Kevin Murphy

Neuroendocrine influences on dynamic cerebrovascular function and implications for functional MRI

This study examines how menstrual-related ovarian hormones affect dynamic cerebrovascular function using MRI and hormone measurements, finding significant neuroendocrine influences on vascular reactivity and hemodynamic response.

Endocrine modulation of cortical and retinal blood flow across the menstrual cycle

This study examines how ovarian hormones affect cerebral and retinal blood flow across the menstrual cycle, finding that estrogen increases blood flow in both the brain and eye, while progesterone affects the brain alone.

Imaging brain vascular function in Cystic Fibrosis: an MRI study of cerebral blood flow and brain oxygenation

This study uses MRI to examine brain blood flow and oxygen metabolism in patients with cystic fibrosis, finding elevated cerebral metabolic rate of oxygen consumption compared to healthy controls.

Velocity-selective arterial spin labelling bolus duration measurements: Implications for consensus recommendations

This paper measures bolus duration in VSASL MRI and shows that imaging after the trailing edge arrives can underestimate perfusion, suggesting adjustments to experimental design.

Alzheimer's genetic risk effects on cerebral blood flow are spatially consistent and proximal to gene expression across the lifespan

This study shows that Alzheimer's genetic risk reduces cerebral blood flow consistently across age groups and is linked to nearby gene expression.

Vascular physiology drives functional brain networks

This study shows vascular regulation influences fMRI signals in specific brain networks, with some networks dominated by neuronal stimuli and others by vascular stimuli.

A frequency-domain machine learning method for dual-calibrated fMRI mapping of oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen consumption (CMRO2)

This paper introduces a machine learning method for dual-calibrated fMRI to estimate OEF and CMRO2, showing reduced computation time, error, and bias compared to existing methods.