External Projects

Pynapple has been designed as a lightweight package for representing time series and epochs in system neuroscience. As such, it can function as a foundational element for other analysis packages handling time series data. Here we keep track of external projects that uses pynapple.

NeMoS

NeMoS is a statistical modeling framework optimized for systems neuroscience and powered by JAX. It streamlines the process of defining and selecting models, through a collection of easy-to-use methods for feature design.

The core of nemos includes GPU-accelerated, well-tested implementations of standard statistical models, currently focusing on the Generalized Linear Model (GLM).

Check out this page for many examples of neural modelling using nemos and pynapple.

Note

Nemos is build on top of [jax](https://jax.readthedocs.io/en/latest/index.html), a library for high-performance numerical computing. To ensure full compatibility with nemos, consider installing [pynajax](pynapple-org/pynajax), a pynapple backend for jax.