The effects of degree distributions in random networks of Type-I neurons
arXiv:2104.14666 · doi:10.1103/PhysRevE.103.052305
Abstract
We consider large networks of theta neurons and use the Ott/Antonsen ansatz to derive degree-based mean field equations governing the expected dynamics of the networks. Assuming random connectivity we investigate the effects of varying the widths of the in- and out-degree distributions on the dynamics of excitatory or inhibitory synaptically coupled networks, and gap junction coupled networks. For synaptically coupled networks, the dynamics are independent of the out-degree distribution. Broadening the in-degree distribution destroys oscillations in inhibitory networks and decreases the range of bistability in excitatory networks. For gap junction coupled neurons, broadening the degree distribution varies the values of parameters at which there is an onset of collective oscillations. Many of the results are shown to also occur in networks of more realistic neurons.
To appear in Physical Review E
References in corpus (8)
- Low Dimensional Behavior of Large Systems of Globally Coupled Oscillators
- Macroscopic description for networks of spiking neurons
- Stability diagram for the forced Kuramoto model
- Exact mean-field theory explains the dual role of electrical synapses in collective synchronization
- A reduction methodology for fluctuation driven population dynamics
- Mean field theory of assortative networks of phase oscillators
- Synchronization scenarios in the Winfree model of coupled oscillators
- Stochastic bursting in unidirectionally delay-coupled noisy excitable systems