Applications of Python in Neuroimaging

Applications in Neuroimaging

Lesson One: Introduction to analysing MRI in Python

Review this beginner's introduction to MRI in Python. Specifically, you should complete:

• Section 3: Anatomy of a NIfTI

• Section 5: Exploring open MRI datasets

The other sections can provide a general overview of basic programming and neuroimaging principles, but these two sections provide the best and most direct introduction to basic neuroimaging in Python.

Lesson Two: Modality Specific Tutorials

Next, complete these more detailed lessons as needed depending on what modality you’re working with:

• sMRI analysis in Python

• fMRI analysis in Python

• dMRI analysis in Python

You do not need to complete all of these lessons, only the ones that you'll need to based on your project's requirements. If you don't know what you'll be using in your project, ask your supervisor and they'll be happy to help.

Lesson Three: Plotting and graphs

Familiarise yourself with some general purpose plotting tools in python via nilearn.plotting, including plotting of:

• Volumetric data

• Surface data

• FC matrices

• fMRI carpet plots

Like the previous lesson, you likely won't need to complete all of these tutorials; only the ones you'll actually use in your specific project.

Optional Lessons

These are some additional lessons that showcase what can be achieved in Python for neuroimaging. If your work needs these speciality tools, this might be helpful. Otherwise, these might be fairly niche.

MRI preprocessing pipelines in Python

• Warning: more complex than previous resources

Gradient analyses in Python