Evidence map›Paper›PMID 32355185›Full record

ArticleScientific reports2020

Simple capacitor-switch model of excitatory and inhibitory neuron with all parts biologically explained allows input fire pattern dependent chaotic oscillations.

Pavel Cejnar, Oldřich Vyšata, Jaromír Kukal, Martin Beránek, Martin Vališ, Aleš Procházka

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Advanced Brain-on-a-Chip for Wetware Computing: A Review.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Pavel CejnarDepartment of Computing and Control Engineering, Faculty of Chemical Engineering, University of Chemistry and Technology in Prague, Prague, Czech Republic. pavel.cejnar@vscht.cz.
Oldřich VyšataDepartment of Computing and Control Engineering, Faculty of Chemical Engineering, University of Chemistry and Technology in Prague, Prague, Czech Republic.
Jaromír KukalDepartment of Computing and Control Engineering, Faculty of Chemical Engineering, University of Chemistry and Technology in Prague, Prague, Czech Republic.
Martin BeránekIndependent researcher, Uppsala, Sweden.
Martin VališDepartment of Neurology, Faculty of Medicine in Hradec Králové, Charles University, Hradec Králové, Czech Republic.
Aleš ProcházkaDepartment of Computing and Control Engineering, Faculty of Chemical Engineering, University of Chemistry and Technology in Prague, Prague, Czech Republic. ales.prochazka@vscht.cz.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to known information processing capabilities of the brain, neurons are modeled at many different levels. Circuit theory is also often used to describe the function of neurons, especially in complex multi-compartment models, but when used for simple models, there is no subsequent biological justification of used parts. We propose a new single-compartment model of excitatory and inhibitory neuron, the capacitor-switch model of excitatory and inhibitory neuron, as an extension of the existing integrate-and-fire model, preserving the signal properties of more complex multi-compartment models. The correspondence to existing structures in the neuronal cell is then discussed for each part of the model. We demonstrate that a few such inter-connected model units are capable of acting as a chaotic oscillator dependent on fire patterns of the input signal providing a complex deterministic and specific response through the output signal. The well-known necessary conditions for constructing a chaotic oscillator are met for our presented model. The capacitor-switch model provides a biologically-plausible concept of chaotic oscillator based on neuronal cells.

Indexed as

Action PotentialsAnimalsBrainModels, NeurologicalNeurons

Identifiers

PMID32355185
PMCPMC7192907

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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.