An interview with Jesse Pfammatter, 2020 Epilepsia Open Prize Winner for Basic Science Research

Abstract

To help better analyze and characterize these interactions, I took a significant number of statistics courses—training I found to be a common thread between research opportunities. In the coming years, I hope to continue working closely with the fantastic group of collaborators that have helped make our work possible and enjoyable! WHAT DOES THE EPILEPSIA OPEN PRIZE MEAN FOR YOU, YOUR LABORATORY, RESEARCH INSTITUTE, AND YOUR FUTURE? Read the winning article “An automated, machine learning‐based detection algorithm for spike‐wave discharges (SWDs) in a mouse model of absence epilepsy.”

WHO ARE YOU?

I'm a postdoc working in Mathew Jones' lab in the department of neuroscience at the University of Wisconsin Madison. I did my graduate research in the entirely unrelated discipline of forest entomology where I studied interactions between communities of bark beetles and phoretic mites (which use the beetles for transportation), and how these communities use pine trees and a host of microorganisms for survival. To help better analyze and characterize these interactions, I took a significant number of statistics courses—training I found to be a common thread between research opportunities. Fortunately, Matt was willing to take a chance and brought me on to work in the lab. As it turns out, the forest and brain are actually quite similar places in many respects!

WHAT GOT YOU INTERESTED IN EPILEPSY RESEARCH?

I became interested in epilepsy research almost entirely as a result of many long conversations about science (had over beer) with Matt. As I was finishing grad school, we began to talk more specifically about his research and it seemed like joining his lab would be an exciting and fulfilling new challenge. How I managed to convince him to hire and entomologist into and epilepsy lab is beyond me.

EXPLAIN FOR OUR GENERAL READERSHIP WHAT QUESTION YOUR STUDY ADDRESSED AND HOW DID YOU GO ABOUT DESIGNING YOU STUDY?

We originally set out to analyze a set of EEG recordings for the frequency of absence seizures (spike and wave discharges or SWDs). As we started manually identifying SWDs from these EEGs, it became clear that consistency between and within well trained humans was a bit lower than we'd like. Humans were having trouble scoring these events in a binary fashion (yes/no) because the events truthfully present on much more of a continuum where some events are clear examples of SWDs and others are more ambiguous. It's at this point that we began to develop and algorithm that was capable of consistently identifying events in a way that captured and utilized the variability in SWD presentation that the humans were identifying/struggling with.

WHAT WERE THE RESULTS AND HOW DO YOU INTERPRET YOUR FINDINGS?

We were able to develop a machine learning‐based algorithm which identifies SWDs and assigns each event with a probability‐based score that mirrors human confidence in event identification. Our data show that the confidence scores produced by the algorithm have temporal and proportional correlations with abrupt changes in EEG power bands that are physiologically linked to sleep. It is notable that our findings align with previous work showing shifts in phase‐amplitude coupling up to a minute prior to SWDs and that SWDs are related to sleep timing.

WHAT NEXT STEPS IN EPILEPSY RESEARCH ARE YOU TAKING AND WHAT ARE YOUR CAREER GOALS?

We are currently working on several epilepsy‐related projects in the lab which mostly involve using our analysis methods (we have also published a method for the automated detection of interictal spikes) to unravel the relationship between sleep and epilepsy. Through uncovering the relationship between sleep and epilepsy, we hope to be able to identify novel therapeutics for the treatment of epilepsy for those patients whose disease remains intractable. In the coming years, I hope to continue working closely with the fantastic group of collaborators that have helped make our work possible and enjoyable!

WHAT DOES THE EPILEPSIA OPEN PRIZE MEAN FOR YOU, YOUR LABORATORY, RESEARCH INSTITUTE, AND YOUR FUTURE?

Receiving this award was a very pleasant surprise for me, the lab, and our department. We really pour our hearts into every paper we publish, and it's lovely to be recognized for that effort! Throughout my time in the department of Neuroscience at the UW Madison, I've been intensely supported, in particular by the late department chair, Donata Ortel. Donata would have been so proud of this award as she was of all accolades our department received. Without her help, my research truly would not be possible.

Read the winning article “An automated, machine learning‐based detection algorithm for spike‐wave discharges (SWDs) in a mouse model of absence epilepsy.”