Brian 2 frontend to the GeNN simulator

A library for deep learning with Spiking Neural Networks (SNN).

Implementation of the paper 'Unsupervised learning of digit recognition using spike-timing-dependent plasticity' by Peter Diehl and Matthew Cook, using the PyGeNN (Python interface of GeNN) SNN framework

Jacobian-Enhanced Neural Networks (JENN) are fully connected multi-layer perceptrons, whose training process was modified to account for gradient information. Specifically, the parameters are learned by minimizing the Least Squares Estimator (LSE), modified to minimize prediction error of both response values and partial derivatives.