Heterogeneity induces emergent functional networks for synchronization

Scafuti, Francesco; Aoki, Takaaki; Bernardo, Mario di

doi:10.1103/physreve.91.062913

Cited by 21 publications

(12 citation statements)

References 28 publications

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“…In short, visual interaction between players was found to affect synchronisation indices, more so when natural individual motions differed largely from each other 43 .…”

Section: Resultsmentioning

confidence: 91%

“…More importantly, the significant Group X Topology interaction (F (1.648, 19.779) = 3.908, p < 0.05, η 2 = 0.246) revealed that the topology effect on synchronisation was more pronounced for the less homogenous group (Group 2), with for instance the Path graph in that group producing the lowest level of synchronisation (Bonferroni post-hoc test, p < 0.01). For further details, see Supplementary Tables 5-7. In short, visual interaction between players was found to affect synchronisation indices, more so when natural individual motions differed largely from each other [43].…”

Section: Introductionmentioning

confidence: 91%

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Interaction patterns and individual dynamics shape the way we move in synchrony

Alderisio

Fiore

Salesse

et al. 2017

Sci Rep

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An important open problem in Human Behaviour is to understand how coordination emerges in human ensembles. This problem has been seldom studied quantitatively in the existing literature, in contrast to situations involving dual interaction. Here we study motor coordination (or synchronisation) in a group of individuals where participants are asked to visually coordinate an oscillatory hand motion. We separately tested two groups of seven participants. We observed that the coordination level of the ensemble depends on group homogeneity, as well as on the pattern of visual couplings (who looked at whom). Despite the complexity of social interactions, we show that networks of coupled heterogeneous oscillators with different structures capture well the group dynamics. Our findings are relevant to any activity requiring the coordination of several people, as in music, sport or at work, and can be extended to account for other perceptual forms of interaction such as sound or feel.

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“…In short, visual interaction between players was found to affect synchronisation indices, more so when natural individual motions differed largely from each other 43 .…”

Section: Resultsmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 91%

Interaction patterns and individual dynamics shape the way we move in synchrony

Alderisio

Fiore

Salesse

et al. 2017

Sci Rep

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“…For example, effects of adaptive rewiring, an adaptive network growth, or evolutionary edgesnapping are studied in Refs. [GLE06,LI11a,SCA15,PAP17,DAM19]. Also the interplay of adaptivity and complex network structure such as multilayers have been only recently numerically investigated [MAK16a, KAS18, KAS19].…”

Section: The Role Of Phase Oscillator Models For Complex Dynamical Networkmentioning

confidence: 99%

Patterns of Synchrony in Complex Networks of Adaptively Coupled Oscillators

Berner¹

2021

Springer Theses

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Collective phenomena in systems of interconnected dynamical units are omnipresent in nature. The swarm behavior in flocks of birds or schools of fish, the synchronous flashing of fireflies or even coherent spiking of neurons in the human brain are just a few examples of collective motion. Elucidating the mechanisms that give rise to synchronization is crucial in order to understand biological self-organization. For this sake, the theory of dynamical networks has been successfully applied over the last decades to boil down the complex dynamics from natural systems to their essentials. In addition, dynamical networks with adaptive couplings and hence non-constant network structure appear naturally in real-world systems such as power grid networks, social networks as well as neuronal networks. In this thesis, we study adaptive networks and their properties which give rise to the emergence of a variety of synchronization patterns, including complete and cluster synchronization as well as solitary and chimera-like states. One of the main fields of application that is investigated in this thesis concerns neuroscience. However, the methods and approaches developed in this work are not restricted to a specific field of application.aus gekoppelten Phasenoszillatoren an und zeigen, wie das subtile Zusammenspiel zwischen Adaptivität und Netzwerkstruktur die Entstehung komplexer partieller Synchronisationsmuster hervorruft.Trotz des regen Interesses an adaptiven Netzwerken ist über das Zusammenspiel adaptiv gekoppelter Netzwerkgruppen wenig bekannt. Solche adaptiven Mehrschicht-oder Multiplex-Netzwerke kommen in neuronalen Netzwerken ganz natürlich vor. Wir schlagen ein Konzept zur Erzeugung und Stabilisierung diverser partieller Synchronisationsmuster (Phasen-Cluster) in adaptiven Netzwerken vor. Wir zeigen, dass das "Multiplexen" verschiedene stabile Phasen-Cluster-Zustände induzieren kann, selbst wenn diese in den Einschicht-Systemen nicht stabil sind oder gar nicht existieren. Weiterhin entwickeln wir eine Methode zur Analyse von Laplace-Matrizen von Multiplex-Netzwerken, die einen Einblick in die spektrale Struktur dieser Netzwerke ermöglicht und damit eine Reduktion des Stabilitätsproblems auf die von Einschicht-Netzwerken ermöglicht. Wir setzen die neue Methode ein, um analytische Ergebnisse für die Stabilität der Zustände im Mehrschicht-System zu erhalten.

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“…For this reason, inhibition and anti-Hebbian coupling have been investigated in neural systems, and they have been shown to play an important role in the control of excessive synchronization and redundancy [8][9][10], and also in the context of circadian rhythms [11]. Anti-Hebbian rules have also been considered more in general in adaptive complex networks, and it has been found that they can be useful to generate features as criticality [12], dissasortativity [6], structural heterogeneity [13], bistability [14] or multistability [15].…”

Section: Introductionmentioning

confidence: 99%

Emergent explosive synchronization in adaptive complex networks

et al. 2018

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Adaptation plays a fundamental role in shaping the structure of a complex network and improving its functional fitting. Even when increasing the level of synchronization in a biological system is considered as the main driving force for adaptation, there is evidence of negative effects induced by excessive synchronization. This indicates that coherence alone cannot be enough to explain all the structural features observed in many real-world networks. In this work, we propose an adaptive network model where the dynamical evolution of the node states toward synchronization is coupled with an evolution of the link weights based on an anti-Hebbian adaptive rule, which accounts for the presence of inhibitory effects in the system. We found that the emergent networks spontaneously develop the structural conditions to sustain explosive synchronization. Our results can enlighten the shaping mechanisms at the heart of the structural and dynamical organization of some relevant biological systems, namely, brain networks, for which the emergence of explosive synchronization has been observed.

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Heterogeneity induces emergent functional networks for synchronization

Cited by 21 publications

References 28 publications

Interaction patterns and individual dynamics shape the way we move in synchrony

Interaction patterns and individual dynamics shape the way we move in synchrony

Patterns of Synchrony in Complex Networks of Adaptively Coupled Oscillators

Emergent explosive synchronization in adaptive complex networks

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