Machine learning identification of EEG features predicting working memory performance in schizophrenia and healthy adults

BACKGROUND: With millisecond-level resolution, electroencephalographic (EEG) recording provides a sensitive tool to assay neural dynamics of human cognition. However, selection of EEG features used to answer experimental questions is typically determined a priori. The utility of machine learning was...

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Detalles Bibliográficos
Autores principales: Johannesen, Jason K., Bi, Jinbo, Jiang, Ruhua, Kenney, Joshua G., Chen, Chi-Ming A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2016
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4928381/
https://www.ncbi.nlm.nih.gov/pubmed/27375854
http://dx.doi.org/10.1186/s40810-016-0017-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4928381/
https://www.ncbi.nlm.nih.gov/pubmed/27375854
http://dx.doi.org/10.1186/s40810-016-0017-0

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