A SIMPLE NETWORK MODEL SIMULATES HIPPOCAMPAL PLACE FIELDS .2. COMPUTING GOAL-DIRECTED TRAJECTORIES AND MEMORY FIELDS

Place cells have been described as the computational elements of a neu ronal cognitive mapping system that encodes and stores relationships a mong spatial stimuli (O'Keefe & Nadel, 1978). Furthermore, place cells seem to encode remembered locations because neural activity is mainta ined when the visual stimuli that influence place field location are v astly degraded, such as when cues are removed or the lights are turned off (O'Keefe & Speakman, 1987; Quirk, Muller, & Kubie, 1990). A feed- forward network model that mapped visual input onto a representation o f location simulated some basic properties of hippocampal place fields , including resistance to disruption after partial cue removal (Shapir o & Hetherington, 1993). However, the simulated place fields required visual input for their activation. We now report that a network that i ncorporates feedback (a) computed correct trajectories toward simulate d goals and (b) simulated place fields that persist in the absence of visual input. The simulation suggests that feedback properties can pro vide a computational account of O'Keefe and Speakman's data.