Generalized splay states in phase oscillator networks DOI
Rico Berner, Serhiy Yanchuk, Yuri Maistrenko

et al.

Chaos An Interdisciplinary Journal of Nonlinear Science, Journal Year: 2021, Volume and Issue: 31(7)

Published: July 1, 2021

Networks of coupled phase oscillators play an important role in the analysis emergent collective phenomena. In this article, we introduce generalized m-splay states constituting a special subclass phase-locked with vanishing mth order parameter. Such typically manifest incoherent dynamics, and they often create high-dimensional families solutions (splay manifolds). For general class oscillator networks, provide explicit linear stability conditions for splay exemplify our results well-known Kuramoto–Sakaguchi model. Importantly, are expressed terms just few observables such as parameter or trace Jacobian. As result, these simple applicable to networks arbitrary size. We generalize findings inertia adaptively models.

Language: Английский

Separating Neural Oscillations from Aperiodic 1/f Activity: Challenges and Recommendations DOI Creative Commons
Moritz Gerster, Gunnar Waterstraat, Vladimir Litvak

et al.

Neuroinformatics, Journal Year: 2022, Volume and Issue: 20(4), P. 991 - 1012

Published: April 7, 2022

Electrophysiological power spectra typically consist of two components: An aperiodic part usually following an 1/f law [Formula: see text] and periodic components appearing as spectral peaks. While the investigation parts, commonly referred to neural oscillations, has received considerable attention, study only recently gained more interest. The is quantified by center frequencies, powers, bandwidths, while parameterized y-intercept exponent text]. For either part, however, it essential separate components. In this article, we scrutinize frequently used methods, FOOOF (Fitting Oscillations & One-Over-F) IRASA (Irregular Resampling Auto-Spectral Analysis), that are from component. We evaluate these methods using diverse obtained with electroencephalography (EEG), magnetoencephalography (MEG), local field potential (LFP) recordings relating three independent research datasets. Each method each dataset poses distinct challenges for extraction both parts. specific features hindering separation highlighted simulations emphasizing features. Through comparison simulation parameters defined a priori, parameterization error quantified. Based on real simulated spectra, advantages discuss common challenges, note which impede separation, assess computational costs, propose recommendations how use them.

Language: Английский

Citations

138
Desynchronization Transitions in Adaptive Networks DOI
Rico Berner,

Simon Vock,

Eckehard Schöll

et al.

Physical Review Letters, Journal Year: 2021, Volume and Issue: 126(2)

Published: Jan. 15, 2021

Adaptive networks change their connectivity with time, depending on dynamical state. While synchronization in structurally static has been studied extensively, this problem is much more challenging for adaptive networks. In Letter, we develop the master stability approach a large class of This allows reducing to low-dimensional system, by decoupling topological and properties. We show how interplay between adaptivity network structure gives rise formation islands. Moreover, report desynchronization transition emergence complex partial patterns induced an increasing overall coupling strength. illustrate our findings using coupled phase oscillators FitzHugh-Nagumo neurons synaptic plasticity.

Language: Английский

Citations

70
Seizure detection algorithm based on improved functional brain network structure feature extraction DOI
Lurong Jiang, Jiawang He,

Hangyi Pan

et al.

Biomedical Signal Processing and Control, Journal Year: 2022, Volume and Issue: 79, P. 104053 - 104053

Published: Aug. 27, 2022

Language: Английский

Citations

41
Order parameter dynamics in complex systems: From models to data DOI Open Access
Zhigang Zheng, Can Xu, Jingfang Fan

et al.

Chaos An Interdisciplinary Journal of Nonlinear Science, Journal Year: 2024, Volume and Issue: 34(2)

Published: Feb. 1, 2024

Collective ordering behaviors are typical macroscopic manifestations embedded in complex systems and can be ubiquitously observed across various physical backgrounds. Elements may self-organize via mutual or external couplings to achieve diverse spatiotemporal coordinations. The order parameter, as a powerful quantity describing the transition collective states, emerge spontaneously from large numbers of degrees freedom through competitions. In this minireview, we extensively discussed dynamics viewpoint order-parameter dynamics. A synergetic theory is adopted foundation dynamics, it focuses on self-organization systems. At onset transitions, slow modes distinguished fast act parameters, whose evolution established terms slaving principle. We explore both model-based data-based scenarios. For situations where microscopic modeling available, prototype examples, synchronization coupled phase oscillators, chimera neuron network analytically studied, constructed reduction procedures such Ott–Antonsen ansatz, Lorentz so on. complicated highly challenging well modeled, proposed eigen-microstate approach (EMP) reconstruct brought by big data decomposed into eigenmodes, behavior traced Bose–Einstein condensation-like transitions emergence dominant eigenmodes. EMP successfully applied some Ising model, climate earth systems, fluctuation patterns stock markets, motion living

Language: Английский

Citations

9
Human brain structural connectivity matrices–ready for modelling DOI Creative Commons
Antonín Škoch, Barbora Bučková, Jan Mareš

et al.

Scientific Data, Journal Year: 2022, Volume and Issue: 9(1)

Published: Aug. 9, 2022

Abstract The human brain represents a complex computational system, the function and structure of which may be measured using various neuroimaging techniques focusing on separate properties tissue activity. We capture organization white matter fibers acquired by diffusion-weighted imaging probabilistic diffusion tractography. By segmenting results tractography into larger anatomical units, it is possible to draw inferences about structural relationships between these parts system. This pipeline in connectivity matrix, contains an estimate connection strength among all regions. However, raw data processing complex, computationally intensive, requires expert quality control, discouraging for researchers with less experience field. thus provide matrices form ready modelling analysis usable wide community scientists. presented dataset together underlying data, as well basic demographic 88 healthy subjects.

Language: Английский

Citations

29
Six decades of the FitzHugh–Nagumo model: A guide through its spatio-temporal dynamics and influence across disciplines DOI

Daniel Cebrían-Lacasa,

Pedro Parra‐Rivas, Daniel Ruiz-Reynés

et al.

Physics Reports, Journal Year: 2024, Volume and Issue: 1096, P. 1 - 39

Published: Oct. 30, 2024

Language: Английский

Citations

7
The time-evolving epileptic brain network: concepts, definitions, accomplishments, perspectives DOI Creative Commons
Timo Bröhl, Thorsten Rings, Jan Pukropski

et al.

Frontiers in Network Physiology, Journal Year: 2024, Volume and Issue: 3

Published: Jan. 16, 2024

Epilepsy is now considered a network disease that affects the brain across multiple levels of spatial and temporal scales. The paradigm shift from an epileptic focus—a discrete cortical area which seizures originate—to widespread network—spanning lobes hemispheres—considerably advanced our understanding epilepsy continues to influence both research clinical treatment this multi-faceted high-impact neurological disorder. network, however, not static but evolves in time requires novel approaches for in-depth characterization. In review, we discuss conceptual basics theory critically examine state-of-the-art recording techniques analysis tools used assess characterize time-evolving human network. We give account on current shortcomings highlight potential developments towards improved management epilepsy.

Language: Английский

Citations

6
Alternate attractor chimeralike states on rings of chaotic Lorenz-type oscillators DOI Creative Commons
Hao Zhang, Zhili Chen, Fei Liu

et al.

New Journal of Physics, Journal Year: 2024, Volume and Issue: 26(2), P. 023016 - 023016

Published: Jan. 30, 2024

Abstract An interesting alternate attractor chimeralike state can self-organize to emerge on rings of chaotic Lorenz-type oscillators. The local dynamics any two neighboring oscillators spontaneously change from the butterfly-like attractors symmetric and converse ones, which forms ring. This is distinctly different traditional chimera states with unique attractor. effective driven-oscillator approach proposed reveal mechanism in forming this new oscillation mode predict critical coupling strengths for emergence mode. existence a pair focus solutions respect external drive found be key factor responsible . linear feedback control scheme introduced suppression reproduction These findings may shed light perspective studies applications complex systems.

Language: Английский

Citations

6
Criticality in FitzHugh-Nagumo oscillator ensembles: Design, robustness, and spatial invariance DOI Creative Commons
Bakr Al Beattie, Petro Feketa, Karlheinz Ochs

et al.

Communications Physics, Journal Year: 2024, Volume and Issue: 7(1)

Published: Feb. 2, 2024

Abstract Reservoir computing is an efficient and flexible framework for decision-making, control, signal processing. It uses a network of interacting components varying from abstract nonlinear dynamical systems to physical substrates. Despite recent progress, the hardware implementation with inherent parameter variability uncertainties, such as those mimicking properties living organisms’ nervous systems, remains active research area. To address these challenges, we propose constructive approach using FitzHugh-Nagumo oscillators, exhibiting criticality across broad range resistive coupling strengths robustness without specific tuning. Additionally, network’s activity demonstrates spatial invariance, offering freedom in choosing readout nodes. We introduce alternative characterization by analyzing power dissipation, demonstrate that supports classification accuracy respect shrinkage. Our results indicate valuable property problems, provides design concepts bio-inspired computational paradigms.

Language: Английский

Citations

6
Partial synchronization patterns in brain networks DOI Open Access
Eckehard Schöll

EPL (Europhysics Letters), Journal Year: 2021, Volume and Issue: 136(1), P. 18001 - 18001

Published: Oct. 1, 2021

Abstract Partial synchronization patterns play an important role in the functioning of neuronal networks, both pathological and healthy states. They include chimera states, which consist spatially coexisting domains coherent (synchronized) incoherent (desynchronized) dynamics, other complex patterns. In this perspective article we show that partial scenarios are governed by a delicate interplay local dynamics network topology. Our focus is particular on applications brain like unihemispheric sleep epileptic seizure.

Language: Английский

Citations

34