Evidence map›Paper›PMID 30793069›Full record

ArticleNetwork neuroscience (Cambridge, Mass.)2017

The modular organization of human anatomical brain networks: Accounting for the cost of wiring.

Richard F Betzel, John D Medaglia, Lia Papadopoulos, Graham L Baum, Ruben Gur, Raquel Gur, David Roalf, Theodore D Satterthwaite, Danielle S Bassett

Abstract read
In one paragraph

Article in Network neuroscience (Cambridge, Mass.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers.

0numbers the graph read from it
0cells of the map it votes in
77citing 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

77 citing papers in PubMed.

  1. Review
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  12. Hierarchical communities in the larvalProceedings of the National Academy of Sciences of the United States of America · 2024
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17 more citing papers are in PubMed but not listed here.

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

9 authors.

Richard F BetzelDepartment of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104.
John D MedagliaDepartment of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104.
Lia PapadopoulosDepartment of Physics, University of Pennsylvania, Philadelphia, PA, 19104.
Graham L BaumNeuropsychiatry Section, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104.
Ruben GurNeuropsychiatry Section, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104.
Raquel GurNeuropsychiatry Section, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104.
David RoalfNeuropsychiatry Section, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104.
Theodore D SatterthwaiteNeuropsychiatry Section, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104.
Danielle S BassettDepartment of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104.

Funding

Postdoctoral Training in Translational Neurorehabilitation ResearchT32HD071844 · NICHD · ALBERT EINSTEIN HEALTHCARE NETWORK · PI WHYTE, JOHN · 2013 to 2022
$2.2M
Dynamic Network Neuroscience and Control Theory: Toward Interventions for Cognitive Control DysfunctionDP5OD021352 · OD · UNIVERSITY OF PENNSYLVANIA · PI MEDAGLIA, JOHN · 2015 to 2019
$2.0M
CRCNS: US-France Modeling & Predicting BCI Learning from Dynamic NetworksR01HD086888 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI BASSETT, DANIELLE SMITH · 2015 to 2018
$506k
NICHD NIH HHS R01 HD086888NICHD NIH HHS T32 HD071844NIH HHS DP5 OD021352
6 · The paper itself

Abstract

Brain networks are expected to be modular. However, existing techniques for estimating a network's modules make it difficult to assess the influence of organizational principles such as wiring cost reduction on the detected modules. Here we present a modification of an existing module detection algorithm that allowed us to focus on connections that are unexpected under a cost-reduction wiring rule and to identify modules from among these connections. We applied this technique to anatomical brain networks and showed that the modules we detected differ from those detected using the standard technique. We demonstrated that these novel modules are spatially distributed, exhibit unique functional fingerprints, and overlap considerably with rich clubs, giving rise to an alternative and complementary interpretation of the functional roles of specific brain regions. Finally, we demonstrated that, using the modified module detection approach, we can detect modules in a developmental dataset that track normative patterns of maturation. Collectively, these findings support the hypothesis that brain networks are composed of modules and provide additional insight into the function of those modules.

Indexed as

Community structureComplex networksGeometryModularityWiring cost

Identifiers

PMID30793069
PMCPMC6372290

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.