I am working on functional connectivity between brain regions, where functional connectivity is represented by the Pearson correlation coefficient between the time series (fMRI) of brain regions. I am interested in the dynamics of functional connectivity over time, and therefore have calculated 1100 correlations coefficients over time (one per time point, per sliding windows analysis) for each connection.
As a measure of dynamics, I calculate the variance of each correlation over time. The variances of several connections are then averaged (and the square root is taken to get the standard deviation) and are compared to the same measure (variance/standard deviation of the same connections) from another participant.
For comparing these variances/standard deviation values across participants, is it necessary to transform the initial r-values into z-scores? Or is this just necessary in the case I want to compare the r-values themselves?
