The phenomenon of self-induced stochastic resonance (SISR) requires a nontrivial scaling limit between the deterministic and the stochastic timescales of an excitable system, leading to the emergence of coherent oscillations which are absent without noise. In this paper, we numerically investigate SISR and its control in single neurons and three-neuron motifs made up of the Morris-Lecar model. In single neurons, we compare the effects of electrical and chemical autapses on the degree of coherence of the oscillations due to SISR. In the motifs, we compare the effects of altering the synaptic time-delayed couplings and the topologies on the degree of SISR. Finally, we provide two enhancement strategies for a particularly poor degree of SISR in motifs with chemical synapses: (1) we show that a poor SISR can be significantly enhanced by attaching an electrical or an excitatory chemical autapse on one of the neurons, and (2) we show that by multiplexing the motif with a poor SISR to another motif (with a high SISR in isolation), the degree of SISR in the former motif can be significantly enhanced. We show that the efficiency of these enhancement strategies depends on the topology of the motifs and the nature of synaptic time-delayed couplings mediating the multiplexing connections.
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http://dx.doi.org/10.1007/s11571-021-09770-2 | DOI Listing |
Small Methods
October 2024
Department of Biomedical Engineering, Technion - Israel Institute of Technology, Haifa, 3200001, Israel.
Front Neurol
May 2024
Department of Neurology, Sanmenxia Hospital of the Yellow River, Sanmenxia, China.
Background: Symptomatic intracranial in-stent restenosis (sISR) poses a major challenge in the management of cerebrovascular diseases, often requiring effective and safe treatment options.
Objectives: This study aims to evaluate the efficacy and safety of paclitaxel-coated balloon (PCB) angioplasty for treating sISR.
Methods: We conducted a retrospective analysis of five patients aged 49-74 years, who were treated with PCB angioplasty between January 2017 and June 2022.
Comput Methods Programs Biomed
June 2024
School of Nursing, The Hong Kong Polytechnic University, Hong Kong.
Background And Objective: Magnetic resonance imaging (MRI) can provide rich and detailed high-contrast information of soft tissues, while the scanning of MRI is time-consuming. To accelerate MR imaging, a variety of Transformer-based single image super-resolution methods are proposed in recent years, achieving promising results thanks to their superior capability of capturing long-range dependencies. Nevertheless, most existing works prioritize the design of transformer attention blocks to capture global information.
View Article and Find Full Text PDFIEEE Trans Neural Netw Learn Syst
November 2024
Many single image super-resolution (SISR) methods that use convolutional neural networks (CNNs) learn the relationship between low- and high-resolution images directly, without considering the context structure and detail fidelity. This can limit the potential of CNNs and result in unrealistic, distorted edges and textures in the reconstructed images. A more effective approach is to incorporate prior knowledge about the image into the model to aid in image reconstruction.
View Article and Find Full Text PDFCogn Neurodyn
August 2022
Chair for Dynamics, Control and Numerics, Department of Data Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Cauerstr. 11, 91058 Erlangen, Germany.
The phenomenon of self-induced stochastic resonance (SISR) requires a nontrivial scaling limit between the deterministic and the stochastic timescales of an excitable system, leading to the emergence of coherent oscillations which are absent without noise. In this paper, we numerically investigate SISR and its control in single neurons and three-neuron motifs made up of the Morris-Lecar model. In single neurons, we compare the effects of electrical and chemical autapses on the degree of coherence of the oscillations due to SISR.
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