We investigate how the strength of entorhinal cortical inputs during traini
ng affects learned performance using computer simulations of a minimal comp
utational model of hippocampal region CA3. After the model learns two parti
ally overlapping sequences, it is tested on two contradictory prediction pr
oblems - disambiguation and goal-finding. Relative to total activity, the a
ctivity level of entorhinal inputs during learning profoundly affects perfo
rmance on each task. The optimal input levels differ for the two sequence p
rediction problems, but a small region of overlap exists where both tasks c
an usually be performed successfully. This sensitivity to relative input ac
tivity suggests critical tests of the model. (C) 2000 Elsevier Science B.V.
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