Data Assimilation in Neuroscience

Since 1 October, Prof. Dr. Tilo Schwalger has held the Junior Professorship in Data Assimilation in Neuroscience, in the Bernstein Network Computational Science (BCCN). His junior research group is based at Technische Universität Berlin and is associated with the Einstein Center Digital Future. The Bernstein Network is a research network that combines experimental approaches in neuroscience with theoretical models and computer simulations.

Professor Schwalger, who moved to Berlin from Lausanne, has focused in his research to date on linking the microscopic description of brain activity (electrical impulses at nerve cell level) with the mesoscopic or macroscopic description of networks of many nerve cells (referred to as neuronal populations) in a mathematical model (multiscale modeling).

“I have set myself three major research focuses for my professorship,” says Schwalger, a native of Berlin. “Firstly, I want to develop a mathematical model that allows us to theoretically describe the universal variability of neuronal population activity. This is a basic requirement for improving the fit with experimental data. The goal is to gain a better understanding of neuronal variability in the brain and how it relates to different cognitive processes, and to create the theoretical groundwork for applied research.”

His second research topic likewise has an applied dimension: The aim is to make further contributions to the analysis of what are known as multiscale data. That is, linking experimental data at microscopic (single neuron), mesoscopic and macroscopic (neuronal population) level using a cross-scale model in order to extract maximum information from the data. “Data are already collected simultaneously at multiple scales in research, but there is still a lack of consistent multiscale models for statistical interpretation of such data.”

The third focus of his research is on evaluating existing standard models of the brain’s computational algorithms. “The new microscopically based population theory permits far more accurate models than before, as the derived macroscopic laws are explained by microscopic observations. This allows us to re-evaluate previous standard models under biologically realistic conditions,” says the 37-year-old theoretical physicist, who spent the last half year as a postdoc in the US.

“I am very pleased to hold the professorship, because it gives me ideal conditions for my research, both in mathematical and theoretical terms and in terms of applications and potential for experimental collaborations,” says Tilo Schwalger. “Berlin is one of the best locations for computational neuroscience worldwide – that I already know from my doctoral studies at Humboldt-Universität and at the BCCN. Association with the ECDF also opens up additional new and attractive possibilities for me with regard to collaboration and knowledge sharing.” (kj)