Derek Kenton Jones

The paper links cerebral oxygen metabolism to gray matter microstructural features in humans using non-invasive MRI methods, finding positive associations between oxygen consumption and soma surface area density.

The paper links structural brain network properties to individual differences in future thinking abilities using MRI and psychometric data.

This study links brain microstructure to neural dynamics by showing that white and grey matter properties significantly correlate with propagation delays measured via MEG.

The paper links infant gut microbiome composition and behavioral responses to maternal unpredictability, showing how microbial metabolism influences behavioral outcomes.

The paper uses MRI and histological analyses to show axonal and myelin changes in a Huntington's Disease mouse model, identifying FR as a potential MRI biomarker for WM microstructure changes.

This paper enhances MEG spatial resolution using BOLD-fMRI and explainable machine learning, achieving high predictive performance and detailed upsampled maps.

This paper introduces multiparametric diffusion MR spectroscopy to estimate cell-type-specific morphology in the human brain by combining diffusion-time-dependent encoding with double-diffusion-encoded spectroscopy.

This paper evaluates ZOOM as an alternative to ZOOMit for cardiac diffusion weighted imaging, showing reduced TE and aliasing artifacts.

This paper develops RCWLS for cardiac DKI to improve signal fitting by combining robust estimation with convexity constraints, showing it reliably captures expected kurtosis patterns and corrects corrupted regions.

This paper demonstrates the feasibility of cardiac diffusion kurtosis imaging (DKI) in humans using high gradient strength MRI, showing non-Gaussian water diffusion behavior and significant radial kurtosis differences.

The paper uses MRI to show age-related changes in cortical microstructure that align with oligodendrocyte gene expression during development.

This study tracks white matter microstructural changes after soccer headers using MRI, finding correlations between impact magnitude and microstructural alterations.

This paper compares two models for mapping brain structure to function in health and psychosis, finding that deep learning outperforms analytical models in predicting functional connectivity in healthy individuals.

This study investigates age-related changes in hippocampal microstructure using diffusion MRI in children and adolescents, finding significant developmental changes in neurites, soma, and mean diffusivity.

This study examines age-related changes in microstructure-informed cortical networks using diffusion MRI data from 8-18 year olds, finding increased global efficiency and mean strength in specific networks.

The paper examines how white matter microstructure in face and body networks relates to perceptual development in children and adolescents.

This paper introduces a weighted generative model of the human connectome that captures both topology and edge-weights, showing improved accuracy over previous models.

This study examines how genetic risk for Alzheimer's disease affects structural brain networks in young adults using MRI and genotype data.

The paper investigates the relationship between structural brain connectivity and schizotypy using diffusion MRI data from two cohorts, finding positive correlations between schizotypy scores and specific graph metrics in sensorimotor and default-mode subnetworks.

This paper estimates axial diffusivity in the NODDI model using high b-value data and shows the impact of noise assumptions on parameter estimates.

This paper develops a surface-based tractography method for short association fibres in the human brain, showing it produces longer streamlines and high cortical coverage but with limited reliability and repeatability.

This paper introduces a non-invasive diffusion MRI method to image microglia and astrocyte activation in vivo, showing it can detect glia proliferation and correlate with histological markers in humans.

This paper introduces hypervoxels to improve neuroimaging analysis by integrating spatial and anatomical information from diffusion MRI data, enhancing detection of white matter effects in ALS.

The paper introduces a method to estimate brain diffusion anisotropy using only 3 gradient directions, showing it works but with increased data variability and metric subestimation.

This study uses ultra-strong gradient MRI to show that myelin changes, not axon density, are linked to premanifest Huntington's disease, with mutation size correlating with myelin levels.

The paper compares methods for computing orientationally-averaged diffusion-weighted MRI signals, finding that MAP-MRI provides better accuracy under low SNR and sparse sampling.

The paper assesses the repeatability of community detection algorithms and graph construction schemes in structural brain networks using Human Connectome Project data, finding optimal pairings for reliable community and hub identification.

This paper identifies challenges in estimating spherical pore size in the human brain using diffusion MRI, highlighting noise biases, signal fraction limits, and sensitivity to cylindrical structures.

This study uses multi-compartment MRI signal analysis to quantify myelin breakdown in premanifest Huntington's disease, finding reduced myelin water fraction and age-related executive function decline.