{"ID":2856862,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.10733","arxiv_id":"2510.10733","title":"Does Re-referencing Matter? Large Laplacian Filter Optimizes Single-Trial P300 BCI Performance","abstract":"Electroencephalography (EEG) provides a non-invasive window into brain activity, enabling Brain-Computer Interfaces (BCIs) for communication and control. However, their performance is limited by signal fidelity issues, among which the choice of re-referencing strategy is a pervasive but often overlooked preprocessing bias. Addressing controversies about its necessity and optimal choice, we adopted a quantified approach to evaluate four strategies - no re-referencing, Common Average Reference (CAR), small Laplacian, and large Laplacian - using 62-channels EEG (31 subjects, 2,520 trials). To our knowledge, this is the first study systematically quantifying their impact on single-trial P300 classification accuracy. Our controlled pipeline isolated re-referencing effects for source-space reconstruction (eLORETA with Phase Lag Index) and anatomically constrained classification. The large Laplacian resolves distributed P3b networks while maintaining P3a specificity, achieving the best P300 peak classification accuracy (81.57% hybrid method; 75.97% majority regions of interest). Performance follows a consistent and statistically significant hierarchy: large Laplacian \u003e CAR \u003e no re-reference \u003e small Laplacian, providing a foundation for unified methodological evaluation.","short_abstract":"Electroencephalography (EEG) provides a non-invasive window into brain activity, enabling Brain-Computer Interfaces (BCIs) for communication and control. However, their performance is limited by signal fidelity issues, among which the choice of re-referencing strategy is a pervasive but often overlooked preprocessing b...","url_abs":"https://arxiv.org/abs/2510.10733","url_pdf":"https://arxiv.org/pdf/2510.10733v1","authors":"[\"Eva Guttmann-Flury\",\"Jian Zhao\",\"Mohamad Sawan\"]","published":"2025-10-12T18:10:57Z","proceeding":"q-bio.NC","tasks":"[\"q-bio.NC\",\"q-bio.QM\"]","methods":"[]","has_code":false}