This paper is a study of the behavioral and spatial firing correlates of neurons in the rat postsubiculum. Recordings were made from postsubicular neurons as rats moved freely throughout a cylindrical chamber, where the major cue for orientation was a white card taped to the inside wall. An automatic video/computer system monitored cell discharge while simultaneously tracking the position of 2 colored light emitting diodes (LEDs) secured to the animal’s head. The animal’s location was calculated from the position of one of the LEDs and head direction in the horizontal plane calculated from the relative positions of the 2 LEDs. Approximately 26 % of the cells were classified as headdirection cells because they discharged as a function of the animal’s head direction in the horizontal plane, independent of the animal’s behavior, location, or trunk position. For each

The firing rate maps of hippocampal place cells recorded in a freely moving rat are viewed as a set of approximate radial basis functions over the (2-D) environment of the rat. It is proposed that these firing fields are constructed during exploration from 'sensory inputs' (tuning curve responses to the distance of cues from the rat) and used by cells downstream to construct firing rate maps that approximate any desired surface over the environment. It is shown that, when a rat moves freely in an open field, the phase of firing of a place cell (with respect to the EEG 0 rhythm) contains information as to the relative position of its firing field from the rat. A model of hippocampal function is presented in which the firing rate maps of cells downstream of the hippocampus provide a 'population vector' encoding the instantaneous direction of the rat from a previously encountered reward site, enabling navigation to it. A neuronal simulation, involving reinforcement only at the goal location, provides good agreement with single cell recording from the hippocampal region, and can navigate to reward sites in open fields using sensory input from environmental cues. The system requires only brief exploration, performs latent learning, and can return to a goal location after encountering it only once.