track termination constraints, quantitative metrics derived for each connectome edge, and parcellations. We found that an approach to motion correction that includes outlier replacement and within-slice volume correction led to a dramatic reduction in cross-subject correlations between head motion and structural connectivity strength, and that motion contamination is more severe when quantifying connectivity strength using mean tract fractional anisotropy rather than streamline count. We also show that the choice of preprocessing strategy can significantly influence subsequent inferences about network organization, with the location of network hubs varying considerably depending on the specific preprocessing steps applied. Our findings indicate that the impact of motion on structural connectivity can be successfully mitigated using recent motion-correction algorithms that include outlier replacement and within-slice motion correction. HighlightsO_LIWe assess how motion affects structural connectivity in 240 preprocessing pipelines C_LIO_LIMotion contamination of structural connectivity depends on preprocessing choices C_LIO_LIAdvanced motion correction tools reduce motion confounds C_LIO_LIFA edge weighting is more susceptible to motion effects than streamline count C_LI

neuroscience↗
bioRxiv2019

Maturation and interhemispheric asymmetry in neurite density and orientation dispersion in early childhood

BackgroundThe brains white matter undergoes profound changes during early childhood, which are believed to underlie the rapid development of cognitive and behavioral skills during this period. Neurite density, and complexity of axonal projections, have been shown to change across the life span, though changes during early childhood are poorly characterized. Here, we utilize neurite orientation dispersion and density imaging (NODDI) to investigate maturational changes in tract-wise neurite density index (NDI) and orientation dispersion index (ODI) during early childhood. Additionally, we assess hemispheric asymmetry of tract-wise NDI and ODI values, and longitudinal changes. MethodsTwo sets of diffusion weighted images (DWI) with different diffusion-weighting were collected from 125 typically developing children scanned at baseline (N=125; age range=4.14-7.29; F/M=73/52), 6-month (N=8; F/M=8/0), and 12-month (N=52; F/M=39/13) timepoints. NODDI and template-based tractography using constrained spherical deconvolution were utilized to calculate NDI and ODI values for major white matter tracts. Mixed-effects models controlling for sex, handedness, and in-scanner head motion were utilized to assess developmental changes in tract-wise NDI and ODI. Paired t-tests were used to assess interhemispheric differences in tract-wise NDI and ODI values and longitudinal changes in cross-sectional and 12-month longitudinal analyses, respectively. ResultsMaturational increases in NDI were seen in all major white matter tracts, though we did not observe the expected tract-wise pattern of maturational rates (e.g. fast commissural/projection and slow frontal/temporal tract change). ODI did not change significantly with age in any tract. We observed higher cross-sectional NDI and ODI values in the right as compared to the left hemisphere for most tracts, but no hemispheric asymmetry for longitudinal changes. ConclusionsThese findings suggest that neurite density, but not orientation dispersion, increases with age during early childhood. In relation to NDI growth trends reported in infancy and late-childhood, our results suggest that early childhood may be a transitional period for neurite density maturation wherein commissural/projection fibers are approaching maturity, maturation in long range association fibers is increasing, and changes in limbic/frontal fibers remain modest. Rightward asymmetry in NDI and ODI values, but not longitudinal changes, suggests that rightward asymmetry of neurite density and orientation dispersion is established prior to age 4.

neuroscience↗
bioRxiv2019

Early childhood development of white matter fiber density and morphology

Early childhood is an important period for cognitive and brain development, though white matter changes specific to this period remain understudied. Here we utilize a novel analytic approach to quantify and track developmental changes in white matter micro- and macro-structure, calculated from individually oriented fiber-bundle populations, termed \"fixels\". Fixel-based analysis and mixed-effects models were used to assess tract-wise changes in fiber density and bundle morphology in 73 girls scanned at baseline (ages 4.09-7.02, mean=5.47, SD=0.81), 6-month (N=7), and one-year follow-up (N=42). For comparison, we also assessed changes in commonly utilized diffusion tensor metrics: fractional anisotropy (FA), and mean, radial and axial diffusivity (MD, RD, AD). Maturational increases in fixel-metrics were seen in most major white matter tracts, with the most rapid increases in the corticospinal tract and slowest or non-significant increases in the genu of the corpus callosum and uncinate fasciculi. As expected, we observed developmental increases in FA and decreases in MD, RD and AD, though percentage changes were smaller relative to fixel-metrics. The majority of tracts showed more substantial morphological than microstructural changes. These findings highlight early childhood as a period of dynamic white matter maturation, characterized by large increases in macroscopic fiber bundle size, mild changes in axonal density, and parallel, albeit less substantial, changes in diffusion tensor metrics.

neuroscience↗