Evidence map›Paper›PMID 37896699›Full record

ArticleSensors (Basel, Switzerland)2023

Analysis of Connectome Graphs Based on Boundary Scale.

María José Moron-Fernández, Ludovica Maria Amedeo, Alberto Monterroso Muñoz, Helena Molina-Abril, Fernando Díaz-Del-Río, Fabiano Bini, Franco Marinozzi, Pedro Real

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 49% of its field
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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

8 authors at 2 institutions in 2 countries.

María José Moron-FernándezHigher Technical School of Informatics Engineering, University of Seville, Avda. Reina Mercedes, s/n, 41012 Seville, Spain.ORCID 0000-0003-3291-7297
Ludovica Maria AmedeoDepartment of Mechanical and Aerospace Engineering, "Sapienza" University of Rome, Via Eudossiana, 18, 00184 Rome, Italy.
Alberto Monterroso MuñozHigher Technical School of Informatics Engineering, University of Seville, Avda. Reina Mercedes, s/n, 41012 Seville, Spain.ORCID 0000-0003-0790-4160
Helena Molina-AbrilHigher Technical School of Informatics Engineering, University of Seville, Avda. Reina Mercedes, s/n, 41012 Seville, Spain.
Fernando Díaz-Del-RíoHigher Technical School of Informatics Engineering, University of Seville, Avda. Reina Mercedes, s/n, 41012 Seville, Spain.ORCID 0000-0001-6184-1629
Fabiano BiniDepartment of Mechanical and Aerospace Engineering, "Sapienza" University of Rome, Via Eudossiana, 18, 00184 Rome, Italy.ORCID 0000-0002-5641-1189
Franco MarinozziDepartment of Mechanical and Aerospace Engineering, "Sapienza" University of Rome, Via Eudossiana, 18, 00184 Rome, Italy.
Pedro RealHigher Technical School of Informatics Engineering, University of Seville, Avda. Reina Mercedes, s/n, 41012 Seville, Spain.ORCID 0000-0002-6853-0505
Universidad de Sevilla · ESSapienza University of Rome · IT

Funding

Mapping the Human Connectome: Structure, Function, and HeritabilityU54MH091657 · NIMH · WASHINGTON UNIVERSITY · PI UGURBIL, KAMIL, VAN ESSEN, DAVID C · 2010 to 2014
$34.7M
NIMH NIH HHS U54 MH091657
6 · The paper itself

Abstract

The purpose of this work is to advance in the computational study of connectome graphs from a topological point of view. Specifically, starting from a sequence of hypergraphs associated to a brain graph (obtained using the Boundary Scale model, BS2), we analyze the resulting scale-space representation using classical topological features, such as Betti numbers and average node and edge degrees. In this way, the topological information that can be extracted from the original graph is substantially enriched, thus providing an insightful description of the graph from a clinical perspective. To assess the qualitative and quantitative topological information gain of the BS2 model, we carried out an empirical analysis of neuroimaging data using a dataset that contains the connectomes of 96 healthy subjects, 52 women and 44 men, generated from MRI scans in the Human Connectome Project. The results obtained shed light on the differences between these two classes of subjects in terms of neural connectivity.

Indexed as

ConnectomeBrainFemaleHealthy VolunteersHumansMagnetic Resonance ImagingMaleNeuroimagingBetti numbersconnectomehypergraph theorytopological scale

Identifiers

PMID37896699
PMCPMC10610691
OpenAlexW4387822772

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.