Learning in spiking neural networks by reinforcement of stochastic synaptic transmission.
about
Selectionist and evolutionary approaches to brain function: a critical appraisalA Hebbian learning rule gives rise to mirror neurons and links them to control theoretic inverse models.Copying and evolution of neuronal topologyVocal experimentation in the juvenile songbird requires a basal ganglia circuitNeuromodulated Spike-Timing-Dependent Plasticity, and Theory of Three-Factor Learning RulesSynaptic size dynamics as an effectively stochastic processGrid cells generate an analog error-correcting code for singularly precise neural computationToward an Integration of Deep Learning and NeuroscienceAn Approximation of the Error Backpropagation Algorithm in a Predictive Coding Network with Local Hebbian Synaptic Plasticity.Training spiking neural models using artificial bee colony.A novel learning rule for long-term plasticity of short-term synaptic plasticity enhances temporal processing.A reward-modulated hebbian learning rule can explain experimentally observed network reorganization in a brain control task.Neural syntax: cell assemblies, synapsembles, and readers.Spike-based reinforcement learning in continuous state and action space: when policy gradient methods failSynaptic state matching: a dynamical architecture for predictive internal representation and feature detection.Robustness of learning that is based on covariance-driven synaptic plasticity.Enabling functional neural circuit simulations with distributed computing of neuromodulated plasticity.Emergence of functional hierarchy in a multiple timescale neural network model: a humanoid robot experiment.Reinforcement learning on slow features of high-dimensional input streamsDemocratic population decisions result in robust policy-gradient learning: a parametric study with GPU simulations.An imperfect dopaminergic error signal can drive temporal-difference learning.Maximization of learning speed in the motor cortex due to neuronal redundancy.Spike-based decision learning of Nash equilibria in two-player gamesReinforcement learning of targeted movement in a spiking neuronal model of motor cortexReinforcement learning, spike-time-dependent plasticity, and the BCM rule.Temporal structure in associative retrieval.Dynamics of dual prism adaptation: relating novel experimental results to a minimalistic neural model.Operant matching is a generic outcome of synaptic plasticity based on the covariance between reward and neural activity.Excitatory, inhibitory, and structural plasticity produce correlated connectivity in random networks trained to solve paired-stimulus tasksPoisson-like spiking in circuits with probabilistic synapsesChoice-correlated activity fluctuations underlie learning of neuronal category representationHow attention can create synaptic tags for the learning of working memories in sequential tasks.Neural networks and perceptual learning.Gradient estimation in dendritic reinforcement learningDynamic afferent synapses to decision-making networks improve performance in tasks requiring stimulus associations and discriminations.What can neurons do for their brain? Communicate selectivity with bursts.Phenomenological models of synaptic plasticity based on spike timing.Decision making in recurrent neuronal circuits.Sniff-Like Patterned Input Results in Long-Term Plasticity at the Rat Olfactory Bulb Mitral and Tufted Cell to Granule Cell Synapse.Role of synaptic dynamics and heterogeneity in neuronal learning of temporal code
P2860
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P2860
Learning in spiking neural networks by reinforcement of stochastic synaptic transmission.
description
2003 nî lūn-bûn
@nan
2003年の論文
@ja
2003年学术文章
@wuu
2003年学术文章
@zh
2003年学术文章
@zh-cn
2003年学术文章
@zh-hans
2003年学术文章
@zh-my
2003年学术文章
@zh-sg
2003年學術文章
@yue
2003年學術文章
@zh-hant
name
Learning in spiking neural networks by reinforcement of stochastic synaptic transmission.
@en
Learning in spiking neural networks by reinforcement of stochastic synaptic transmission.
@nl
type
label
Learning in spiking neural networks by reinforcement of stochastic synaptic transmission.
@en
Learning in spiking neural networks by reinforcement of stochastic synaptic transmission.
@nl
prefLabel
Learning in spiking neural networks by reinforcement of stochastic synaptic transmission.
@en
Learning in spiking neural networks by reinforcement of stochastic synaptic transmission.
@nl
P1433
P1476
Learning in spiking neural networks by reinforcement of stochastic synaptic transmission.
@en
P2093
H Sebastian Seung
P304
P356
10.1016/S0896-6273(03)00761-X
P407
P577
2003-12-01T00:00:00Z