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Recent research in nanotechnology has led to the practical realization of nanoscale devices that behave as memristors, a device that was postulated in the seventies by Chua based on circuit theoretical reasonings. On the other hand, neuromorphic engineering, a discipline that implements physical artifacts based on neuroscience knowledge, has related neural learning mechanisms to the operation of memristors. As a result, neuro-inspired learning architectures can be proposed that exploit nanoscale memristors for building very large scale systems with very dense synaptic-like memory elements. At present, the deep understanding of the internal mechanisms governing memristor operation is still an open issue, and the practical realization of very large scale and reliable ?memristive fabric? for neural learning applications is not a reality yet. However, in the meantime, researchers are proposing and analyzing …