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Confounds in the Data—Comments on “Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features”
Neuroimaging experiments in general, and EEG experiments in particular, must take care to avoid confounds. A recent TPAMI paper uses data that suffers from a serious previously reported confound. We demonstrate that their new model and analysis methods do not remedy this confound, and therefore that...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9719395/ https://www.ncbi.nlm.nih.gov/pubmed/34665721 http://dx.doi.org/10.1109/TPAMI.2021.3121268 |
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author | Ahmed, Hamad Wilbur, Ronnie B. Bharadwaj, Hari M. Siskind, Jeffrey Mark |
author_facet | Ahmed, Hamad Wilbur, Ronnie B. Bharadwaj, Hari M. Siskind, Jeffrey Mark |
author_sort | Ahmed, Hamad |
collection | PubMed |
description | Neuroimaging experiments in general, and EEG experiments in particular, must take care to avoid confounds. A recent TPAMI paper uses data that suffers from a serious previously reported confound. We demonstrate that their new model and analysis methods do not remedy this confound, and therefore that their claims of high accuracy and neuroscience relevance are invalid. |
format | Online Article Text |
id | pubmed-9719395 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
record_format | MEDLINE/PubMed |
spelling | pubmed-97193952022-12-03 Confounds in the Data—Comments on “Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features” Ahmed, Hamad Wilbur, Ronnie B. Bharadwaj, Hari M. Siskind, Jeffrey Mark IEEE Trans Pattern Anal Mach Intell Article Neuroimaging experiments in general, and EEG experiments in particular, must take care to avoid confounds. A recent TPAMI paper uses data that suffers from a serious previously reported confound. We demonstrate that their new model and analysis methods do not remedy this confound, and therefore that their claims of high accuracy and neuroscience relevance are invalid. 2022-12 2022-11-07 /pmc/articles/PMC9719395/ /pubmed/34665721 http://dx.doi.org/10.1109/TPAMI.2021.3121268 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Ahmed, Hamad Wilbur, Ronnie B. Bharadwaj, Hari M. Siskind, Jeffrey Mark Confounds in the Data—Comments on “Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features” |
title | Confounds in the Data—Comments on “Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features” |
title_full | Confounds in the Data—Comments on “Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features” |
title_fullStr | Confounds in the Data—Comments on “Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features” |
title_full_unstemmed | Confounds in the Data—Comments on “Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features” |
title_short | Confounds in the Data—Comments on “Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features” |
title_sort | confounds in the data—comments on “decoding brain representations by multimodal learning of neural activity and visual features” |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9719395/ https://www.ncbi.nlm.nih.gov/pubmed/34665721 http://dx.doi.org/10.1109/TPAMI.2021.3121268 |
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