Here we present a real-time model of fear conditioning in which the functional anatomy and neurophysiology of the lateral amygdala and perirhinal cortex provide a mechanism for temporal learning during Pavlovian conditioning. The model uses realistic neuronal and circuit dynamics to map time onto space and relies on a conventional Hebbian learning rule that requires strict temporal contiguity for synaptic modification. The input-output relationships of the model neurons simulate our physiological recordings with respect to latency to fIre, firing frequency, and accommodation tendency. Chains of these neurons form a spectrum of activity windows delayed by various amounts from the conditioned stimulus onset. Simulations reveal that learning occurs only when the conditioned and unconditioned stimuli are explicitly paired, that the interstimulus interval (lSn is accurately learned over a time range from 0.5 to 16 sec, and that low-frequency noise causes the accuracy of temporal learning to decrease as the lSI increases, in accordance with a Weber-type law.