Annual Workshop Speaker: Felix Schürmann
Digital twins in neuroscience
Felix Schürmann is adjunct professor at the Ecole polytechnique fédérale de Lausanne (EPFL), co-director of the Blue Brain Project and affiliated with the Brain Mind Institute.
ABSTRACT
Biologically detailed digital models of brain tissue, digital twins, aim at complementing experimental and theoretical approaches to study the brain. They represent a data-driven computational framework capable of absorbing the brain’s diversity and heterogeneity and enabling in silico experimentation. However, not only is the brain a highly complex system but also are we faced with the difficulty to measure it holistically and simultaneously, our experimental account is thus vastly incomplete. Creating faithful digital twins thus requires specialized computational methods that allow the building of dense brain tissue models from sparse data. For problems such as the building of biophysically detailed neuronal models, we were able to devise advanced optimization algorithms yielding some of the most faithful models to date. In other cases, such as the microconnectome, we developed first principle computational methods that derive dense parameters by predicting the connectome from neuronal structure and other data. These methods provide fundamental insights into our state of knowledge of the brain and yield some of the most accurate digital twins of brain tissue. With the help of supercomputers and massively-parallel simulation software, they represent a unique way to study the complex nature of the brain and the multi-scale nature of brain signals in health and disease.
ABOUT THE SPEAKER
Prof. Felix Schürmann studied physics at the University of Heidelberg, Germany, supported by the German National Academic Foundation. Later, as a Fulbright Scholar, he obtained his Master’s degree in Physics from SUNY at Buffalo, USA, on simulating quantum computers. He received his Ph.D. at the University of Heidelberg, Germany, under the supervision of the late Karlheinz Meier. For his thesis he co-designed an efficient implementation of a neural network in hardware.
Since 2005 he is involved in EPFL’s Blue Brain Project, where he oversees all computer science research and engineering to enable reconstruction and simulation of brain tissue models at unprecedented scale and detail. Since he strongly believes that the futures of neuroscience and computing are entangled, he also directs his own research group to rethink today’s simulation capabilities and leverage neuroscience for future computing.