About me

I have a PhD in Biostatistics with a specialty in the analysis of fMRI data. I am currently working as a Research Scientist in the lab of Russ Poldrack at Stanford University. You can check out my CV for the nitty gritty.


Handbook of Functional MRI Data Analysis by Russel A Poldrack, Jeanette Mumford and Thomas E Nichols

Learning resources

Get your learn on. The MumfordBrainStats YouTube channel and Tumblr covers a wide range of topics related to the analysis of fMRI data as well as some non-Neuroimaging tutorials. Here are a few examples of topic covered.

  • Learning Mixed Models? The MumfordBrainStats Mixed Models Series was designed to help users of lmer() in R gain more intuition about their models and includes a companion bookdown with code and examples

  • Mean Centering Regressors This is an old one, but a commonly asked question. Why do we mean center? Is it always necessary? This document is a quick summary of when you definitely need mean centering and when you can save yourself a few lines of code.

  • Just getting started with fMRI? Check out my End of Summer Cram Session.

  • What makes an fMRI experiment efficient? This series on efficiency of fMRI designs explains the concept and supplies code so you can design your own efficient study.

  • Collinearity…what is it? Is it bad? Should I orthogonalize?. The answer to the last question is a firm NO, but this series answers all of these questions and more.

  • Calculating percent signal change with FSL. This is an old one! Explains what featquery does and why you probably shouldn’t use it (unless they’ve changed it, but I don’t think so). Most importantly, the calculation is simple and why not do it yourself so you are 100% sure what was done?