Faculty Spotlight: Monica Hurdal

Monica Hurdal is a professor of biomathematics and associate chair for academic affairs in the Department of Mathematics, part of Florida State University’s College of Arts and Sciences. She specializes in brain mapping — developing mathematical models that explain how the brain forms its folds and their connection to neurological disorders. Her research has improved neuroimaging analysis techniques, allowing for the precise analysis of brain structure and function. Hurdal has been an invited speaker at several international conferences, and she is also the director of FSU Math Fun Day, an annual outreach event that engages K-12 students with hands-on activities, presentations, exhibits, and demonstrations showcasing how math applies to everyday life.

Tell us a little about your background, where you’re from and what brought you to FSU.

I’m originally from Canada, and I earned my bachelor’s degree in mathematics, statistics and computer science in 1991 from the University of Waterloo in Ontario, Canada. In 1994, I earned a master’s in applied mathematics at the University of Newcastle, Australia in New South Wales. This is when my mentor, professor D.L. Sean McElwain, introduced me to neuroscience research.

After earning my doctorate in applied mathematics from Queensland University of Technology in Brisbane, Australia in 1999, I looked for mathematical neuroscience opportunities. FSU stood out for its strong research environment. I joined FSU as a postdoctoral research associate in 1998, eager to advance brain modeling research.

Can you break down your area of research for us?

My recent research focuses on developing mathematical models to investigate the biomechanical and biological mechanisms underlying brain folding, the process by which the brain forms its sulci, or grooves, and gyri, or ridges. An approach I use involves Turing patterns, a concept from mathematical biology that explains how natural patterns — such as zebra stripes or leopard spots — arise through the interaction of chemical signals known as activators and inhibitors.

I also explore the biomechanical theory of buckling, which explains how brain folds form by axonal tension. By combining these findings, my models provide insights into brain folding abnormalities such as lissencephaly, a lack of folds, and polymicrogyria, excessive folding. Both abnormalities are linked to neurological disorders and developmental challenges such as delayed motor skills, cognitive impairments and epilepsy.

What inspired you to choose your field of study?

From the start, I wanted to combine my interests in math and biology, so I focused on research in both fields during graduate school. During my work-study programs as a computer programmer, I realized I wanted more challenging, open-ended problems that required deeper mathematical thinking, which led me to pursue a research career.

Can you share an exciting breakthrough in your research that you’re passionate about?

The development of conformal flat maps of the brain using quasiconformal maps has been an exciting breakthrough in my research. This method transforms the brain's curved surface into a flat representation while preserving angles. Early in my career, I used EEG and MRI data, but they had limitations in capturing the brain's complexity. Applying this new method has improved our understanding of neuroimaging data and allows for comparing data across patients more easily, which advances our understanding of brain structure, function and neurological disorders.

What are some of the biggest challenges in your research?

One of the biggest challenges in publishing in academic journals is effectively connecting with researchers across disciplines, as varying terminology across fields often creates communication barriers. Finding dedicated collaborators for long-term, interdisciplinary research is also difficult, and it can take years to build the right team. However, these relationships are crucial because impactful research rarely happens in isolation — it thrives on teamwork and curiosity. Overcoming challenges is part of the reward, leading to meaningful advancements through collaboration, discovery and persistence.

Do you have any exciting upcoming projects or goals you’re working toward?

I’m working with Julie Capece, a doctoral student in biomathematics, who’s implementing a model to better understand brain folding patterns. We plan to analyze ferret brain data, as their brain folding occurs following birth, which is crucial for studying later stages of brain development. Another exciting project is with biomathematics graduate student Kaylie Green in collaboration with the Department of Chemical and Biomedical Engineering, part of the FAMU-FSU College of Engineering, and biologists at the University of North Carolina Wilmington. This research focuses on proteostasis, or how cells maintain protein balance, and analyzes how protein misfolding leads to cell death and affects energy use in cells.

Tell me about your experience as the director of Math Fun Day.

Math Fun Day is a community outreach event hosted by the Department of Mathematics to engage K-12 students, showing them that math is more than just worksheets; it's a fun, interactive and engaging experience. This year marked our 10th event and featured topics like symmetry, fractals, and math in nature led by over 100 volunteers including faculty, staff and students.

What do you want the public to know about the importance of your research?

My research demonstrates how mathematics is a powerful tool that transcends interdisciplinary skills. My developments in mathematical and computational models help researchers ask new questions, analyze complex processes and improve medical visualization techniques. Mathematical approaches are crucial for tackling challenges in neuroscience, leading to breakthroughs in diagnosing and treating neurological disorders. I want the public to see how math fuels scientific discovery and drives progress in health care and beyond.

If your students only learned one thing from you (of course, hopefully they learn much more than that), what would you hope it to be?

In mathematics, it’s typically taught that there’s a right answer to a problem. When it comes to modeling, there isn’t always a single correct solution. I want my students to understand that there are many ways to approach a problem by applying different techniques and theories. The key is to be willing to make mistakes because that’s where real learning happens. Additionally, mathematics is continually evolving. Theories and principles from hundreds of years ago can still find relevance and application in emerging technologies today.