Evidence map›Paper›PMID 19023409›Full record

ArticlePLoS computational biology2008

Order-based representation in random networks of cortical neurons.

Goded Shahaf, Danny Eytan, Asaf Gal, Einat Kermany, Vladimir Lyakhov, Christoph Zrenner, Shimon Marom

Abstract read
In one paragraph

Article in PLoS computational biology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing 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

38 citing papers in PubMed.

  1. Article
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  6. A Theoretical Comprehensive Framework for the Process of Theories Formation.Computational intelligence and neuroscience · 2021
    Review
  7. Article
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  14. Mesoscale Architecture Shapes Initiation and Richness of Spontaneous Network Activity.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2017
    Article
  15. Development of Cortical Networks under Continuous Stimulation.Frontiers in molecular neuroscience · 2017
    Article
  16. Article
  17. 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.

Goded ShahafTechnion-Israel Institute of Technology, Haifa, Israel.
Danny Eytan
Asaf Gal
Einat Kermany
Vladimir Lyakhov
Christoph Zrenner
Shimon Marom

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The wide range of time scales involved in neural excitability and synaptic transmission might lead to ongoing change in the temporal structure of responses to recurring stimulus presentations on a trial-to-trial basis. This is probably the most severe biophysical constraint on putative time-based primitives of stimulus representation in neuronal networks. Here we show that in spontaneously developing large-scale random networks of cortical neurons in vitro the order in which neurons are recruited following each stimulus is a naturally emerging representation primitive that is invariant to significant temporal changes in spike times. With a relatively small number of randomly sampled neurons, the information about stimulus position is fully retrievable from the recruitment order. The effective connectivity that makes order-based representation invariant to time warping is characterized by the existence of stations through which activity is required to pass in order to propagate further into the network. This study uncovers a simple invariant in a noisy biological network in vitro; its applicability under in vivo constraints remains to be seen.

Indexed as

Action PotentialsAlgorithmsAnimalsAnimals, NewbornCerebral CortexComputational BiologyElectrodesMicrotechnologyModels, NeurologicalNerve NetNeural PathwaysNeurobiologyNeuronsRatsRats, Sprague-DawleySynaptic Potentials

Identifiers

PMID19023409
PMCPMC2580731

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.