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Simon Weber studied physics at Ludwig-Maximilians-Universität in Munich, Columbia University in New York City and Universidad de La Laguna in Spain. He obtained his B.Sc. in 2009 and his M.Sc. in 2012 in Munich, focusing on statistical biophysics and active matter. Simon began his doctoral studies at Humboldt Universität in 2013 and followed his PhD supervisor Henning Sprekeler to Technische Universität Berlin in 2015. His current research focuses on the effects of inhibitory plasticity on adaptive sensory and spatial processing. In particular, he is working to understand how spatially periodic patterns can be obtained from general spatial inputs in feedforward and recurrent neural networks. Moreover, Simon develops methods to analyze experimental data from neurons in the entorhinal cortex, in order to understand local properties of grid cells.
Models of Spatial Representation
Neurons in the hippocampus and adjacent brain areas show a large diversity in their tuning to location and head direction. The underlying circuit mechanisms are not resolved. In particular, it is unclear why certain cell types are selective to one spatial variable, but invariant to another. For example, place cells are typically invariant to head direction. We use simulations and mathematical analyses of feedforward and recurrent neural networks to study how all observed spatial tuning patterns — in both their selectivity and their invariance — could arise from the same mechanism: Excitatory and inhibitory synaptic plasticity that is driven by the spatial tuning statistics of synaptic inputs.