On the applicability of STDP-based learning mechanisms to spiking neuron network models-Reference-Cited by-同舟云学术

On the applicability of STDP-based learning mechanisms to spiking neuron network models

Published:2016-11 Issue:11 Volume:6 Page:111305
ISSN:2158-3226
Container-title:AIP Advances
language:en
Short-container-title:AIP Advances

Author:

Sboev A.¹,Vlasov D.²,Serenko A.³,Rybka R.⁴,Moloshnikov I.⁴

Affiliation:

1. National Research Centre Kurchatov Institute, MEPhI National Research Nuclear University and Plekhanov Russian University of Economics, Moscow, Russia

2. MEPhI National Research Nuclear University, Moscow, Russia

3. National Research Centre Kurchatov Institute, Moscow, Russia and Moscow Institute of Physics and Technology, Moscow, Russia

4. National Research Centre Kurchatov Institute, Moscow, Russia

Funder

Russian Science Foundation (RSF)

Publisher

AIP Publishing

Subject

General Physics and Astronomy

Link

http://aip.scitation.org/doi/pdf/10.1063/1.4967353

Reference16 articles.

1. How to Build a Brain

2. Supervised Spike-Timing-Dependent Plasticity: A Spatiotemporal Neuronal Learning Rule for Function Approximation and Decisions

3. NEST (NEural Simulation Tool)

4. Learning Input Correlations through Nonlinear Temporally Asymmetric Hebbian Plasticity

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