Learning Resources: Neuromatch Academy's Lessons | Cosyne 2018 Tutorial
Useful Links: Getting Help | Issue Tracker | Contributing Guidelines

Overview

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

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  Run the following pip command in your virtual environment.

  macOS/LinuxWindows

  pip install nemos
  

  python -m pip install nemos
  

  For more information see:
  Install

• Getting Started

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

  Quickstart

•   Background

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

  Background

•   Neural Modeling

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

  Requires familiarity with the theory.
  Tutorials

•   How-To Guide

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

  Requires familiarity with the theory.
  How-To Guide

•   API Guide

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

  Requires familiarity with the theory.
  API Guide

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.