Alex Bowring is a DPhil in Population Health student based in the Big Data Institute at the University of Oxford. His research is centred on functional MRI, with a particular focus on statistical methodology for neuroimaging analyses and developing open science practices. He is currently applying newly developed statistical methods to obtain precise confidence statements about where activation occurs in the brain for population neuroimaging studies, where thousands of subjects have been scanned. As well as this, he is also working on a software comparison project to understand the differences between the main neuroimaging software packages used for fMRI analyses.
Prior to starting a DPhil, he obtained a BSc in Mathematics from the University of Warwick in 2015. Following this he worked as a Research Assistant in the Institute of Digital Healthcare at the University of Warwick, where he assisted Dr. Camille Maumet and Professor Thomas Nichols in developing standard practices for data sharing and meta-analysis in neuroimaging as part of the project "Transforming Statistical Methodology for Neuroimaging Meta-Analysis
Variability in the analysis of a single neuroimaging dataset by many teams.
Botvinik-Nezer R. et al, (2020), Nature, 582, 84 - 88
Confidence Sets for Cohen’s d Effect Size Images
Bowring A. et al, (2020)
Spatial confidence sets for raw effect size images.
Bowring A. et al, (2019), NeuroImage, 203