A stochastic framework to model axon interactions within growing neuronal populations.

ABSTRACT: The confined and crowded environment of developing brains imposes spatial constraints on neuronal cells that have evolved individual and collective strategies to optimize their growth. These include organizing neurons into populations extending their axons to common target territories. How individual axons interact with each other within such populations to optimize innervation is currently unclear and difficult to analyze experimentally in vivo. Here, we developed a stochastic model of 3D axon growth that takes into account spatial environmental constraints, physical interactions between neighboring axons, and branch formation. This general, predictive and robust model, when fed with parameters estimated on real neurons from the Drosophila brain, enabled the study of the mechanistic princ

SUBMITTER: Razetti A 

PROVIDER: S-EPMC6292646 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature