Results 31 to 40 of about 25,328 (252)
Recurrently connected and localized neuronal communities initiate coordinated spontaneous activity in neuronal networks. [PDF]
PLoS Computational Biology, 2017 Developing neuronal systems intrinsically generate coordinated spontaneous activity that propagates by involving a large number of synchronously firing neurons.
Davide Lonardoni +5 more
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F1000Research, 2016 Neuronal activity in the central nervous system varies strongly in time and across neuronal populations. It is a longstanding proposal that such fluctuations generically arise from chaotic network dynamics.
Rainer Engelken +4 more
doaj +1 more source
Advanced Intelligent Systems, 2020 Beyond the great success in machine learning (ML), the engineering community has been actively exploring neuromorphic computing systems based on spiking neural networks (SNNs).
Lin Bao +5 more
doaj +1 more source
Weak electric fields promote resonance in neuronal spiking activity: Analytical results from two-compartment cell and network models. [PDF]
PLoS Computational Biology, 2019 Transcranial brain stimulation and evidence of ephaptic coupling have sparked strong interests in understanding the effects of weak electric fields on the dynamics of neuronal populations. While their influence on the subthreshold membrane voltage can be
Josef Ladenbauer, Klaus Obermayer
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Information Encoding in Bursting Spiking Neural Network Modulated by Astrocytes
Entropy, 2023 We investigated a mathematical model composed of a spiking neural network (SNN) interacting with astrocytes. We analysed how information content in the form of two-dimensional images can be represented by an SNN in the form of a spatiotemporal spiking ...
Sergey V. Stasenko, Victor B. Kazantsev
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Image Processing with Spiking Neuron Networks [PDF]
, 2013 Artificial neural networks have been well developed so far. First two generations of neural networks have had a lot of successful applications. Spiking Neuron Networks (SNNs) are often referred to as the third generation of neural networks which have potential to solve problems related to biological stimuli. They derive their strength and interest from
Meftah, Boudjelal +4 more
openaire +2 more sources
Core processing neuron‐enabled circuit motifs for neuromorphic computing
InfoMat, 2023 Based on brain‐inspired computing frameworks, neuromorphic systems implement large‐scale neural networks in hardware. Although rapid advances have been made in the development of artificial neurons and synapses in recent years, further research is beyond
Hanxi Li +11 more
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Unsupervised Spiking Neural Network with Dynamic Learning of Inhibitory Neurons
Sensors, 2023 A spiking neural network (SNN) is a type of artificial neural network that operates based on discrete spikes to process timing information, similar to the manner in which the human brain processes real-world problems.
Geunbo Yang +7 more
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Physics Open, 2022 We create a Spiking Neural Network (SNN) architecture based on transforming the dynamics – Unstable Periodic Orbits (UPOs) – of a chaotic spiking neuron model to Neuronal Groups composed from Resonant Neurons. An input fed to the SNN will activate one of
Mario Antoine Aoun
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Synaptic plasticity enables adaptive self-tuning critical networks. [PDF]
PLoS Computational Biology, 2015 During rest, the mammalian cortex displays spontaneous neural activity. Spiking of single neurons during rest has been described as irregular and asynchronous.
Nigel Stepp +2 more
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