Sir Henry Wellcome Postdoctoral Fellow
My background is in physics, specialising in its application to the field of neuroscience. I am interested in developing new techniques to identify processes in brain disease using Magnetic Resonance Imaging (MRI). My fellowship aims to develop an imaging technique based on diffusion MRI, which produces images sensitive to the tiny motions of water in the brain. I will use my technique to see its potential in identifying brain markers of Parkinson's disease.
I will achieve this using a combination of post-mortem and in vivo imaging, based on a technique known as 'diffusion-weighted steady-state free precession'. More broadly, my research interests span diffusion MRI, susceptibility-based MRI and quantitative MRI, investigating how we can these methods to obtain more information about the composition and structure of the brain.
Over the past few years at Oxford, I have been focused on developing these techniques in the context of post-mortem brain imaging. For a brief explanation of this work, please see this video: https://youtu.be/-QUfZP4NOdg
To see how we are utilising post-mortem imaging in our research, and what datasets we have collected, please visit the Digital Brain Bank: https://open.win.ox.ac.uk/DigitalBrainBank/
The Digital Brain Bank, an open access platform for post-mortem imaging datasets.
Tendler BC. et al, (2022), Elife, 11
Quantifying myelin in crossing fibers using diffusion-prepared phase imaging: Theory and simulations.
Cottaar M. et al, (2021), Magn Reson Med, 86, 2618 - 2634
A method to remove the influence of fixative concentration on postmortem T2 maps using a kinetic tensor model.
Tendler BC. et al, (2021), Hum Brain Mapp
Diffusion MRI data, sulcal anatomy, and tractography for eight species from the Primate Brain Bank
Bryant K. et al, (2021), Brain Structure and Function
Methods for quantitative susceptibility and R2* mapping in whole post-mortem brains at 7T applied to amyotrophic lateral sclerosis
Wang C. et al, (2020), NeuroImage, 222, 117216 - 117216