[Question] What is the traditional/literature supported approach to identifying statistically significant changes in a tiem-varying correlation matrix?

Have a correlation matrix whose elements vary with time. I want to be able to do statistical tests to identify statistically significant changes over time, and filter out nonsignificant changes over time.

I have found numerous methods in the literature but am not sure whether whatever method I'll be using is well supported or is not a recognized approached.

I am thinking about using some dimensionality reduction technique to see if the correlation structure enters certain "regimes" at different points in time, but I'm not sure if these methods would enable determining whether changes are statistically significant.