Imaging and modelling brain physiology with functional MRI
Avery J.L. Berman
Postdoctoral fellow
Tuesday, March 2, 2021
Virtual talk via Zoom

Functional magnetic resonance imaging (fMRI) based on the Blood Oxygenation Level-Dependent (BOLD) signal has revolutionized human neurosciences by providing a non-invasive tool for dynamically mapping brain activity without the use of ionizing radiation or exogenous contrast agents. BOLD fMRI, whereby the oxygen saturation of hemoglobin in blood modulates the MRI signal level, is influenced by a wide range of biophysical and physiological factors. This makes BOLD fMRI challenging to relate to both the underlying neuronal activity and brain physiology. In this talk, I will overview my efforts to make calibrated fMRI – a quantitative technique that can tease apart the metabolic and hemodynamic contributions to the BOLD signal – more widely accessible through improved biophysical signal modelling and image acquisition. I will then describe my contributions to pulse sequence development for performing high spatial resolution fMRI at 7 tesla, where I demonstrated functional activation at 0.6-mm isotropic voxel size – the highest published in vivo spatial resolution for human fMRI using a whole-head receiver coil. Finally, I will outline my proposed research program to advance imaging of microvascular physiology for both basic and clinical neurosciences.


Avery Berman, PhD, is a postdoctoral fellow in Radiology at Harvard Medical School working at the Athinoula A. Martinos Center for Biomedical Imaging at the Massachusetts General Hospital in Charlestown, MA. He received a BSc in Physics at the University of Victoria and an MSc in Medical Radiation Physics and a PhD in Biomedical Engineering at McGill University, both under the supervision of Prof. Bruce Pike. His PhD thesis was on the development of advanced biophysical models to extract quantitative physiological parameters from the Blood Oxygenation Level-Dependent (BOLD) functional MRI signal. His postdoctoral training has been under the supervision of Dr. Jonathan Polimeni, and has focused on developing methods to improve the acquisition and modelling of high spatial resolution functional MRI at ultra-high magnetic field.