Introduction: Area and power-efficient neuromorphic circuits have the potential to efficiently solve many 'big data' problems using brain-like non-Von Neumann approaches. Developing a synaptic device capable of capturing correlations between neuronal signals that are far apart in time in what is commonly known as Spike Timing Dependent Plasticity (STDP) is a central challenge in this task. Most efforts so far has relied on applying long (∼100ms) neuronal waveforms to resistive memory devices which seriously limits the learning rate  or complex signaling schemes that require synchronization of multiple finite state controllers across neuron circuits . In biology, such time correlations are implemented in the synapse. In this paper, we propose that the intrinsic transient behavior of a novel 4F 2 I-NPN device that was recently demonstrated [3,4] can be used to implement timing dependent resistance changes using very short and simple pulse signals as issued by biological neurons.