Computational neuroscience
The dramatic increase in affordable computing power has made complex computational modelling and simulations of neuronal structures feasible. These models will become an important tool in linking different aspects of neuroscientific research. Biologically plausible models that are based on biophysical and behavioral data are especially relevant for the overall goal of this consortium. This is ensured by the circumstance that many members of the consortium have revealed key computational mechanisms relevant for learning and memory at each level from the intracellular processes underlying synaptic plasticity to complex large-scale ensembles of specific populations of nerve cells and networks. These models can then be used to make predictions which in turn can experimentally be tested in humans and rodents.
This approach has recently been strengthened by a large (2 Mio €) Bernstein Computational Neuroscience Focus program on learning and memory which is coordinated by C. Büchel. In addition with several collaborative projects funded by the EU (A.K. Engel), the Volkswagen Foundation (A.K. Engel) and the DFG (C. Büchel, A.K. Engel, B. Röder, J. Zhang), the neuroscientific community in Hamburg has already established a solid basis in computational neuroscience. However, to further foster this field and exploit the full expertise of all associated groups, it will be vital to improve this development by establishing a central professorship (W3) and group comprising usual administrative staff and 1.5 scientific positions. In addition, we will establish a computational methods platform for mathematical modelling and simulations.
This group will be tightly linked to the group “Technical Aspects of Multimodal Systems” at the Department of Informatics (Zhang) as it is also envisaged that neurobiological mechanisms of learning and memory emerging from neuroscientific research will inform learning in technical systems. This link has already been successfully implemented through the interdisciplinary DFG-funded International Research Training Grant (GRK 1247 CINACS) with B. Röder, A. Engel, J. Zhang and C. Büchel as PIs.
