Brain tissue is known to exhibit regional and directional variations in its mechanical response to external loads. Material models traditionally used to simulate brain tissue deformation in the human head have been primarily region independent and limited to isotropic and linear viscoelastic. The primary goal of this research is to develop a biofidelic material model for brain tissue by accounting for the underlying microstructure of the material. A computational and analytical approach was undertaken in our attempt to develop a more realistic material model. Based on the microstructure observed at the neuron level, a mesoscale model was developed which included neurons, glial cells and Cerebro-Spinal Fluid (CSF). A semi-analytical model was first developed using a simplified geometry accounting for separate fiber and matrix (fluid) behavior of the medium. A second computational model was also constructed by developing a representative volume element (RVE) of brain tissue that includes the neurons, glial cells and CSF. Diffusion Tensor Imaging (DTI) was also utilized to capture anisotropy and directional dependence of the tissue on the continuum scale. Using the aforementioned material models, computational simulations were performed to predict the mechanical response of the brain tissue when subjected to a non-penetrating, impact load.