Axonal tension contributes to consistent fold placement.

Cortical folding is a critical process during brain development, resulting in morphologies that are both consistent and distinct between individuals and species. While earlier studies have highlighted important aspects of cortical folding, most existing computational models, based on the differential growth theory, fall short of explaining why folds tend to appear in particular locations. The axon tension hypothesis may provide insight into this conundrum; however, there has been significant controversy about a potential role of axonal tension during the gyrification. The common opinion in the field is that axonal tension is inadequate to drive gyrification, but we currently run the risk of discarding this hypothesis without comprehensively studying the role of axonal tension. Here we propose a novel bi-layered finite element model incorporating the two theories, including characteristic axonal tension in the subcortex and differential cortical growth. We show that axon tension can serve as a perturbation sufficient to trigger buckling in simulations; similarly to other types of perturbations, the natural stability behavior of the system tends to determine some characteristics of the folding morphology (e.g. the wavelength) while the perturbation determines the location of folds. Certain geometries, however, can interact or compete with the natural stability of the system to change the wavelength. When multiple perturbations are present, they similarly compete with each other. We found that an axon bundle of reasonable size will overpower up to a 5% thickness perturbation (typical in the literature) and determine fold placement. Finally, when multiple axon tracts are present, even a slight difference in axon stiffness, representing the heterogeneity of axonal connections, is enough to significantly change the folding pattern. While the simulations presented here are a very simple representation of white matter connectivity, our findings point to urgent future research on the role of axon connectivity in cortical folding.

Orchestrated neuronal migration and cortical folding: A computational and experimental study.

Brain development involves precisely orchestrated genetic, biochemical, and mechanical events. At the cellular level, neuronal proliferation in the innermost zone of the brain followed by migration towards the outermost layer results in a rapid increase in brain surface area, outpacing the volumetric growth of the brain, and forming the highly folded cortex. This work aims to provide mechanistic insights into the process of brain development and cortical folding using a biomechanical model that couples cell division and migration with volumetric growth. Unlike phenomenological growth models, our model tracks the spatio-temporal development of cohorts of neurons born at different times, with each cohort modeled separately as an advection-diffusion process and the total cell density determining the extent of volume growth. We numerically implement our model in Abaqus/Standard (2020) by writing user-defined element (UEL) subroutines. For model calibration, we apply in utero electroporation (IUE) to ferret brains to visualize and track cohorts of neurons born at different stages of embryonic development. Our calibrated simulations of cortical folding align qualitatively with the ferret experiments. We have made our experimental data and finite-element implementation available online to offer other researchers a modeling platform for future study of neurological disorders associated with atypical neurodevelopment and cortical malformations.

Computational models of cortical folding: A review of common approaches.

The process of gyrification, by which the brain develops the intricate pattern of gyral hills and sulcal valleys, is the result of interactions between biological and mechanical processes during brain development. Researchers have developed a vast array of computational models in order to investigate cortical folding. This review aims to summarize these studies, focusing on five essential elements of the brain that affect development and gyrification and how they are represented in computational models: (i) the constraints of skull, meninges, and cerebrospinal fluid; (ii) heterogeneity of cortical layers and regions; (iii) anisotropic behavior of subcortical fiber tracts; (iv) material properties of brain tissue; and (v) the complex geometry of the brain. Finally, we highlight areas of need for future simulations of brain development.

Multi-physics modeling and finite element formulation of corneal UV cross-linking.

The UV cross-linking technique applied to the cornea is a popular and effective therapy for eye diseases such as keratoconus and ectatic disorders. The treatment strengthens the cornea by forming new cross-links via photochemical reactions and, in turn, prevents the disease from further developing. To better understand and capture the underlying mechanisms, we develop a multi-physics model that considers the migration of the riboflavin (i.e., the photo-initializer), UV light absorption, the photochemical reaction that forms the cross-links, and biomechanical changes caused by changes to the microstructure. Our model is calibrated to a set of nanoindentation tests on UV cross-linked corneas from the literature. Additionally, we implement our multi-physics model numerically into a commercial finite element software. We also compare our simulation against a set of inflation tests from the literature. The simulation capability allows us to make quantitative predictions of a therapy's outcomes in full 3-D, based on the actual corneal geometry; it also helps medical practitioners with surgical planning.

Constitutive Modeling of Corneal Tissue: Influence of Three-Dimensional Collagen Fiber Microstructure.

The cornea, the transparent tissue in the front of the eye, along with the sclera, plays a vital role in protecting the inner structures of the eyeball. The precise shape and mechanical strength of this tissue are mostly determined by the unique microstructure of its extracellular matrix. A clear picture of the 3D arrangement of collagen fibrils within the corneal extracellular matrix has recently been obtained from the secondary harmonic generation images. However, this important information about the through-thickness distribution of collagen fibrils was seldom taken into account in the constitutive modeling of the corneal behavior. This work creates a generalized structure tensor (GST) model to investigate the mechanical influence of collagen fibril through-thickness distribution. It then uses numerical simulations of the corneal mechanical response in inflation experiments to assess the efficacy of the proposed model. A parametric study is also done to investigate the influence of model parameters on numerical predictions. Finally, a brief comparison between the performance of this new constitutive model and a recent angular integration (AI) model from the literature is given.

Numerical investigation of biomechanically coupled growth in cortical folding.

Cortical folding-the process of forming the characteristic gyri (hills) and sulci (valleys) of the cortex-is a highly dynamic process that results from the interaction between gene expression, cellular mechanisms, and mechanical forces. Like many other cells, neurons are sensitive to their mechanical environment. Because of this, cortical growth may not happen uniformly throughout gyri and sulci after the onset of cortical folding, which is accompanied by patterns of tension and compression in the surrounding tissue. Here, as an extension of our previous work, we introduce a biomechanically coupled growth model to investigate the importance of interaction between biological growth and mechanical cues during brain development. Our earlier simulations of cortical growth consisted of a homogeneous growing cortex attached to an elastic subcortex. Here, we let the evolution of cortical growth depend on a geometrical quantity-the mean curvature of the cortex-to achieve preferential growth in either gyri or sulci. As opposed to the popular pre-patterning hypothesis, our model treats inhomogeneous cortical growth as the result of folding rather than the cause. The model is implemented numerically in a commercial finite element software Abaqus/Explicit in Abaqus reference manuals, Dassault Systemes Simulia, Providence (2019) by writing user-defined material subroutine (VUMAT). Our simulations show that gyral-sulcal thickness variations are a phenomenon particular to low stiffness ratios. In comparison with cortical thickness measurements of [Formula: see text] human brains via a consistent sampling scheme, our simulations with similar cortical and subcortical stiffnesses suggest that cortical growth is higher in gyri than in sulci.