Biology subjects

Jones, D. K.

Publications and source records attributed to Jones, D. K..

47 records · Page 3Linked to original sources

bioRxiv2020

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 0 - 6000 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=6000 s/mm2, median R2 = .34; b=4000 s/mm2, median R2 = .29; b=2400 s/mm2, median R2 = .21; b=1200 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.

neuroscience↗

bioRxiv2019

A microtranslatome coordinately regulates sodium and potassium currents in the heart

Catastrophic arrhythmias and sudden cardiac death can occur with even a small imbalance between inward sodium currents and outward potassium currents, but mechanisms establishing this critical balance are not understood. Here, we show that mRNA transcripts encoding INa and IKr channels (SCN5A and hERG, respectively) are associated in defined complexes during protein translation. Using biochemical, electrophysiological and single-molecule fluorescence localization approaches, we find that roughly half the hERG translational complexes contain SCN5A transcripts. Moreover, the transcripts are regulated in a way that alters functional expression of both channels at the membrane. Association and coordinate regulation of transcripts in discrete \"microtranslatomes\" represents a new paradigm controlling electrical activity in heart and other excitable tissues.

cell biology↗

bioRxiv2019

Asymptotic Behavior of the Direction-Averaged Diffusion-Weighted MRI Signal using Different B-Tensor Encoding Schemes

PurposeIt has been shown previously that for the conventional Stejskal-Tanner pulsed gradient, or linear tensor encoding (LTE), as well as planar tensor encoding (PTE) and in tissue in which diffusion exhibits a stick-like geometry, the diffusion-weighted MRI signal at extremely high b-values follows a power-law. Specifically, the signal decays as a [Formula] in LTE and 1/b in PTE. Here, the direction-averaged signal for arbitrary diffusion encoding waveforms is considered to establish whether power-law behaviors occur with other encoding wave-forms and for other (non-stick-like) diffusion geometries.\n\nMethodsWe consider the signal decay for high b-values for encoding geometries ranging from 2-dimensional planar tensor encoding (PTE), through isotropic or spherical tensor encoding (STE) to linear tensor encoding. When a power-law behavior was suggested, this was tested using in-silico simulations and in-vivo using an ultra-strong gradient (300 mT/m) Connectom scanner.\n\nResultsThe results show that using an axisymmetric b-tensor a power-law only exists for two scenarios: For stick-like geometries, (i) the already-discovered LTE case; and (ii) for pure planar encoding. In this latter case, to first order, the signal decays as 1/b. Our in-silico and in-vivo experiments confirm this 1/b relationship.\n\nConclusionA complete analysis of the power-law dependencies of the diffusion-weighted signal at high b-values has been performed. Only two forms of encoding result in a power-law dependency, pure linear and pure planar tensor encoding and when the diffusion geometry is stick-like. The different exponents of these encodings could be used to provide independent validation of the presence of stick-like geometries in-vivo.

bioengineering↗

bioRxiv2019

The dot-compartment revealed? Diffusion MRI with ultra-strong gradients and spherical tensor encoding in the living human brain

The so-called \"dot-compartment\" is conjectured in diffusion MRI to represent small spherical spaces, such as cell bodies, in which the diffusion is restricted in all directions. Previous investigations inferred its existence from data acquired with directional diffusion encoding which does not permit a straightforward separation of signals from sticks (axons) and signals from dots. Here we combine isotropic diffusion encoding with ultra-strong diffusion gradients (240 mT/m) to achieve high diffusion-weightings with high signal to noise ratio, while suppressing signal arising from anisotropic water compartments with significant mobility along at least one axis (e.g., axons). A dot-compartment, defined to have apparent diffusion coefficient equal to zero and no exchange, would result in a non-decaying signal at very high b-values (b {gtrsim} 7000 s/mm2). With this unique experimental setup, a residual yet slowly decaying, signal above the noise floor for b-values as high as 15000 s/mm2 was seen clearly in the cerebellar grey matter (GM), and in several white matter (WM) regions to some extent. Upper limits of the dot-signal-fraction were estimated to be ~2% in cerebellar GM and ~0.2% in WM. By relaxing the assumption of zero diffusivity, the signal at high b-values in cerebellar GM could be represented more accurately by an isotropic water pool with a low apparent diffusivity of 0.11 {micro}m2/ms and a substantial signal fraction of ~7-16%. This remaining signal at high b-values has potential to serve as a novel and simple marker for isotropically-restricted water compartments in cerebellar GM.

neuroscience↗

bioRxiv2019

Dimensionality Reduction of Diffusion MRI Measures for Improved Tractometry of the Human Brain

Various diffusion MRI measures have been proposed for characterising tissue microstructure over the last 15 years. Despite the growing number of experiments using different diffusion 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. In this work, we first demonstrate redundancies in the amount of information captured by 10 diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI) measures. Using a data-reduction approach, we identified two biologically-interpretable components that capture 80% of the variance in commonly-used DTI and HARDI measures profiled along 22 brain pathways extracted from typically developing children aged 8 - 18 years (n = 36). 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 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. Our results also suggest that HARDI measures are more sensitive at detecting age-related changes in tissue microstructure than DTI measures.

neuroscience↗

bioRxiv2019

Optimization of graph construction can significantly increase the power of structural brain network studies

Structural brain networks derived from diffusion magnetic resonance imaging data have been used extensively to describe the human brain, and graph theory has allowed quantification of their network properties. Schemes used to construct the graphs that represent the structural brain networks differ in the metrics they use as edge weights and the algorithms they use to define the network topologies. In this work, twenty graph construction schemes were considered. The schemes use the number of streamlines, the fractional anisotropy, the mean diffusivity or other attributes of the tracts to define the edge weights, and either an absolute threshold or a data-driven algorithm to define the graph topology. The test-retest data of the Human Connectome Project were used to compare the reproducibility of the graphs and their various attributes (edges, topologies, graph theoretical metrics) derived through those schemes, for diffusion images acquired with three different diffusion weightings. The impact of the scheme on the statistical power of the study and on the number of participants required to detect a difference between populations or an effect of an intervention was also calculated. The reproducibility of the graphs and their attributes depended heavily on the graph construction scheme. Graph reproducibility was higher for schemes that used thresholding to define the graph topology, while data-driven schemes performed better at topology reproducibility. Additionally, schemes that used thresholding resulted in better reproducibility for local graph theoretical metrics, while data-driven schemes performed better for global metrics. Crucially, the number of participants required to detect a difference between populations or an effect of an intervention could change by a large factor depending on the scheme used, affecting the power of studies to reveal the effects of interest.

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

The causal structure of age-dependent limbic decline: fornix white matter glia damage causes hippocampal grey matter damage, not vice versa.

Aging leads to gray and white matter decline but their causation remains unclear. We explored two broad classes of models of age and dementia risk related brain changes. The first class of models emphasises the importance of gray matter: age and risk-related processes cause neurodegeneration and this causes damage in associated white matter tracts. The second class of models reverses the direction of causation: aging and risk factors cause white matter damage and this leads to gray matter damage. We compared these models with linear mediation analysis and quantitative multi-modal MRI indices (from diffusion, quantitative magnetization transfer and relaxometry imaging) of tissue properties in two limbic structures implicated in age-related memory decline: the hippocampus and the fornix in 166 asymptomatic individuals (aged 38 - 71 years). Aging was associated with apparent glia but not axon density damage in the fornix. Mediation analysis unambiguously supported white matter damage causing gray matter decline; controlling for fornix glia damage, the correlation between age and hippocampal damage disappears, but not vice versa. Fornix and hippocampal tissue loss were both associated with reductions in episodic memory performance. The implications of these findings for neuroglia and neurodegenerative models of aging and late onset dementia are discussed.

neuroscience↗

bioRxiv2018

Adipokines contribute to central-obesity related reductions in myelin-sensitive MRI indices in the fornix.

Midlife obesity is a risk factor of late onset Alzheimers disease (LOAD) but why this is the case remains unknown. As systemic inflammation is involved in both conditions, one possibility is that obesity-related neuroinflammation may contribute to the development of LOAD. Neuroinflammation is closely linked to white matter myelin loss, and this can be measured in vivo with quantitative magnetization transfer (qMT) imaging. Here, we investigated whether differences in obesity measures, i.e., in Waist Hip Ratio (WHR), abdominal visceral and subcutaneous fat volume fractions and Body Mass Index (BMI), were associated with reductions in qMT indices of apparent myelin in temporal white matter pathways involved in LOAD (i.e., the fornix, the parahippocampal cingulum and the uncinate fasciculus compared with whole brain and cortico-spinal white matter) in 166 cognitively healthy individuals (38-71 years of age). Obesity-related effects on myelin-sensitive markers were contrasted with differences in apparent axon density from dual-shell diffusion Neurite Orientation Dispersion and Density Imaging (NODDI). Differences in WHR and in visceral fat volume fractions were negatively correlated with differences in qMT estimates of apparent myelin and tissue metabolism in the fornix but not with any other microstructural components. These correlations were not explained by demographic (age, sex, education), health (hypertension, alcohol consumption, sedentary lifestyle) or genetic (APOE genotype, family history of dementia) risk factors of LOAD. Furthermore, differences in the ratio of plasma concentrations of leptin and adiponectin were also positively correlated with differences in C-Reactive Protein concentrations, and contributed significantly to the correlations between central obesity and myelin-sensitive metrics in the fornix. These results are consistent with the view that visceral fat-related chronic inflammation may damage white matter myelin in limbic regions, known to be vulnerable to LOAD pathology.

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↗

bioRxiv2018

Superoanterior Fasciculus (SAF): Novel fiber tract revealed by diffusion MRI fiber tractography

Substantial progress in acquisition, processing, and analysis boosted the reliability of diffusion-weighted MRI and increased the accuracy of mapping white matter pathways with fiber tractography. Since the introduction of region of interest (ROI) based virtual dissection by Conturo et al. in 1999, researchers have used tractography to identify white matter pathways, which faithfully represented previously known structures revealed by dyeing studies or post-mortem descriptions. The reconstructed streamlines are subjects of bundle-specific in vivo investigations to show differences between groups (e.g., comparing fractional anisotropy (FA) between patients and healthy controls) or to describe the relation between diffusion scalars and metrics of interest (e.g.: normal aging or changes due to learning). By applying a reverse strategy in using diffusion-weighted MRI tractography first, then supporting the findings with other techniques, we have identified a bilateral tract in the frontal cortex - the superoanterior fasciculus (SAF). The tract resembles the anterior shape of the cingulum bundle, but is located more frontally. To erase the chance that our findings are confounded by acquisition, processing or modeling artifacts, we analyzed a total of 421 subjects from four cohorts with different acquisition schemes and diverse processing pipelines. The findings were also completed with other non-MRI techniques, such as polarized light microscopy and dissection. Tractography results demonstrate a long pathway and are consistent among cohorts, while dissection indicates a series of U-shaped fibers connecting adjacent gyri. In conclusion, we hypothesize that these consecutive U-shaped fibers emerge to form a pathway, thereby resulting in a multicomponent bundle.

neuroscience↗