Neural ModelS#

NeMoS (Neural ModelS) 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).

We provide a Poisson GLM for analyzing spike counts, and a Gamma GLM for calcium or voltage imaging traces.

  Installation Instructions

Run the following pip command in your virtual environment.

pip install nemos
Install
  Getting Started

New to NeMoS? Get the ball rolling with our quickstart.

Quickstart
  Background

Refresh your theoretical knowledge before diving into data analysis with our notes.

Background
  How-to Guide

Already familiar with the concepts? Learn how you to process and analyze your data with NeMoS.

How-to-Guide
  Neural Modeling

Explore fully worked examples to learn how to analyze neural recordings from scratch.

Tutorials
  API Reference

Access a detailed description of each module and function, including parameters and functionality.

API Reference

License#

Open source, licensed under MIT.

Support#

This package is supported by the Center for Computational Neuroscience, in the Flatiron Institute of the Simons Foundation.

Flatiron Center for Computational Neuroscience logo White. Flatiron Center for Computational Neuroscience logo.