Important

This guide hasn’t been updated since January 2017 and is based on an older version of Nipype. The code in this guide is not tested against newer Nipype versions and might not work anymore. For a newer, more up to date and better introduction to Nipype, please check out the the Nipype Tutorial.

Welcome to Nipype Beginner’s Guide!

This Beginner’s guide will teach you all you need to know for your first steps with Nipype. You will see that Nipype is a really practical and easy to learn neuroimaging toolbox, written in Python, that helps to connect many of the different softwares used in neuroimaging, such as SPM, FSL, FreeSurfer and AFNI. The goal of this Beginner’s guide is to teach you the basics about Neuroimaging and to show you each step along the way of a complete neuroimaging analysis. By learning Nipype, you will become an expert in neuroimaging and be able to analyze your own dataset in no time.

Neuroimaging and Nipype

This part introduces you to Nipype, explains what it is and how it works. It will also introduce you to neuroimaging in general and tell you all you need to know for the analysis of a basic neuroimaging dataset. At the end, you should be able to understand what Nipype is, how it is working and why it is so useful in neuroimaging.

Introduction to Nipype What is Nipype? A Short Example Nipype’s Architecture Introduction to Neuroimaging Acquisition of MRI Data Specifics of MRI Data Modalities of MRI Data Analysis Steps Nipype and Neuroimaging Neuroimaging Workflow Nipype Workflow

Get Nipype to run on your System

This part is all about downloading and installing Nipype and its dependencies. It will also show you how to set up all necessary environment variables and prepare everything, so that at the end you will be ready to run Nipype on your system.

Download and Install Nipype Prepare your System Anaconda NeuroDebian Nipype Download and Install Interfaces FSL FreeSurfer MATLAB SPM12 ANTs AFNI Additional interfaces Clean up your System Test your System

First steps with Nipype

This part will show you how to use Nipype by analyzing an fMRI dataset. By going through a neuroimaging analysis step by step, you will learn all about Nipype, its building blocks and how to connect them to create your own analysis workflow. At the end you will be able to run your own neuroimaging analysis and make your first experiences with Nipype on real data.

Prepare your Dataset Download the tutorial dataset Make the dataset ready for Nipype Resulting Folder Structure How To Build A Pipeline Important building blocks Example preprocessing pipeline Example Script Resulting Folder Structure Common Issues, Problems and Crashes How To Visualize A Pipeline What kind of graph do you need? Tweak your visualization Examples of each visualization type

From beginner to expert

This part contains many different implementations of Nipype. Amongst others, you will learn how to do a first and second level analysis, how to normalize your data, how to use Nipype in a more flexible way (e.g. import and reuse of other workflows), how to do a region of interest (ROI) analysis, how to do a surfaced based morphometry (SBM) analysis, how to use ANTs to create your own dataset template, how to quality control your data, how to use additional supporting toolboxes such as bips and mindboggle and more…

How To Build A Pipeline For A First Level fMRI Analysis Define the structure of your pipeline Write your pipeline script Visualize your pipeline Resulting Folder Structure How To Normalize Your Data Normalize Your Data with ANTs Normalize Your Data with SPM12 How To Build A Pipeline For A Second Level fMRI Analysis Write your pipeline script Visualize your pipeline Resulting Folder Structure

Support

First things first: Don’t panic! This part will show you how to tackle almost all problems you can encounter by using Nipype, iPython or this beginner’s guide. And for everything else, there’s always chocolate!

Help & Support Links to Nipype, Programming and Neuroimaging Frequently Asked Questions Glossary

Downloads

Everything important to download can be found in this section. Nipype can be downloaded here: How to install Nipype. All Scripts used in this Beginner’s Guide can be found on the Beginner’s Guide Github homepage. The dataset DS102: Flanker task (event-related) used as the tutorial dataset for this beginner’s guide can be directly downloaded here: ds102_raw.tgz. This Beginner’s Guide can be downloaded as a PDF here.