Adaptive neural network classifier for decoding MEG signals

We introduce two Convolutional Neural Network (CNN) classifiers optimized for inferring brain states from magnetoencephalographic (MEG) measurements. Network design follows a generative model of the electromagnetic (EEG and MEG) brain signals allowing explorative analysis of neural sources informing...

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Detalles Bibliográficos
Autores principales: Zubarev, Ivan, Zetter, Rasmus, Halme, Hanna-Leena, Parkkonen, Lauri
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academic Press 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6609925/
https://www.ncbi.nlm.nih.gov/pubmed/31059799
http://dx.doi.org/10.1016/j.neuroimage.2019.04.068

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6609925/
https://www.ncbi.nlm.nih.gov/pubmed/31059799
http://dx.doi.org/10.1016/j.neuroimage.2019.04.068

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