Memristors: Associative Learning with Temporal Contiguity in a Memristive Circuit for Large‐Scale Neuromorphic Networks (Adv. Electron. Mater. 8/2015)

Memristors are promising candidates for applications as artificial synapses in neuromorphic engineering. In article number 1500125, Xiang-Shui Miao and co-workers demonstrate associative learning and extinction functions in a compact circuit with only one memristor and two resistors. Based on the spike-timing-dependent plasticity rule, learning with temporal contiguity is realized, consistent with biological behaviors.