GCNs-Net: A Graph Convolutional Neural Network Approach for Decoding Time-resolved EEG Motor Imagery Signals

Understand

Towards developing effective and efficient brain-computer interface (BCI) systems, precise decoding of brain activity measured by electroencephalogram (EEG), is highly demanded.

• Traditional works classify EEG signals without considering the topological relationship among electrodes.
• However, neuroscience research has increasingly emphasized network patterns of brain dynamics.
• Thus, the Euclidean structure of electrodes might not adequately reflect the interaction between signals.