funcapprox-with-lowrank-EI-spikes

This repository accompanies the paper:

WF Podlaski & CK Machens (2024). "Approximating nonlinear functions with latent boundaries in low-rank excitatory-inhibitory spiking networks". Neural Computation 36.5: 803-857.

• The folder figure_generation_code contains a set of python scripts to generate each figure of the paper.
• The folder net_sim_code contains some python functions used to simulate the spiking networks in the figures.
• The folder tutorial_code contains a notebook demonstrating function approximation in the rank-2 E-I network.