Deep learning applied to EEG data with different montages using spatial attention

Understand

The ability of Deep Learning to process and extract relevant information in complex brain dynamics from raw EEG data has been demonstrated in various recent works.

• Deep learning models, however, have also been shown to perform best on large corpora of data.
• When processing EEG, a natural approach is to combine EEG datasets from different experiments to train large deep-learning models.
• However, most EEG experiments use custom channel montages, requiring the data to be transformed into a common space.