ArticleFrontiers in computational neuroscience2020
Fano Factor: A Potentially Useful Information.
Article in Frontiers in computational neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Critical scaling of novelty in the cortex.Nature communications · 2026Article
- Dysregulated cortical excitability and tau phosphorylation in a β3 integrin mouse model of autism.Brain : a journal of neurology · 2025Article
- Learning and inference with correlated neural variability.PNAS nexus · 2025Article
- An applied noise model for scintillation-based CCD detectors in transmission electron microscopy.Scientific reports · 2025Article
- Thalamocortical interactions shape hierarchical neural variability during stimulus perception.iScience · 2024Article
- Modulation of electrical activity of proteinoid microspheres with chondroitin sulfate clusters.PloS one · 2024Article
- Four ways of implementing robustness quantification in strain characterisation.Biotechnology for biofuels and bioproducts · 2023Article
- Progress in Discovering Transcriptional Noise in Aging.International journal of molecular sciences · 2023Review
- Stimulus presentation can enhance spiking irregularity across subcortical and cortical regions.PLoS computational biology · 2022Article
- A Spiking Neural Network Builder for Systematic Data-to-Model Workflow.Frontiers in neuroinformatics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.