1 Answers
The Galves–Löcherbach model is a mathematical model for a network of neurons with intrinsic stochasticity.
In the most general definition, a GL network consists of a countable number of elements that interact by sporadic nearly-instantaneous discrete events. At each moment, each neuron N fires independently, with a probability that depends on the history of the firings of all neurons since the last time N last fired. Thus each neuron "forgets" all previous spikes, including its own, whenever it fires. This property is a defining feature of the GL model.
In specific versions of the GL model, the past network spike history since the last firing of a neuron N may be summarized by an internal variable, the potential of that neuron, that is a weighted sum of those spikes. The potential may include the spikes of only a finite subset of other neurons, thus modeling arbitrary synapse topologies. In particular, the GL model includes as a special case the general leaky integrate-and-fire neuron model.