Functional MRI (fMRI) methods are presented for utilizing a magnetic resonance tomograph to map connectivity between brain areas in the resting state in real-time without the use of regression of confounding signal changes. They encompass: (a) iterative computation of the sliding window correlation between the signal time courses in a seed region and each voxel of an fMRI image series, (b) Fisher Z-transformation of each correlation map, (c) computation of a running mean and a running standard deviation of the Z-maps across a second sliding window to produce a series of meta mean maps and a series of meta standard deviation maps, and (d) thresholding of the meta maps. This methodology can be combined with regression of confounding signals within the sliding window. It is also applicable to task-based real-time fMRI, if the location of at least one task-activated voxel is known.
Seed-Based Connectivity Analysis in Functional MRI