Predicting Motor Imagery Performance From Resting-State EEG Using Dynamic Causal Modeling. | Front Hum Neurosci;14: 321, 2020. | MEDLINE

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Predicting Motor Imagery Performance From Resting-State EEG Using Dynamic Causal Modeling.

Lee, Minji; Yoon, Jae-Geun; Lee, Seong-Whan.

Affiliation

Lee M; Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea.
Yoon JG; Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea.
Lee SW; Department of Artificial Intelligence, Korea University, Seoul, South Korea.

Front Hum Neurosci ; 14: 321, 2020.

Article in En | MEDLINE | ID: mdl-32903663

Key words

brain-computer interface; dynamic causal modeling; effective connectivity; electroencephalography; motor imagery

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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Front Hum Neurosci Year: 2020 Document type: Article Affiliation country: Corea del Sur

Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Front Hum Neurosci Year: 2020 Document type: Article Affiliation country: Corea del Sur