Chapter 3: Preprocessing¶
Continuing from Chapter 2 — Importing and Inspecting Data.
The steps in this chapter clean up the continuous recording before it's cut into epochs — the same goal as the MNE-Python track's Preprocessing chapter, reached through EEGLAB's Tools menu instead of code.
Filtering¶
Tools → Filter the data → Basic FIR filter (new, default) applies EEGLAB's standard filter (pop_eegfiltnew under the hood) — enter a low cutoff, a high cutoff, or both, exactly like setting l_freq/h_freq in raw.filter() on the Python side. A separate notch filter option in the same menu removes electrical line noise (50 or 60 Hz depending on where the data was recorded).
Re-referencing¶
Tools → Re-reference the data lets you switch the recording's reference: average reference (every channel's mean, subtracted from every channel), a single channel, or the average of a specific pair (commonly the two mastoids). This is the direct GUI equivalent of MNE's raw.set_eeg_reference().
Bad channels¶
A channel that's flat, saturated, or dominated by noise should usually be excluded rather than dragging down every analysis downstream:
- Tools → Reject data using... → Reject channels for manual, visual selection, or an automated criterion (e.g. Clean Rigor, installed as a plugin) that flags outlier channels statistically.
- Once a channel is marked bad, Tools → Interpolate electrodes reconstructs it from its neighbors — useful when you'd rather keep a full, regular channel set for later group averaging than simply drop the channel.
Resampling¶
Tools → Change sampling rate downsamples the recording — smaller files and faster processing, at the cost of the very highest frequencies. A common choice is resampling to somewhere around 250–500 Hz for standard EEG/ERP work, well above where most signal of interest lives.
A note on reproducibility: EEG.history¶
Every GUI operation you run is silently logged as an equivalent line of MATLAB code in EEG.history. File → Save history (or Edit history) exports that log as a runnable .m script — meaning a pipeline you clicked together in the GUI once can be replayed exactly, or adapted into a script that runs unattended over many subjects. This is EEGLAB's built-in bridge between "exploring by hand" and "scripted and reproducible," worth keeping in mind heading into Chapter 7.