The potential of convolutional neural networks for identifying neural states based on electrophysiological signals: experiments on synthetic and real patient data

Processing incoming neural oscillatory signals in real-time and decoding from them relevant behavioral or pathological states is often required for adaptive Deep Brain Stimulation (aDBS) and other brain-computer interface (BCI) applications. Most current approaches rely on first extracting a set of...

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Detalles Bibliográficos
Autores principales: Rodriguez, Fernando, He, Shenghong, Tan, Huiling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10272439/
https://www.ncbi.nlm.nih.gov/pubmed/37333834
http://dx.doi.org/10.3389/fnhum.2023.1134599

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10272439/
https://www.ncbi.nlm.nih.gov/pubmed/37333834
http://dx.doi.org/10.3389/fnhum.2023.1134599

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