[Eeglablist] RELAX: a fully automated EEG pre-processing toolbox

[Neil Bailey]

Dear EEGLAB users

Clinical Neuropsychology recently published our manuscripts introducing
RELAX, a fully automated EEG pre-processing toolbox (citations below).

RELAX uses evidence-based and well-established approaches to identify
artifacts. It then combines multi-channel Wiener filtering (MWF) and
wavelet enhanced ICA (wICA) with ICLabel to effectively clean all types of
artifacts from the data, while successfully preserving neural signal. Some
key advantages of RELAX are that applying the MWF cleaning first improves
the ICA decomposition, and the use of wICA reduces the removal of the
neural signal that is commonly mixed into artifact components.

As a result, RELAX showed superior performance at both cleaning artifacts
(blinks, muscle, and other artifacts) and preserving signal compared to 6
commonly used pre-processing pipelines across five datasets, each with
different recording parameters (N = 213, 127, 73, 60 and 23 respectively).

RELAX is modular, so the MWF or wICA cleaning can be applied separately.
RELAX also allows data to be high-pass filtered using settings appropriate
for analysing event-related potentials (~0.25Hz), the results of which we
reported in our second paper. Finally, RELAX outputs metrics that indicate
how well the data was cleaned and whether artifacts remain, as well as
notifying the user if visual inspection of any of the data is recommended,
for example in the case of extremely noisy raw data.

RELAX can be installed from EEGLAB's plugin manager, or from GitHub, where
a detailed user manual can be found:
https://urldefense.com/v3/__https://github.com/NeilwBailey/RELAX/releases/tag/RELAX-v1.1.3__;!!Mih3wA!AdfUWK3o-AuTsB64McP2KMifBOJ9ljdzWzqcvJXrctM_tgqJcZCxb2vtMn95f5CvANrgS5iyXAkIX-bcUApty_oa7RD_oZhs$ 

Given the effective cleaning, fully automated, and oscillation/ERP
compatible nature of RELAX, we recommend it for use across EEG research.

Kind regards,

Neil Bailey

Bailey, N. W., Biabani, M., Hill, A. T., Miljevic, A., Rogasch, N. C.,
McQueen, B., ... & Fitzgerald, P. B. (2023). Introducing RELAX: An
automated pre-processing pipeline for cleaning EEG data-Part 1: Algorithm
and application to oscillations. *Clinical Neurophysiology*.
https://urldefense.com/v3/__https://doi.org/10.1016/j.clinph.2023.01.017__;!!Mih3wA!AdfUWK3o-AuTsB64McP2KMifBOJ9ljdzWzqcvJXrctM_tgqJcZCxb2vtMn95f5CvANrgS5iyXAkIX-bcUApty_oa7ZssqT1V$ 

Bailey, N. W., Hill, A. T., Biabani, M., Murphy, O. W., Rogasch, N. C.,
McQueen, B., ... & Fitzgerald, P. B. (2023). RELAX part 2: A fully
automated EEG data cleaning algorithm that is applicable to
Event-Related-Potentials. *Clinical Neurophysiology*.
https://urldefense.com/v3/__https://doi.org/10.1016/j.clinph.2023.01.018__;!!Mih3wA!AdfUWK3o-AuTsB64McP2KMifBOJ9ljdzWzqcvJXrctM_tgqJcZCxb2vtMn95f5CvANrgS5iyXAkIX-bcUApty_oa7T_6B79T$