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Hebbian theory
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1	LETTER Communicated by Friedrich Sommer A Sparse Generative Model of V1 Simple Cells with Intrinsic Plasticity Add to Reading List Source URL: fias.uni-frankfurt.de Language: English - Date: 2008-09-09 03:37:37 Nervous system Computational neuroscience Neuroscience Computational statistics Artificial neural network Mathematical psychology Receptive field Biological neuron model Hebbian theory Visual cortex Feature learning Visual tilt effects
2	Simplified Rules and Theoretical Analysis for Information Bottleneck Optimization and PCA with Spiking Neurons Lars Buesing, Wolfgang Maass Institute for Theoretical Computer Science Add to Reading List Source URL: www.gatsby.ucl.ac.uk Language: English - Date: 2014-10-13 19:51:13 Computational neuroscience Neuroscience Nervous system Artificial neural networks Statistics Multivariate statistics Biophysics Biological neuron model Principal component analysis Artificial neuron Spike-timing-dependent plasticity Hebbian theory
3	Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity Bernhard Nessler1, Michael Pfeiffer1,2, Lars Buesing1, Wolfgang Maass1 1 Institute for Theoretical Computer Scienc Add to Reading List Source URL: www.gatsby.ucl.ac.uk Language: English* - Date: 2014-10-13 19:51:18 Neuroscience Nervous system Biology Computational neuroscience Neural networks Neurophysiology Spike-timing-dependent plasticity Biological neuron model Neural coding Hebbian theory Neuron Neural oscillation
4	ARTICLE Communicated by Erkki Oja Synergies Between Intrinsic and Synaptic Plasticity Mechanisms Add to Reading List Source URL: fias.uni-frankfurt.de Language: English - Date: 2007-03-20 04:22:35 Nervous system Neuroscience Biology Synaptic weight Hebbian theory Synaptic scaling BCM theory Synaptic plasticity Long-term depression Intrinsic plasticity Artificial neural network Nonsynaptic plasticity
5	Fully Autonomous Real-Time Autoencoder-Augmented Hebbian Learning through the Collection of Novel Experiences To appear in: Proc. of the Fifteenth International Conference on the Synthesis and Simulation of Living System Add to Reading List Source URL: eplex.cs.ucf.edu Language: English - Date: 2016-04-27 14:27:24 Computational neuroscience Neuroscience Artificial neural networks Cybernetics Cognition Machine learning Computational statistics Hebbian theory Autoencoder Deep learning Feature learning Unsupervised learning
6	Cogsci Virginia de Sa Application of Hopfield Memories to Understanding Human Conceptual Memory (From a paper with Ken McRae and Mark Seidenberg) Link to paper 1 Add to Reading List Source URL: www.cogsci.ucsd.edu Language: English - Date: 2009-06-03 14:17:19 Artificial neural networks Computational neuroscience Hopfield network Hebbian theory Semantics
7	From Modulated Hebbian Plasticity to Simple Behavior Learning through Noise and Weight Saturation Preprint accepted for publication in Neural Networksdoi: j.neunetAndrea Soltoggioa, Kenneth O Add to Reading List Source URL: eplex.cs.ucf.edu Language: English - Date: 2012-07-05 22:51:04 Neuroscience Computational neuroscience Neural networks Neurophysiology Artificial neural networks Hebbian theory Synaptic weight Chemical synapse Synaptic plasticity Biological neural network Biological neuron model Spike-timing-dependent plasticity
8	Real-time Hebbian Learning from Autoencoder Features for Control Tasks To appear in: Proc. of the Fourteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE 14). Cambridge, MA: MIT Press Add to Reading List Source URL: eplex.cs.ucf.edu Language: English - Date: 2014-06-04 09:58:39 Artificial neural networks Neuroscience Applied mathematics Cybernetics Autoencoder Hebbian theory Feature learning Deep learning Restricted Boltzmann machine Unsupervised learning Biological neural network Backpropagation
9	ARTIFICIALINTELLIGENCE 185 Connectionist Learning Procedures Geoffrey E. Hinton Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2009-01-08 11:44:02 Science Machine learning Connectionism Hopfield network Perceptron Self-organizing map Feature Pattern recognition Hebbian theory Neural networks Computational neuroscience Cybernetics
10	Effectiveness of Neural Network Learning Rules Generated by a Biophysical Model of Synaptic Plasticity David J. Jilk, Daniel M. Cer, and Randall C. O’Reilly Department of Psychology University of Colorado, Boulder 345 Add to Reading List Source URL: psych.colorado.edu Language: English - Date: 2003-06-14 00:35:46 Neural networks Neurophysiology Computational neuroscience Cell signaling Hebbian theory Synaptic weight Synaptic plasticity Spike-timing-dependent plasticity Chemical synapse Biology Neuroscience Nervous system

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