Answers.Body: <p>Yes, they can. <a href="https://machinelearningmastery.com/gentle-introduction-backpropagation-time/" rel="nofollow noreferrer">Backpropagation through-time</a> (BPTT) and gradient
  descent is usually used to train such networks. The networks are are
  arranged in orderly layers which makes them unlike biological
  brains. And BPTT is not how real brains learn.</p>
  <p>For example, see the paper <a href="https://arxiv.org/abs/2210.04195" rel="nofollow noreferrer">Online Training Through Time for Spiking
  Neural Networks</a>. It demonstrates how regular artificial neural
  networks for image classification can be &quot;spikified&quot; and then trained
  using the method the authors proposes, online training through
  time. The figure shows their VGG11 spiking architecture for CIFAR10:</p>
  <p><a href="https://i.sstatic.net/822FQ5oTm.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/822FQ5oTm.png" alt="enter image description here" /></a></p>
  
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Body: <p>Can traditional neural networks be combined with spiking neural networks? And can there be training algorithms for such hybrid network? Does such hybrid network model biological brains? </p>
  
  <p>As I understand, brains contain only spiking networks and traditional networks are more or less crude approximation of them. But we can imagine that evolutionary computing can surpass the biological evolution and so the new structure can be created that are better than mind. And that is why the question about such tradition-spiking hybrid neural networks should be interesting.</p>
  
Tags: <neural-networks><spiking-neural-networks>
Title: Can traditional neural networks be combined with spiking neural networks?
UserDisplayName: TomR
ThreadText: # Can traditional neural networks be combined with spiking neural networks?
  
  (Asked by: username_0 on 2019-02-10)
  
  Can traditional neural networks be combined with spiking neural networks? And can there be training algorithms for such hybrid network? Does such hybrid network model biological brains?
  
  As I understand, brains contain only spiking networks and traditional networks are more or less crude approximation of them. But we can imagine that evolutionary computing can surpass the biological evolution and so the new structure can be created that are better than mind. And that is why the question about such tradition-spiking hybrid neural networks should be interesting.
  
  **Tags:** neural-networks, spiking-neural-networks
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2024-08-04. Score: 0
  
  Yes, they can. [Backpropagation through-time](https://machinelearningmastery.com/gentle-introduction-backpropagation-time/) (BPTT) and gradient
  descent is usually used to train such networks. The networks are are
  arranged in orderly layers which makes them unlike biological
  brains. And BPTT is not how real brains learn.
  
  For example, see the paper [Online Training Through Time for Spiking
  Neural Networks](https://arxiv.org/abs/2210.04195). It demonstrates how regular artificial neural
  networks for image classification can be "spikified" and then trained
  using the method the authors proposes, online training through
  time. The figure shows their VGG11 spiking architecture for CIFAR10:
  
  [![enter image description here](https://i.sstatic.net/822FQ5oTm.png)](https://i.sstatic.net/822FQ5oTm.png)
  
  
  ---
  
  