On 1st April 2018, Prof. Dr. Robert Gütig was appointed W3 Professor in Mathematical Modeling of Neural Learning at Charité – Universitätsmedizin Berlin and the Berlin Institute of Health (BIH). As a theoretical neuroscientist, Prof. Gütig studies the brain processes involved in learning inside the brain’s neuronal networks. He hopes to advance the translation of theoretical knowledge into clinical practice.
How do nerve cells acquire knowledge? What are the brain mechanisms and neuronal networks involved in learning? How can we develop computer models of the neurobiological processes involved? Prof. Gütig is an expert in computational neuroscience – an emerging discipline that combines neuroscience, mathematics, computer science and biophysics – and these key questions are at the center of his research. The discipline uses mathematical models to implement computer simulations of different components of the nervous system, and allows researchers to study the complex mechanisms at play within the central nervous system.
“In Prof. Gütig, we have found both an outstanding mathematician and a distinguished expert – one who will be a valuable addition to our computational neuroscience endeavors. We are particularly pleased to see him strengthen the expertise of our NeuroCure Cluster of Excellence,” says Prof. Dr. Axel Radlach Pries, Dean of Charité – Universitätsmedizin Berlin.
Prof. Gütig’s work is aimed at identifying the algorithms that control the human brain; for instance, he is exploring the question of how to reproduce perception within a neuronal network. This fundamental knowledge is essential to understand how we process information and how we learn. As part of his efforts, Prof. Gütig is developing mathematical models that will be able to simulate neuronal networks on a computer. This type of computational modeling enables researchers to study sensory representations in the brain, for instance, following the exposure to stimuli, such as sounds or scents. The aim is to analyze the mechanisms involved in neuronal networks in order to deduce the rules and principles that underlie learning.
“As part of my work at Charité, I am hoping to advance the modeling of multi-layer neuronal networks; this will allow us to produce more realistic models of more complex neuronal circuits and cellular processes,” explains Prof. Gütig. He is also determined to translate his basic research endeavors into clinical applications: “I look forward to being able to promote the integration of current theoretical findings into clinical practice.”
Prof. Gütig has headed the ‘Theoretical Neuroscience’ research group at the Max Planck Institute for Experimental Medicine in Göttingen since 2011. Prior to this, he was a postdoctoral researcher in Theoretical Neuroscience at the Hebrew University of Jerusalem and a visiting researcher at Harvard University. Prof. Gütig, now aged 44, was born in Berlin and studied Physics and Psychology in Berlin, Cambridge and Heidelberg. He obtained his PhD in Computational Neuroscience from Freiburg University. In 2017, he was awarded the Newcomb Cleveland Prize for his article entitled ‘Spiking neurons can discover predictive features by aggregate-label learning’. This prize is awarded by the American Association for the Advancement of Science, and honors the best paper published in the journal Science during the previous year.