Neural Noise- Motor imagery is a core EEG-BCI paradigm for non-invasive neural control.1
- Advances in classification and signal processing continue to improve motor imagery BCI performance.1 1
Gardner updates
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A controlled eight-dataset bioRxiv benchmark finds a compact Riemannian tangent-space geometric recentering pipeline matches deep sequence models for cross-session EEG motor-imagery decoding when features are held fixed, challenging complexity-first decoder design. 2
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A Scientific Reports Riemannian manifold dynamic attention fusion network improves motor-imagery EEG classification by combining geometry-aware covariance features with dynamic attention. 3