Biology subjects

Drakesmith, M.

Publications and source records attributed to Drakesmith, M..

6 recordsLinked to original sources

bioRxiv2021

Validating Pore Size Estimates in a Complex Microfibre Environment on a Human MRI System

PurposeRecent advances in diffusion-weighted MRI provide restricted diffusion signal fraction and restricting pore size estimates. Materials based on co-electrospun oriented hollow cylinders have been introduced to provide validation for such methods. This study extends this work, exploring accuracy and repeatability using an extended acquisition on a 300 mT/m gradient human MRI scanner, in substrates closely mimicking tissue, i.e., non-circular cross-sections, intra-voxel fibre crossing, intra-voxel distributions of pore-sizes and smaller pore-sizes overall. MethodsIn a single-blind experiment, diffusion-weighted data were collected from a biomimetic phantom on a 3T Connectom system using multiple gradient directions/diffusion times. Repeated scans established short-term and long-term repeatability. The total scan time (54 minutes) matched similar protocols used in human studies. The number of distinct fibre populations was estimated using spherical deconvolution, and median pore size estimated through the combination of CHARMED and AxCaliber3D framework. Diffusion-based estimates were compared with measurements derived from scanning electron microscopy. ResultsThe phantom contained substrates with different orientations, fibre configurations and pore size distributions. Irrespective of one or two populations within the voxel, the pore-size estimates (~5m) and orientation-estimates showed excellent agreement with the median values of pore-size derived from scanning electron microscope and phantom configuration. Measurement repeatability depended on substrate complexity, with lower values seen in samples containing crossing-fibres. Sample-level repeatability was found to be good. ConclusionWhile no phantom mimics tissue completely, this study takes a step closer to validating diffusion microstructure measurements for use in vivo by demonstrating the ability to quantify microgeometry in relatively complex configurations.

biophysics↗

bioRxiv2020

Estimating intra-axonal axial diffusivity in the presence of fibre orientation dispersion

To estimate microstructure-related parameters from diffusion MRI data, biophysical models make strong, simplifying assumptions about the underlying tissue. The extent to which many of these assumptions are valid remains an open research question. This study was inspired by the disparity between the estimated intra-axonal axial diffusivity from literature and that typically assumed by the Neurite Orientation Dispersion and Density Imaging (NODDI) model (d[boxV] = 1.7m2/ms). We first demonstrate how changing the assumed axial diffusivity results in considerably different NODDI parameter estimates. Second, we illustrate the ability to estimate axial diffusivity as a free parameter of the model using high b-value data and an adapted NODDI framework. Using both simulated and in vivo data we investigate the impact of fitting to either real-valued or magnitude data, with Gaussian and Rician noise characteristics respectively, and what happens if we get the noise assumptions wrong in this high b-value and thus low SNR regime. Our results from real-valued human data estimate intra-axonal axial diffusivities of ~ 2 - 2.5m2/ms, in line with current literature. Crucially, our results demonstrate the importance of accounting for both a rectified noise floor and/or a signal offset to avoid biased parameter estimates when dealing with low SNR data.

neuroscience↗

bioRxiv2020

Imaging Microglia and Astrocytes non-invasively using Diffusion MRI

Glia, and particularly microglia, are increasingly implicated in the pathophysiology of psychiatric and neurodegenerative disorders. However, to date the only methods for imaging these cells in vivo involve either invasive procedures (e.g. multi-photon imaging in rodents) or TSPO-PET radiotracers, which afford low resolution and specificity, since TSPO expresses across multiple cell types. Here, we present a non-invasive diffusion-weighted MRI method to image changes in glia morphometry in vivo. Using two rat models of neuroinflammation, with and without neurodegeneration, we demonstrate that diffusion-weighted MRI carries the fingerprint of microglia and astrocytes activation, and that specific signatures from each population can be quantified non-invasively. We demonstrate that the method can further detect glia proliferation, and provide a quantitative account of neuroinflammation regardless of the existence of a concomitant neuronal loss. We prove the translational value of the approach showing significant correlations between MRI and histological microglia markers measured across different brain regions in humans. This framework holds the potential to transform basic and clinical research by providing a tool to clarify the role of inflammation in health and disease across the lifespan.

neuroscience↗

bioRxiv2019

Electrophysiological network alterations in adults with copy number variants associated with high neurodevelopmental risk

Rare copy number variants associated with increased risk for neurodevelopmental and psychiatric disorders (referred to as ND-CNVs) are characterized by heterogeneous phenotypes thought to share a considerable degree of overlap. Altered neural integration has often been linked to psychopathology and is a candidate marker for potential convergent mechanisms through which ND-CNVs modify risk; however, the rarity of ND-CNVs means that few studies have assessed their neural correlates. Here, we used magnetoencephalography (MEG) to investigate resting-state oscillatory connectivity in a cohort of 42 adults with ND-CNVs, including deletions or duplications at 22q11.2, 15q11.2, 15q13.3, 16p11.2, 17q12, 1q21.1, 3q29, and 2p16.3, and 42 controls. We observed decreased connectivity between occipital, temporal and parietal areas in participants with ND-CNVs. This pattern was common across genotypes and not exclusively characteristic of 22q11.2 deletions, which were present in a third of our cohort. Furthermore, a data-driven graph theory framework enabled us to successfully distinguish participants with ND-CNVs from unaffected controls using differences in node centrality and network segregation. Together, our results point to alterations in electrophysiological connectivity as a putative common mechanism through which genetic factors confer increased risk for neurodevelopmental and psychiatric disorders.

neuroscience↗

bioRxiv2018

Mapping axon conduction delays in vivo from microstructural MRI

The conduction velocity (CV) of action potentials along axons is a key neurophysiological property central to neural communication. The ability to estimate CV in humans in vivo from non-invasive MRI methods would therefore represent a significant advance in neuroscience. However, there are 2 major challenges that this paper aims to address: (1) much of the complexity of the neurophysiology of action potentials cannot be captured with currently available MRI techniques. Therefore, we seek to establish the variability in CV that can be captured when predicting CV purely from parameters that can be estimated from MRI (axon diameter and g-ratio); and (2) errors inherent in existing MRI-based biophysical models of tissue will propagate through to estimates of CV, the extent to which is currently unknown. Issue (1) is investigated by performing a sensitivity analysis on a comprehensive model of axon electrophysiology and determining the relative sensitivity to various morphological and electrical parameters. The investigations suggest that 89.2 % of the variance in CV is accounted for by variation in AD and g-ratio. The observed dependency of CV on AD and g-ratio is well characterised by a previously reported model by Rushton. Issue (2) is investigated through simulation of diffusion and relaxometry MRI data for a range of axon morphologies, applying models of restricted diffusion and relaxation processes to derive estimates of axon volume fraction (AVF), AD and g-ratio and estimating CV from the derived parameters. The results show that errors in the AVF have the biggest detrimental impact on estimates of CV, particularly for sparse fibre populations (AVF< 0.3). CV estimates are most accurate (below 5% error) where AVF is above 0.3, g-ratio is between 0.6 and 0.85 and AD is below 10 {micro}m. Fortunately, these parameter bounds are typically satisfied by most myelinated axons. In conclusion, we demonstrate that accurate CV estimates can be inferred in axon populations across a range of configurations, except in some exceptional cases or where axonal density is low. As a proof of concept, for the first time, we generated an in vivo map of conduction velocity in the human corpus callosum with estimates consistent with values previously reported from invasive electrophysiology in primates.

neuroscience↗

bioRxiv2018

Genetic risk for schizophrenia and developmental delay is associated with shape and microstructure of midline white matter structures

Genomic copy number variants (CNVs) are amongst the most highly penetrant genetic risk factors for neuropsychiatric disorders. The scarcity of carriers of individual CNVs and their phenotypical heterogeneity limits investigations of the associated neural mechanisms and endophenotypes. We applied a novel design based on CNV penetrance for schizophrenia and developmental delay that allows us to identify structural sequelae that are most relevant to neuropsychiatric disorders. Our focus on brain structural abnormalities was based on the hypothesis that convergent mechanisms contributing to neurodevelopmental disorders would likely manifest in the macro- and microstructure of white matter and cortical and subcortical grey matter. 21 adult participants carrying neuropsychiatric risk CNVs (including those located at 22q11.2, 15q11.2, 1q21.1, 16p11.2, and 17q12) and 15 age- and gender matched controls underwent T1-weighted structural, diffusion and quantitative T1 relaxometry MRI.\n\nThe macro- and microstructural properties of the cingulum bundles were associated with penetrance for both developmental delay and schizophrenia, in particular curvature along the anterior-posterior axis (Sz: pcorr=0.026; DD: pcorr=0.035) and intracellular volume fraction (Sz: pcorr=0.019; DD: pcorr=0.064) Further principal component analysis showed alterations in the interrelationships between the volumes of several mid-line white matter structures (Sz: pcorr=0.055; DD, pcorr=0.027). In particular, the ratio of volumes in the splenium and body of the corpus callosum was significantly associated with both penetrance scores (Sz: p=0.037; DD; p=0.006). Our results are consistent with the notion that a significant alteration in developmental trajectories of mid-line white-matter structures constitutes a common neurodevelopmental aberration contributing to risk for schizophrenia and intellectual disability.

neuroscience↗