Evidence map›Paper›PMID 29874234›Full record

ArticlePLoS computational biology2018

Limits on reliable information flows through stochastic populations.

Lucas Boczkowski, Emanuele Natale, Ofer Feinerman, Amos Korman

Erratum issuedAbstract read
In one paragraph

Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. The 2025 motile active matter roadmap.Journal of physics. Condensed matter : an Institute of Physics journal · 2025
    Review
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Lucas BoczkowskiCNRS, IRIF, Université Paris Diderot, Paris, France.ORCID 0000-0002-0505-5081
Emanuele NataleAlgorithms and Complexity Department, Max-Planck-Institut für Informatik, Saarbrücken, Germany.ORCID 0000-0002-8755-3892
Ofer FeinermanDepartment of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel.
Amos KormanCNRS, IRIF, Université Paris Diderot, Paris, France.ORCID 0000-0001-8652-9228

Funding

European Research Council 648032
6 · The paper itself

Abstract

Biological systems can share and collectively process information to yield emergent effects, despite inherent noise in communication. While man-made systems often employ intricate structural solutions to overcome noise, the structure of many biological systems is more amorphous. It is not well understood how communication noise may affect the computational repertoire of such groups. To approach this question we consider the basic collective task of rumor spreading, in which information from few knowledgeable sources must reliably flow into the rest of the population. We study the effect of communication noise on the ability of groups that lack stable structures to efficiently solve this task. We present an impossibility result which strongly restricts reliable rumor spreading in such groups. Namely, we prove that, in the presence of even moderate levels of noise that affect all facets of the communication, no scheme can significantly outperform the trivial one in which agents have to wait until directly interacting with the sources-a process which requires linear time in the population size. Our results imply that in order to achieve efficient rumor spread a system must exhibit either some degree of structural stability or, alternatively, some facet of the communication which is immune to noise. We then corroborate this claim by providing new analyses of experimental data regarding recruitment in Cataglyphis niger desert ants. Finally, in light of our theoretical results, we discuss strategies to overcome noise in other biological systems.

Indexed as

CommunicationModels, BiologicalStochastic ProcessesAlgorithmsAnimalsAntsComputational BiologyNoiseReproducibility of Results

Identifiers

PMID29874234
PMCPMC6005642

What OpenQuestion holds

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LicenceCC BY
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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.