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Synchrony and clustering in heterogeneous networks with global coupling and parameter dispersion
Collins G Assisi1, Viktor K Jirsa, J A Scott Kelso
1Center for Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, FL 33431, USA.
Abstract:
Networks with nonidentical nodes and global coupling may display a large variety of dynamic behaviors, such as phase clustered solutions, synchrony, and oscillator death. The network dynamics is a function of the parameter dispersion and may be captured by conventional mean field approaches if it is close to the completely synchronous state. In this Letter we introduce a novel method based on a mode decomposition in the parameter space, which provides a low-dimensional network description for more complex dynamic behaviors and captures the mean field approach as a special case. The example of globally coupled Fitzhugh-Nagumo neurons is discussed.
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