Topic: spike-trains

Various models of spiking neural networks have been proposed in the literature. These models are governed by their parameters, such as time constants, input currents, and synaptic weights. While we have a good understanding of how these parameters affect the behavior of isolated neurons, a similar intuition for connected groups of neurons is lacking. Here, we simulated millions of neuronal network models using a range of parameters, building a library of dynamics that catalogs network parameters and their resulting dynamics. Towards this end, we collected spike-trains by simulating network mod