Results 41 to 50 of about 52,867 (269)

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
doaj   +1 more source

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
doaj   +1 more source

A geographically distributed bio-hybrid neural network with memristive plasticity [PDF]

, 2017
Throughout evolution the brain has mastered the art of processing real-world inputs through networks of interlinked spiking neurons. Synapses have emerged as key elements that, owing to their plasticity, are merging neuron-to-neuron signalling with ...
Corna, Andrea, George, Richard, Indiveri, Giacomo, Khiat, Ali, Maschietto, Marta, Mayr, Chirstian, Prodromakis, Themistoklis, Reato, Marco, Rocchi, Federico, Serb, Alexantrou, Vassanelli, Stefano   +10 more
core   +1 more source

An Efficient Method for online Detection of Polychronous Patterns in Spiking Neural Network [PDF]

, 2017
Polychronous neural groups are effective structures for the recognition of precise spike-timing patterns but the detection method is an inefficient multi-stage brute force process that works off-line on pre-recorded simulation data.
Chrol-Cannon, Joseph, Grüning, André, Jin, Yaochu   +2 more
core   +2 more sources

Computing with Spiking Neuron Networks [PDF]

, 2012
Abstract Spiking Neuron Networks (SNNs) are often referred to as the 3rd gener- ation of neural networks. Highly inspired from natural computing in the brain and recent advances in neurosciences, they derive their strength and interest from an ac- curate modeling of synaptic interactions between neurons, taking into account the time of spike firing ...
Paugam-Moisy, Hélène, Bohte, Sander M.
openaire   +2 more sources

Constructing Precisely Computing Networks with Biophysical Spiking Neurons [PDF]

Journal of Neuroscience, 2015
While spike timing has been shown to carry detailed stimulus information at the sensory periphery, its possible role in network computation is less clear. Most models of computation by neural networks are based on population firing rates. In equivalent spiking implementations, firing is assumed to be random such that averaging across populations of ...
M. A. Schwemmer, A. L. Fairhall, S. Deneve, E. T. Shea-Brown   +3 more
openaire   +3 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, Jiayang Hu, Anzhe Chen, Yishu Zhang, Chenhao Wang, Beiduo Wang, Yi Tong, Jiachao Zhou, Kian Ping Loh, Yang Xu, Tawfique Hasan, Bin Yu   +11 more
doaj   +1 more source

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, Wongyu Lee, Youjung Seo, Choongseop Lee, Woojoon Seok, Jongkil Park, Donggyu Sim, Cheolsoo Park   +7 more
doaj   +1 more source

Communication through Resonance in Spiking Neuronal Networks

PLoS Computational Biology, 2014
The cortex processes stimuli through a distributed network of specialized brain areas. This processing requires mechanisms that can route neuronal activity across weakly connected cortical regions. Routing models proposed thus far are either limited to propagation of spiking activity across strongly connected networks or require distinct mechanisms ...
Hahn, Gerald, Bujan, Alejandro F., Frégnac, Yves, Aertsen, Ad, Kumar, Arvind, Brunel, Nicolas   +5 more
openaire   +5 more sources

Resonant neuronal groups

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
doaj   +1 more source