Temporally Resolved Axonal Growth Rates: A Stochastic Study

Description of neuron growth behavior is essential in elucidating the environmental factors that prompt the formation of neural networks. However, the staggering number of physical and chemical guidance cues that influence axonal growth prohibits understanding of growth behavior from a purely mechanistic perspective. Using a phenomenological approach, we record the distribution of growth speeds in neurons at several time points, under well-controlled conditions. Using these distributions in combination with a 1-dimensional Fokker-Planck equation, we solve for the velocity potential of axonal growth for our system as a function of time. In so doing, we aim to resolve time-sensitive growth events that are otherwise overlooked in post-growth studies.