Related references
Note: Only part of the references are listed.Reinforcement learning in populations of spiking neurons
Robert Urbanczik et al.
NATURE NEUROSCIENCE (2009)
Spiking Neurons Can Learn to Solve Information Bottleneck Problems and Extract Independent Components
Stefan Klampfl et al.
NEURAL COMPUTATION (2009)
A Spiking Neural Network Model of an Actor-Critic Learning Agent
Wiebke Potjans et al.
NEURAL COMPUTATION (2009)
Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail
Eleni Vasilaki et al.
PLOS COMPUTATIONAL BIOLOGY (2009)
Modular toolkit for Data Processing (MDP): a Python data processing framework
Tiziano Zito
Frontiers in Neuroinformatics (2009)
Compartmentalized dendritic plasticity and input feature storage in neurons
Attila Losonczy et al.
NATURE (2008)
Unsupervised natural experience rapidly alters invariant object representation in visual cortex
Nuo Li et al.
SCIENCE (2008)
A Learning Theory for Reward-Modulated Spike-Timing-Dependent Plasticity with Application to Biofeedback
Robert Legenstein et al.
PLOS COMPUTATIONAL BIOLOGY (2008)
Reinforcement learning with modulated spike timing-dependent synaptic plasticity
Michael A. Farries et al.
JOURNAL OF NEUROPHYSIOLOGY (2007)
Solving the distal reward problem through linkage of STDP and dopamine signaling
Eugene M. Izhikevich
CEREBRAL CORTEX (2007)
Reinforcement learning, spike-time-dependent plasticity, and the BCM rule
Dorit Baras et al.
NEURAL COMPUTATION (2007)
Slowness and sparseness lead to place, head-direction, and spatial-view cells
Mathias Franzius et al.
PLOS COMPUTATIONAL BIOLOGY (2007)
Slowness: An objective for spike-timing-dependent plasticity?
Henning Sprekeler et al.
PLOS COMPUTATIONAL BIOLOGY (2007)
Reinforcement learning through modulation of spike-timing-dependent synaptic plasticity
Razvan V. Florian
NEURAL COMPUTATION (2007)
Gradient learning in spiking neural networks by dynamic perturbation of conductances
Ila R. Fiete et al.
PHYSICAL REVIEW LETTERS (2006)
Optimal spike-timing-dependent plasticity for precise action potential firing in supervised learning
Jean-Pascal Pfister et al.
NEURAL COMPUTATION (2006)
A model of the ventral visual system based on temporal stability and local memory
Reto Wyss et al.
PLOS BIOLOGY (2006)
Learning viewpoint invariant object representations using a temporal coherence principle
W Einhäuser et al.
BIOLOGICAL CYBERNETICS (2005)
Wire length as a circuit complexity measure
RA Legenstein et al.
JOURNAL OF COMPUTER AND SYSTEM SCIENCES (2005)
Slow feature analysis yields a rich repertoire of complex cell properties
P Berkes et al.
JOURNAL OF VISION (2005)
Learning in spiking neural networks by reinforcement of stochastic synaptic transmission
HS Seung
NEURON (2003)
Variable resolution discretization in optimal control
R Munos et al.
MACHINE LEARNING (2002)
Dopamine-dependent plasticity of corticostriatal synapses
JNJ Reynolds et al.
NEURAL NETWORKS (2002)
Slow feature analysis: Unsupervised learning of invariances
L Wiskott et al.
NEURAL COMPUTATION (2002)
A global geometric framework for nonlinear dimensionality reduction
JB Tenenbaum et al.
SCIENCE (2000)
A wire length minimization approach to ocular dominance patterns in mammalian visual cortex
DB Chklovskii et al.
PHYSICA A (2000)