Evidence map›Paper›PMID 23247601›Full record

ArticleNeurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology2013

Dynamical properties of firing patterns in ELL pyramidal neuron under external electric field stimulus.

Lei Wang, Shenquan Liu, Linlin Zhang, Yanjun Zeng

Abstract read
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In one paragraph

Article in Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 3 institutions in 1 country.

Lei WangDepartment of Mathematics, South China University of Technology, 510640, Guangzhou, China.
Shenquan Liu
Linlin Zhang
Yanjun Zeng
Beijing University of Technology · CNShanghai Jiao Tong University · CNSouth China University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pyramidal neurons in the electrosensory lateral line lobe (ELL) of weakly electric fish activate in an environment of time-varying electric fields, which are generated by the fish itself, while how these pyramidal neurons would behave or what kinds of firing patterns these neurons would produce under different electric fields is still unclear. In this research, the firing behaviors of ELL pyramidal neuron under DC and AC electric field stimulus are investigated in a two-compartment neuron model. By means of numerical simulations we show that firing patterns of the model ELL pyramidal neuron are much diverse under different values of DC electric field, and neuronal spike frequency exhibits a monotone decreasing trend with the linearly increased DC fields, moreover, the transition mode between these firing patterns with the variation of DC electric fields demonstrates an explicit periodic route. While for AC electric fields, neuronal firing frequency periodically transforms with the increase of AC frequency, particularly, a special transition pattern (from multi-period bursting to spiking) repeatedly appears with the change of AC frequency. Our simulation results indicate that ELL pyramidal neurons fire dynamically under the time-varying electric fields, the diversity of firing patterns and their periodic transition modes may imply the potential roles of these dynamical firings in the coding strategy of sensory information processing.

Indexed as

AlgorithmsModels, NeurologicalAction PotentialsAnimalsElectric FishElectric StimulationLateral Line SystemPyramidal Cells

Identifiers

PMID23247601
OpenAlexW2035907389

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Registered trials

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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.