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Anna Martius receives prestigious Sofja Kovalevskaja Award 2017 of Alexander von Humboldt Foundation

The Sofja Kovalevskaja Award is one of the most valuable academic awards in Germany and allows the recipients to carry out research work under unique conditions: They may spend five years working on a research project at a university of their own choice in Germany and build up their own working groups – independently and largely untroubled by administrative constraints. The Alexander von Humboldt Foundation has singled out six international researchers between 30 and 37 years of age for one of Germany’s most valuable science awards: the winners will each be granted up to €1.65 million. Tübingen scientist Anna Marius (Levina) is one of this year’s awardees. She is based at the Berstein Center for Computational Neuroscience Tübingen and Werner Reinhardt Centre for Integrative Neuroscience (CIN) at the University of Tübingen and works in the field of systemic neuroscience and computational neuroscience with the host professor Matthias Bethge.
Anna Martius receives prestigious Sofja Kovalevskaja Award 2017 of Alexander von Humboldt Foundation

Anna Martius (photo: private)

Millions of neurons interact in the brain that organises itself into a complex system. The neuroscientist Anna Martius focuses her attention on what is known as criticality, an important characteristic of the brain’s self-organisation: In a critical state, the transmission of signals resembles an avalanche. If a nerve cell transmits an electrical impulse, it can trigger another impulse in the next neuron down the line, but does not necessarily do so. Depending on whether and how often impulses are transmitted it can lead to a chain of neuronal discharges like an avalanche. It is believed that these events play an important role in processing information in the brain. In earlier work, Anna Marius already made significant contributions to the mathematical analysis and modelling of such critical states. In the future, she  intends not only to advance the knowledge of such neuronal dynamics in the brain but to focus on the analysis of highly efficient neuronal networks, which play an important role in the development of artificial intelligence.

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