Evidence map›Paper›PMID 31637330›Full record

ArticleNetwork neuroscience (Cambridge, Mass.)2019

Editorial: Linking experimental and computational connectomics.

Alexander Peyser, Sandra Diaz Pier, Wouter Klijn, Abigail Morrison, Jochen Triesch

Abstract read
In one paragraph

Article in Network neuroscience (Cambridge, Mass.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. RateML: A Code Generation Tool for Brain Network Models.Frontiers in network physiology · 2022
    Article
  3. 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.

Alexander PeyserSimLab Neuroscience, Jülich Supercomputing Centre (JSC), Institute for Advanced Simulation, JARA, Forschungszentrum Jülich GmbH, Jülich, Germany.ORCID https://orcid.org/0000-0002-3453-310X
Sandra Diaz PierSimLab Neuroscience, Jülich Supercomputing Centre (JSC), Institute for Advanced Simulation, JARA, Forschungszentrum Jülich GmbH, Jülich, Germany.
Wouter KlijnSimLab Neuroscience, Jülich Supercomputing Centre (JSC), Institute for Advanced Simulation, JARA, Forschungszentrum Jülich GmbH, Jülich, Germany.
Abigail MorrisonSimLab Neuroscience, Jülich Supercomputing Centre (JSC), Institute for Advanced Simulation, JARA, Forschungszentrum Jülich GmbH, Jülich, Germany.
Jochen TrieschFrankfurt Institute for Advanced Studies, Johann Wolfgang Goethe University, Frankfurt am Main, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Large-scale in silico experimentation depends on the generation of connectomes beyond available anatomical structure. We suggest that linking research across the fields of experimental connectomics, theoretical neuroscience, and high-performance computing can enable a new generation of models bridging the gap between biophysical detail and global function. This Focus Feature on "Linking Experimental and Computational Connectomics" aims to bring together some examples from these domains as a step toward the development of more comprehensive generative models of multiscale connectomes.

Indexed as

brain structure to functionconnectomicshigh performance computinginterdisciplinary neurosciencemultiscale

Identifiers

PMID31637330
PMCPMC6777942

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.