eeg preprocessing pipeline guide

EEG preprocessing transforms raw electrophysiological recordings into clean data suitable for analysis. Unlike generic signal processing, every preprocessing decision in EEG involves domain-specific trade-offs: filtering at the wrong cutoff distorts ERP component morphology, choosing the wrong reference scheme biases topographic maps, and automated artifact rejection with incorrect parameters either leaves artifac...

A competent programmer without EEG training would not know that a 1 Hz high-pass filter is needed before ICA but distorts slow ERP components, that average reference requires a minimum of 64 channels, or that the order of preprocessing steps matters critically. This skill encodes the domain judgment required to build a correct EEG preprocessing pipeline.

This skill was generated by AI from academic literature. All parameters, thresholds, and citations require independent verification before use in research. If you find errors, please open an issue.