November 19, 2021
Eccellenza Fellowship for Friedemann Zenke
FMI group leader Friedemann Zenke receives an Eccellenza Professorial Fellowship from the Swiss National Science Foundation (SNSF). These recognitions are awarded yearly to outstanding independent researchers who aspire to a permanent professorship.
The SNSF uses the Eccellenza Professorial Fellowships to finance outstanding young researchers who aspire to a professorship. The five-year funding period comprises salary and project funds, which enables the researchers to lead a research project with their own team. The fellowships are linked to an appointment as assistant professor at the university chosen by the researchers for their project.
This year the SNSF received 244 Eccellenza proposals. After a two-stage evaluation process, 32 projects were selected for funding, for a total of 57 million Swiss francs. Friedemann Zenke, trained in Computational Neuroscience and a group leader in FMI Neurobiology since 2019, is among the Eccelenza 2021 recipients. He will be funded for his project dedicated to elucidating the role of inhibitory circuits in neuronal networks, and will become an assistant professor at the University of Basel.
About the Zenke project
Neurons do not work alone but process information in vast networks whose function is largely determined by their connectivity. The connectivity, again, is shaped by experience-dependent synaptic plasticity. In addition, diverse inhibitory interneurons exert powerful control over plasticity and neuronal dynamics. How these complex interactions shape neural network function remains poorly understood. To gain a deeper understanding of the underlying principles, computational models are indispensable. However, a major obstacle for building such models is that the precise connectivity of functional biological networks is difficult to access experimentally and, thus, generally unknown.
The Zenke group will address this problem from two angles using approaches inspired by machine learning. On the one hand, the researchers will study plasticity mechanisms in spiking neural network models and develop theories of how interneurons contribute to coordinate learning in brain-wide networks through the targeted control of synaptic plasticity. On the other hand, they will investigate whether sensory networks could learn by predicting future inputs. Crucially, the researchers will work closely with experimental groups to inform and validate their models through comparison with in-vivo data.
This work will deepen our conceptual understanding of how inhibitory interneurons contribute to the brain's remarkable information processing capabilities, which is an essential step for understanding psychiatric, neurodevelopmental and neurodegenerative conditions.