Winner-takes-all mechanism realized by memristive neural network

Winner-takes-all (WTA), an important mechanism in neural networks of recurrently connected neurons, is a critical element of many models of cortical processing. However, few WTA neural networks have been realized physically, especially by memristor networks. In this work, we have designed and implemented a neural network with memristor-based synapses to realize the WTA in a neural system. Neuronal self-excitatory, excitatory, and inhibition by other neurons have been demonstrated. Competitions between two neurons, among three neurons, and between two groups of neurons are realized based on the memristive neural network. The winner neuron or winner group can suppress the other neuron(s) or other group(s) of neurons and dominate the neuronal firing. This work paves the way for further realization of complex models of cortical processing with memristive neural networks.Winner-takes-all (WTA), an important mechanism in neural networks of recurrently connected neurons, is a critical element of many models of cortical processing. However, few WTA neural networks have been realized physically, especially by memristor networks. In this work, we have designed and implemented a neural network with memristor-based synapses to realize the WTA in a neural system. Neuronal self-excitatory, excitatory, and inhibition by other neurons have been demonstrated. Competitions between two neurons, among three neurons, and between two groups of neurons are realized based on the memristive neural network. The winner neuron or winner group can suppress the other neuron(s) or other group(s) of neurons and dominate the neuronal firing. This work paves the way for further realization of complex models of cortical processing with memristive neural networks.