# Training spiking neural networks with surrogate gradient descent

**URL:** https://brian.discourse.group/t/training-spiking-neural-networks-with-surrogate-gradient-descent/21
**Category:** Science, Projects, and Showcases
**Created:** [13 August 2020 14:54 UTC](https://brian.discourse.group/t/training-spiking-neural-networks-with-surrogate-gradient-descent/21 "2020-08-13T14:54:04Z")
**Posts on this page:** 1
**Page:** 1

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### Author: ![dan](https://yyz2.discourse-cdn.com/free1/user_avatar/brian.discourse.group/dan/32/7_2.png) [@dan](https://brian.discourse.group/u/dan)
#### Post date: [13 August 2020 14:54 UTC](https://brian.discourse.group/t/training-spiking-neural-networks-with-surrogate-gradient-descent/21/1 "2020-08-13T14:54:04Z")

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I’m super excited at the moment about Friedemann Zenke’s work on “surrogate gradient descent”. It’s a neat trick that lets you train SNNs with gradient descent that gets around the problem that gradients are zero almost everywhere in SNNs. It can give some pretty amazing results. Check out their [paper](https://arxiv.org/abs/1901.09948) and [tutorial](https://github.com/fzenke/spytorch).

Unfortunately, there’s no support for this at the moment in Brian but we’re working on it!