Probabilistic Modeling of Pseudorabies Virus Infection in a Neural Circuit.

Abstract

Viral transneuronal tracing methods effectively label synaptically connected neurons in a time-dependent manner. However, the modeling of viral vectors has been largely absent. An objective of this article is to motivate and initiate a basis for computational modeling of viral labeling and the questions that can be investigated through modeling of pseudorabies virus (PRV) virion progression in a neural circuit. In particular, a mathematical model is developed for quantitative analysis of PRV infection. Probability expressions are presented to evaluate the progression of viral labeling along the neural circuit. The analysis brings forth various parameters, the numerical values of which must be attained through future experiments. This is the first computational model for PRV viral labeling of a neural circuit.