tutorials:tutorial_3
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tutorials:tutorial_3 [2016/09/01 22:04] – created zenke | tutorials:tutorial_3 [2016/09/02 04:46] (current) – [Running the simulation] moves section zenke | ||
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As you have seen in the previous section the firing rate distribution is relatively wide in our random network. Moreover firing rates are pretty high. If you have tried to tune the weights such that the network exhibits a more plausible activity level, you might have noticed that this not completely trivial and the rates can in fact be quite sensitive to the synaptic weight parameters. | As you have seen in the previous section the firing rate distribution is relatively wide in our random network. Moreover firing rates are pretty high. If you have tried to tune the weights such that the network exhibits a more plausible activity level, you might have noticed that this not completely trivial and the rates can in fact be quite sensitive to the synaptic weight parameters. | ||
- | However, we know that real synapses are plastic and a diversity of plasticity processes is at work in real neural networks which could achieve this tuning automatically. Let's now extend our previous model with one form of homeostatic plasticity. To that end we would like to exchange our sparse static connectivity of the excitatory-to-excitatory synapses in [[Tutorial 2]] to plastic synapses. Here we will use a homeostatic form of [[http:// | + | However, we know that real synapses are plastic and a diversity of plasticity processes is at work in real neural networks which could achieve this tuning automatically. Let's now extend our previous model with one form of homeostatic plasticity. To that end we would like to exchange our sparse static connectivity of the excitatory-to-excitatory synapses in [[Tutorial 2]] with plastic synapses. Here we will use a homeostatic form of [[http:// |
- | ===== Changing the static model ===== | + | The code of this example can be found here |
+ | https:// | ||
+ | |||
+ | ===== Changing the static | ||
All we need to change in our [[Tutorial 2|previous code]] is to replace the line in which we define con_ee with the following code | All we need to change in our [[Tutorial 2|previous code]] is to replace the line in which we define con_ee with the following code | ||
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That's it. Save the file and [[manual: | That's it. Save the file and [[manual: | ||
- | ===== Visualizations ===== | + | |
+ | ==== Speeding up simulations: | ||
+ | |||
+ | By now you have simulated plastic recurrent spiking neural networks with Auryn. You might have noticed that these simulations have started to be increasingly time consuming. Fortunately, | ||
+ | |||
+ | |||
+ | ====== Visualizations | ||
As you can see the transition around 10s where we switch plasticity on is quite drastic: | As you can see the transition around 10s where we switch plasticity on is quite drastic: | ||
- | {{ : | + | {{ : |
To appreciate this in more detail, let us take a look at the new files from the population rate monitors with the extension '' | To appreciate this in more detail, let us take a look at the new files from the population rate monitors with the extension '' | ||
+ | {{ : | ||
+ | As we can see the transition to low firing rates is indeed quite rapid, but the target rate of '' | ||
+ | Finally we can look at the firing rate distribution of homeostatic triplet STDP (every neuron in the model has the same homeostatic target rate, so we expect something uni-modal). | ||
+ | {{ : | ||
- | The full code for this tutorial can be found [[here]]. | ||
- | ===== Speeding up simulations: | ||
- | By now you have simulated plastic recurrent spiking neural networks with Auryn. You might have noticed that these simulations have started to be increasingly time consuming. Fortunately, | ||
+ | ====== Exercises ====== | ||
+ | |||
+ | * Speed up the simulation using parallelism | ||
+ | * Find a slower tau for which the network activity oscillates or explodes (see for [[http:// | ||
+ | * Add inhibitory synaptic plasticity to this simulation (see [[manual: |
tutorials/tutorial_3.1472767447.txt.gz · Last modified: 2016/09/01 22:04 by zenke