Spiking Neural Network Classifier Implementation

Question

Are there any machine learning packages that implement spiking neural networks? or any other stand-alone implementations of them that could get me started to work with?

Answer 1

A python library named Brian ought to be useful for you.

There's also what I believe is a programing language named NEURON, but Brian is fairly easy to learn, at least for the basics. It took me a while though to figure out how to do a couple small things, since its a really high level language or whatnot.

Answer 2

Here are links for brain simulator

https://github.com/brian-team/brian2

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2605403/

http://briansimulator.org/

Answer 3

There are several other SNN platforms these days that allows you to run classification. I have worked with NeuCube (https://kedri.aut.ac.nz/R-and-D-Systems/neucube) which is a Matlab & Java-based SNN platform.

Also, check out Akida Development Environment (ADE) from Brainchip Inc (https://brainchipinc.com/). One of the best features of ADE is that it's APIs are based on tensorflow/keras structure and also supports CNN2SNN converter to use your deep learning models in SNN domain. SNN models developed using this platform can be deployed on their neuromorphic processor Akida.

I believe there are other platforms such as PyNN and Nengo (compatibility to run models on Loihi) within the SNN domain.

Answer 4

You can install the Nengo Loihi library for deployment not only of spiking neural networks but also neuromorphic neural networks. here's the link to their website: https://www.nengo.ai/nengo-loihi/v1.0.0/index.html

You can find on Kaggle an implementation of the ciphar10 dataset, locally loaded, using Nengo Loihi library. Here's the link: https://www.kaggle.com/migueltoms/neuromorphic-ciphar-10-loihi-comparison-of-results