Evidence map›Paper›PMID 41684440›Full record

ArticleImaging neuroscience (Cambridge, Mass.)

The Comet Toolbox: Improving robustness in network neuroscience through multiverse analysis.

Micha Burkhardt, Carsten Gießing

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Micha BurkhardtDepartment of Psychology, Psychological Methods and Statistics, Carl von Ossietzky University Oldenburg, Oldenburg, Germany.ORCID https://orcid.org/0000-0002-6268-3527
Carsten GießingDepartment of Psychology, Biological Psychology, Carl von Ossietzky University Oldenburg, Oldenburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In network neuroscience, a broad range of methods for estimating dynamic functional connectivity from fMRI data and subsequent analyses using network-based approaches have been introduced in recent years. However, in the absence of ground truths about the validity of analytical steps in capturing true brain dynamics, researchers are often faced with a multitude of arbitrary yet defensible choices, raising concerns about the robustness of results. Here, we aim to address this issue by implementing a comprehensive suite of dynamic functional connectivity methods in a unified Python software package, allowing for a diverse exploration of brain dynamics. Anchored in the framework of multiverse analysis, the present work introduces a workflow for systematically exploring different methodological choices. The developed toolbox includes a graphical user interface to enhance ease of use and accessibility for those who prefer to work outside a script-based pipeline. Comprehensive documentation and demo scripts are included to support adoption and usability. By promoting transparency and robustness, Comet aims to advance best practices in the study of brain dynamics.

Indexed as

dynamic functional connectivityfMRIgraph analysismultiverse analysistoolbox

Identifiers

PMID41684440
PMCPMC12892349

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.