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Article
Mathematics, Interdisciplinary Applications
Xueqi Li et al.
Summary: Chimera states in non-pairwise interaction networks are investigated in this study. Higher-order interactions are found to promote chimera states in nonlocally coupled Kuramoto oscillators. By studying a higher-order interaction network of nonlocally coupled pendulum with inertia, different collective states, including synchronization, coherent traveling waves, single-head, multi-head, imperfect traveling chimera states, and incoherent states, are observed. A novel non-stationary chimera state, known as a penetrable traveling chimera state, is discovered, where oscillators in the coherent domain travel regularly while others drift randomly in the incoherent domain. The study of rich dynamic behavior is deemed crucial for understanding the impact of higher-order interactions and damping effects on complex real-world networks.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Mathematics, Applied
Feifei Yang et al.
Summary: The field energy in neuron can be changed under shape deformation due to external energy injection. Stimulating neurons in the same region enables energy pumping through electromagnetic field superposition, and synaptic connection can be created for local energy balance. Neurons in the network maintain energy balance through continuous energy propagation and exchange, with identical neurons forming a homogeneous state and non-identical ones supporting gradient spatial patterns. This study improves the Fitzhugh-Nagumo neural circuit by adding a thermistor and a phototube, making the neuron sensitive to light and temperature. The energy diversity between neurons controls heterogeneity and defects in the network, and local energy injection regulates the firing patterns by modulating wave propagation.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2023)
Article
Physics, Multidisciplinary
Zeric Tabekoueng Njitacke et al.
Summary: This study focuses on the collective behavior of two HR neurons and a network of HR neurons. By connecting a traditional 3D HR neuron and a memristive 2D HR neuron through a gap junction, the collective behavior of the coupled neurons is obtained. Numerical simulations reveal that the coupled neurons exhibit various behaviors, including periodic, quasi-periodic, and chaotic bursting or spiking, by adjusting the control parameter. The network topology affects the spatiotemporal patterns, with cluster states observed in non-homogenous ring and star structures.
Review
Physics, Multidisciplinary
Peng Ji et al.
Summary: Signal propagation in complex networks has significant implications in various fields, including epidemiology, social dynamics, neuroscience, engineering, and robotics. The geometry of signal propagation is determined by the network topology and diverse forms of nonlinear interactions. This comprehensive review explores different models and types of complex networks, network time series analysis techniques, and applications. It aims to provide an up-to-date understanding of signal propagation complexities for innovative applications and future research.
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS
(2023)
Article
Physics, Multidisciplinary
F. Yang et al.
Summary: Due to the diversity in excitability and intrinsic parameters, neurons present different firing patterns and energy diversity. In this work, four FHN neurons in chain and ring networks are connected via memristive synapses, and their collective activities are controlled by adaptively taming the memristive coupling. Bifurcation analysis, Lyapunov exponent spectrum and Hamilton energy are calculated to investigate the dynamics dependence on external stimulus and parameters.
INDIAN JOURNAL OF PHYSICS
(2023)
Article
Engineering, Mechanical
Guowei Wang et al.
Summary: This study investigates the influence of electromagnetic induction on chaotic resonance phenomenon in neuronal network motifs. The results show that electromagnetic induction can enhance the detection ability of neurons for weak signals, and there exists an optimal chaotic current intensity for achieving the best weak signal detection. Additionally, adjusting the parameters of electromagnetic induction can lead to more pronounced chaotic resonance phenomenon in certain network motifs compared to others.
NONLINEAR DYNAMICS
(2022)
Article
Mathematics, Interdisciplinary Applications
K. Sathiyadevi et al.
Summary: We investigated the aging transition in a globally coupled network of Stuart-Landau oscillators under discrete time-dependent coupling. Our findings reveal that by adjusting the time period and duty cycle of the ON-OFF intervals, the aging region can significantly shrink, leading to the restoration of oscillatory dynamics. The results also indicate that the type of coupling and pulse interval play crucial roles in controlling the aging dynamics, providing a noninvasive approach to restore oscillatory dynamics from an aging state in a coupled oscillator network.
CHAOS SOLITONS & FRACTALS
(2022)
Article
Physics, Multidisciplinary
Ramesh Ramamoorthy et al.
Summary: The study investigates the effects of repulsive coupling in coupled nonlinear oscillators, revealing different dynamical transitions through the manipulation of control parameters.
EUROPEAN PHYSICAL JOURNAL-SPECIAL TOPICS
(2022)
Article
Physics, Multidisciplinary
Anitha Karthikeyan et al.
Summary: The study investigates the behavior of a 2D piecewise linear learning neuron model with periodic excitation and magnetic flux coupling. It is found that increasing the excitation amplitude leads to highly turbulent exotic waves in the network, and calculating the sample entropy can showcase the excitability changes of individual nodes in the network.
EUROPEAN PHYSICAL JOURNAL-SPECIAL TOPICS
(2022)
Article
Physics, Fluids & Plasmas
K. Sathiyadevi et al.
Summary: This study investigates the impact of additional complex conjugate feedback on globally coupled Stuart-Landau oscillators, revealing phenomena such as symmetry breaking clusters, out-of-phase clusters, explosive amplitude death, and disparate multistable states. By characterizing the first-order transition and hysteresis nature through the amplitude order parameter, mapping global dynamical transitions in parametric spaces, analyzing bifurcation scenarios of the reduced model, and exploring basin stability, the research sheds light on emergent dynamics in the presence of additional feedback.
Article
Physics, Fluids & Plasmas
Fatemeh Parastesh et al.
Summary: This paper studies the synchronization of a network with linear diffusive coupling that blinks between the variables periodically. The stability of the synchronous solution is shown to depend only on the averaged coupling and not on the instantaneous coupling. The effect of the blinking period on network synchronization is examined using the Hindmarsh-Rose model. The results demonstrate that decreasing the blinking period reduces the required coupling strength for synchrony and leads to enhanced synchronization compared to single-variable coupling.
Article
Physics, Fluids & Plasmas
K. Sathiyadevi et al.
Summary: This study explores the importance of frequency in the coexisting corotating and counter-rotating systems. The researchers found that the dynamical states of the system do not preserve symmetry and revealed a transition from incoherent mixed synchronization to coherent mixed synchronization through a chimera state. They also discovered that partial symmetry breaking exists due to the coexistence of symmetry-preserving and symmetry-breaking behavior in the initial state space.
Article
Mathematics, Interdisciplinary Applications
Balamurali Ramakrishnan et al.
Summary: This paper investigates synchronization problems in a multiple network of Caputo-Fabrizio type fractional order neurons with different derivative orders in each layer. It is found that lower fractional orders result in intralayer synchronization and decreased interlayer coupling strength needed for near synchronization. Moreover, the dynamics of neurons become periodic and the frequency of bursts in synchronization manifold increases with decreasing derivative order, contrary to the behavior of a single neuron.
FRACTAL AND FRACTIONAL
(2022)
Article
Mathematics, Interdisciplinary Applications
Xinlei An et al.
Summary: This paper investigates the discharge patterns of a HR neuron under electromagnetic induction, including hidden, period-adding, mixed-mode oscillations, and their control methods. Theoretical analysis and numerical simulations are combined to study the equilibrium points and stability in the system, as well as the existence of Hopf bifurcation points. The results provide insights into understanding discharge patterns and controlling membrane voltage transfer in the magnetic flux HR neuron system.
CHAOS SOLITONS & FRACTALS
(2021)
Review
Physics, Multidisciplinary
Fatemeh Parastesh et al.
Summary: Chimeras, observed in both biological and physical systems, represent an important new paradigm of nonlinear dynamics. They have been linked to various phenomena such as uni-hemispheric sleep in animals, power grid outages, and optomechanics. Future research opportunities and challenges in understanding chimeras are outlined.
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS
(2021)
Article
Mathematics, Interdisciplinary Applications
Guowei Wang et al.
Summary: The effects of electric field on vibrational resonance in single Hindmarsh-Rose (HR) neuron and coupled HR neurons system were investigated, showing that the electric field weakens MVR in a single neuron model but enhances it in a coupled system. The number of resonance peaks in system response to low-frequency signals decreases with higher signal frequency, with the possibility of observing local anti-resonance under appropriate parameters. Systems with MVR demonstrate better signal detection and propagation capabilities.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Mathematics, Interdisciplinary Applications
Dong Yu et al.
Summary: This paper investigates the synchronization mode transition of multiple time delays coupled FitzHugh-Nagumo (FHN) models, revealing different synchronization modes under varying system parameters. In the absence of noise, increasing coupling strength leads to transitions in the firing mode of coupled neurons, while in the presence of noise, the synchronization mode of neurons becomes more diverse. By adjusting time-delay and coupling strength, the sensitivity of neurons to noise can be altered, thereby adjusting the synchronization mode transition.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Engineering, Mechanical
Armand Sylvin Eteme et al.
Summary: The study demonstrates that the electromagnetic induction phenomenon can suppress chaotic states and enhance neural synchrony in neural systems. Increasing memristor strength can reduce the threshold for achieving synchronized states in electrically coupled neuron systems.
NONLINEAR DYNAMICS
(2021)
Review
Engineering, Mechanical
Luyao Guo et al.
Summary: Researchers have investigated Turing patterns of the Gierer-Meinhardt model on complex networks, studying the influences of system parameters, network types, and average degree on pattern formations through numerical simulations. Additionally, an exponential decay of Turing patterns on complex networks was presented, providing a quantitative depiction of the influence of network topology on pattern formations and the possibility of predicting pattern formations.
NONLINEAR DYNAMICS
(2021)
Review
Multidisciplinary Sciences
Ehsan Hosseini
Summary: Recent research has shown that there may be direct brain-to-brain communication between different animals, possibly achieved through the perception and conversion of magnetic fields. The magnetic field plays an important role in the brains of animals, and iron particles found in the brain may have the ability to perceive magnetic fields and transmit information.
Review
Computer Science, Artificial Intelligence
Pablo Lanillos et al.
Article
Engineering, Mechanical
Han Bao et al.
NONLINEAR DYNAMICS
(2020)
Article
Mathematics, Interdisciplinary Applications
Mengyan Ge et al.
CHAOS SOLITONS & FRACTALS
(2020)
Review
Computer Science, Information Systems
Roberto Interdonato et al.
COMPUTER SCIENCE REVIEW
(2020)
Article
Engineering, Mechanical
I Gowthaman et al.
NONLINEAR DYNAMICS
(2020)
Article
Mathematics, Applied
D. Premraj et al.
Article
Neurosciences
Fatemeh Parastesh et al.
COGNITIVE NEURODYNAMICS
(2018)
Article
Cell Biology
Mengyan Ge et al.
IET SYSTEMS BIOLOGY
(2018)
Article
Engineering, Mechanical
Fei Xu et al.
NONLINEAR DYNAMICS
(2018)
Article
Biochemical Research Methods
Rory G. Townsend et al.
PLOS COMPUTATIONAL BIOLOGY
(2018)
Article
Physics, Fluids & Plasmas
D. Premraj et al.
Article
Physics, Multidisciplinary
Jun Ma et al.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2017)
Article
Mathematical & Computational Biology
Keming Tang et al.
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE
(2017)
Article
Mathematical & Computational Biology
Feibiao Zhan et al.
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE
(2017)
Article
Multidisciplinary Sciences
Mozart B. C. Menezes et al.
Article
Mathematics, Interdisciplinary Applications
Ying Xu et al.
CHAOS SOLITONS & FRACTALS
(2017)
Article
Mathematics, Applied
Soumen Majhi et al.
Article
Engineering, Mechanical
Mi Lv et al.
NONLINEAR DYNAMICS
(2016)
Article
Neurosciences
C. G. Hales
JOURNAL OF INTEGRATIVE NEUROSCIENCE
(2014)
Article
Mathematics, Applied
Serhiy Yanchuk et al.
Article
Multidisciplinary Sciences
VK Vanag et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2003)
