Influence of Resting Venous Blood Volume Fraction on Dynamic Causal Modeling and System Identifiability

Changes in BOLD signals are sensitive to the regional blood content associated with the vasculature, which is known as V(0) in hemodynamic models. In previous studies involving dynamic causal modeling (DCM) which embodies the hemodynamic model to invert the functional magnetic resonance imaging signals into neuronal activity, V(0) was arbitrarily set to a physiolog-ically plausible value to overcome the ill-posedness of the inverse problem. It is interesting to investigate how the V(0) value influences DCM. In this study we addressed this issue by using both synthetic and real experiments. The results show that the ability of DCM analysis to reveal information about brain causality depends critically on the assumed V(0) value used in the analysis procedure. The choice of V(0) value not only directly affects the strength of system connections, but more importantly also affects the inferences about the network architecture. Our analyses speak to a possible refinement of how the hemody-namic process is parameterized (i.e., by making V(0) a free parameter); however, the conditional dependencies induced by a more complex model may create more problems than they solve. Obtaining more realistic V(0) information in DCM can improve the identifiability of the system and would provide more reliable inferences about the properties of brain connectivity.