EONS modeling platform is a resourceful learning and research tool to study the mechanisms underlying the non-linear dynamics of synaptic transmission with the aid of mathematical models. Mathematical modeling of information processing in CNS pathways, in particular modeling of molecular events and synaptic dynamics, have not been extensively developed owing to the complex computations involved in integrating a multitude of parameters. In this paper, we discuss the development of a strategy to adapt the EONS synaptic modeling platform to a multi-node environment using a parallel computational framework to compute data intensive long simulations in a shorter time frame. We describe how this strategy can be applied to (i) determine the optimal values of the numerous parameters required for fitting experimental data, (ii) determine the impact of all parameters on various aspects of synaptic transmission (under normal conditions or conditions mimicking pathological conditions) and (iii) study the effects of exogenous molecules on both healthy and pathological synaptic models.

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