Article
Mathematics, Interdisciplinary Applications
Xueqi Li, Dibakar Ghosh, Youming Lei
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
Hyunsuk Hong, Erik A. Martens
Summary: This study investigated the phase coherence dynamics in coupled oscillators based on the correlation between frequencies and coupling strengths. Results showed that in the case of correlated disorder, the oscillator population splits into two subpopulations, while in the uncorrelated case, it may split into four phase-locked subpopulations, leading to periodic global synchronization motion. In both cases of disorder, an incoherent state exists, with instability observed in the correlated case and neutral stability in the uncorrelated case.
Article
Mathematics, Applied
L. Messee Goulefack, Marlon F. Ramos, R. Yamapi, C. Anteneodo
Summary: In this study, the dynamics of nonlocally coupled Hindmarsh-Rose neurons modified by coupling the induced magnetic flux to the membrane potential with a quadratic memristor of strength k were investigated. The nonlocal coupling involved the interaction of each neuron with its neighbors within a fixed radius, influencing the membrane potential with coupling intensity sigma. The study examined how variations of k and sigma affect the collective dynamics, finding that coherence typically increased when k and sigma were increased, except for small parameter ranges where the opposite behavior could occur. Moreover, varying k also affected the pattern of bursts and spikes, resulting in an increase in burst frequency, a decrease in the number and amplitude of spikes, and longer quiescent periods.
Article
Physics, Fluids & Plasmas
A. Ragavan, M. Manoranjani, D. V. Senthilkumar, V. K. Chandrasekar
Summary: We have observed the emergence of distinct multistable chimera states, in addition to chimera death and synchronized states, in a smallest population of three globally coupled oscillators with mean-field diffusive coupling. A series of torus bifurcations result in the manifestation of distinct periodic orbits, leading to the creation of chimera states with two synchronized oscillators coexisting with an asynchronous oscillator. Subsequent Hopf bifurcations lead to homogeneous and inhomogeneous steady states, resulting in desynchronized steady states and chimera death state among the coupled oscillators. The stability of periodic orbits and steady states is lost through a sequence of saddle-loop and saddle-node bifurcations, ultimately resulting in a stable synchronized state. We have also extended these findings to N coupled oscillators and derived the variational equations corresponding to perturbation transverse to the synchronization manifold, confirming the synchronized state in the two-parameter phase diagrams using its largest eigenvalue. Chimera states in three coupled oscillators emerge as a solitary state in N coupled oscillator ensemble.
Article
Physics, Multidisciplinary
Rok Cestnik, Arkady Pikovsky
Summary: We study the collective behavior of phase oscillators in the thermodynamic limit and propose an Ansatz for the circular moments of the distribution that allows for truncation at any number of modes. By simulating a Josephson junction array, we demonstrate the higher-dimensional behavior facilitated by dynamics on extended manifolds.
PHYSICAL REVIEW LETTERS
(2022)
Article
Mathematics, Applied
Vinesh Vijayan, Biplab Ganguli
Summary: Complexity frontier focuses on the study of collective phenomena arising from complex interactions of a large number of parts, including the formation of spatio-temporal patterns and chimera states. These phenomena shed light on a wide range of collective behaviors and help us better understand complex emergent behaviors.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2021)
Article
Mathematics, Applied
Guillermo H. Goldsztein, Lars Q. English, Emma Behta, Hillel Finder, Alice N. Nadeau, Steven H. Strogatz
Summary: Using theory, experiment, and simulation, this study examines the dynamics of two coupled metronomes on a moving platform. The experiments show that the platform motion is damped by a dry friction force of Coulomb type, contrary to previous assumptions of viscous linear friction force. A new mathematical model is developed based on previous models but with a different treatment of friction. The model analysis reveals various long-term behaviors, including synchronization, phase locking, and suppression, shedding light on the dynamics of coupled metronomes.
Article
Engineering, Mechanical
Mingxue Yang, Shuangjian Guo, Yirui Chen, Qionglin Dai, Haihong Li, Junzhong Yang
Summary: This study identified a two-frequency chimera state in which oscillators in different coherent domains oscillate at different velocities. Oscillators in coherent domains with higher mean phase velocity almost synchronize, while those in domains with lower mean phase velocity are randomly partitioned into two groups in antiphase. Additionally, the dynamics of local mean fields in these two types of coherent domains are found to be different.
NONLINEAR DYNAMICS
(2021)
Article
Mathematics, Applied
David Mersing, Shannyn A. Tyler, Benjamas Ponboonjaroenchai, Mark R. Tinsley, Kenneth Showalter
Summary: The study investigates photochemically coupled micro-oscillators in star networks, showing that synchronization can be achieved through adjusting coupling strength. Both experimental and theoretical analysis provide insights into the synchronization mechanism, where phase divergence in heterogeneous oscillators can be realigned by perturbations from hub oscillator.
Article
Physics, Fluids & Plasmas
Kazuha Itabashi, Quoc Hoan Tran, Yoshihiko Hasegawa
Summary: By proposing a topological approach to characterize the phase dynamics in coupled oscillators, this study gains insights into the collective dynamics of complex systems. The method extracts quantitative features describing the shape of the phase data and extends these features to time-variant characteristics. Combining these features with the kernel method allows for characterization of multiclustered synchronized dynamics and qualitative explanation of chimera states.
Article
Mathematics, Applied
Mahtab Mehrabbeik, Sajad Jafari, Riccardo Meucci, Matjaz Perc
Summary: This paper studies the synchronization of globally coupled identical laser models via linear and nonlinear forms of diffusive couplings. The results show that complete synchronization can be achieved in laser models under linear diffusive function but not under nonlinear diffusive function. Multistability is observed in different network states such as cluster synchronization, chimera, and solitary states.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2023)
Article
Mathematics, Applied
Anjuman Ara Khatun, Haider Hasan Jafri
Summary: The study explores the coexistence of synchronous and asynchronous dynamical behaviors in an ensemble of nonlinear oscillators coupled through different variables, resulting in chimera states. By tuning the coupling parameter in a different variable, the region of multistability can be shifted, providing an additional means to create chimera states. In an ensemble of coupled Rossler systems, multiple attractors and intertwined basins are observed, with the strength of incoherence (SI) serving as a useful order parameter for characterizing chimera states.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2021)
Article
Mathematics, Applied
Dawid Dudkowski, Krzysztof Czolczynski, Tomasz Kapitaniak
Summary: This paper introduces a novel type of chimera state, known as multi-headed loop chimera, by studying a network of pendulum clocks. The study examines the occurrence and stability of these chimera states, analyzing the geometrical regions of the system with the highest probability of their occurrence, discussing the mechanisms of their creation, and exploring the influence of global coupling on their stability. The paper also investigates the bifurcation analysis of these states and generalizes their appearance into large networks of oscillators.
Article
Physics, Fluids & Plasmas
Biswabibek Bandyopadhyay, Tanmoy Banerjee
Summary: This study investigates the impact of Kerr anharmonicity on the symmetry-breaking phenomena of coupled quantum oscillators, revealing that Kerr nonlinearity hinders the process of symmetry breaking in both cases. The findings provide a means to control and engineer symmetry-breaking states for quantum technology.
Article
Mathematics, Applied
Georgi S. Medvedev, Matthew S. Mizuhara, Andrew Phillips
Summary: In this study, we investigate a system of coupled phase oscillators driven by random intrinsic frequencies near a saddle-node on invariant circle bifurcation. The system undergoes a phase transition and changes its qualitative properties of collective dynamics under the variation of control parameters. By using Ott-Antonsen reduction and geometric techniques for ordinary differential equations, we identify heteroclinic bifurcation in a family of vector fields on a cylinder, which explains the change in collective dynamics. Specifically, we demonstrate that heteroclinic bifurcation separates two topologically distinct families of limit cycles: contractible limit cycles before bifurcation and noncontractible ones after bifurcation. Both families are stable in the model at hand.
Article
Biophysics
Xucheng Liu, Gang Li, Sujie Wang, Feng Wan, Yi Sun, Hongtao Wang, Anastasios Bezerianos, Chuantao Li, Yu Sun
Summary: This study achieved practical driving fatigue detection using the NHB method, with mixed features from the frontal NHB area showing significant contribution to fatigue detection with high reliability and generalizability.
PHYSIOLOGICAL MEASUREMENT
(2021)
Article
Computer Science, Artificial Intelligence
Min Wang, Kathryn Kasmarik, Anastasios Bezerianos, Kay Chen Tan, Hussein Abbass
Summary: This study reveals a trade-off between channel density and stability in EEG biometric systems. A framework integrating channel density augmentation, functional connectivity estimation and deep learning models is proposed to improve the stability of EEG biometric systems while retaining high usability advantages.
PATTERN RECOGNITION LETTERS
(2021)
Article
Engineering, Civil
Manuel Seet, Jonathan Harvy, Rohit Bose, Andrei Dragomir, Anastasios Bezerianos, Nitish Thakor
Summary: The study found that trust levels significantly decreased in subjects during malfunctions in full automation driving mode of autonomous vehicles, while it remained stable in conditional automation driving mode. EEG analysis revealed enhanced approach motivation and disrupted executive cognition during malfunctions in full automation mode, with no neurocognitive disruptions observed in conditional automation mode malfunctions.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Automation & Control Systems
Heba El-Fiqi, Min Wang, Kathryn Kasmarik, Anastasios Bezerianos, Kay Chen Tan, Hussein A. Abbass
Summary: The article introduces weighted gate layer autoencoders (WGLAE) to update the error based on which variables are critical and encourage the network to learn these variables. Compared to similar architectures, the proposed WGLAE architecture can produce more robust autoencoders with high accuracy in reconstructing incomplete synthetic and real data.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Tian Wang, Anastasios Bezerianos, Andrzej Cichocki, Junhua Li
Summary: A multi-kernel capsule network (MKCapsnet) was proposed for identifying schizophrenia, considering brain anatomical structure and outperforming existing methods. Comparison of performances using different parameters and illustration of routing process revealed characteristics of the proposed method.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Neurosciences
Ze Ou, Yu Guo, Payam Gharibani, Ariel Slepyan, Denis Routkevitch, Anastasios Bezerianos, Romergryko G. Geocadin, Nitish V. Thakor
Summary: Cardiac arrest (CA) is the main cause of coma, and early recovery indicators are needed to allocate resources properly. High-frequency oscillations (HFOs) of somatosensory evoked potentials (SSEPs) have been shown to indicate wakefulness following CA. However, their potential in the acute recovery phase has not been tested. We hypothesized that time-frequency (TF) analysis of HFOs can determine arousal recovery in this phase.
Article
Computer Science, Artificial Intelligence
Tao Xu, Hongtao Wang, Guanyong Lu, Feng Wan, Mengqi Deng, Peng Qi, Anastasios Bezerianos, Cuntai Guan, Yu Sun
Summary: Due to the increasing number of fatal traffic accidents, there is a strong demand for more effective and convenient techniques for driving fatigue detection. This study proposes a unified framework called E-Key, which uses a convolutional neural network and attention structure to simultaneously perform personal identification and driving fatigue detection. The performance of the framework was assessed using EEG data collected from 31 healthy subjects, and it achieved the best performance in both personal identification (98.5%) and fatigue detection (97.8%) compared to other competitive models. The findings of this study show great potential for practical implementation in autonomous driving and car-sharing systems.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2023)
Article
Chemistry, Multidisciplinary
Georgios N. Dimitrakopoulos, Ioannis Kakkos, Athanasios Anastasiou, Anastasios Bezerianos, Yu Sun, George K. Matsopoulos
Summary: Mental workload has a significant impact on an individual's performance in real-world tasks, leading to potential errors. This study investigated the effects of workload on brain network organization using EEG data. The results showed that higher workload led to reduced clustering coefficient, characteristic path length, and small-worldness metrics. Additionally, the brain network reorganized in a task-independent manner with increasing mental load. The network metrics were also effective in classifying workload levels.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Biomedical
Yinhu Yu, Anastasios Bezerianos, Andrzej Cichocki, Junhua Li
Summary: In this study, a novel deep learning model called latent space coding capsule network (LSCCN) was proposed to integrate the features of band power and brain connectivity for workload classification. The results showed that LSCCN outperformed other methods, achieving higher testing accuracy and more reliable classification with localized features. This study not only provides a new deep learning model but also promotes practical usage of workload monitoring.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2023)
Article
Engineering, Biomedical
Chuangquan Chen, Zhouyu Ji, Yu Sun, Anastasios Bezerianos, Nitish Thakor, Hongtao Wang
Summary: This paper proposes a Self-Attentive Channel-Connectivity Capsule Network (SACC-CapsNet) for EEG-based driving fatigue detection, which can effectively extract critical temporal information, important channels, and capture the intrinsic inter-channel relations. The results show that our proposed model outperforms state-of-the-art methods, and it is also suitable for limited data.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
Shun Liu, Chi Man Wong, Xucheng Liu, Hongtao Wang, Anastasios Bezerianos, Yu Sun, Tzyy-Ping Jung, Feng Wan
Summary: This study examined the neural mechanism of driver fatigue by investigating the cross-frequency coupling of slow and fast oscillations in a multilayer brain network. It was found that the coupling in the fatigue state was enhanced, particularly in beta-gamma coupling and the frontal, frontal pole, and parietal regions. Significant differences were also observed in the topology of the multilayer brain network between vigilant and fatigue states, including increased global and local efficiencies in the fatigue state. A graph neural network (GNN) was developed to detect fatigue with high accuracy (96.23%) by imitating the features of the within-frequency subnetworks diffused through cross-frequency coupling. This research provides insights into neural coordination in driver fatigue and can contribute to reducing traffic accidents.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Biomedical
Jonathan Harvy, Anastasios Bezerianos, Junhua Li
Summary: Reliability investigation of measures is crucial in brain science and neuroengineering studies. This study evaluated the reliability of measures at both sensor and source levels, finding that measures at the sensor level generally showed higher reliability than those at the source level, except for directed between-region measures. Single-region measures displayed higher reliability compared to between-region measures. Exploration of brain network topology revealed varying degrees of reliability for nodal metrics across different regions, and global metrics varied in association with nodal metrics. This study provides important insights for measure selection in practical mental monitoring.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2022)
Article
Engineering, Electrical & Electronic
Chuangquan Chen, Zhencheng Li, Feng Wan, Leicai Xu, Anastasios Bezerianos, Hongtao Wang
Summary: This article investigates the fusion of frequency-domain and brain connectivity features for cross-subject emotion recognition using electroencephalography (EEG). Through multiple perspectives, including critical frequency bands, complementary characteristics for each emotional state, critical channels, and crucial connections, the study reveals that the fused features outperform individual features, especially in high-frequency bands, and significantly enhance classification performance for negative emotion. The findings contribute to the research on emotion-related brain mechanisms and offer new insights into affective computing.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Engineering, Electrical & Electronic
Hongtao Wang, Zian Pei, Linfeng Xu, Tao Xu, Anastasios Bezerianos, Yu Sun, Junhua Li
Summary: The study introduced a multiscale convolutional neural network model, successfully applied to P300 detection and achieving the best performance in a robot contest, laying a promising foundation for the efficient implementation of P300-based spelling systems.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Proceedings Paper
Computer Science, Theory & Methods
Keqin Ding, Andrei Dragomir, Rohit Bose, Luke Osborn, Manuel Seet, Anastasios Bezerianos, Nitish Thakor
Summary: The study found that sensory stimulation in upper limb amputees can increase information transfer speed and enhance the number of connections, primarily in dynamic functional connections related to the primary and secondary somatosensory systems.
2021 10TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER)
(2021)
