Evidence map›Paper›PMID 32058633›Full record

ArticleHuman brain mapping2020

Time-varying nodal measures with temporal community structure: A cautionary note to avoid misinterpretation.

William Hedley Thompson, Granit Kastrati, Karolina Finc, Jessey Wright, James M Shine, Russell A Poldrack

Abstract read
In one paragraph

Article in Human brain mapping, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

6 authors.

William Hedley ThompsonDepartment of Psychology, Stanford University, Stanford, California.ORCID 0000-0002-0533-6035
Granit KastratiDepartment of Clinical Neuroscience, Karolinska Institutet, Solna, Sweden.
Karolina FincCentre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University in Toruń, Toruń, Poland.
Jessey WrightDepartment of Psychology, Stanford University, Stanford, California.
James M ShineBrain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia.
Russell A PoldrackDepartment of Psychology, Stanford University, Stanford, California.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In network neuroscience, temporal network models have gained popularity. In these models, network properties have been related to cognition and behavior. Here, we demonstrate that calculating nodal properties that are dependent on temporal community structure (such as the participation coefficient [PC]) in time-varying contexts can potentially lead to misleading results. Specifically, with regards to the participation coefficient, increases in integration can be inferred when the opposite is occurring. Further, we present a temporal extension to the PC measure (temporal PC) that circumnavigates this problem by jointly considering all community partitions assigned to a node through time. The proposed method allows us to track a node's integration through time while adjusting for the possible changes in the community structure of the overall network.

Indexed as

Models, TheoreticalAdultBrainConnectomeHumansMagnetic Resonance ImagingNerve NetTime Factorsintegrationnetwork neuroscienceparticipation coefficienttemporal networktime-varying connectivity

Identifiers

PMID32058633
PMCPMC7268033

What OpenQuestion holds

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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.