Seed Map Parcellation Wrapper

Overview

Seed-based Correlation Analysis (SCA) is one of the most common ways to explore functional connectivity within the brain. Based on the time series of a seed voxel (or collection of voxels, often called a region of interest [ROI]), connectivity is calculated as the correlation of time series for all other voxels in the brain. The result of Seed based correlation is a connectivity map showing Pearson correlation for each voxel indicating how well its time series correlates with the time series of the seed.

Code Locations

You can find the code to run the seed map wrapper on Gitlab. There is also a full tutorial of how to run the code.