Kristina M. Zvolanek

This paper develops methods to estimate cerebrovascular reactivity (CVR) amplitude and delay in breath-hold fMRI when PETCO2 data quality is low, using rescaled RVT and deep learning-predicted PETCO2.

This study examines macrovascular and microvascular coupling in adolescents using 4D flow MRI and BOLD reactivity, finding age-related changes in cerebrovascular responses.

This study evaluates ME-ICA's effectiveness in reducing task-correlated head motion artifacts in motor-task fMRI data, showing improved signal clarity and stability in both subject and group analyses.

This paper compares alternative reference signals for mapping cerebrovascular reactivity using breath-hold task BOLD fMRI, showing that RVT and GM-BOLD can produce comparable CVR maps when PETCO2 quality is insufficient.

The paper investigates how data acquisition and modelling choices affect the relationship between baseline cerebral blood flow and BOLD cerebrovascular reactivity, finding that breathing task data and lag-optimization improve correlations.

This paper modifies a resting-state fMRI protocol by adding breathing tasks to improve cerebrovascular reactivity (CVR) characterization and hemodynamic lag estimation.