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Overfitting the Literature to One Set of Stimuli and Data
A large number of papers in Computational Cognitive Neuroscience are developing and testing novel analysis methods using one specific neuroimaging dataset and problematic experimental stimuli. Publication bias and confirmatory exploration will result in overfitting to the limited available data. We...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8295535/ https://www.ncbi.nlm.nih.gov/pubmed/34305552 http://dx.doi.org/10.3389/fnhum.2021.682661 |
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author | Grootswagers, Tijl Robinson, Amanda K. |
author_facet | Grootswagers, Tijl Robinson, Amanda K. |
author_sort | Grootswagers, Tijl |
collection | PubMed |
description | A large number of papers in Computational Cognitive Neuroscience are developing and testing novel analysis methods using one specific neuroimaging dataset and problematic experimental stimuli. Publication bias and confirmatory exploration will result in overfitting to the limited available data. We highlight the problems with this specific dataset and argue for the need to collect more good quality open neuroimaging data using a variety of experimental stimuli, in order to test the generalisability of current published results, and allow for more robust results in future work. |
format | Online Article Text |
id | pubmed-8295535 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82955352021-07-23 Overfitting the Literature to One Set of Stimuli and Data Grootswagers, Tijl Robinson, Amanda K. Front Hum Neurosci Neuroscience A large number of papers in Computational Cognitive Neuroscience are developing and testing novel analysis methods using one specific neuroimaging dataset and problematic experimental stimuli. Publication bias and confirmatory exploration will result in overfitting to the limited available data. We highlight the problems with this specific dataset and argue for the need to collect more good quality open neuroimaging data using a variety of experimental stimuli, in order to test the generalisability of current published results, and allow for more robust results in future work. Frontiers Media S.A. 2021-07-08 /pmc/articles/PMC8295535/ /pubmed/34305552 http://dx.doi.org/10.3389/fnhum.2021.682661 Text en Copyright © 2021 Grootswagers and Robinson. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Grootswagers, Tijl Robinson, Amanda K. Overfitting the Literature to One Set of Stimuli and Data |
title | Overfitting the Literature to One Set of Stimuli and Data |
title_full | Overfitting the Literature to One Set of Stimuli and Data |
title_fullStr | Overfitting the Literature to One Set of Stimuli and Data |
title_full_unstemmed | Overfitting the Literature to One Set of Stimuli and Data |
title_short | Overfitting the Literature to One Set of Stimuli and Data |
title_sort | overfitting the literature to one set of stimuli and data |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8295535/ https://www.ncbi.nlm.nih.gov/pubmed/34305552 http://dx.doi.org/10.3389/fnhum.2021.682661 |
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