Emma Lejeune, Boston University
Manuel Rausch, University of Texas-Austin
Johannes Weickenmeier, Stevens Institute
Mona Eskandari, University of California-Riverside
Biological materials are spatially heterogeneous on the sub-cellular, cellular, tissue, and organ scales. This spatial heterogeneity can be investigated experimentally through techniques such as microscopy, medical imaging, nanoindentation, and full field measurements of material response. For example, we can visualize spatially dependent fiber directions in cardiac muscle with histology, and we can probe the variable stiffness of regions of brain tissue with nanoindentation. Even in structurally and/or referentially homogeneous tissues, heterogeneous phenomena such as growth and remodeling may induce spatial-dependency. Critically, computational tools, such as constitutive modeling, inverse methods, surrogate modeling, and machine learning, are often required to meaningfully interpret these experimental results. And, advancing methods for capturing spatially heterogeneous (and often uncertain) properties in computational models of biological systems is an area of active research.