Evidence map›Paper›PMID 37555184›Full record

ArticleFrontiers in neuroimaging2022

Reproducing FSL's fMRI data analysis

Yibei Chen, Frederic R Hopp, Musa Malik, Paula T Wang, Kylie Woodman, Sungbin Youk, René Weber

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in neuroimaging, 2022. 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. Review
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.

Yibei ChenMedia Neuroscience Lab, Department of Communication, College of Letters and Science, University of California, Santa Barbara, Santa Barbara, CA, United States.
Frederic R HoppAmsterdam School of Communication Research, University of Amsterdam, Amsterdam, Netherlands.
Musa MalikMedia Neuroscience Lab, Department of Communication, College of Letters and Science, University of California, Santa Barbara, Santa Barbara, CA, United States.
Paula T WangMedia Neuroscience Lab, Department of Communication, College of Letters and Science, University of California, Santa Barbara, Santa Barbara, CA, United States.
Kylie WoodmanMedia Neuroscience Lab, Department of Communication, College of Letters and Science, University of California, Santa Barbara, Santa Barbara, CA, United States.
Sungbin YoukMedia Neuroscience Lab, Department of Communication, College of Letters and Science, University of California, Santa Barbara, Santa Barbara, CA, United States.
René WeberMedia Neuroscience Lab, Department of Communication, College of Letters and Science, University of California, Santa Barbara, Santa Barbara, CA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The "replication crisis" in neuroscientific research has led to calls for improving reproducibility. In traditional neuroscience analyses, irreproducibility may occur as a result of issues across various stages of the methodological process. For example, different operating systems, different software packages, and even different versions of the same package can lead to variable results. Nipype, an open-source Python project, integrates different neuroimaging software packages uniformly to improve the reproducibility of neuroimaging analyses. Nipype has the advantage over traditional software packages (e.g., FSL, ANFI, SPM, etc.) by (1) providing comprehensive software development frameworks and usage information, (2) improving computational efficiency, (3) facilitating reproducibility through sufficient details, and (4) easing the steep learning curve. Despite the rich tutorials it has provided, the Nipype community lacks a standard three-level GLM tutorial for FSL. Using the classical Flanker task dataset, we first precisely reproduce a three-level GLM analysis with FSL

Indexed as

fMRI analysisFSLmethodsNipypereproducibility

Identifiers

PMID37555184
PMCPMC10406235

What OpenQuestion holds

Textmetadata
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.