Depth selectivity in time-domain fNIRS by analyzing moments and time windows

Time-domain fNIRS facilitates the elimination of the influence of extracerebral, systemic effects on measured signals since it contains time-of-flight information that is related to the penetration depth. Employing perturbation and MonteCarlo simulations, we quantitatively characterized and compared the performance of measurands based on moments and time windows of time-of-flight distributions. We extend our analysis to investigate whether higher moments and MellinLaplace (ML) moments promise improvements in performance. The comparison is based on spatial sensitivity profiles as well as metrics for relative contrast, contrast-to-noise ratio (CNR), depth selectivity, and the product of CNR and depth selectivity for layered absorption changes. The influence of reduced scattering coefficient, thickness of the superficial layer, and source-detector distance was analyzed. The third central moment performs similarly to variance and is worth considering for data analyzes. Higher order ML moments perform similarly to time windows and they likewise provide variable depth selectivity.