I recently read a potentially relevant review on this subject from earlier this year: A review of learning in biologically plausible spiking neural networks

Does anyone have thoughts on how to think about the differences (esp. in terms of learning) between BindsNet, Norse, and Rockpool? 

Best wishes,
Josh





On Mon, Jun 15, 2020 at 11:18 AM Benedikt S. Vogler <benedikt.s.vogler@tum.de> wrote:
Dear Sonja,

nest is a spiking neural network simulator and not a machine learning library.
My current knowledge on SNN is that there is no established learning algorithm as there are best-practices for ANNs.
Here is a brief overview over some methods:
There ist STDP for correlation learning, reward based STDP is a reinforcement learning algorithm still being researched. Another option is to train a ANN and then convert it to a SNN.
SNN don’t have derivative of the activation function, therefore backprop is not transferable easily to SNN. There are methods like BPTT and e-prop to make backprop work. There might be more methods in the area of backprop adaptions. I am not an expert on this.
SNNs can also be used for reservoir computing which is yet another thing (https://gitlab.com/aiCTX/rockpool).
I am not sure which learning algorithm norse uses, they mention Policy gradient.

Kind regards,
Benedikt S. Vogler


> Am 15.06.2020 um 14:24 schrieb s.kraemer96@gmx.net:
>
> Dear all,
> I´m writing a master thesis on spiking neural networks and how transparent they are. For that I need to implement a SNN network and train it. So I started with Brian but that is much to complex and I don´t need something special. So I decided to use PyNest. I did all the tutorials but I´m missing a tutorial how to train the network. I don´t know how to put in a dataset to train the model. I haven´t found anything to this topic. So my questions are:
> 1.    Can PyNest train set up a SNN and train it trough data and if  not is there another simulator who can do this?
> 2.    How do I do it? Is there anything I missed to read or can someone send me an example? This would be very helpful.
> Thanks for your help.
>
> Best,
> Sonja
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