Spatial navigation is a common ability among animals. Many neural populations in the brain of mammals, e.g. place cells and grid cells, exhibit activity correlated with spatial variables and therefore represent spatial information. However, the link between neural activity of such neurons and spatial navigation behavior or learning is not well understood. I propose to develop and study a computational model of spatial navigationand learning based on spiking neural networks. First, I will extend an existing computational model, which is currently able to navigate with place cells, and enhance it with the ability to navigate with grid cells in several different 2D environments. Learning is reinforced when the agent moves close to the location of the reward. Next, I will compare navigation based on either place or grid cells. Finally I will simulate pathological conditionsof different neurological disorders such as Parkinson’s and Alzheimer’s disease in the place and grid cells of my agent. Hereby, my work will contribute to translational neuroscience and potentially suggest treatments for neurological disorders.