Impact of Damaged Neurons on Continuous Attractor Network Models of Grid Cells.

Grid cells in the dorsolateral band of the medial entorhinal cortex(dMEX) display strikingly regular firing responses to animal’s position in 2-D space. This helps animals be able to encode relative spatial location without reference to external cues. Within a continuous attractor model of grid cell activity^[1,2], we focus on the question of how two different kinds of damage to the dMEX that can arise from neurodegenerative diseases affect grid cell performance: I) randomly distributed discrete damage and II) diffusing damage that can arise from propagation of neurofibrillary tangles. Drawing on models from the existing literature, we employ 1- and 2-dimensional neural networks with background excitation sensitive to motion and a ring of inhibitory couplings modeled as a difference of Gaussians around each firing neuron. For sufficiently strong inhibition, the model always produces a stable 1-dimensional or 2-dimensional lattice. We will study the impact of the two damage types on the attractor model and contrast this with the impact of damage on an oscillatory grid cell model^[3].