A Post-Recurrent Module added to RNNs yields 9% better P300 classification while identifying key spatio-temporal EEG patterns that match established neuroscience descriptions of the P300 wave.
An electrode selection approach in P300-based BCIs to address inter-and intra- subject variability, in: 2018 6th International Conference on Brain- Computer Interface (BCI), IEEE
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Explainability of Recurrent Neural Networks for Enhancing P300-based Brain-Computer Interfaces
A Post-Recurrent Module added to RNNs yields 9% better P300 classification while identifying key spatio-temporal EEG patterns that match established neuroscience descriptions of the P300 wave.