TY - JOUR
T1 - Perspective
T2 - Challenges and opportunities in computational brain mechanics research: How can we use recent experimental data to improve models of brain mechanics?
AU - Bayly, Philip V.
N1 - Funding Information:
NIH grants U01NS112120 , R01EB027577 and ONR grant N00014-22-1-2198 .
Publisher Copyright:
© 2023
PY - 2023/1
Y1 - 2023/1
N2 - 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.
AB - 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.
KW - Anisotropy
KW - Brain mechanics
KW - Cortical folding
KW - MR elastography
KW - TBI
UR - http://www.scopus.com/inward/record.url?scp=85161661072&partnerID=8YFLogxK
U2 - 10.1016/j.brain.2023.100075
DO - 10.1016/j.brain.2023.100075
M3 - Letter
AN - SCOPUS:85161661072
SN - 2666-5220
VL - 4
JO - Brain Multiphysics
JF - Brain Multiphysics
M1 - 100075
ER -