Name
Abstract | ||
|---|---|---|
We consider a network of coupled excitatory and inhibitory theta neurons which is capable of supporting stable spatially-localized "bump" solutions. We randomly add long-range and simultaneously remove short-range connections within the network to form a small-world network and investigate the effects of this rewiring on the existence and stability of the bump solution. We consider two limits in which continuum equations can be derived; bump solutions are fixed points of these equations. We can thus use standard numerical bifurcation analysis to determine the stability of these bumps and to follow them as parameters (such as rewiring probabilities) are varied. We find that under some rewiring schemes bumps are quite robust, whereas in other schemes they can become unstable via Hopf bifurcation or even be destroyed in saddle-node bifurcations. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.3389/fncom.2016.00053 | FRONTIERS IN COMPUTATIONAL NEUROSCIENCE |
Keywords | Field | DocType |
Ott/Antonsen,theta neuron,bump,small-world,working memory,bifurcation | Topology,Bifurcation analysis,Control theory,Small-world network,Artificial intelligence,Fixed point,Hopf bifurcation,Machine learning,Mathematics,Bifurcation | Journal |
Volume | ISSN | Citations |
10 | 1662-5188 | 0 |
PageRank | References | Authors |
0.34 | 13 | 1 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Carlo R. Laing | 1 | 295 | 41.21 |