Path integration in an attractor network model of grid cells with recurrency through conjunctive cells
Abstract Over the past years various studies were conducted and research was done on the topic of spatial navigation inside the brain. More evidence was found describing functions and behavior of spatial cells, especially grid cells, and how they enable path integration. These grid cells show no direct connection to each other but instead use “conjunctive” cells as link. In this thesis I study the way grid cells and conjunctive cells operate and try to create a continuous attractor network model by making use of research results focusing on these cells. By starting the implementation of the network one-dimensionial first I take an iterative and intuitive approach at modeling a fully working two-dimensional network.
Used libraries:
https://github.com/matplotlib/matplotlib