Evidence map›Paper›PMID 36554129›Full record

ArticleEntropy (Basel, Switzerland)2022

Functional Connectome of the Human Brain with Total Correlation.

Qiang Li, Greg Ver Steeg, Shujian Yu, Jesus Malo

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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  5. Altered Functional Network Energy Across Multiscale Brain Networks in Preterm vs. Full-Term Subjects: Insights from the Adolescent Brain Cognitive Development (ABCD) Study.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2025
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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

4 authors.

Qiang LiImage Processing Laboratory, University of Valencia, 46980 Valencia, Spain.ORCID 0000-0002-5337-0676
Greg Ver SteegInformation Sciences Institute, University of Southern California, Marina del Rey, CA 90292, USA.ORCID 0000-0002-0793-141X
Shujian YuMachine Learning Group, UiT-The Arctic University of Norway, 9037 Tromsø, Norway.
Jesus MaloImage Processing Laboratory, University of Valencia, 46980 Valencia, Spain.ORCID 0000-0002-5684-8591

Funding

DARPA FA8750-17-C-0106GVA Grisolía P/2019/035MICINN PDC2021-121522-C21MICINN PID2020-118071GB-I00Research Council of Norway 309439
6 · The paper itself

Abstract

Recent studies proposed the use of Total Correlation to describe functional connectivity among brain regions as a multivariate alternative to conventional pairwise measures such as correlation or mutual information. In this work, we build on this idea to infer a large-scale (whole-brain) connectivity network based on Total Correlation and show the possibility of using this kind of network as biomarkers of brain alterations. In particular, this work uses Correlation Explanation (CorEx) to estimate Total Correlation. First, we prove that CorEx estimates of Total Correlation and clustering results are trustable compared to ground truth values. Second, the inferred large-scale connectivity network extracted from the more extensive open fMRI datasets is consistent with existing neuroscience studies, but, interestingly, can estimate additional relations beyond pairwise regions. And finally, we show how the connectivity graphs based on Total Correlation can also be an effective tool to aid in the discovery of brain diseases.

Indexed as

biomarkersCorExfMRIfunctional connectivitylarge-scale connectomeTotal Correlation

Identifiers

PMID36554129
PMCPMC9777567

What OpenQuestion holds

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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.