Neurocomputing

We investigate how the strength of entorhinal cortical inputs during training a!ects learned performance using computer simulations of a minimal computational model of hippocampal region CA3. After the model learns two partially overlapping sequences, it is tested on two contradictory prediction problems * disambiguation and goal-"nding. Relative to total activity, the activity level of entorhinal inputs during learning profoundly a!ects performance on each task. The optimal input levels di!er for the two sequence prediction problems, but a small region of overlap exists where both tasks can usually be performed successfully. This sensitivity to relative input activity suggests critical tests of the model. ( 2000 Elsevier Science B.V. All rights reserved.