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

First Steps

Get started with nilearn

Examples

Visit our example gallery

User Guide

Browse the full documentation

  • glass_brain

  • surface_plot

  • oasis_weights

  • connectome

  • rest_parcellations

  • canica

  • tvl1_haxby

  • haxby_weights

  • searchlight

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Nilearn is part of the NiPy ecosystem.