A Stochastic Compartmental Model for Fast Axonal Transport

In this paper we develop a probabilistic micro-scale model and use it to study macro-scale properties of axonal transport, the processes by which materials are moved in the axons of neurons. By directly modeling the smallest scale interactions, we can use recent microscopic experimental observations to infer all the parameters of the model. Then using techniques from queueing theory, we can predict macroscopic behavior in order to investigate three important biological questions: (1) How homogeneous are axons at stochastic equilibrium? (2) How quickly can axons return to stochastic equilibrium after large local perturbations? (3) How inhomogeneous does deposition and turnover make the axon?