# PySpike - A Python library for analyzing spike train synchrony

arXiv: https://arxiv.org/abs/1603.03293 · HTML: https://mlsanity.com/paper/1603.03293/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Mar 2016.

## Built on by (most cited first, 1 of 1)

- [Tree-Based Learning on Amperometric Time Series Data Demonstrates High Accuracy for Classification](https://mlsanity.com/paper/2302.02650/) (2023)

## Abstract (arXiv)

Understanding how the brain functions is one of the biggest challenges of our time. The analysis of experimentally recorded neural firing patterns (spike trains) plays a crucial role in addressing this problem. Here, the PySpike library is introduced, a Python package for spike train analysis providing parameter-free and time-scale independent measures of spike train synchrony. It allows to compute similarity and dissimilarity profiles, averaged values and distance matrices. Although mainly focusing on neuroscience, PySpike can also be applied in other contexts like climate research or social sciences. The package is available as Open Source on Github and PyPI.