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Synaptic regulation on various STDP rules
Neurocomputing, 2004Abstract An additive rule of spike-timing-dependent synaptic plasticity (STDP) automatically achieves synaptic competition and activity regulation, where synaptic balance is moderately regulated to control the post synaptic activity (Song et al., Nature Neurosci. 3 (2000) 919).
Yutaka Sakai +2 more
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Competitive STDP Learning of Overlapping Spatial Patterns
Neural Computation, 2015Spike-timing-dependent plasticity (STDP) is a set of Hebbian learning rules firmly based on biological evidence. It has been demonstrated that one of the STDP learning rules is suited for learning spatiotemporal patterns. When multiple neurons are organized in a simple competitive spiking neural network, this network is capable of learning multiple ...
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STDP-based behavior learning on the TriBot robot
SPIE Proceedings, 2009This paper describes a correlation-based navigation algorithm, based on an unsupervised learning paradigm for spiking neural networks, called Spike Timing Dependent Plasticity (STDP). This algorithm was implemented on a new bio-inspired hybrid mini-robot called TriBot to learn and increase its behavioral capabilities.
ARENA, Paolo Pietro +4 more
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Spike-Timing Dependent Plasticity (STDP), Biophysical Models
2014Book 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 +2 more
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The Trouble with Weight-Dependent STDP
2007 International Joint Conference on Neural Networks, 2007We fit a weight-dependent STDP rule to the classic data of Bi and Poo (1998), showing that this rule leads to slow learning in a simulation with an integrate-and-fire neuron. The slowness of learning is explained by an inequality between the range of initial weights in the data and the largest relative potentiation.
Dominic Standage, Thomas Trappenberg
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Analog Neurons with Dopamine-Modulated STDP
2019 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2019Neuron circuits embedded with dopamine-modulated spike-timing-dependent plasticity (STDP) are described in this paper. The circuit functions are discussed in detail with HSPICE simulations. This work explores a possible learning process including short-term STDP and longer-term dopamine reward in neuromorphic systems including a noisy synapse that ...
Kun Yue, Alice C. Parker
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2010
We investigate the use of Spike Time Dependent Plasticity (STDP) in a network of Nonlinear Dynamic State (NDS) Neurons We find out that NDS Neurons can implement a form of STDP; a biological phenomenon that neocortical neurons own, and would preserve their temporal asymmetric windows of firing activity, while stabilizing to Unstable Periodic Orbits ...
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We investigate the use of Spike Time Dependent Plasticity (STDP) in a network of Nonlinear Dynamic State (NDS) Neurons We find out that NDS Neurons can implement a form of STDP; a biological phenomenon that neocortical neurons own, and would preserve their temporal asymmetric windows of firing activity, while stabilizing to Unstable Periodic Orbits ...
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Deriving STDP from Backpropagation.
Proposed for presentation at the Spiking Neural networks as Universal Function Approximators (SNUFA) 2022 held November 9-10, 2022 in ,, 2022Corinne Teeter +2 more
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Spike Timing-Dependent Plasticity (STDP)
2017We mentioned spike timing-dependent plasticity (STDP) in Section 33.2 already. Experimental evidence for STDP was presented in [68]: The connection from cell A to cell B was shown to be strengthened when A fired just before B (Hebbian learning), and weakened when B fired just before A (anti-Hebbian learning).
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STDP Learning Under Variable Noise Levels
Proceedings of the International Conference on Neural Computation Theory and Applications, 2014Spike-timing-dependent plasticity (STDP) is a set of Hebbian learning rules which are firmly based on biological evidence. It has been demonstrated that one of the STDP learning rules is suited for learning spatiotemporal patterns in a very noisy environment.
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