Dynamic Modeling of Neural Cell Network Formation: Some Insights into Early Brain Development

Abstract

This study presents a computational simulation that illustrates the early stages of neural cell network formation, a fundamental process in brain development. We developed a two-phase model to simulate the dynamic and complex interactions of neural cells during and after migration. In the first phase, we focused on the radial and tangential migration of neural cells, incorporating movements influenced by both genetic programming and environmental factors. This phase was characterized by increased radial and tangential migration strengths, allowing cells to disperse and form initial connections. In the second phase, we shifted our focus to network development, simulating the reinforcement of existing connections and the formation of new ones, leading to the emergence of complex network structures. My simulation employed a rule-based approach to model cell movement and adhesion, capturing the essence of cell migration patterns and early network formation such a rich clubs and small worlds. The results highlight how neural cells, starting from random positions, migrate directionally, forming rudimentary networks that evolve into more complex structures. The study provides a visual and conceptual framework for understanding the initial formation of neural networks and offers insights into the interplay between genetic predispositions and environmental stimuli in brain development. This model serves as a foundation for future research exploring the intricacies of neural network formation and its implications for neurological development and disorders.