Application of neural networks to brain dynamics identification by EEG

We have constructed a multilayered neural network system that identifies brain dynamics from electroencephalogram (EEG) data by error backpropagation (BP) learning. EEG data in the rest state with closed eyes and open eyes are measured with electrodes that are placed by the international 10-20 syste...

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Bibliographic Details
Main Authors: Nagashino, H., Kawano, T., Akutagawa, M., Zhang, Q., Kinouchi, Y., Shichijo, F., Nagahiro, S.
Format: Conference Proceeding
Language:English
Subjects:
Biological neural networks
Biomedical electrodes
Brain
Data engineering
Data mining
Electroencephalography
Eyes
Multi-layer neural network
Neural networks
Nonlinear dynamical systems
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Summary:We have constructed a multilayered neural network system that identifies brain dynamics from electroencephalogram (EEG) data by error backpropagation (BP) learning. EEG data in the rest state with closed eyes and open eyes are measured with electrodes that are placed by the international 10-20 system. The brain dynamics are embedded in the neural networks. The developed system discriminates the dynamics of the brain dynamics of the brain activities associated with open eyes from those with closed eyes.
DOI:10.1109/ICARCV.2002.1234885