Results 301 to 310 of about 46,898 (329)

Memristive Spike- Timing-Dependent Plasticity

2021 Third International Conference Neurotechnologies and Neurointerfaces (CNN), 2021
We implement in simulation and hardware the Spike- Timing-Dependent Plasticity (STDP) rule that uses Fitzhugh-Nagumo neuron-like generators as spiking neurons and memristive device as a synapse. Weight functions in dependence of spikes delays are measured and fitted by mathematical functions suitable for designing memristive learning rules in scalabel ...
Svetlana Gerasimova, Dmitry Korolev, Dmitry Pavlov, Victor Kazantsev, Alexey Belov, Alexey Mikhaylov   +5 more
openaire   +1 more source

Restickable Oxide Neuromorphic Transistors with Spike‐Timing‐Dependent Plasticity and Pavlovian Associative Learning Activities

Advanced Functional Materials, 2018
In neural system, both spike‐timing‐dependent plasticity (STDP) and conditioned reflex are vital synaptic learning mechanisms to regulate advanced neural activities, being associated with temporally coupled stimuli.
Fei Yu, L. Zhu, Hui Xiao, Wan Tian Gao, Y. Guo   +4 more
semanticscholar   +1 more source

Spike-Timing-Dependent-Plasticity with Memristors

2014
(This chapter is reprints material from Zamarreno-Ramos et al. in Front. Neurosci. 5:26, 2011 and Serrano-Gotarredona et al. in Front. Neurosci. 7:02, 2013, with permission.) Here we present a very exciting overlap between emergent nano technology and neuroscience, which has been discovered by neuromorphic engineers.
Serrano-Gotarredona, T., Masquelier, Timothée, Linares-Barranco, B.   +2 more
openaire   +1 more source

Presynaptic Spike-Driven Spike Timing-Dependent Plasticity With Address Event Representation for Large-Scale Neuromorphic Systems

IEEE Transactions on Circuits and Systems Part 1: Regular Papers, 2020
Learning plays an important role in the brain to make it adaptive to dynamical environments. This paper presents a presynaptic spike-driven spike timing-dependent plasticity (STDP) learning rule in the address domain for a neuromorphic architecture using
Jongkil Park, Sang-Don Jung
semanticscholar   +1 more source

Spike-timing dependent plasticity in striatal interneurons

Neuropharmacology, 2011
Basal ganglia, an ensemble of interconnected subcortical nuclei, are involved in adaptive motor planning and procedural learning. Striatum, the primary input nucleus of basal ganglia, extracts the pertinent cortical and thalamic information from background noise in relation with the environmental stimuli and motivation. The striatum comprises different
Fino, Elodie, Venance, Laurent
openaire   +4 more sources

Flexible Artificial Synaptic Devices Based on Collagen from Fish Protein with Spike‐Timing‐Dependent Plasticity

Advanced Functional Materials, 2018
Neuromorphic and cognitive computing with a capability of analyzing complicated information is explored as a new paradigm of intelligent systems. An implementation of a renewable material as an essential building block of an artificial synaptic device is
Niloufar Raeis-Hosseini, Youngjun Park, Jang‐Sik Lee   +2 more
semanticscholar   +1 more source

Classifying Neuromorphic Datasets with Tempotron and Spike Timing Dependent Plasticity

IEEE International Joint Conference on Neural Network, 2020
Although the spike rate of a neuron codes useful information, there is a lot of evidence that information is contained in the precise timing of spikes.Static images have long been used as benchmarks for ANNs.
Laxmi R. Iyer, Yansong Chua
semanticscholar   +1 more source

Stochastic Perturbation Methods for Spike-Timing-Dependent Plasticity

Neural Computation, 2012
Online machine learning rules and many biological spike-timing-dependent plasticity (STDP) learning rules generate jump process Markov chains for the synaptic weights. We give a perturbation expansion for the dynamics that, unlike the usual approximation by a Fokker-Planck equation (FPE), is well justified. Our approach extends the related system size
Leen, Todd K., Friel, Robert
openaire   +3 more sources

Spike-Timing Dependent Plasticity (STDP), Biophysical Models

2014
Book chapter from Encyclopedia of Computational Neuroscience, published by Springer and available via doi:10.1007/978-1-4614-7320-6_359-1 ; Copyright holder: Springer Science+Business Media New ...
Griffith, T, Mellor, JR, Tsaneva-Atanasova, Krasimira   +2 more
openaire   +3 more sources

Frequency Selectivity Emerging from Spike-Timing-Dependent Plasticity

Neural Computation, 2012
Periodic neuronal activity has been observed in various areas of the brain, from lower sensory to higher cortical levels. Specific frequency components contained in this periodic activity can be identified by a neuronal circuit that behaves as a bandpass filter with given preferred frequency, or best modulation frequency (BMF).
Gilson, Matthieu, Bürck, Moritz, Burkitt, Anthony N., Van Hemmen, J. Leo   +3 more
openaire   +3 more sources