Memristors as synapse emulators in the context of event-based computation

Event-based computation is a well-established way of reducing the complexity of neural modelling, often used as an enabling step towards the simulation of large neuronal ensembles. Recently, the advent of the physical memristor has provided the scientific community with a stand-alone nanoelectronic device that exhibits strongly `synapse-like´ behaviour and can be used in general neural modelling. In this paper we review the suitability of the most common, basic memristor models for use in tandem with event-based techniques and conclude that neither of them can support spike timing-dependent plasticity (STDP); a staple of modern neuroscience.We then identify the necessary attributes of any model that can enmesh STDP into event-based computation and present measured results evidencing that solid-state TiO₂-based memristors intrinsically support such feature.