Mathematical Modelling of Neuroblast Chemotaxis Migration towards the Olfactory Bulb
Daniel Acosta-Soba, Carmen Castro-González, Noelia Geribaldi-Doldán, Francisco Guillén-González, Pedro Núñez-Abades, Noelia Ortega-Román, Patricia Pérez-García, J. Rafael Rodríguez-Galván
TL;DR
The paper develops a PDE model for neuroblast migration along the rostral migratory stream toward the olfactory bulb in a realistic 2D brain domain, where migration is driven by a chemoattractant gradient of a specially designed OB function $\mathcal{O}$ and modulated by anisotropic diffusion in the corpus callosum. The OB attractant is obtained from a steady elliptic problem with diffusion coefficient $\mu_O$, while the neuroblast density $u$ satisfies a convection–reaction equation with parameters $\Lambda=(\alpha, \beta, \gamma, \chi, \sigma)$ and a tunable time weight $\tau$, solved numerically using upwind discontinuous Galerkin methods to preserve the maximum principle. The authors calibrate the model to experimental rodent data by a two-stage optimization (initial-condition fit and evolution fit) using grid search, random forest regression, and L-BFGS-B, achieving a close quantitative match and revealing parameter ranges that reproduce the observed RMS trajectory. This framework provides a tractable, validated starting point for more advanced 3D models and for exploring neuroblast migration in damaged or injured brain tissue, with a robust numerical methodology suitable for complex brain geometries.
Abstract
This article is devoted to the mathematical modeling of migration of neuroblasts, precursor cells of neurons, along the pathway they usually follow before maturing. This pathway is determined mainly by chemotaxis and the heterogeneous mobility of neuroblasts in different regions of the brain. In numerical simulations, the application of novel discontinuous Galerkin methods allows to maintain the properties of the continuous model such as the maximum principle. We present some successful computer tests including parameter adjust to fit real data from rodent brains.
