Otto Hahn Medal for Rachel Zsido and Markus Frey
Every year, the Max Planck Society honors young scientists with the Otto Hahn Medal for outstanding scientific achievements. This year, Rachel Zsido from the Department of Neurology and Markus Frey from the Department of Psychology at the Max Planck Institute for Human Cognitive and Brain Sciences (MPI CBS) received two of the coveted awards. Here they answer three questions about their research in a short interview.
Your dissertation has just been awarded the Otto Hahn Medal. What makes your work so special?
Rachel Zsido:
The title of my dissertation was, "Ovarian hormones affect brain structure, function, and chemistry: a neuropsychiatric framework for female brain health." In it, I try to answer these questions: How do reproductive aging and sex hormones shape brain structure, function, and chemistry across the lifespan, and can this help us better understand risk for depression and dementia? The underrepresentation of women in neuroscience directly limits opportunities for fundamental scientific discovery; and without basic knowledge of the biological underpinnings of sex differences, we cannot address critical sex-related differences in pathology.
Markus Frey:
My dissertation addresses the interface between machine learning and neuroscience and explores what opportunities there are for interdisciplinary collaboration. Researchers in the field of machine learning look to neuroscience for inspiration to build intelligent machines, and neuroscience uses the tools developed in machine learning to explore their datasets. In my research, I explored how these models can be used to explain datasets, such as from fMRI or electrophysiology experiments.
In one of my projects, we were interested in data derived from functional magnetic resonance imaging (fMRI) studies. One behavior we are particularly interested in is the movement of the eyes across the screen, which we usually track with an eye tracker. I developed a system that tracks the eye movements of the study participants without additional hardware by relying solely on the MR signal of the eye movements. Compared to a dedicated eye tracker, our method is free of charge. Furthermore, it can be applied to existing data sets for which no eye-tracking data was available and works even when the participants' eyes are closed.
In other projects, I was able to show how neural networks can be used to explain how the brain processes sensory information, which we use to create a stable, motion-independent internal map of the world around us.This shows that we can use neural networks in neuroscience not only to analyze data but also to explain neural processes.
What is your motivation for dealing with this topic in particular?
Rachel Zsido:
With a rapidly ageing population and the current lack of preventative therapeutic options, it is vital that we develop strategies that support healthy cognitive ageing throughout life. Crucially, two-thirds of Alzheimer's patients are women, which cannot be explained by longevity alone, and the risk increases during the transition to menopause. In addition, major depressive disorder is an independent risk factor for Alzheimer's disease and is twice as common in women - a gender difference that is already evident in early adulthood. Since Alzheimer's pathology occurs decades before clinical symptoms appear later in life, understanding the common pathophysiology and sex differences in Alzheimer's (in the context of reproductive aging) may provide important clues for early detection and prevention of Alzheimer's.
Markus Frey:
We still live in a time when many fundamental questions about how the brain works remain unanswered. Addressing these questions and deepening the global knowledge of our brain is incredibly motivating and not just relevant to neuroscience. The brain is a large part of what makes us human, and understanding it will help us in the future to cure other diseases, but also to better understand and categorize human interaction - unfortunately often also interaction against each other. It also opens up new possibilities for new technologies and therapies that can improve our daily lives.
The award-winning dissertation is in the bag. What comes next?
Rachel Zsido:
During my postdoc at Harvard Medical School and Massachusetts General Hospital, I want to find out how prenatal immune programming, sex hormones and stress circuitry in the brain interact and contribute to the common pathophysiology underlying three chronic diseases: Depression, cardiovascular disease and Alzheimer's disease.
Markus Frey:
In addition to advancing machine learning tools, I would like to further uncover the evolution of above-mentioned cognitive processes and ideally understand why these processes are disrupted in neurodegenerative diseases. Interestingly, the brain areas responsible for spatial perception are the first to be affected by Alzheimer's disease. This may make it possible to develop therapies that can be individualized for each patient.
I would also like to investigate and understand the neuronal networks that we use for this in more detail. Researchers in machine learning are often more interested in improving the performance of their models than in understanding them. Fortunately, this opens up opportunities where a neuroscience background is beneficial, and I look forward to exploring more of these questions in the future.
