The strength of a memory trace is modulated by a variety of factors such as arousal, attention, context, type of processing during encoding, salience and novelty of the experience. Some of these factors can be modeled as a variable plasticity level in the memory system, controlled by arousal or relevance-estimating systems. We demonstrate that a Bayesian confidence propagation neural network with learning time constant modulated in this way exhibits enhanced recall of an item tagged as salient. Proactive and retroactive inhibition of other items is also demonstrated as well as an inverted U-shape response to overall plasticity