A Survey of Signal Propagation in Feedforward Neuronal Networks

Understanding how neural activities are propagated through different brain regions is a critical and fundamental problem in neuroscience. A simple model for this type of signal propagation is the feedforward neuronal network, in which each neuron in a given layer only receives synaptic signals from neurons in its previous layer. This paper introduces and reviews the basic modeling framework about the signal propagation, two neural activities propagation modes, and several recent important results about signal propagation in the feedforward neuronal networks. Furthermore, a more generalized modeling framework based on unreliable synapses is also proposed and discussed.