Several efforts have been made in the past half century to characterize the behavior of brain tissue under different modes of loading and deformation rates; however each developed model has been associated with limitations. This dissertation aims at addressing the non-linear and rate dependent behavior of brain tissue specially in high strain rates (above 100 s-1) that represents the loading conditions occurring in blast induced neurotrauma (BINT) and development of a universal constitutive model for brain tissue that describes the tissue mechanical behavior from medium to high loading rates.. In order to evaluate the nature of nonlinearity of brain tissue, bovine brain samples (n=30) were tested under shear stress-relaxation loading with medium strain rate of 10 s-1 at strain levels ranging from 2% to 40% and the isochronous stress strain curves at 0,1 s and 10 s after the peak force formed. This approach enabled verification of the applicability of the quasilinear viscoelastic (QLV) theory to brain tissue and derivation of its elastic function based on the physics of the material rather than relying solely on curve fitting. The results confirmed that the QLV theory is an acceptable approximation for engineering shear strain levels below 40% that is beyond the level of axonal injury and the shape of the instantaneous elastic response was determined to be a 5th order odd polynomial with instantaneous linear shear modulus of 3.48±0.18 kPa. To investigate the rate dependent behavior of brain tissue at high strain rates, a novel experimental setup was developed and bovine brain samples (n=25) were tested at strain rates of 90, 120, 500, 600 and 800 s-1 and the resulting deformation and shear force were recorded. The stress-strain relationships showed significant rate dependency at high rates and was characterized using a QLV model with a 739 s-1 decay rate and validated with finite element analysis. The results showed the brain instantaneous elastic response can be modeled with a 3rd order odd polynomial and the instantaneous linear shear modulus was 19.2±1.1 kPa. A universal constitutive model was developed by combining the models developed for medium and high rate deformations and based on the QLV theory, in which the relaxation function has 5 time constants for 5 orders of magnitude in time (from 1 ms to 10 s) and therefore, is capable of predicting the brain tissue behavior in a wide range of deformation rates. Although the universal model presented in this study was developed based on only shear tests and the material parameters could not be found uniquely, by comparing the results of this study with previously available data in the literature under tension unique material parameters were determined for a 5 parameter generalized Rivlin elastic function (C10=3.208±0.602 kPa, C01=4.191±1.074 kPa, C11=79.898±18.974 kPa, C20=-37.093±7.273 kPa, C02=-37.712±5.678 kPa). The universal constitutive model for brain tissue presented in this dissertation is capable of characterizing the brain tissue behavior under large deformation in a wide range of strain rates and can be used in computational modeling of Traumatic Brain Injury (TBI) to predict injuries that result from falls and sports to automotive accidents and BINT. / Mechanical Engineering

<p dir="ltr">The brain is a dynamic tissue that is passively driven by a combination of the cardiac cycle, respiration, and slow wave oscillations. The function of the brain relies on its ability to maintain a normal homeostatic balance between its mechanical environment and metabolic demands, which can be greatly altered in the cases of neurodegeneration or traumatic brain injury. It has been a challenge in the field to quantify the dynamics of the tissue and cerebrospinal fluid flow in human subjects on a patient-specific basis over the many spatial and temporal scales that it relies upon. Non-invasive imaging tools like structural, functional, and dynamic MRI sequences provide modern researchers with an unprecedented view into the human brain. Our work leverages these sequences by developing novel, open-source pipelines to 1) quantify the biomechanical environment of the brain tissue over 133 functional brain regions, and 2) estimate real-time cerebrospinal fluid velocity from flow artifacts on functional MRI by employing breathing regimens to enhance fluid motion. These pipelines provide a comprehensive view of the macroscale tissue and fluid motion in a given patient. Additionally, we sought to understand how the transmission of macroscale forces, in the context of traumatic brain injury, contribute to neuronal damage by 3) developing a digital twin to simulate 30-200 g-force loading of 2D neuronal cultures and observing the morphological and electrophysiological consequences of these impacts in vitro by our collaborators. Taken together, we believe these works are a steppingstone that will enable future researchers to deeply understand the mechanical contributions that underly clinical neurological outcomes and perhaps lead to the development of earlier diagnostics, which is of dire need in the case of neurodegenerative diseases.</p>