Before revision:  We demonstrate that the proposed method is useful for identifying distinct state spacesin the resting-state connectivities of males and females through the transition matrices of the common states .
After revision:  We demonstrate that the proposed method is useful for identifying distinct state spacesin the resting-state connectivities of males and females is identified. Comparison with existing methods: We demonstrate that the proposed statistical model has less rapid state changes caused by noise and improves the accuracy in identifying and discriminating different states. Conclusions: We propose a new regression model on dynamically changing correlation matrices that provides better performance over existing windowed correlation and is more reliable for the modeling of dynamic connectivity .