Mark A. Kramer
Professor, Mathematics & Statistics, Boston University
We develop mathematical, statistical, and machine learning/AI approaches to characterize brain activity. Our work is driven by data and a motivation to understand how biological brains work and breakdown.
As mathematicians, we develop biological models of neural dynamics.
Biophysical models of single-neuron dynamics.
Field models of neural population activity in epilepsy.
And, as mathematicians, we get to explore fun, big-picture concepts.
Is the golden ratio an organizing principle for brain rhythms?
Why is 1/f so common in neural field data?
As statisticians/data analysts, we develop computational methods to characterize brain activity.
Machine learning approaches to detect pathological brain rhythms.
Tools to teach neural data analysis.
As neuroscientists, we investigate how the brain functions in health and dysfunctions in disease.
How does epileptic brain activity disrupt healthy brain rhythms?
How do waves of activity travel over the brain during seizures?
How do multiple brain rhythms coordinate to support brain function?