Synchronization of pulse-coupled biological oscillators
SIAM Journal on Applied Mathematics
Self-sustained firing in populations of integrate-and-fire neurons
SIAM Journal on Applied Mathematics
Synchrony and desynchrony in integrate-and-fire oscillators
Neural Computation
Self-Organization of Pulse-Coupled Oscillators with Application to Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Integrate-and-fire neurons driven by correlated stochastic input
Neural Computation
Polychronization: Computation with Spikes
Neural Computation
A Review of the Integrate-and-fire Neuron Model: I. Homogeneous Synaptic Input
Biological Cybernetics
A scalable synchronization protocol for large scale sensor networks and its applications
IEEE Journal on Selected Areas in Communications
| Hi-index | 0.00 |
An ensemble of stochastic nonleaky integrate-and-fire neurons with global, delayed, and excitatory coupling and a small refractory period is analyzed. Simulations with adiabatic changes of the coupling strength indicate the presence of a phase transition accompanied by a hysteresis around a critical coupling strength. Below the critical coupling production of spikes in the ensemble is governed by the stochastic dynamics, whereas for coupling greater than the critical value, the stochastic dynamics loses its influence and the units organize into several clusters with self-sustained activity. All units within one cluster spike in unison, and the clusters themselves are phase-locked. Theoretical analysis leads to upper and lower bounds for the average interspike interval of the ensemble valid for all possible coupling strengths. The bounds allow calculating the limit behavior for large ensembles and characterize the phase transition analytically. These results may be extensible to pulse-coupled oscillators.