<--- Back to Details
First PageDocument Content
Computational neuroscience / Neuroscience / Neural networks / Nervous system / Artificial neural networks / Biological neuron model / Spiking neural network / Neuron / Biological neural network / Inhibitory postsynaptic potential / Action potential / Synaptic weight
Date: 2008-11-13 06:07:09
Computational neuroscience
Neuroscience
Neural networks
Nervous system
Artificial neural networks
Biological neuron model
Spiking neural network
Neuron
Biological neural network
Inhibitory postsynaptic potential
Action potential
Synaptic weight

Spiking Neural Networks Introduction 3 v(t) (mV)

Add to Reading List

Source URL: www.inrialpes.fr

Download Document from Source Website

File Size: 853,08 KB

Share Document on Facebook

Similar Documents

Journal of Computational Neuroscience 18, 105–121, 2005 c 2005 Springer Science + Business Media, Inc. Manufactured in The Netherlands.  A Cellular Mechanism for Graded Persistent Activity in a Model Neuron and Its Im

Journal of Computational Neuroscience 18, 105–121, 2005 c 2005 Springer Science + Business Media, Inc. Manufactured in The Netherlands.  A Cellular Mechanism for Graded Persistent Activity in a Model Neuron and Its Im

DocID: 1vcJi - View Document

munich  Bernstein Center for Computational Neuroscience Munich

munich Bernstein Center for Computational Neuroscience Munich

DocID: 1vcv8 - View Document

Blending computational and experimental neuroscience

Blending computational and experimental neuroscience

DocID: 1v9kZ - View Document

Florentin Wörgötter Bernstein Center for Computational Neuroscience Göttingen Florentin Wörgötter studied biology and mathematics at the University of Düsseldorf, Germany. He received a Ph.D. degree, studying

Florentin Wörgötter Bernstein Center for Computational Neuroscience Göttingen Florentin Wörgötter studied biology and mathematics at the University of Düsseldorf, Germany. He received a Ph.D. degree, studying

DocID: 1v914 - View Document

Nonlinear synaptic interaction as a computational resource in the Neural Engineering Framework Andreas Stöckel, Aaron R. Voelker, Chris Eliasmith Centre for Theoretical Neuroscience, University of Waterloo {astoecke, ar

Nonlinear synaptic interaction as a computational resource in the Neural Engineering Framework Andreas Stöckel, Aaron R. Voelker, Chris Eliasmith Centre for Theoretical Neuroscience, University of Waterloo {astoecke, ar

DocID: 1uuia - View Document