Topological features dictate the mechanics of the mammalian brains

Abstract Understanding brain mechanics is crucial in the study of pathologies involving brain deformations such as tumor, strokes, or in traumatic brain injury. Apart from the intrinsic mechanical properties of the brain tissue, the topology and geometry of the mammalian brains are particularly important for its mechanical response. We use computational methods in combination with geometric models to understand the role of these features. We find that the geometric quantifiers such as the gyrification index play a fundamental role in the overall mechanical response of the brain. We further demonstrate that topological diversity in brain models is more important than differences in mechanical properties: Topological differences modify not only the stresses and strains in the brain but also its spatial distribution. Therefore, computational brain models should always include detailed geometric information to generate accurate mechanical predictions. These results suggest that mammalian brain gyrification acts as a damping system to reduce mechanical damage in large-mass brain mammals. Our results are relevant in several areas of science and engineering related to brain mechanics, including the study of tumor growth, the understanding of brain folding, and the analysis of traumatic brain injuries.

[1]  T. Gerriets,et al.  Aggravation of infarct formation by brain swelling in a large territorial stroke: a target for neuroprotection? , 2008, Journal of neurosurgery.

[2]  Shingo Shimoda,et al.  Function Based Brain Modeling and Simulation of an Ischemic Region in Post-Stroke Patients using the Bidomain , 2019, Journal of Neuroscience Methods.

[3]  C. Birkl,et al.  Mechanical characterization of human brain tissue. , 2017, Acta biomaterialia.

[4]  van der Tpj Tom Sande,et al.  Mechanical properties of brain tissue by indentation: interregional variation. , 2010, Journal of the mechanical behavior of biomedical materials.

[5]  Barbara Wirthl,et al.  Modelling of Brain Deformation After Decompressive Craniectomy , 2016, Annals of Biomedical Engineering.

[6]  Guillermo Sapiro,et al.  Geometric computation of human gyrification indexes from magnetic resonance images , 2013, Human brain mapping.

[7]  C. Jack,et al.  Measuring the Characteristic Topography of Brain Stiffness with Magnetic Resonance Elastography , 2013, PLoS ONE.

[8]  John D. Joannopoulos,et al.  An animal-to-human scaling law for blast-induced traumatic brain injury risk assessment , 2014, Proceedings of the National Academy of Sciences.

[9]  William J. Tyler,et al.  The mechanobiology of brain function , 2012, Nature Reviews Neuroscience.

[10]  A. Constantinesco,et al.  Fifty years of brain tissue mechanical testing: from in vitro to in vivo investigations. , 2010, Biorheology.

[11]  G. Bachmann,et al.  Noninvasive Quantification of Brain Edema and the Space-Occupying Effect in Rat Stroke Models Using Magnetic Resonance Imaging , 2004, Stroke.

[12]  Rjh Rudy Cloots,et al.  The influence of anisotropy on brain injury prediction. , 2014, Journal of biomechanics.

[13]  Maria A. Holland,et al.  Symmetry Breaking in Wrinkling Patterns: Gyri Are Universally Thicker than Sulci. , 2018, Physical review letters.

[14]  Michael S. Jaffee,et al.  Computational biology — Modeling of primary blast effects on the central nervous system , 2009, NeuroImage.

[15]  J. Ponsford,et al.  Decompressive craniectomy in diffuse traumatic brain injury. , 2011, The New England journal of medicine.

[16]  F. Zipp,et al.  Neuronal damage in brain inflammation. , 2007, Archives of neurology.

[17]  Ellen Kuhl,et al.  Magnetic resonance elastography of the brain: A comparison between pigs and humans. , 2018, Journal of the mechanical behavior of biomedical materials.

[18]  Alain Goriely,et al.  Stress Singularities in Swelling Soft Solids. , 2016, Physical review letters.

[19]  R. W. Carlsen,et al.  The Importance of Structural Anisotropy in Computational Models of Traumatic Brain Injury , 2015, Front. Neurol..

[20]  R.J.H. Cloots,et al.  Biomechanics of Traumatic Brain Injury: Influences of the Morphologic Heterogeneities of the Cerebral Cortex , 2008, Annals of Biomedical Engineering.

[21]  Kristian Franze,et al.  Predicting local tissue mechanics using immunohistochemistry , 2018, bioRxiv.

[22]  Debasis Sahoo,et al.  Finite element head model simulation and head injury prediction , 2013, Computer methods in biomechanics and biomedical engineering.

[23]  V. Di Lazzaro,et al.  Patient Semi-specific Computational Modeling of Electromagnetic Stimulation Applied to Neuroprotective Treatments in Acute Ischemic Stroke , 2020, Scientific Reports.

[24]  Owen Carmichael,et al.  Magnetic resonance elastography of the brain: A study of feasibility and reproducibility using an ergonomic pillow-like passive driver. , 2019, Magnetic resonance imaging.

[25]  P. Manger,et al.  Quantitative analysis of neocortical gyrencephaly in African elephants (Loxodonta africana) and six species of cetaceans: Comparison with other mammals , 2012, The Journal of comparative neurology.

[26]  Weinong W Chen,et al.  Dynamic mechanical response of bovine gray matter and white matter brain tissues under compression. , 2009, Journal of biomechanics.

[27]  Molly T. Townsend,et al.  Effect of Tissue Material Properties in Blast Loading: Coupled Experimentation and Finite Element Simulation , 2018, Annals of Biomedical Engineering.

[28]  Curtis L. Johnson,et al.  Magnetic resonance elastography for examining developmental changes in the mechanical properties of the brain , 2017, Developmental Cognitive Neuroscience.

[29]  Antonia Trotta,et al.  Biofidelic finite element modelling of brain trauma: Importance of the scalp in simulating head impact , 2020 .

[30]  A. Goriely,et al.  Bulging Brains , 2016, Journal Of Elasticity.

[31]  Wytse J. Wadman,et al.  Regional variations in stiffness in live mouse brain tissue determined by depth-controlled indentation mapping , 2018, Scientific Reports.

[32]  Valerie M. Weaver,et al.  A tense situation: forcing tumour progression , 2009, Nature Reviews Cancer.

[33]  Xiaobo Zhou,et al.  Computational Modeling of 3D Tumor Growth and Angiogenesis for Chemotherapy Evaluation , 2014, PloS one.

[34]  P V Bayly,et al.  Deformation of the human brain induced by mild acceleration. , 2005, Journal of neurotrauma.

[35]  Hessam Babaee,et al.  Mechanistic Insights into Human Brain Impact Dynamics through Modal Analysis. , 2018, Physical review letters.

[36]  Simon Chatelin,et al.  An anisotropic viscous hyperelastic constitutive law for brain material finite-element modeling , 2013 .

[37]  P. Flory,et al.  Thermodynamic relations for high elastic materials , 1961 .

[38]  L. Sundstrom,et al.  Temporal development of hippocampal cell death is dependent on tissue strain but not strain rate. , 2006, Journal of biomechanics.

[39]  D. Holtzman,et al.  Diffusion Tensor Imaging Reliably Detects Experimental Traumatic Axonal Injury and Indicates Approximate Time of Injury , 2007, The Journal of Neuroscience.

[40]  Alain Goriely,et al.  Is the Donnan effect sufficient to explain swelling in brain tissue slices? , 2014, Journal of The Royal Society Interface.

[41]  S. Kleiven,et al.  Can sulci protect the brain from traumatic injury? , 2009, Journal of biomechanics.

[42]  Robert Leech,et al.  White matter damage and cognitive impairment after traumatic brain injury , 2010, Brain : a journal of neurology.

[43]  I. Sack,et al.  Measurement of the hyperelastic properties of ex vivo brain tissue slices. , 2011, Journal of biomechanics.

[44]  Triantafyllos Stylianopoulos,et al.  Towards patient-specific modeling of brain tumor growth and formation of secondary nodes guided by DTI-MRI , 2018, NeuroImage: Clinical.

[45]  E. Kuhl,et al.  Mechanics of the brain: perspectives, challenges, and opportunities , 2015, Biomechanics and Modeling in Mechanobiology.

[46]  Scott T. Grafton,et al.  Combining the Finite Element Method with Structural Connectome-based Analysis for Modeling Neurotrauma: Connectome Neurotrauma Mechanics , 2012, PLoS Comput. Biol..

[47]  Claude Tarriere,et al.  Development of a F.E.M. of the human head according to a specific test protocol , 1992 .

[48]  E. Kuhl,et al.  Neuromechanics: From Neurons to Brain , 2015 .

[49]  James C. Ford,et al.  Parametric Comparisons of Intracranial Mechanical Responses from Three Validated Finite Element Models of the Human Head , 2013, Annals of Biomedical Engineering.

[50]  J. Ghajar Traumatic brain injury , 2000, The Lancet.

[51]  David J. Sharp,et al.  Network dysfunction after traumatic brain injury , 2014, Nature Reviews Neurology.

[52]  Michael Chopp,et al.  Animal models of traumatic brain injury , 2013, Nature Reviews Neuroscience.

[53]  M. Rusnak,et al.  Traumatic brain injury: Giving voice to a silent epidemic , 2013, Nature Reviews Neurology.

[54]  Thibault P. Prevost,et al.  Dynamic mechanical response of brain tissue in indentation in vivo, in situ and in vitro. , 2011, Acta biomaterialia.

[55]  K. T. Ramesh,et al.  An axonal strain injury criterion for traumatic brain injury , 2012, Biomechanics and modeling in mechanobiology.

[56]  A. Goriely The Mathematics and Mechanics of Biological Growth , 2017 .

[57]  E. Kuhl,et al.  A family of hyperelastic models for human brain tissue , 2017 .

[58]  Blaine Hoshizaki,et al.  A centric/non-centric impact protocol and finite element model methodology for the evaluation of American football helmets to evaluate risk of concussion , 2014, Computer methods in biomechanics and biomedical engineering.

[59]  X Gary Tan,et al.  Towards Identification of Correspondence Rules to Relate Traumatic Brain Injury in Different Species , 2018, Annals of Biomedical Engineering.

[60]  Rémy Willinger,et al.  Improved head injury criteria based on head FE model , 2008 .

[61]  W. Goldsmith,et al.  Impact on a model head-helmet system , 1974 .

[62]  E. Kuhl,et al.  Mechanical properties of gray and white matter brain tissue by indentation. , 2015, Journal of the mechanical behavior of biomedical materials.

[63]  Paolo A. Netti,et al.  Solid stress inhibits the growth of multicellular tumor spheroids , 1997, Nature Biotechnology.

[64]  Scott Tashman,et al.  A study of the response of the human cadaver head to impact. , 2007, Stapp car crash journal.

[65]  Paul A Taylor,et al.  Simulation of blast-induced early-time intracranial wave physics leading to traumatic brain injury. , 2009, Journal of biomechanical engineering.

[66]  Sriram Vasudevan,et al.  Global white matter analysis of diffusion tensor images is predictive of injury severity in traumatic brain injury. , 2007, Journal of neurotrauma.