Assessing the impact of artifact correction and artifact rejection on the performance of SVM-based decoding of EEG signals.

• Tác giả: Steven J Luck, Guanghui Zhang
• Ngôn ngữ: eng
• Ký hiệu phân loại: 794.147 King
• Thông tin xuất bản: United States : bioRxiv : the preprint server for biology , 2025
• Bộ sưu tập: NCBI
• ID: 683527

Tóm tắt

 Numerous studies have demonstrated that eyeblinks and other large artifacts can decrease the signal-to-noise ratio of EEG data, resulting in decreased statistical power for conventional univariate analyses. However, it is not clear whether eliminating these artifacts during preprocessing enhances the performance of multivariate pattern analysis (MVPA