Bursting hierarchy in an adaptive exponential integrate-and-fire network synchronization.

Congping Lin, Xiaoyue Wu, Yiwei Zhang

Abstract read

In one paragraph

Article in Biological cybernetics, 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

–field-weighted citation impact, top 89% of its field

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.

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0 citing papers in PubMed, 0 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Congping LinSchool of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China.

Xiaoyue WuSchool of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China.

Yiwei ZhangSchool of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, China. yiweizhang@hust.edu.cn.ORCID 0000-0002-3499-9911

Huazhong Agricultural University · CNHuazhong University of Science and Technology · CN

Funding

National Natural Science Foundation of China 11871061National Natural Science Foundation of China 11871262National Natural Science Foundation of China 12161141002National Natural Science Foundation of China 12171179Natural Science Foundation of Hubei Province 2020CFB847

6 · The paper itself

Abstract

Neuronal network synchronization has received wide interest. In the present manuscript, we study the influence of initial membrane potentials together with network topology on bursting synchronization, in particular the sequential order of stabilized bursting among neurons. We find a hierarchical phenomenon on their bursting order. With a focus on situations where network coupling advances spiking times of neurons, we grade neurons into different layers. Together with the neuronal network structure, we construct directed graphs to indicate bursting propagation between different layers. More explicitly, neurons in upper layers burst earlier than those in lower layers. More interestingly, we find that among the same layer, bursting order of neurons is mainly associated with the number of neurons they connected to the upper layer; more stimuli lead to earlier bursting. Receiving effectively the same stimuli from the upper layer, we observe neurons with fewer connections would burst earlier.

Indexed as

Models, NeurologicalNerve NetAction PotentialsMembrane PotentialsNeuronsBursting hierarchyBursting patternNeuronal networkSynchronization

Identifiers

PMID36044046

DOI10.1016/j.physa.2008.02.039

OpenAlexW4293773042

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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.