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Synchronization in complex networks
Residue iteration decomposition (RIDE): A new method to separate ERP components on the basis of latency variability in single trials.
This work proposes a novel method based on an iteration strategy of the residues of averaged ERPs (RIDE) to separate latency-variable component clusters that can then serve as templates to estimate latencies in single trials with high precision.
The synchronization of chaotic systems
A toolbox for residue iteration decomposition (RIDE)—A method for the decomposition, reconstruction, and single trial analysis of event related potentials
Testing the stimulus-to-response bridging function of the oddball-P3 by delayed response signals and residue iteration decomposition (RIDE)
Evidence for a bimodal distribution in human communication
- Ye Wu, Changsong Zhou, Jinghua Xiao, J. Kurths, H. Schellnhuber
- Computer ScienceProceedings of the National Academy of Sciences
- 19 October 2010
This work presents clear empirical evidence from Short Message correspondence that observed human actions are the result of the interplay of three basic ingredients: Poisson initiation of tasks and decision making for task execution in individual humans as well as interaction among individuals.
Exploiting the intra-subject latency variability from single-trial event-related potentials in the P3 time range: A review and comparative evaluation of methods
Updating and validating a new framework for restoring and analyzing latency-variable ERP components from single trials with residue iteration decomposition (RIDE).
The updated RIDE method solves the divergence problem inherent to previous latency-based decomposition methods and yields dynamic information about single trials by implementing the model of ERPs as consisting of time-variable and invariable single-trial component clusters.
Hierarchical organization unveiled by functional connectivity in complex brain networks.
- Changsong Zhou, L. Zemanova, Gorka Zamora, C. Hilgetag, J. Kurths
- BiologyPhysical review letters
- 8 December 2006
This work study synchronization dynamics in the cortical brain network of the cat finds that in the biologically plausible regime the dynamics exhibits a hierarchical modular organization, in particular, revealing functional clusters coinciding with the anatomical communities at different scales.
Enhancing complex-network synchronization
Heterogeneity in the degree (connectivity) distribution has been shown to suppress synchronization in networks of symmetrically coupled oscillators with uniform coupling strength (unweighted…