“Computational Modeling of Neuromodulation” by Lauren Madden, PhD Candidate

Description/Abstract: Neuromodulation is a well-established, yet quickly expanding,
field of bioelectronic medicine that involves using electrodes to either stimulate or record
from the nervous system. Within the past decade or so, using computational models
and the principles of electrical biophysics has allowed biomedical engineers to not only
learn more about how neuromodulation devices work, but also make predictions about
how we can better design and program these devices for the patients that need them.
There are many different types of computer models that are built to study the nervous
system, but today we'll be discussing a particular type that integrates many different
factors of biophysical neuroscience - ion channel dynamics, cable theory, and electric
fields.
Biography:
Lauren is a fourth year PhD candidate at the University of Michigan in the
Biomedical Engineering Program's Neural Engineering concentration. Her research
focuses on peripheral neuromodulation, where she is exploring the different factors that
influence how neuromodulation devices interface with the peripheral nervous system.
She earned her B.S. in Neuroscience and a minor in Computer Science at the
University of Minnesota in the Twin Cities. After graduating from her undergraduate
institution in 2018, she worked as an Associate Research and Development Engineer at
Medtronic's Neuromodulation facility in Fridley, Minnesota on the Applied Physics and
Modeling team. After earning her PhD, she hopes to pursue a career as a teaching
professor and continue with neural engineering academic research.