Nilearn 2016

Introduction

Nilearn enables approachable and versatile analyses of brain volumes. It provides statistical and machine-learning tools, with instructive documentation & open community.

It supports general linear model (GLM) based analysis and leverages the scikit-learn Python toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis.

Nilearn also includes the functionality of Nistats. Here’s a guide to replacing Nistats imports to work in Nilearn. ¹

Installed version(s)

The following versions are installed and currently available...

... on environment hpc-env/8.3:

• Nilearn/0.7.1-foss-2019b-Python-3.7.4

Loading / Using Nilearn

To load the desired version of the module, use the module load command, e.g.

module load hpc-env/8.3
module load Nilearn

Always remember: this command is case sensitive!

If you want to find out more about Nilearnon the HPC cluster, you can use the command

module spider Nilearn

This will show you basic information e.g. a short description and the currently installed version.

Documentation

The full documentation can be found here.