Synchronised firing patterns in a random network of adaptive exponential integrate-and-fire neuron model.

We have studied neuronal synchronisation in a random network of adaptive exponential integrate-and-fire neurons. We study how spiking or bursting synchronous behaviour appears as a function of the coupling strength and the probability of connections, by constructing parameter spaces that identify these synchronous behaviours from measurements of the inter-spike interval and the calculation of the order parameter. Moreover, we verify the robustness of synchronisation by applying an external perturbation to each neuron. The simulations show that bursting synchronisation is more robust than spike synchronisation.

Short-time memories in a network with randomly distributed connections.

Coupled map lattices are able to store short-term memories when an external periodic input is applied. We consider short-term memory formation in networks with both regular (nearest-neighbor) and randomly chosen connections. The regimes under which single or multiple memorized patterns are stored are studied in terms of the coupling and nonlinear parameters of the network.