Results 31 to 40 of about 4,781,385 (251)

Integrated workflows for spiking neuronal network simulations

Frontiers in Neuroinformatics, 2013
The increasing availability of computational resources is enabling more detailed, realistic modelling in computational neuroscience, resulting in a shift towards more heterogeneous models of neuronal circuits, and employment of complex experimental ...
Ján eAntolík, Andrew P Davison
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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
doaj   +1 more source

Electrophysiological Heterogeneity of Fast-Spiking Interneurons: Chandelier versus Basket Cells [PDF]

, 2013
In the prefrontal cortex, parvalbumin-positive inhibitory neurons play a prominent role in the neural circuitry that subserves working memory, and alterations in these neurons contribute to the pathophysiology of schizophrenia.
Povysheva, Nadezhda V., Aleksey V Zaitsev, Lewis, David A., Guillermo Gonzalez-Burgos, Lewis David A., Nadezhda V Povysheva, Zaitsev, Aleksey V., David A Lewis, Maccaferri, Gianmaria, Povysheva Nadezhda V., Gonzalez-Burgos Guillermo, Zaitsev, AV, González-Burgos, Guillermo, Lewis, DA, Povysheva, NV, Zaitsev Aleksey V., Gonzalez-Burgos, G   +16 more
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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
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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, Wongyu Lee, Youjung Seo, Choongseop Lee, Woojoon Seok, Jongkil Park, Donggyu Sim, Cheolsoo Park   +7 more
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Inverse stochastic resonance in networks of spiking neurons. [PDF]

PLoS Computational Biology, 2017
Inverse Stochastic Resonance (ISR) is a phenomenon in which the average spiking rate of a neuron exhibits a minimum with respect to noise. ISR has been studied in individual neurons, but here, we investigate ISR in scale-free networks, where the average ...
Muhammet Uzuntarla, Ernest Barreto, Joaquin J Torres   +2 more
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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

An adaptive silicon synapse [PDF]

, 2003
Chicca E, Indiveri G, Douglas R. An adaptive silicon synapse. Presented at the Proceedings of the 2003 International Symposium on Circuits and Systems (ISCAS).We present an analog circuit for implementing models of synapses with short-term adaptation ...
Douglas, R., Indiveri, G., Chicca, Elisabetta ; https://orcid.org/   +2 more
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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, Dietmar Plenz, Narayan Srinivasa   +2 more
doaj   +1 more source

Systematic configuration and automatic tuning of neuromorphic systems [PDF]

, 2011
In the past recent years several research groups have proposed neuromorphic Very Large Scale Integration (VLSI) devices that implement event-based sensors or biophysically realistic networks of spiking neurons.
Sheik, S., Neftci, E, Indiveri, G, Fabio Stefanini, Emre Neftci, Sheik, S, Sadique Sheik, Chicca, E, Stefanini, F., Indiveri, G., Giacomo Indiveri, Elisabetta Chicca, Chicca, Elisabetta ; https://orcid.org/, Neftci, E., Stefanini, F   +14 more
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