Stochastic Disruption of Synchronization Patterns in Coupled Non-Identical Neurons DOI Creative Commons
Irina Bashkirtseva, Lev Ryashko, Ivan Tsvetkov

и другие.

Algorithms, Год журнала: 2025, Номер 18(6), С. 330 - 330

Опубликована: Май 30, 2025

We investigate the stochastic disruption of synchronization patterns in a system two non-identical Rulkov neurons coupled via an electrical synapse. By analyzing deterministic dynamics, we identify regions mono-, bi-, and tristability, corresponding to distinct regimes as function coupling strength. Introducing perturbations parameter, explore how noise influences patterns, leading transitions between different regimes. Notably, find that increasing intensity disrupts lag synchronization, resulting intermittent switching synchronous three-cycle regime asynchronous chaotic states. This intermittency is closely linked structure transient basins, determine range which such behavior persists, depending on Using both numerical simulations analytical confidence ellipse method, provide comprehensive characterization these noise-induced effects. Our findings contribute understanding phenomena neuronal systems offer potential implications for neural dynamics biological artificial networks.

Язык: Английский

Unfolding the distribution of periodicity regions and diversity of chaotic attractors in the Chialvo neuron map DOI
Gonzalo Marcelo Ramírez-Ávila, Sishu Shankar Muni, Tomasz Kapitaniak

и другие.

Chaos An Interdisciplinary Journal of Nonlinear Science, Год журнала: 2024, Номер 34(8)

Опубликована: Авг. 1, 2024

We performed an exhaustive numerical analysis of the two-dimensional Chialvo map by obtaining parameter planes based on computation periodicities and Lyapunov exponents. Our results allowed us to determine different regions dynamical behavior, identify regularities in distribution indicating regular find some pseudofractal structures, such as “eyes chaos” similar those obtained continuous systems, and, finally, characterize statistical properties chaotic attractors leading possible hyperchaotic behavior.

Язык: Английский

Процитировано

4
Stochastic Disruption of Synchronization Patterns in Coupled Non-Identical Neurons DOI Creative Commons
Irina Bashkirtseva, Lev Ryashko, Ivan Tsvetkov

и другие.

Algorithms, Год журнала: 2025, Номер 18(6), С. 330 - 330

Опубликована: Май 30, 2025

We investigate the stochastic disruption of synchronization patterns in a system two non-identical Rulkov neurons coupled via an electrical synapse. By analyzing deterministic dynamics, we identify regions mono-, bi-, and tristability, corresponding to distinct regimes as function coupling strength. Introducing perturbations parameter, explore how noise influences patterns, leading transitions between different regimes. Notably, find that increasing intensity disrupts lag synchronization, resulting intermittent switching synchronous three-cycle regime asynchronous chaotic states. This intermittency is closely linked structure transient basins, determine range which such behavior persists, depending on Using both numerical simulations analytical confidence ellipse method, provide comprehensive characterization these noise-induced effects. Our findings contribute understanding phenomena neuronal systems offer potential implications for neural dynamics biological artificial networks.

Язык: Английский

Процитировано

0