BR Net: A novel deep learning model guided by brain region features for decoding single-trial visual EEG signals

Key Points

• Decoded single-trial visual EEG signals with high accuracy using the novel BR Net model.
• For the initial validation, BR Net achieved an accuracy of 85% on visual task EEG data across various trials.
• This work utilized a deep learning framework designed specifically for analyzing EEG signals influenced by distinct brain regions.
• Supports the potential for improving neural interface technologies but needs validation in larger, more diverse populations.