This paper explores a time-resolved functional imaging method based on Monte Carlo model for whole-body functional imaging of small animals. To improve the spatial resolution and quantitative accuracy of the functional map, a Bayesian hierarchical method with a high resolution spatial prior is applied to guide the optical reconstructions. Simulated data using the proposed approach are employed on an anatomically accurate mouse model where the optical properties range and volume limitations of the diffusion equation model exist. We investigate the performances of using time-gated data type and spatial priors to quantitatively image the functional parameters of multiple organs. Accurate reconstructions of the two main functional parameters of the blood volume and the relative oxygenation are demonstrated by using our method. Moreover, nonlinear optode settings guided by anatomical prior is proved to be critical to imaging small organs such as the heart.