I am the creator of Andy’s Brain Blog, a website that hosts tutorials and videos about neuroimaging analysis from start to finish in all the major software packages (AFNI, SPM, and FSL). Since founding the blog in 2012, I have created 300 videos about neuroimaging analysis, connectivity, E-Prime, and other topics related to cognitive neuroscience. As of 2018, the blog’s YouTube channel has over four thousand subscribers and over one million views. I continue to produce and edit new tutorials, in addition to answering questions from readers.
An expert in the fMRI packages AFNI, SPM, and FSL, I have worked as a neuroimaging consultant for several research laboratories around the world, including UC Irvine, Michigan State University, Radboud University, University of Antwerp, McLean Hospital at Harvard University, and others. My teaching of fMRI, surface-based morphometry, and white matter tractography have led to invited talks and workshops at institutions such as the University of Rochester, the National Institutes of Health, and University of Massachusetts Amherst. My research focuses on the role of prediction within the medial prefrontal cortex, and how this applies to domains such as pain, cognitive control, and linguistic processing.
Originally from the Midwest, I received my B.A. at Carleton College and completed my Ph.D. in cognitive neuroscience at Indiana University. I currently work as a postdoctoral fellow at Haskins Laboratories in New Haven, Connecticut.
When creating tutorial videos or assisting clients at other universities, I always ask myself: How would I like to be taught? When I began my neuroimaging career I often found documentation about neuroimaging analysis difficult to follow, and I assumed others faced the same obstacles I did. I began my first set of online videos as screencasts which made it easy to replicate the steps to do a certain procedure, a format that I've continued to build upon. As I taught courses and workshops at different universities, I discovered common questions about neuroimaging analysis - What does the General Linear Model look like? Is this a circular analysis? What is the best way to model my data? - and paid attention to which illustrations and analogies worked best at clarifying these concepts. I use these illustrations and analogies in my videos - see, for example, my tutorial series on FreeSurfer.
With the advent of online neuroimaging databases, it is now possible for anyone with a computer and an Internet connection to do fMRI analysis. This is especially important for students at smaller colleges and universities without an MRI scanner; a decade ago, it would be nearly impossible for a student at one of these institutions to have any experience with fMRI analysis.
My goal is to make neuroimaging analysis understandable and accessible for anyone around the globe. Undergraduates seeking to do graduate work in the cognitive neurosciences will now have the tools they need to be competitive applicants; graduate students and postdocs will find answers to basic problems and will have an online forum for discussion.
Above all, I aim to make learning fMRI analysis enjoyable. Neuroimaging is a complex field that draws upon physics, physiology, statistics, experimental design, and much more. The first steps toward learning it can be daunting, but they don't have to be. By explaining concepts clearly, concisely, and with a bit of humor, I hope to empower the next generation of neuroimaging researchers to realize their full potential.