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The change of BOLD signal relies heavily upon the resting blood volume fraction (    ) associated with regional vasculature. However, existing hemodynamic data assimilation studies pretermit such concern. They simply assign the value in a physiologically plausible range to get over ill-conditioning of the assimilation problem and fail to explore actual. Such performance might lead to unreliable model estimation. In this work, we present the first exploration of the influence ofon fMRI data assimilation, where actualwithin a given cortical area was calibrated by an MR angiography experiment and then was augmented into the assimilation scheme. We have investigated the impact ofon single-region data assimilation and multi-region data assimilation (dynamic cause modeling, DCM) in a classical flashing checkerboard experiment.  Results  show that the employment of an assumedin fMRI data assimilation is only suitable for fMRI signal reconstruction and activation detection grounded on this signal, and not suitable for estimation of unobserved states and effective connectivity study. We thereby argue that introducing physically realisticin the assimilation process may provide more reliable estimation of physiological information, which contributes to a better understanding of the underlying hemodynamic processes. Such an effort is valuable and should be well appreciated.

Exploiting Magnetic Resonance Angiography Imaging Improves Model Estimation of BOLD Signal