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Literature DB >> 21721744

Average dynamics of a driven set of globally coupled excitable units.

Abstract

We investigate the behavior of the order parameter describing the collective dynamics of a large set of driven, globally coupled excitable units. We derive conditions on the parameters of the system that allow to bound the degree of synchrony of its solutions. We describe a regime where time dependent nonsynchronous dynamics occurs and, yet, the average activity displays low dimensional, temporally complex behavior.

Year: 2011 PMID： 21721744 PMCID： PMC3085534 DOI： 10.1063/1.3574030

Source DB: PubMed Journal: Chaos ISSN： 1054-1500 Impact factor: 3.642

6 in total

1. Symmetry in locomotor central pattern generators and animal gaits.

Authors: M Golubitsky; I Stewart; P L Buono; J J Collins
Journal: Nature Date: 1999-10-14 Impact factor: 49.962

2. Low dimensional behavior of large systems of globally coupled oscillators.

Authors: Edward Ott; Thomas M Antonsen
Journal: Chaos Date: 2008-09 Impact factor: 3.642

3. Stability diagram for the forced Kuramoto model.

Authors: Lauren M Childs; Steven H Strogatz
Journal: Chaos Date: 2008-12 Impact factor: 3.642

4. Long time evolution of phase oscillator systems.

Authors: Edward Ott; Thomas M Antonsen
Journal: Chaos Date: 2009-06 Impact factor: 3.642

5. Low-dimensional dynamical model for the diversity of pressure patterns used in canary song.

Authors: Leandro M Alonso; Jorge A Alliende; F Goller; Gabriel B Mindlin
Journal: Phys Rev E Stat Nonlin Soft Matter Phys Date: 2009-04-30

6. Nonlinear model predicts diverse respiratory patterns of birdsong.

Authors: Marcos A Trevisan; Gabriel B Mindlin; Franz Goller
Journal: Phys Rev Lett Date: 2006-02-06 Impact factor: 9.161

6 in total

4 in total

Average dynamics of a driven set of globally coupled excitable units.

1. Symmetry in locomotor central pattern generators and animal gaits.

2. Low dimensional behavior of large systems of globally coupled oscillators.

3. Stability diagram for the forced Kuramoto model.

4. Long time evolution of phase oscillator systems.

5. Low-dimensional dynamical model for the diversity of pressure patterns used in canary song.

6. Nonlinear model predicts diverse respiratory patterns of birdsong.

1. Generating macroscopic chaos in a network of globally coupled phase oscillators.

2. Average activity of excitatory and inhibitory neural populations.

3. Average dynamics of a finite set of coupled phase oscillators.

4. Drifting States and Synchronization Induced Chaos in Autonomous Networks of Excitable Neurons.