University of Tehran researchers Farnood Merrikh-Bayat and Saeed Bagheri have found that two memristors used in a series work more like a human brain using Hebbian learning. In a single memristor connecting two neurons, the memristance decreases when a voltage is applied, which increases the current and causes the memristance to drop further, similar to a positive feedback effect. The researchers say that a lower memristance allows more current to flow, which increases the strengthen of the connection.
However, the positive feedback effect means that later signals will have a bigger effect on the connection than earlier ones, which is the opposite of the way real neurons behave. Merrikh-Bayat and Bagheri found that using two memristors in series enables them to reproduce Hebbian-style synapse strengthening.
From Technology Review
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