Spikeometric

The spikeometric package is a framework for simulating spiking neural networks (SNNs) using generalized linear models (GLMs) and Linear-Nonlinear-Poisson models (LNPs) in Python. It is built on top of the PyTorch Geometric package and makes use of their powerful graph neural network (GNN) modules and efficient graph representation. It is designed to be fast, flexible and easy to use, and is intended for research purposes.

Installation

To use this package you will need to first install the following packages:

• PyTorch

• PyTorch Geometric

Make sure you get the cuda versions if you are planning to use a GPU.

Then you can install spikeometric using pip:

pip install spikeometric

Introduction

• Introduction by example

Tutorials

• Parameter tuning
• Implementing a new model
• Working with stimuli

Benchmarks

• Memory usage and performance

API Reference

• Connectivity datasets
• Models
• Stimulus