Evidence map›Paper›PMID 29415033›Full record

ArticlePloS one2018

Theta rhythm-like bidirectional cycling dynamics of living neuronal networks in vitro.

Arseniy Gladkov, Oleg Grinchuk, Yana Pigareva, Irina Mukhina, Victor Kazantsev, Alexey Pimashkin

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 34% 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.

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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Coupling ofFrontiers in neuroscience · 2022
    Article
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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 at 3 institutions in 1 country.

Arseniy GladkovLaboratory of Neuroengineering, Center of Translational Technologies, Lobachevsky State University of Nizhni Novgorod, Nizhny Novgorod, Russia.
Oleg GrinchukInformation Science and Technology Department, Skolkovo Institute of Science and Technology, Moscow, Russia.ORCID 0000-0003-4628-5577
Yana PigarevaLaboratory of Neuroengineering, Center of Translational Technologies, Lobachevsky State University of Nizhni Novgorod, Nizhny Novgorod, Russia.
Irina MukhinaLaboratory of Neuroengineering, Center of Translational Technologies, Lobachevsky State University of Nizhni Novgorod, Nizhny Novgorod, Russia.
Victor KazantsevLaboratory of Neuroengineering, Center of Translational Technologies, Lobachevsky State University of Nizhni Novgorod, Nizhny Novgorod, Russia.
Alexey PimashkinLaboratory of Neuroengineering, Center of Translational Technologies, Lobachevsky State University of Nizhni Novgorod, Nizhny Novgorod, Russia.ORCID 0000-0001-7024-8827
N. I. Lobachevsky State University of Nizhny Novgorod · RUPrivolzhsky Research Medical University · RUSkolkovo Institute of Science and Technology · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The phenomena of synchronization, rhythmogenesis and coherence observed in brain networks are believed to be a dynamic substrate for cognitive functions such as learning and memory. However, researchers are still debating whether the rhythmic activity emerges from the network morphology that developed during neurogenesis or as a result of neuronal dynamics achieved under certain conditions. In the present study, we observed self-organized spiking activity that converged to long, complex and rhythmically repeated superbursts in neural networks formed by mature hippocampal cultures with a high cellular density. The superburst lasted for tens of seconds and consisted of hundreds of short (50-100 ms) small bursts with a high spiking rate of 139.0 ± 78.6 Hz that is associated with high-frequency oscillations in the hippocampus. In turn, the bursting frequency represents a theta rhythm (11.2 ± 1.5 Hz). The distribution of spikes within the bursts was non-random, representing a set of well-defined spatio-temporal base patterns or motifs. The long superburst was classified into two types. Each type was associated with a unique direction of spike propagation and, hence, was encoded by a binary sequence with random switching between the two "functional" states. The precisely structured bidirectional rhythmic activity that developed in self-organizing cultured networks was quite similar to the activity observed in the in vivo experiments.

Indexed as

Action PotentialsAnimalsHippocampusMiceNeuronsTheta Rhythm

Identifiers

PMID29415033
PMCPMC5802926
OpenAlexW2785624401

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.