Study of data analysis methods in functional connectivity photoacoustic tomography (fcPAT)

Resting-state functional connectivity (RSFC) is a method to monitor the health of the brain and find out abnormalities in brain networks. Recently functional connectivity photoacoustic tomography (fcPAT) has been used to study RSFC in the mouse brain. The current method of RSFC data analysis is called "seed-based". This method is not data-driven, and involves user intervention. Alternative signal processing approaches, such as singular value decomposition (SVD) and independent component analysis (ICA), will be explored to complement and cross validate the seed-based approach, possibly substituting them for the seed-based method. The methods are implemented and applied on the fcPAT data of a mouse brain.