Topic: feedforward neural network

A cortical neuron often establishes multiple synaptic contacts with the same postsynaptic neuron. To avoid functional redundancy of these parallel synapses, it is crucial that each synapse exhibits distinct computational properties. We discuss models of a neuron in which the current to the soma contributed by each synapse is described by a sigmoidal transmission function of its presynaptic input, with learnable parameters. We evaluate the classification capacity of a neuron equipped with such nonlinear parallel synapses, and show that with a small number of parallel synapses per axon, it subst