Evidence map›Paper›PMID 26138277›Full record

ArticleNature communications2015

Navigable networks as Nash equilibria of navigation games.

András Gulyás, József J Bíró, Attila Kőrösi, Gábor Rétvári, Dmitri Krioukov

Abstract read
In one paragraph

Article in Nature communications, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
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  5. Geometric renormalization unravels self-similarity of the multiscale human connectome.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  6. Article
  7. Signal propagation via cortical hierarchies.Network neuroscience (Cambridge, Mass.) · 2020
    Article
  8. Reply to Muscoloni and Cannistraci: Navigation performance measures.Proceedings of the National Academy of Sciences of the United States of America · 2019
    Article
  9. Navigation of brain networks.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  10. Communication dynamics in complex brain networks.Nature reviews. Neuroscience · 2017
    Review
  11. Small-World Brain Networks Revisited.The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry · 2017
    Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
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

5 authors.

András Gulyás1] High Speed Networks Laboratory, Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, 2 Magyar tudósok str., Budapest 1117, Hungary [2] MTA-BME Information Systems Research Group, Budapest University of Technology and Economics, 2 Magyar tudósok str., Budapest 1117, Hungary.
József J Bíró1] High Speed Networks Laboratory, Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, 2 Magyar tudósok str., Budapest 1117, Hungary [2] MTA-BME Future Internet Research Group, Budapest University of Technology and Economics, 2 Magyar tudósok str., Budapest 1117, Hungary.
Attila KőrösiMTA-BME Information Systems Research Group, Budapest University of Technology and Economics, 2 Magyar tudósok str., Budapest 1117, Hungary.
Gábor Rétvári1] High Speed Networks Laboratory, Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, 2 Magyar tudósok str., Budapest 1117, Hungary [2] MTA-BME Future Internet Research Group, Budapest University of Technology and Economics, 2 Magyar tudósok str., Budapest 1117, Hungary.
Dmitri KrioukovNortheastern University, Department of Physics, Department of Mathematics, Department of Electrical&Computer Engineering, 360 Huntington Ave, 111 Dana Research Center, Boston, Massachusetts 02115, USA.ORCID 0000000194788182

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Common sense suggests that networks are not random mazes of purposeless connections, but that these connections are organized so that networks can perform their functions well. One function common to many networks is targeted transport or navigation. Here, using game theory, we show that minimalistic networks designed to maximize the navigation efficiency at minimal cost share basic structural properties with real networks. These idealistic networks are Nash equilibria of a network construction game whose purpose is to find an optimal trade-off between the network cost and navigability. We show that these skeletons are present in the Internet, metabolic, English word, US airport, Hungarian road networks, and in a structural network of the human brain. The knowledge of these skeletons allows one to identify the minimal number of edges, by altering which one can efficiently improve or paralyse navigation in the network.

Indexed as

BrainGame TheoryInternetLanguageProtein Interaction MapsTransportationComputer Communication NetworksHumans

Identifiers

PMID26138277
PMCPMC4506547

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

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.