Why experimental variation in neuroimaging should be embraced

Gregory Kiar (), Jeanette A. Mumford, Ting Xu, Joshua T. Vogelstein, Tristan Glatard and Michael P. Milham
Additional contact information
Gregory Kiar: Child Mind Institute
Jeanette A. Mumford: Stanford University
Ting Xu: Child Mind Institute
Joshua T. Vogelstein: Johns Hopkins University
Tristan Glatard: The Centre for Addiction and Mental Health
Michael P. Milham: Child Mind Institute

Nature Communications, 2024, vol. 15, issue 1, 1-9

Abstract: Abstract In a perfect world, scientists would develop analyses that are guaranteed to reveal the ground truth of a research question. In reality, there are countless viable workflows that produce distinct, often conflicting, results. Although reproducibility places a necessary bound on the validity of results, it is not sufficient for claiming underlying validity, eventual utility, or generalizability. In this work we focus on how embracing variability in data analysis can improve the generalizability of results. We contextualize how design decisions in brain imaging can be made to capture variation, highlight examples, and discuss how variability capture may improve the quality of results.

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-024-53743-y Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-53743-y

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-024-53743-y

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().