The broad edge of synchronization: Griffiths effects and collective phenomena in brain networks

Buendía, Victor; Villegas, Pablo; Burioni, Raffaella; Muñoz, Miguel A.

doi:10.1098/rsta.2020.0424

Cited by 19 publications

(12 citation statements)

References 89 publications

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“…We have observed (not shown) similar behavior in small-world networks generated by adding long-range connections and keeping the short-range ones [59]. Other works have also observed dynamical malleability in Kuramoto oscillators coupled under both human-connectome structural networks and hierarchicalmodular networks [19,60]. Additionally, of course, the theory of phase transitions and, consequently, of sampleto-sample fluctuations, is known to apply for a variety of distinct systems.…”

Section: Discussionsupporting

confidence: 70%

“…Fixing the coupling strength, we can also look at the distribution of the degree of phase synchronization across samples (purple inset). The magnitude of the sample-to-sample fluctuations peaks during the transitions, at the edge of phase synchronization [19].…”

Section: Introductionmentioning

confidence: 99%

“…Despite these differences, however, both topologies present a similar phenomenology: going from k-nearest-neighbor rings to mean-field rings leads to a transition from desynchronization to phase synchronization [32,35]. Furthermore, the systems become very sensitive to parameters changes (very dynamically malleable) in the path to phase synchronization (at the edge of phase synchronization [19]). The parameter changes considered here are mainly changes to the oscillators' natural frequencies, but we also show that changes to the topology have similar effects.…”

Section: Introductionmentioning

confidence: 99%

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Small changes at single nodes can shift global network dynamics

Rossi¹,

Budzinski²,

Boaretto³

et al. 2022

Preprint

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Understanding the sensitivity of a system's behavior with respect to parameter changes is essential for many applications. This sensitivity may be desired -for instance in the brain, where a large repertoire of different dynamics, particularly different synchronization patterns, is crucial -or may be undesired -for instance in power grids, where disruptions to synchronization may lead to blackouts. In this work, we show that the dynamics of networks of phase oscillators can acquire a very large and complex sensitivity to changes made in either their units' parameters or in their connectionseven modifications made to a parameter of a single unit can radically alter the global dynamics of the network in an unpredictable manner. As a consequence, each modification leads to a different path to phase synchronization manifested as large fluctuations along that path. This dynamical malleability occurs over a wide parameter region, around the network's two transitions to phase synchronization. One transition is induced by increasing the coupling strength between the units, and another is induced by increasing the prevalence of long-range connections. Specifically, we study Kuramoto phase oscillators connected under either Watts-Strogatz or distance-dependent topologies to analyze the statistical properties of the fluctuations along the paths to phase synchrony. We argue that this increase in the dynamical malleability is a general phenomenon, as suggested by both previous studies and the theory of phase transitions.

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Section: Discussionsupporting

confidence: 70%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Small changes at single nodes can shift global network dynamics

Rossi¹,

Budzinski²,

Boaretto³

et al. 2022

Preprint

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show abstract

“…In the same vein, it was shown in-silico that neuronal avalanches occur at a critical (asynchronous-to-synchronous) phase transition, where they coexist with incipient oscillations (Di Santo et al, 2018). However, while SOC provides a candidate framework for a unified theory of Consciousness (Melloni et al, 2021), a critical state is not strictly required for explaining the presence of spontaneous scale-free neuronal avalanches (e.g., Buendía et al, 2020aBuendía et al, , 2022. For example, it was suggested that during deep sleep or under anesthesia, the brain self-organizes at the edge of bistability (SOB, a first order phase transition Buendía et al, 2020b), rather than SOC (Priesemann et al, 2013).…”

Section: Discussionmentioning

confidence: 99%

Spontaneous neuronal avalanches as a correlate of access consciousness

et al. 2022

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Decades of research have advanced our understanding of the biophysical mechanisms underlying consciousness. However, an overarching framework bridging between models of consciousness and the large-scale organization of spontaneous brain activity is still missing. Based on the observation that spontaneous brain activity dynamically switches between epochs of segregation and large-scale integration of information, we hypothesize a brain-state dependence of conscious access, whereby the presence of either segregated or integrated states marks distinct modes of information processing. We first review influential works on the neuronal correlates of consciousness, spontaneous resting-state brain activity and dynamical system theory. Then, we propose a test experiment to validate our hypothesis that conscious access occurs in aperiodic cycles, alternating windows where new incoming information is collected but not experienced, to punctuated short-lived integration events, where conscious access to previously collected content occurs. In particular, we suggest that the integration events correspond to neuronal avalanches, which are collective bursts of neuronal activity ubiquitously observed in electrophysiological recordings. If confirmed, the proposed framework would link the physics of spontaneous cortical dynamics, to the concept of ignition within the global neuronal workspace theory, whereby conscious access manifest itself as a burst of neuronal activity.

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“…In the brain, we also find synchronisation phenomena. Buendía and coauthors provide in The broad edge of synchronisation: Griffiths effects and collective phenomena in brain networks [174] a thorough characterization of the rich dynamical repertoire that arises in brain synchronization when it is combined a minimal dynamical model of neural activity with empirically-observed properties of brain connectivity, such as hierarchical-modular and coreperiphery structures. They reveal the emergence of complex collective states with flexible levels of synchronization, which is a necessary step towards a better understanding of the functional capabilities of brains.…”

Section: Summary Of the Theme Issuementioning

confidence: 99%

From the origin of life to pandemics: Emergent phenomena in complex systems

Artime,

De Domenico

2022

Preprint

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When a large number of similar entities interact among each other and with their environment at a low scale, unexpected outcomes at higher spatio-temporal scales might spontaneously arise. This nontrivial phenomenon, known as emergence, characterizes a broad range of distinct complex systems -from physical to biological and social ones -and is often related to collective behavior. It is ubiquitous, from non-living entities such as oscillators that under specific conditions synchronize, to living ones, such as birds flocking or fish schooling. Despite the ample phenomenological evidence of the existence of systems' emergent properties, central theoretical questions to the study of emergence remain still unanswered, such as the lack of a widely accepted, rigorous definition of the phenomenon or the identification of the essential physical conditions that favour emergence. We offer here a general overview of the phenomenon of emergence and sketch current and future challenges on the topic. Our short review also serves as an introduction to the Theme Issue Emergent phenomena in complex physical and socio-technical systems: from cells to societies, where we provide a synthesis of the contents tackled in the Issue and outline how they relate to these challenges, spanning from current advances in our understanding on the origin of life to the large-scale propagation of infectious diseases.

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The broad edge of synchronization: Griffiths effects and collective phenomena in brain networks

Cited by 19 publications

References 89 publications

Small changes at single nodes can shift global network dynamics

Small changes at single nodes can shift global network dynamics

Spontaneous neuronal avalanches as a correlate of access consciousness

From the origin of life to pandemics: Emergent phenomena in complex systems

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