This is a guest post written by Damon Pham. Damon is a recent graduate from Indiana University, where he was a Wells Scholar (the highest honor for incoming IU students) and all around extraordinaire. He has been part of my research group for the last several years, where one of his main focuses has been … Continue reading How to perform CompCor on HCP fMRI data in R
Dual regression is maybe the simplest way to obtain subject-specific estimates of ICA-based resting-state networks (RSNs). RSNs are regions of the brain that tend to act in a coordinated manner in the absence of a specific task, such as the three shown below (from a 50-component ICA of the Human Connectome Project). Popular ICA toolboxes for … Continue reading The Role of Centering in Dual Regression
I recently got around to reading the high-profile PNAS paper titled “Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates” (Eklund et al. 2016), which called attention to the importance of properly processing and analyzing fMRI data. This lead me to an earlier paper titled “Does parametric fMRI analysis with SPM yield valid … Continue reading How to efficiently prewhiten fMRI timeseries the “right” way
As I wrote about previously, CIFTI files are a new and useful file format for storing, analyzing and visualizing imaging data on the cortical surface AND subcortical areas (gray matter structures and cerebellum). Much of the imaging data available through the Human Connectome Project is in CIFTI format, so anyone who wants to be able to … Continue reading R function to write CIFTI files
[Update: Here is another nice intro to CIFTI files, by Jo Etzel at WashU.] My research group recently began working with the Human Connectome Project (HCP) dataset, a large database of resting-state fMRI, task fMRI and other brain imaging and demographic data for 500+ subjects. The HCP is pretty unique in that it combines a large number of … Continue reading A layman’s guide to working with CIFTI files
I was recently looking online for an explicit derivation of leverage — the diagonals of the “hat matrix” — in simple linear regression. If X is the n-times-p matrix of explanatory variables in a linear model, then the hat matrix is H=X(X’X)-1X’, so called because it puts the “hat” on the predicted values, since Ŷ … Continue reading Derivation and interpretation of leverage in SLR
Today I successfully submitted my first paper to arXiv! We’ve submitted this paper to a journal, but it hasn’t been published yet, so we wanted to get a pre-print up before advertising the corresponding software packages. Unfortunately, the process of submitting to arXiv wasn’t painless. Now that I’ve figured out some of the quirks, however, hopefully your … Continue reading Tips for submitting to arXiv for the first time
Being a statistician working in neuroimaging is a little like living abroad and trying to speak a foreign language. For example, my first language is English, but I spent my first summer as a PhD student doing research at LMU in Munich, Germany. I had taken German in college and could have really basic conversations, … Continue reading Three ways to use MATLAB from R
I’ve recently made several upgrades to my workflow that make me say “WHY OH WHY did it take me this long to start doing this?” One of the big upgrades was using Sublime + Enhanced-R as explained by Alyssa Frazee to send code line-by-line to the Terminal with a simple keystroke. Copy and paste no more! It makes … Continue reading Why I’m a Screen evangelist (and how to get started)
This post is going to be a gentle introduction to MRI, which is a type of brain imaging and my current focus of research. I’m planning a future post or two about my research, so I thought I’d provide a little background for people who don’t know much, if anything, about MRI. I am by … Continue reading What is quantitative MRI, and why does it matter?
