Brain Multiphysics (Jan 2023)
Perspective: Challenges and opportunities in computational brain mechanics research: How can we use recent experimental data to improve models of brain mechanics?
Abstract
The importance of the brain, its location inside the skull, and its soft, delicate, nature pose multiple practical challenges to studying brain mechanics. These challenges have elevated the role of theoretical models and computational studies of brain mechanics for understanding TBI and developing countermeasures, to gain insight into cortical folding and misfolding, and to improve the precision of brain surgery. Ultimately, experimental measurements remain necessary to build accurate computational models and to evaluate these models objectively, so that these models may be used with confidence to inform scientists and clinicians concerned with TBI, brain development, and neurosurgery. This perspective reviews recent progress, unresolved questions, and future challenges in using experimental data to improve computer models of brain mechanics. Statement of significance: Computational models of brain mechanics will play important roles in preventing traumatic brain injury, understanding brain development, and improving brain surgery. Comprehensive experimental measurements remain necessary to build accurate computational models and to evaluate these models objectively. The fragility of the brain and its fundamental importance complicate the questions of what measurements can be made, and how to interpret them. This perspective reviews recent progress, unresolved questions, and future challenges in using experimental data to improve computer models of brain mechanics.
