New paper out that investigates the accuracy of methods to improve quantification of cerebral blood flow with DCS

Traditionally, DCS estimates an index of brain blood flow by modeling the head as a homogeneous medium. However, this approach can lead to significant errors due to the influence of the scalp and skull. More sophisticated models that treat the head as a three-layered medium (i.e., scalp, skull, brain) are becoming more common because they help minimize the influence of extracerebral layers on the estimate of cerebral blood flow. However, these models rely on a priori knowledge of the optical properties and thicknesses of the scalp, skull, and brain. Errors in these values can lead to errors in the estimation of brain blood flow, although the magnitude of this influence has not been rigorously characterized. In this paper, we investigate the accuracy of measuring cerebral blood flow with a three-layer model when errors in layer optical properties or thicknesses are present.  Through a series of in silico  experiments, we demonstrate that brain blood flow is highly sensitive to errors in brain optical properties and skull and scalp thicknesses. Relative changes in brain blood flow are less sensitive to optical properties but are influenced appreciably by errors in layer thickness. Thus, when using the three-layer model, accurate estimation of scalp and skull thickness are required for reliable results. More details here.