Reproducibility and replicability in neuroimaging data analysis
| dc.contributor.author | Adali, Tulay | |
| dc.contributor.author | Calhoun, Vince D. | |
| dc.date.accessioned | 2022-08-05T20:49:55Z | |
| dc.date.available | 2022-08-05T20:49:55Z | |
| dc.date.issued | 2022-08 | |
| dc.description.abstract | Purpose of review Machine learning solutions are being increasingly used in the analysis of neuroimaging (NI) data, and as a result, there is an increase in the emphasis of the reproducibility and replicability of these data-driven solutions. Although this is a very positive trend, related terminology is often not properly defined, and more importantly, (computational) reproducibility that refers to obtaining consistent results using the same data and the same code is often disregarded. Recent findings We review the findings of a recent paper on the topic along with other relevant literature, and present two examples that demonstrate the importance of accounting for reproducibility in widely used software for NI data. Summary We note that reproducibility should be a first step in all NI data analyses including those focusing on replicability, and introduce available solutions for assessing reproducibility. We add the cautionary remark that when not taken into account, lack of reproducibility can significantly bias all subsequent analysis stages. | en_US |
| dc.description.sponsorship | We would like to thank Furkan Kantar for generating the FNC map image. This work was supported in part by NSF-NCS 1631838, NSF 2112455, and NIH grants R01 MH118695, R01 MH123610, R01 AG073949. | en_US |
| dc.description.uri | https://journals.lww.com/co-neurology/Abstract/2022/08000/Reproducibility_and_replicability_in_neuroimaging.6.aspx | en_US |
| dc.format.extent | 8 pages | en_US |
| dc.genre | journal articles | en_US |
| dc.genre | postprints | en_US |
| dc.identifier | doi:10.13016/m28o3x-yap6 | |
| dc.identifier.citation | Adali, Tü̈laya; Calhoun, Vince D.b. Reproducibility and replicability in neuroimaging data analysis. Current Opinion in Neurology: August 2022 - Volume 35 - Issue 4 - p 475-481 doi: 10.1097/WCO.0000000000001081 | en_US |
| dc.identifier.uri | https://doi.org/10.1097/WCO.0000000000001081 | |
| dc.identifier.uri | http://hdl.handle.net/11603/25290 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Lippincott | en_US |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department Collection | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.rights | This is not the final published version. | en_US |
| dc.rights | Access to this item will begin on 9/1/2023. | |
| dc.title | Reproducibility and replicability in neuroimaging data analysis | en_US |
| dc.type | Text | en_US |
| dcterms.creator | https://orcid.org/0000-0003-0594-2796 | en_US |