ArticleCognitive neurodynamics2021
Aperiodic stochastic resonance in neural information processing with Gaussian colored noise.
Article in Cognitive neurodynamics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- A neuron model with nonlinear membranes.Cognitive neurodynamics · 2024Article
- Random fluctuations and synaptic plasticity enhance working memory activities in the neuron-astrocyte network.Cognitive neurodynamics · 2024Article
- Multilevel and multifaceted brain response features in spiking, ERP and ERD: experimental observation and simultaneous generation in a neuronal network model with excitation-inhibition balance.Cognitive neurodynamics · 2023Article
- Mutual information measure of visual perception based on noisy spiking neural networks.Frontiers in neuroscience · 2023Article
- Autonomous learning of nonlocal stochastic neuron dynamics.Cognitive neurodynamics · 2022Article
- Emergence of stochastic resonance in a two-compartment hippocampal pyramidal neuron model.Journal of computational neuroscience · 2022Article
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3 authors.
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Abstract
The aim of this paper is to explore the phenomenon of aperiodic stochastic resonance in neural systems with colored noise. For nonlinear dynamical systems driven by Gaussian colored noise, we prove that the stochastic sample trajectory can converge to the corresponding deterministic trajectory as noise intensity tends to zero in mean square, under global and local Lipschitz conditions, respectively. Then, following forbidden interval theorem we predict the phenomenon of aperiodic stochastic resonance in bistable and excitable neural systems. Two neuron models are further used to verify the theoretical prediction. Moreover, we disclose the phenomenon of aperiodic stochastic resonance induced by correlation time and this finding suggests that adjusting noise correlation might be a biologically more plausible mechanism in neural signal processing.
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