Multiscale interaction promotes chimera states in complex networks

Макаров, В. В.; Kundu, Srilena; Kirsanov, Daniil V.; Frolov, Nikita S.; Maksimenko, Vladimir A.; Ghosh, Dibakar; Dana, Syamal K.; Hramov, Alexander E.

doi:10.1016/j.cnsns.2018.11.015

Cited by 37 publications

(9 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Laing studied chimaera state in heterogeneous networks, analyzing the influence of heterogeneous coupling strengths. Of further interest for human dynamics is the emergence of chimaera states in multiscale networks that result from the networking of different networks [ 50 , 51 ]. The ubiquity of chimaera mapping of synchronization and its different typologies extended its original definition to areas that might include nonidentical coupling oscillators in hybrid networks and multiscale networking of networks that were already known to present chimeralike dynamics before this definition started to be used.…”

Section: Discussion the Chimera States In Human Interactionsmentioning

confidence: 99%

“…Further neural interactions involve neuromodulators and hormones, faster or slower action, and different time frames [ 55 ]. Various types of neural interaction are undoubtedly an additional factor in the emergence of chimaera dynamically states in human hybrid synchronization [ 51 ]. As separate regions interact to perform neurocognitive tasks, variable patterns of partial synchrony form chimaera states [ 3 ].…”

Section: Discussion the Chimera States In Human Interactionsmentioning

confidence: 99%

See 1 more Smart Citation

Human Synchronization Maps—The Hybrid Consciousness of the Embodied Mind

Orsucci

2021

Entropy

View full text Add to dashboard Cite

We examine the theoretical implications of empirical studies developed over recent years. These experiments have explored the biosemiotic nature of communication streams from emotional neuroscience and embodied mind perspectives. Information combinatorics analysis enabled a deeper understanding of the coupling and decoupling dynamics of biosemiotics streams. We investigated intraindividual and interpersonal relations as coevolution dynamics of hybrid couplings, synchronizations, and desynchronizations. Cluster analysis and Markov chains produced evidence of chimaera states and phase transitions. A probabilistic and nondeterministic approach clarified the properties of these hybrid dynamics. Thus, multidimensional theoretical models can represent the hybrid nature of human interactions.

show abstract

Section: Discussion the Chimera States In Human Interactionsmentioning

confidence: 99%

Section: Discussion the Chimera States In Human Interactionsmentioning

confidence: 99%

Human Synchronization Maps—The Hybrid Consciousness of the Embodied Mind

Orsucci

2021

Entropy

View full text Add to dashboard Cite

show abstract

“…Especially after the studies of Watts and Strogatz on small-world networks [37], Barabási and Albert on scale-free networks [4] and Girvan and Newman on community structures [17], this model gained more and more attention from applied areas and the complex networks became a widely used technique for the analysis of real world data in several research fields such as in physics [29], medicine [39], meteorology [14], agriculture [40], sociology [6], and others.…”

Section: Introductionmentioning

confidence: 99%

VisGraphNet: A complex network interpretation of convolutional neural features

Florindo

Lee

Jun

et al. 2021

Information Sciences

View full text Add to dashboard Cite

Here we propose and investigate the use of visibility graphs to model the feature map of a neural network. The model, initially devised for studies on complex networks, is employed here for the classification of texture images. The work is motivated by an alternative viewpoint provided by these graphs over the original data. The performance of the proposed method is verified in the classification of four benchmark databases, namely, KTHTIPS-2b, FMD, UIUC, and UMD and in a practical problem, which is the identification of plant species using scanned images of their leaves. Our method was competitive with other state-of-theart approaches, confirming the potential of techniques used for data analysis in different contexts to give more meaningful interpretation to the use of neural networks in texture classification.

show abstract

“…Meanwhile, the chimera states in different integer-order networks have been investigated, such as bursting neurons [11], ephaptically coupled bursting neurons [12], memristive neuron networks [13,14], and threedimensional locally coupled systems [15]. Moreover, there have also been many other studies on this topic [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Complexity and Chimera States in a Ring-Coupled Fractional-Order Memristor Neural Network

2020

Front. Appl. Math. Stat.

View full text Add to dashboard Cite

At present, dynamics and coupled control of fractional-order non-linear systems are arousing much interest from researchers. In this paper, the fractional-order derivative is introduced into an improved memristor neural system. The dynamics of the fractional-order memristor neural model are investigated by means of bifurcation diagrams, Lyapunov exponents, and phase diagrams. To discuss the dynamical behavior of a fractional-order memristor neuron in a network, we construct a ring network of neurons and capture the spatiotemporal patterns of the neurons in the network in the presence of different excitations. Finally, the chimera state is observed, and the complexity of the network is analyzed. The analysis shows that the complexity algorithm provides a new approach for the dynamical analysis of the network.

show abstract

Multiscale interaction promotes chimera states in complex networks

Cited by 37 publications

References 52 publications

Human Synchronization Maps—The Hybrid Consciousness of the Embodied Mind

Human Synchronization Maps—The Hybrid Consciousness of the Embodied Mind

VisGraphNet: A complex network interpretation of convolutional neural features

Complexity and Chimera States in a Ring-Coupled Fractional-Order Memristor Neural Network

Contact Info

Product

Resources

About