Entorhinal/dentate excitation of CA3: A critical variable in hippocampal models
We investigate how the strength of entorhinal cortical inputs during training affects 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-finding. Relative to total activity, the activity level of entorhinal inputs during learning profoundly affects performance on each task. The optimal input levels differ 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.
ca3 disambiguation hippocampus recurrent network sequence learning