Synchronization of an Excitatory Integrate-and-Fire Neural Network
Dumont, Grégory ; Henry, Jacques
HAL, hal-00822472 / Harvested from HAL
In this paper, we study the influence of the coupling strength on the synchronization behavior of a population of leaky integrate-and-fire neurons that is selfexcitatory with a population density approach. Each neuron of the population is assumed to be stochastically driven by an independent Poisson spike train and the synaptic interaction between neurons is modeled by a potential jump at the reception of an action potential. Neglecting the synaptic delay, we will establish that for a strong enough connectivity between neurons, the solution of the partial differential equation which describes the population density function must blow up in finite time. Furthermore, we will give a mathematical estimate on the average connection per neuron to ensure the occurrence of a burst. Interpreting the blow up of the solution as the presence of a Dirac mass in the firing rate of the population, we will relate the blow up of the solution to the occurrence of the synchronization of neurons. Fully stochastic simulations of a finite size network of leaky integrate-and-fire neurons are performed to illustrate our theoretical results.
Publié le : 2013-02-22
Classification:  Integrate-and-fire,  Synchronization,  Blow up,  Population of neurons,  Partial differential equation,  [MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP]
@article{hal-00822472,
     author = {Dumont, Gr\'egory and Henry, Jacques},
     title = {Synchronization of an Excitatory Integrate-and-Fire Neural Network},
     journal = {HAL},
     volume = {2013},
     number = {0},
     year = {2013},
     language = {en},
     url = {http://dml.mathdoc.fr/item/hal-00822472}
}
Dumont, Grégory; Henry, Jacques. Synchronization of an Excitatory Integrate-and-Fire Neural Network. HAL, Tome 2013 (2013) no. 0, . http://gdmltest.u-ga.fr/item/hal-00822472/