An introduction to nilearn
Contents
An introduction to nilearn¶
In this tutorial, we’ll see how the Python library nilearn allows us to easily perform machine learning analyses with neuroimaging data, specifically MRI and fMRI.
Structure of the workshop¶
This workshop is divided into two main topics:
Extracting meaningful features from neuroimaging data
Performing classification analyses and visualizing results
Although we highlight a small subset of the available functionality here, please see the Nilearn documentation for an in-depth review of the many different kinds of analyses that can be run using Nilearn. For example, in addition to classification analyses, Nilearn can also be used to conduct Multi-Voxel Pattern (MVP) decoding and General Linear Model (GLM) analyses.