Auryn simulator

Simulator for spiking neural networks with synaptic plasticity

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tutorials:start [2016/11/17 07:11] – Streamlines text zenketutorials:start [2018/05/30 07:21] (current) – Changes link zenke
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   * [[Tutorial 1]]: Simulate a single AdEx neuron and record spikes and membrane potentials.   * [[Tutorial 1]]: Simulate a single AdEx neuron and record spikes and membrane potentials.
-  * [[Tutorial 2]]: A simple balanced network model.  +  * [[Tutorial 2]]: Build the Vogels & Abbott balanced network model.  
-  * [[Tutorial 3]]: network model with inhibitory plasticity.+  * [[Tutorial 3]]: Create and simulate a network model with inhibitory plasticity
 +  * [[Tutorial 4]]: [[manual:SuperSpike]]: Supervised learning in spiking networks (coming soon).
  
  
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   * [[Writing your own plasticity model]]. This is a simple walk-through for the logic behind plastic updates and what methods are called where and when. It sketches in simple terms what needs to be done to implement a new custom synapse model in Auryn.   * [[Writing your own plasticity model]]. This is a simple walk-through for the logic behind plastic updates and what methods are called where and when. It sketches in simple terms what needs to be done to implement a new custom synapse model in Auryn.
   * [[Multiple synaptic state variables]]. This example aims at creating a plastic connection object in which the the actual weight change is the low-pass filtered output of meta-variable which is influenced by STDP.   * [[Multiple synaptic state variables]]. This example aims at creating a plastic connection object in which the the actual weight change is the low-pass filtered output of meta-variable which is influenced by STDP.
-  * Neuron Models: Coming soon. 
  
  
tutorials/start.1479366714.txt.gz · Last modified: 2016/11/17 07:11 by zenke