Neuronal Communication: Presynaptic Terminals as Transmitter Array

In this paper, a communication engineering model is proposed for capturing the actual behavior of biological neurons by accounting for the specific and unique processing performed by the presynaptic terminals. Specifically, experimental evidences show that: i) the release sites from a single axon can have variable release probabilities, even when the axon contacts the same postsynaptic neuron; ii) this variability in the release probability implies a compartmentalization at the level of the presynaptic terminals of the neuronal processing; iii) the specificity of the presynaptic terminal processing is driven by and reflects the complex biophysical mechanisms activated at the axon terminals by the spikes fired by the neuron in response to a stimulus. Stemming from these experimental evidences, we propose to model the presynaptic terminals as an array of transmitters, where each transmitter models the specific processing made by a presynaptic terminal. We conduct the analysis through a stochastic approach, since the synaptic transmission is inherently stochastic. In particular, we first analytically characterize the stochastic filtering of the spike train performed by each presynaptic terminal. Then, we characterize the propagation of the presynaptic-filtered signal through the synaptic cleft, and we derive the signaling delay as a function of the distance between the pre- and the postsynaptic neurons. Finally, the conducted theoretical analysis is validate through numerical simulation.