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Precise timing of spikes and temporal locking are key elements of neural computation. Here we demonstrate how even strongly heterogeneous, deterministic neural networks with delayed interactions and complex topology can exhibit periodic…

Neurons and Cognition · Quantitative Biology 2009-11-13 Raoul-Martin Memmesheimer , Marc Timme

Developing networks of neural systems can exhibit spontaneous, synchronous activities called neural bursts, which can be important in the organization of functional neural circuits. Before the network matures, the activity level of a burst…

Neurons and Cognition · Quantitative Biology 2017-05-24 Chih-Hsu Huang , Yu-Ting Huang , Chun-Chung Chen , C. K. Chan

We investigate the entrainment of a neuron model exhibiting a chaotic spiking-bursting behavior in response to a weak periodic force. This model exhibits two types of oscillations with different characteristic time scales, namely, long and…

Chaotic Dynamics · Physics 2015-06-05 Hiroyasu Ando , Hiromichi Suetani , Juergen Kurths , Kazuyuki Aihara

In analogy with equilibrium phase transitions, we address the problem of the instability to symmetry-breaking perturbations of systems undergoing a laser transition. The symmetry in question is the $U(1)$ invariance with respect to a phase…

Mesoscale and Nanoscale Physics · Physics 2019-03-26 P. Gartner

Large networks of spiking neurons show abrupt changes in their collective dynamics resembling phase transitions studied in statistical physics. An example of this phenomenon is the transition from irregular, noise-driven dynamics to…

Adaptation and Self-Organizing Systems · Physics 2008-11-25 Vicenç Gómez , Andreas Kaltenbrunner , Vicente López , Hilbert J. Kappen

Extreme events such as rogue wave in optics and fluids are often associated with the merging dynamics of coherent structures. We present experimental and numerical results on the physics of extreme events appearance in a spatially extended…

Repetitive spatio-temporal propagation patterns are encountered in fields as wide-ranging as climatology, social communication and network science. In neuroscience, perfectly consistent repetitions of the same global propagation pattern are…

Data Analysis, Statistics and Probability · Physics 2017-05-24 Thomas Kreuz , Eero Satuvuori , Martin Pofahl , Mario Mulansky

Weakly coupled semiconductor superlattices under dc voltage bias are excitable systems with many degrees of freedom that may exhibit spontaneous chaos at room temperature and act as fast physical random number generator devices.…

Mesoscale and Nanoscale Physics · Physics 2021-08-27 E. Mompó , M. Carretero , L. L. Bonilla

Based upon the moment closure approach, a Gaussian random field is constructed to quantitatively and analytically characterize the dynamics of a random point field. The approach provides us with a theoretical tool to investigate…

Dynamical Systems · Mathematics 2022-04-08 Ning Hua , Xiangnan He , Wenlian Lu , Jianfeng Feng

The basic physics of lasers is characterized by a second-order continuous phase transition at the critical lasing threshold. Nevertheless, laser bistability with abrupt transitions has been reported in some laser systems, but its underlying…

We characterize the operation of semiconductor microring lasers in an excitable regime. Our experiments reveal a statistical distribution of the characteristics of noise-triggered optical pulses that is not observed in other excitable…

We consider a model for two lasers that are mutually coupled optoelectronically by modulating the pump of one laser with the intensity deviations of the other. Signal propagation time in the optoelectronic loop causes a significant delay…

Chaotic Dynamics · Physics 2007-05-23 T. W. Carr , I. B. Schwartz , Min-Young Kim , Rajarshi Roy

Spatio-temporal instabilities are widespread phenomena resulting from complexity and nonlinearity. In broad-area edge-emitting semiconductor lasers, the nonlinear interactions of multiple spatial modes with the active medium can result in…

We investigate the synchronization features of a network of spiking neurons under a distance-dependent coupling following a power-law model. The interplay between topology and coupling strength leads to the existence of different…

Neurons and Cognition · Quantitative Biology 2020-11-11 R. C. Budzinski , K. L. Rossi , B. R. R. Boaretto , T. L. Prado , S. R. Lopes

We consider time-periodically perturbed 1D Hamiltonian systems possessing one or more separatrices. If the perturbation is weak, then the separatrix chaos is most developed when the perturbation frequency lies in the logarithmically small…

Chaotic Dynamics · Physics 2015-05-13 S. M. Soskin , R. Mannella , O. M. Yevtushenko , I. A. Khovanov , P. V. E. McClintock

Spiking activity of neurons engaged in learning and performing a task show complex spatiotemporal dynamics. While the output of recurrent network models can learn to perform various tasks, the possible range of recurrent dynamics that…

Neurons and Cognition · Quantitative Biology 2018-08-21 Christopher Kim , Carson Chow

We disclose a new class of patterns, called patched patterns, in arrays of non-locally coupled excitable units with attractive and repulsive interactions. Self-organization process involves formation of two types of patches, majority and…

Pattern Formation and Solitons · Physics 2022-09-28 Igor Franović , Sebastian Eydam

We investigate the dynamic mechanisms for low frequency fluctuations in semiconductor lasers subject to delayed optical feedback, using the Lang-Kobayashi model. This system of delay differential equations displays pronounced envelope…

Pattern Formation and Solitons · Physics 2017-12-12 S. Ruschel , S. Yanchuk

Spikes and rhythms organize control and communication in the animal world, in contrast to the bits and clocks of digital technology. As continuous-time signals that can be counted, spikes have a mixed nature. This paper reviews ongoing…

Systems and Control · Electrical Eng. & Systems 2022-03-10 Rodolphe Sepulchre

Chimera is a rich and fascinating class of self-organized solutions developed in high dimensional networks having non-local and symmetry breaking coupling features. Its accurate understanding is expected to bring important insight in many…

Optics · Physics 2018-10-03 Laurent Larger , Bogdan Penkovsky , Yuri Maistrenko
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