We consider a network of leaky integrate and fire neurons, whose learning mechanism is based on the Spike-Timing-Dependent Plasticity. The spontaneous temporal dynamic of the system is studied, including its storage and replay properties, when a Poissonian noise is added to the post-synaptic potential of the units. The temporal patterns stored in the network are periodic spatiotemporal patterns of spikes. We observe that, even in absence of a cue stimulation, the spontaneous dynamics induced by the noise is a sort of intermittent replay of the patterns stored in the connectivity and a phase transition between a replay and non-replay regime exists at a critical value of the spiking threshold. We characterize this transition by measuring the order parameter and its fluctuations. © 2013 Elsevier Ireland Ltd.
Effects of Poisson noise in a IF model with STDP and spontaneous replay of periodic spatiotemporal patterns, in absence of cue stimulation
De Candia;
2013
Abstract
We consider a network of leaky integrate and fire neurons, whose learning mechanism is based on the Spike-Timing-Dependent Plasticity. The spontaneous temporal dynamic of the system is studied, including its storage and replay properties, when a Poissonian noise is added to the post-synaptic potential of the units. The temporal patterns stored in the network are periodic spatiotemporal patterns of spikes. We observe that, even in absence of a cue stimulation, the spontaneous dynamics induced by the noise is a sort of intermittent replay of the patterns stored in the connectivity and a phase transition between a replay and non-replay regime exists at a critical value of the spiking threshold. We characterize this transition by measuring the order parameter and its fluctuations. © 2013 Elsevier Ireland Ltd.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.