Numerical uncertainty in analytical pipelines lead to impactful variability in brain networks
The analysis of brain-imaging data requires complex processing pipelines to support findings on brain function or pathologies. Recent work has shown that variability in analytical decisions, small amounts of noise, or computational environments can lead to substantial differences in the results, end...
Guardado en:
Autores principales: | Gregory Kiar, Yohan Chatelain, Pablo de Oliveira Castro, Eric Petit, Ariel Rokem, Gaël Varoquaux, Bratislav Misic, Alan C. Evans, Tristan Glatard |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Public Library of Science (PLoS)
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/39cbacb61c4f4cbbb9139fb3f8c817fb |
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