The tempotron: a neuron that learns spike timing-based decisions.
about
Abstracts of the 16th Annual Meeting of the Israel Society for Neuroscience, November 25-27, 2007, Eilat, IsraelQualitative-Modeling-Based Silicon Neurons and Their NetworksContext matters: the illusive simplicity of macaque V1 receptive fieldsSimilarity of cortical activity patterns predicts generalization behavior.A Comprehensive Account of Sound Sequence Imitation in the Songbird.Integrating information from different senses in the auditory cortexPlasticity of cortical excitatory-inhibitory balance.Cortical activity patterns predict robust speech discrimination ability in noise.A novel learning rule for long-term plasticity of short-term synaptic plasticity enhances temporal processing.Simulation of networks of spiking neurons: a review of tools and strategies.Time-warp-invariant neuronal processing.Representation of time-varying stimuli by a network exhibiting oscillations on a faster time scale.Neural syntax: cell assemblies, synapsembles, and readers.An Approximation to the Adaptive Exponential Integrate-and-Fire Neuron Model Allows Fast and Predictive Fitting to Physiological DataDistinct Spatiotemporal Response Properties of Excitatory Versus Inhibitory Neurons in the Mouse Auditory Cortex.Spike timing dependent plasticity finds the start of repeating patterns in continuous spike trainsA learning theory for reward-modulated spike-timing-dependent plasticity with application to biofeedbackThe temporal winner-take-all readoutSupervised learning with decision margins in pools of spiking neuronsSpectral analysis of input spike trains by spike-timing-dependent plasticity.The chronotron: a neuron that learns to fire temporally precise spike patterns.Computing complex visual features with retinal spike times.Temporal modulation of spike-timing-dependent plasticityState-dependent computations: spatiotemporal processing in cortical networks.The Convallis rule for unsupervised learning in cortical networks.Precise-spike-driven synaptic plasticity: learning hetero-association of spatiotemporal spike patternsEnergy Efficient Sparse Connectivity from Imbalanced Synaptic Plasticity RulesSomato-dendritic Synaptic Plasticity and Error-backpropagation in Active Dendrites.Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity.Supervised Learning in Spiking Neural Networks for Precise Temporal EncodingLow error discrimination using a correlated population codeEncoding in Balanced Networks: Revisiting Spike Patterns and Chaos in Stimulus-Driven SystemsNeural ensemble dynamics underlying a long-term associative memory.Emulating short-term synaptic dynamics with memristive devicesTemporal compression mediated by short-term synaptic plasticityAn Efficient Supervised Training Algorithm for Multilayer Spiking Neural NetworksQuantifying neuronal network dynamics through coarse-grained event trees.Building functional networks of spiking model neurons.A plastic temporal brain code for conscious state generationRole of synaptic dynamics and heterogeneity in neuronal learning of temporal code
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The tempotron: a neuron that learns spike timing-based decisions.
description
2006 nî lūn-bûn
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name
The tempotron: a neuron that learns spike timing-based decisions.
@en
The tempotron: a neuron that learns spike timing-based decisions.
@nl
type
label
The tempotron: a neuron that learns spike timing-based decisions.
@en
The tempotron: a neuron that learns spike timing-based decisions.
@nl
prefLabel
The tempotron: a neuron that learns spike timing-based decisions.
@en
The tempotron: a neuron that learns spike timing-based decisions.
@nl
P356
P1433
P1476
The tempotron: a neuron that learns spike timing-based decisions.
@en
P2093
Haim Sompolinsky
Robert Gütig
P2860
P2888
P304
P356
10.1038/NN1643
P407
P577
2006-02-12T00:00:00Z