Introduction

What is scona

scona is a toolkit to analyse structural covariance brain networks using python.

scona takes regional cortical thickness data from structural MRI and generates a matrix of correlations between brain regions over a cohort of subjects. This correlation matrix is used to generate a variety of networks and network measures.

The logic behind structural covariance networks

Installing scona

You can install scona directly from the GitHub repository:

pip install git+https://github.com/WhitakerLab/scona.git

If you want to edit scona it’s recommended that you pass the -e flag to pip to install the package editably.

Getting Started

We have automatically generated docstring documentation and here’s how to navigate to it.

See all docs organized in the alphabetical order:

• Index

See the structure of the package:

• Module Index

See the submodules page:

• Subpackages

Besides, you can type any function into the search bar and come up with some results.

Alongside this documentation scona has some jupyter notebook tutorials.

Finding Help

If you have questions or want to get in touch, you can join our gitter lobby, tweet @Whitaker_Lab or email Isla at islastaden@gmail.com.