Spike-timing dependent plasticity is a learning mechanism used extensively within neural modelling. The learning rule has been shown to allow a neuron to find the beginning of a repeated spatio-temporal pattern among its afferents. In this study we adduce that such learning is dependent on background activity, and is un-stable when in a noisy framework. We also present insights into the neuron’s encoding.