Evidence map›Paper›PMID 36371779›Full record

Trial reportHuman brain mapping2023

Differences in functional connectivity distribution after transcranial direct-current stimulation: A connectivity density point of view.

Bohao Tang, Yi Zhao, Archana Venkataraman, Kyrana Tsapkini, Martin A Lindquist, James Pekar, Brian Caffo

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Human brain mapping, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 24% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Article
  5. GAMing the Brain: Investigating the Cross-modal Relationships between Functional Connectivity and Structural Features using Generalized Additive Models.Machine learning in clinical neuroimaging : 7th international workshop, MLCN 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, proceedings. MLCN (Workshop) (7th : 2024 : Marrakesh, Morocco) · 2025
    Article
  6. Article
  7. 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

7 authors at 3 institutions in 1 country.

Bohao TangDepartment of Biostatistics, Johns Hopkins University, Baltimore, Maryland, USA.ORCID 0000-0002-9322-4438
Yi ZhaoDepartment of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, USA.ORCID 0000-0003-4766-5934
Archana VenkataramanDepartment of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, Maryland, USA.ORCID 0000-0003-2653-5591
Kyrana TsapkiniDepartment of Neurology, Johns Hopkins Medicine, Baltimore, Maryland, USA.ORCID 0000-0001-6020-5532
Martin A LindquistDepartment of Biostatistics, Johns Hopkins University, Baltimore, Maryland, USA.ORCID 0000-0003-2289-0828
James PekarF.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA.
Brian CaffoDepartment of Biostatistics, Johns Hopkins University, Baltimore, Maryland, USA.ORCID 0000-0002-0793-9497
Johns Hopkins University · USIndiana University School of MedicineKennedy Krieger Institute · US

Funding

TR&D 4: Algorithms for functional and anatomical brain analysisP41EB015909 · NIBIB · HUGO W. MOSER RES INST KENNEDY KRIEGER · PI VAN ZIJL, PETER CM · 2012 to 2020
$13.1M
TRD 4: Platforms for multi-modal and multi-scale imaging dataP41EB031771 · NIBIB · HUGO W. MOSER RES INST KENNEDY KRIEGER · PI Hanzhang Lu, Peter CM Van Zijl · 2021 to 2026
$9.9M
Phase II clinical trial of transcranial direct current stimulation in the treatment of primary progressive aphasiaR01AG075111 · NIA · UNIVERSITY OF PENNSYLVANIA · PI Roy H Hamilton, Kyrana Tsapkini · 2022 to 2026
$6.7M
Individualized spatial topology in functional neuroimagingR01EB026549 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI Abhirup Datta, Martin Lindquist · 2018 to 2026
$4.5M
Effects of transcranial direct current stimulation in spoken and written production in primary progressive aphasiaR01DC014475 · NIDCD · JOHNS HOPKINS UNIVERSITY · PI TSAPKINI, KYRANA · 2015 to 2019
$4.1M
Targeting language-specific and executive-control networks with transcranial direct current stimulation in aphasic ADR01AG075404 · NIA · JOHNS HOPKINS UNIVERSITY · PI Kyrana Tsapkini · 2022 to 2026
$4.0M
Transcranial direct current stimulation in typical and atypical Alzheimer's diseaseR01AG068881 · NIA · JOHNS HOPKINS UNIVERSITY · PI TSAPKINI, KYRANA · 2020 to 2024
$3.8M
Longitudinal Causal Inferencer for fMRIR01EB016061 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI LINDQUIST, MARTIN · 2013 to 2020
$2.3M
Statistical methods for structural and functional integration in multi-modal neuroimaging dataR01EB029977 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI CAFFO, BRIAN SCOTT · 2021 to 2024
$1.9M
NIA NIH HHS R01 AG068881NIA NIH HHS R01 AG075111NIA NIH HHS R01 AG075404NIBIB NIH HHS P41 EB015909NIBIB NIH HHS P41 EB031771NIBIB NIH HHS R01 EB016061NIBIB NIH HHS R01 EB026549NIBIB NIH HHS R01 EB029977NIDCD NIH HHS R01 DC014475
6 · The paper itself

Abstract

In this manuscript, we consider the problem of relating functional connectivity measurements viewed as statistical distributions to outcomes. We demonstrate the utility of using the distribution of connectivity on a study of resting-state functional magnetic resonance imaging association with an intervention. The method uses the estimated density of connectivity between nodes of interest as a functional covariate. Moreover, we demonstrate the utility of the procedure in an instance where connectivity is naturally considered an outcome by reversing the predictor/response relationship using case/control methodology. The method utilizes the density quantile, the density evaluated at empirical quantiles, instead of the empirical density directly. This improved the performance of the method by highlighting tail behavior, though we emphasize that by being flexible and non-parametric, the technique can detect effects related to the central portion of the density. To demonstrate the method in an application, we consider 47 primary progressive aphasia patients with various levels of language abilities. These patients were randomly assigned to two treatment arms, transcranial direct-current stimulation and language therapy versus sham (language therapy only), in a clinical trial. We use the method to analyze the effect of direct stimulation on functional connectivity. As such, we estimate the density of correlations among the regions of interest and study the difference in the density post-intervention between treatment arms. We discover that it is the tail of the density, rather than the mean or lower order moments of the distribution, that demonstrates a significant impact in the classification. The new approach has several benefits. Among them, it drastically reduces the number of multiple comparisons compared with edge-wise analysis. In addition, it allows for the investigation of the impact of functional connectivity on the outcomes where the connectivity is not geometrically localized.

Indexed as

Transcranial Direct Current StimulationCognitionHumansMagnetic Resonance ImagingNerve NetTranscranial Magnetic Stimulationdensity regressionfunctional connectivityrandom graph

Identifiers

PMID36371779
PMCPMC9783448
OpenAlexW4308890807

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.