Litcius/Paper detail

Fano Factor: A Potentially Useful Information

Kamil Rajdl, Petr Lánský, Lubomir Kostal

2020Frontiers in Computational Neuroscience44 citationsDOIOpen Access PDF

Abstract

The Fano factor, defined as the variance-to-mean ratio of spike counts in a time window, is often used to measure the variability of neuronal spike trains. However, despite its transparent definition, careless use of the Fano factor can easily lead to distorted or even wrong results. One of the problems is the unclear dependence of the Fano factor on the spiking rate, which is often neglected or handled insufficiently. In this paper we aim to explore this problem in more detail and to study the possible solution, which is to evaluate the Fano factor in the operational time. We use equilibrium renewal and Markov renewal processes as spike train models to describe the method in detail, and we provide an illustration on experimental data.

Topics & Concepts

Fano factorFano planeComputer scienceSpike (software development)Factor (programming language)Variance (accounting)Measure (data warehouse)Markov chainTrainStatistical physicsMathematicsData miningMachine learningPhysicsTelecommunicationsPure mathematicsShot noiseGeographyDetectorCartographySoftware engineeringBusinessProgramming languageAccountingNeural dynamics and brain functionstochastic dynamics and bifurcationAdvanced Memory and Neural Computing
Fano Factor: A Potentially Useful Information | Litcius