Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
2076024 | Biosystems | 2013 | 7 Pages |
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.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Modelling and Simulation
Authors
Silvia Scarpetta, Ferdinando Giacco, Fabrizio Lombardi, Antonio de Candia,