ROBOTIC AND NEURONAL SIMULATION OF THE HIPPOCAMPUS AND RAT NAVIGATION

The properties of hippocampal place cells are reviewed, with particula r attention to the nature of the internal and external signals that su pport their firing A neuronal simulation of the firing of place cells in open-field environments of varying shape is presented. This simulat ion is coupled with an existing model of how place-cell firing can be used to drive navigation, and is tested by implementation as a miniatu re mobile robot. The sensors on the robot provide visual, odometric an d short-range proximity data, which are combined to estimate the dista nce of the walls of the enclosure from the robot and the robot's curre nt heading direction. These inputs drive the hippocampal simulation, i n which the robot's location is represented as the firing of place cel ls. If a goal location is encountered, learning occurs in connections from the concurrently active place cells to a set of 'goal cells', whi ch guide subsequent navigation, allowing the robot to return to an unm arked location. The system shows good agreement with actual place-cell firing, and makes predictions regarding the firing of cells in the su biculum, the effect of blocking long-term synaptic changes, and the lo cus of search of rats after deformation of their environment.