Simon Weber: Computational models of spatial representations: The emergence of location-specific neuronal activity

BCCN Berlin / TU Berlin

Our sense of location depends on a structure deep within the brain called the hippocampal formation, and on its neighbor, the parahippocampal region. Studies in rodents have shown that these brain areas contain different types of neurons that help the animal to work out where it is. The activity of those neurons is modulated by the trajectory of the animal, and this modulation varies among cells: place cells fire whenever an animal occupies a specific location in its environment, grid cells fire at multiple locations that together form a grid of equilateral triangles and head direction cells fire only when the animal faces a particular direction. The circuit mechanisms that give rise to these firing patterns 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 and head direction cells are often invariant to location.

This thesis contains three research projects.

In the first project, we propose that all observed spatial tuning patterns—in both their selectivity and their invariance—arise from the same mechanism: excitatory and inhibitory synaptic plasticity that is driven by the spatial tuning statistics of synaptic inputs. Using simulations and a mathematical analysis, we show that combined excitatory and inhibitory plasticity can lead to localized, grid-like or invariant activity. Combinations of different input statistics along different spatial dimensions reproduce all major spatial tuning patterns observed in rodents. The model is robust to changes in parameters, develops patterns on behavioral timescales and makes distinctive experimental predictions. For the development of grid cells, our model requires that the spatial tuning of inhibitory input is smoother than that of excitatory input and that different input neurons have different preferred firing locations.

In the second project, we model different network architectures to study the emergence of the required smooth inhibitory tuning in a population of interneurons and the simultaneous development of grid-like firing in entorhinal principal cells using interacting excitatory and inhibitory plasticity on all synapses.

In the third project, we introduce a method that allows to visualize and quantify local distortions of grid cell firing patterns, by assigning both a local grid score and a local orientation to each individual spike of a neuronal recording. Introducing a local analysis of grid patterns is motivated by recent experiments that show local distortions to the activity patterns of grid cells in both space and time.

In summation, this thesis provides new insight into how spatial representations can emerge from experience and how the symmetry of these representations can be analyzed.

Additional Information

PhD defense

Organized by

Henning Sprekeler / Margret Franke