Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance

Identification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to classify active electrodes showing event-related intrac...

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Detalhes bibliográficos
Publicado no:Sci Rep
Main Authors: Saboo, Krishnakant V., Varatharajah, Yogatheesan, Berry, Brent M., Kremen, Vaclav, Sperling, Michael R., Davis, Kathryn A., Jobst, Barbara C., Gross, Robert E., Lega, Bradley, Sheth, Sameer A., Worrell, Gregory A., Iyer, Ravishankar K., Kucewicz, Michal T.
Formato: Artigo
Idioma:Inglês
Publicado em: Nature Publishing Group UK 2019
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Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6874617/
https://ncbi.nlm.nih.gov/pubmed/31758077
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-019-53925-5
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