Evidence map›Paper›PMID 35013356›Full record

ArticleScientific reports2022

Ageing transitions in a network of Rulkov neurons.

Dhrubajyoti Biswas, Sayan Gupta

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Dhrubajyoti BiswasDepartment of Physics, Indian Institute of Technology Madras, Chennai, Tamil Nadu, 700036, India.
Sayan GuptaThe Uncertainty Lab, Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai, Tamil Nadu, 700036, India. sayan@iitm.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The phenomenon of ageing transitions (AT) in a Erdős-Rényi network of coupled Rulkov neurons is studied with respect to parameters modelling network connectivity, coupling strength and the fractional ratio of inactive neurons in the network. A general mean field coupling is proposed to model the neuronal interactions. A standard order parameter is defined for quantifying the network dynamics. Investigations are undertaken for both the noise free network as well as stochastic networks, where the interneuronal coupling strength is assumed to be superimposed with additive noise. The existence of both smooth and explosive AT are observed in the parameter space for both the noise free and the stochastic networks. The effects of noise on AT are investigated and are found to play a constructive role in mitigating the effects of inactive neurons and reducing the parameter regime in which explosive AT is observed.

Identifiers

PMID35013356
PMCPMC8748446

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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.