Fano Factor: A Potentially Useful Information - Rajdl, Kamil; Lansky, Petr; Kostal, Lubomir (Frontiers in Computational Neuroscience, 2020)
Fano factor, the variance to mean ratio of numbers of spikes in a time window, is a very often used measure of variability of neuronal spike trains due to its simple and transparent definition. However, despite the simplicity, careless use of Fano factor can easily lead to wrong, distorted results. One of the problems is its unclear dependence on the spike rate which is often neglected or handled insufficiently. In this paper, we aim to explore this problem in more detail and to study a possible solution, which is calculation of Fano factor in the operational time. For illustration of the problems and evaluation of the theoretical methods, we use equilibrium renewal processes and their generalization, Markov renewal processes, as model of the spike trains. An example of application on real experimental data is included.