Arthur P C Spencer

This study evaluates microstructure-weighted connectomes using diffusion MRI data and finds that DePerp provides the most consistent structure-function coupling across spatial scales.

This study compares isotropic ADC-fMRI and BOLD-fMRI in detecting resting-state networks and grey-to-white matter connectivity, finding ADC more sensitive to structural grounding and functional coupling.

The paper investigates negative BOLD responses using interleaved TMS-fMRI and dfMRI in the human brain, finding no ADC-fMRI response and suggesting sensitivity to subtle neural activity in ipsilateral regions.

This paper introduces directed connectomics using bicommunities to reveal asymmetric pathways in brain networks and validates them with electrophysiological data.

This paper develops a whole-brain model to predict conduction velocity from MRI-derived microstructural features, explaining 29% of variance in neurophysiological conduction velocity.

This study uses BOLD- and ADC-fMRI to investigate how the lateral superior colliculus contributes to the transition from static to dynamic vision in rats.

This study introduces isotropic ADC-fMRI to detect grey and white matter activity, showing it is more temporally specific than BOLD-fMRI and provides balanced mapping of both brain regions.

This study compares BOLD and ADC-fMRI in functional connectivity, finding ADC-fMRI provides more robust white matter connectivity and higher inter-subject similarity.

This study compares ADC-fMRI and BOLD-fMRI to show ADC-fMRI provides complementary insights into brain function by detecting neuromorphological activity in white matter and revealing functional organisation of visual pathways.

This study evaluates ADC-fMRI's dependence on haemodynamics during breath-hold and resting-state conditions, finding it less affected by vascular contributions compared to dfMRI and BOLD.

This paper evaluates deep clustering methods for improving dynamic functional connectivity analysis in fMRI data, showing that deep autoencoders outperform traditional methods in capturing temporal properties.

This paper develops an age-specific probabilistic white matter atlas for children aged 6-8 years, showing improved accuracy in diffusion metrics compared to adult templates and revealing FA reductions in treated children.