Evidence map›Paper›PMID 27404281›Full record

ArticleScientific reports2016

The role of dimensionality in neuronal network dynamics.

Francesco Paolo Ulloa Severino, Jelena Ban, Qin Song, Mingliang Tang, Ginestra Bianconi, Guosheng Cheng, Vincent Torre

Abstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

  1. Three-dimensional microelectrode arrays forBiomedical engineering letters · 2026
    Review
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  10. Two-dimensional TiJournal of nanobiotechnology · 2022
    Article
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  13. Application of Graphene in Tissue Engineering of the Nervous System.International journal of molecular sciences · 2021
    Review
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  15. Review
  16. 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

7 authors.

Francesco Paolo Ulloa SeverinoNeurobiology Sector, International School for Advanced Studies (SISSA), via Bonomea, 265, 34136 Trieste, Italy.
Jelena BanNeurobiology Sector, International School for Advanced Studies (SISSA), via Bonomea, 265, 34136 Trieste, Italy.
Qin SongKey Laboratory of Nano-Bio Interface, Suzhou Institute of Nano-tech and Nano-bionics, Chinese Academy of Sciences, 398 Ruoshui Road, Jiangsu 215123, China.
Mingliang TangInstitute of Life Sciences, Southeast University, Sipailou 2, Nanjing 210096, China.
Ginestra BianconiSchool of Mathematical Sciences, Queen Mary University of London, Mile End Rd, London E1 4NS, United Kingdom.
Guosheng ChengKey Laboratory of Nano-Bio Interface, Suzhou Institute of Nano-tech and Nano-bionics, Chinese Academy of Sciences, 398 Ruoshui Road, Jiangsu 215123, China.
Vincent TorreNeurobiology Sector, International School for Advanced Studies (SISSA), via Bonomea, 265, 34136 Trieste, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent results from network theory show that complexity affects several dynamical properties of networks that favor synchronization. Here we show that synchronization in 2D and 3D neuronal networks is significantly different. Using dissociated hippocampal neurons we compared properties of cultures grown on a flat 2D substrates with those formed on 3D graphene foam scaffolds. Both 2D and 3D cultures had comparable glia to neuron ratio and the percentage of GABAergic inhibitory neurons. 3D cultures because of their dimension have many connections among distant neurons leading to small-world networks and their characteristic dynamics. After one week, calcium imaging revealed moderately synchronous activity in 2D networks, but the degree of synchrony of 3D networks was higher and had two regimes: a highly synchronized (HS) and a moderately synchronized (MS) regime. The HS regime was never observed in 2D networks. During the MS regime, neuronal assemblies in synchrony changed with time as observed in mammalian brains. After two weeks, the degree of synchrony in 3D networks decreased, as observed in vivo. These results show that dimensionality determines properties of neuronal networks and that several features of brain dynamics are a consequence of its 3D topology.

Identifiers

PMID27404281
PMCPMC4939604

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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.