Biomechanical model - opinion, youOur Discord hit 10K members! Join Here! Uh oh! There is no answer available. Request an answer from our educators and we will get to it right away! A biomechanical model of the lumbar region of the human trunk is shown. Express the results in Cartesian vector form. biomechanical model
In this paper, we investigate the effect of the cortical biomechanical model, the initial geometry and the initial cortical thickness on folding patterns. In addition, we not only use several descriptors of the folds such as the dimensionless mean curvature, the surface-based three-dimensional gyrification index and the sulcal depth, but also propose a new metric to quantify the folds orientation. The results demonstrate that the cortical growth mode does almost not affect the complexity degree of surface morphology; the variation in the initial biomechanical model changes the folds orientation and depth, and in particular, the slenderer the shape is, the more folds along its longest axis could be seen and the deeper the sulci become.
Moreover, the thinner the initial cortical thickness is, the higher the spatial frequency of the folds is, but the shallower the sulci become, which is in agreement with the previously reported effects of cortical thickness.
Human brain growth is accompanied by the folding of the cerebral cortex, which takes place biomechanical model a hierarchical mode during biomechanical model mldel 16—40 1with primary folds forming the earliest and highly conserved, then secondary folds elaborating on these folds, etc 23. Recent studies have revealed that not thank troy movie analysis thank the molecular and cellular processes but also mechanical forces play an important role in the formation of the gyral and sulcal convolutions 4 — 7. It has been revealed that mechanical models based on the hypothesis of differential tangential growth could produce realistic folding patterns when they are applied on human fetal brain data 67. It has been shown that the cortical folding patterns are influenced by various physical parameters, e.
In addition to these recent observations, many questions are still open regarding the morphogenesis of folding patterns, including links between the physical parameters of simulation models and the folding patterns observed in in vivo MRI data. A deeper understanding of these parameters can biomechanical model contribute to biomechanical model pathologies associated with characteristic changes in cortical folding. For instance, polymicrogyria, pachygyria and lissencephaly malformations can be accompanied by bioomechanical 1718schizophrenia 1920 or epilepsy Thus, in this work, we investigate the influence of physical parameters on surface morphology using the brain growth model proposed by Tallinen et al. The simulation results first allow us to visually remark the difference in the appearance of folding patterns.
Then we quantify these folds through various quantitative metrics, such as the mean curvatures, the surface-based three-dimensional gyrification index and biomechanocal sulcal depth, which can be used to describe the complexity degree of surface morphology 22 Besides we introduce a novel approach to measure the anisotropy of the folding orientation, through geometric tools 2425 and the Kullback-Leibler divergence. Specifically, this work attempts to answer the following questions: 1 What is the impact of biomechanical model temporal cortical growth model onto the folding patterns? Tallinen et biomechajical. Brain growth is modeled by a relative tangential expansion of the cortical layer and the white matter layer, the cortical layer is assumed to grow more rapidly than the white matter layer.
The nonlinear stress-strain property of the human brain 26 and the bulk modulus K that is assumed to be five times the shear biomechanical model 7 can be brought into the frame of a modestly compressible Neo-Hookean material solid.
The model is based on an explicit dynamic solver for quasi-static equilibrium of the system and allows the simulation of the large strains and highly nonlinear mechanics biomechanical model in gyrification, but the brain solid should be discretized into high-density tetrahedral finite elements 6. The model uses free boundary conditions and the initial displacement and velocity are zero. Biomechanical model main forces are considered in this model. One is the elastic force, which is derived from the volumetric strain energy density of neo-Hookean and a deformation gradient.
Another is the biomechanical model force, which takes place when a separation between a node and a biomechanical model face at the brain surface is mosel than a threshold in order to prevent nodes from penetrating element faces. The contact force is obtained via penalty based vertex-triangle contact processing When the relative tangential growth tensor G is initialized, the brain solid starts to grow and the deformation gradient is formed, then the corresponding elastic force can be calculated.]