Abstract

Winner-takes-all (WTA) is an important mechanism in artificial and biological neural networks. We present a biologically plausible two layer WTA architecture with biologically plausible spiking neuron model and conductance based synapses. The excitatory neurons in the WTA layer receive spiking signals from an input layer and can inhibit other excitatory WTA neurons via related inhibitory neurons. The connections from the input layer to WTA layer can be trained by Spike-Time-Dependent Plasticity to discriminate between different classes of input patters. The overall input of the WTA neurons are controlled by synaptic scaling.

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