A neural network model of hippocampally mediated trace conditioning

In this paper a simple biological model of hippocampal region CA3 simulates the learning of hippocampally dependent trace classical conditioning. In this biologically based model, the time span of the associative modification rule is 5-fold less than the trace interval, implying that recurrent cell firing must play a significant role in encoding the trace interval. The results show that this simple network, with its moderate time spanning synaptic modification rule and sparse connectivity, can learn to span trace intervals comparable to those in rabbit eyeblink experiments. That is, the model learns to produce a cell firing pattern equivalent to an anticipatory unconditioned stimulus. This anticipatory pattern contains the information needed to intercept the unconditioned stimulus with a conditioned response because it is delivered at an appropriate time before the actual unconditioned stimulus