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RELAX v 1.1.1
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@NeilwBailey NeilwBailey released this 18 Oct 03:26
v1.1.1
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RELAX

The Reduction of Electroencephalographic Artifacts (RELAX) is an open source extension for EEGLAB that provides a fully automated method to clean EEG data.

Downloading RELAX:
To download and install RELAX, click on the source code in the "Assets" section below, and unzip into your EEGLAB plugins folder.

Further information:
Further information can be found in the publication manuscripts, which must be cited when RELAX is used:

Bailey NW, Biabani M, Hill AT, Miljevic A, Rogasch NC, McQueen B, Murphy OW, Fitzgerald PB (2022). Introducing RELAX (the Reduction of Electroencephalographic Artifacts): A fully automated pre-processing pipeline for cleaning EEG data - Part 1: Algorithm and Application to Oscillations. BioRxiv.

Bailey NW, Hill AT, Biabani M, Murphy OW, Rogasch NC, McQueen B, Miljevic A, Fitzgerald PB (2022). Introducing RELAX (the Reduction of Electroencephalographic Artifacts): A fully automated pre-processing pipeline for cleaning EEG data – Part 2: Application to Event-Related Potentials. BioRxiv.

Additional details can also be found in the supplementary materials, the PDFs of which are in this release.

Instructions can be found in the Wiki (the fourth button from the left in the toolbar at the top of the webpage), which is currently under development.

v1.1.1

Fixed an error in the specification of triggers to levels for a single factor regression baseline correction in the epoching wrapper, so that the regression baseline correction method should be functional for any user set trigger.

Altered the labelling of the extended infomax ICA option in the GUI so it should be more clear to the user what this option reflects.

v1.1.0

Introduced new options in a beta version, which have not been formally tested but may improve performance:

Provided the option to leave low pass filtering until after the MWF cleaning, which significantly alleviates the risk of rank deficiencies in the MWF cleaning, allowing for much longer MWF delay periods (we've tested up to 30), providing theoretically better cleaning performance.

Provided the option to use EEGLAB's filter rather than just Butterworth filtering (previously this was not available as low pass filtering with EEGLAB's filter led to almost constant rank deficiencies in MWF cleaning).

Provided the option to use Zapline Plus to clean line noise (instead of just Butterworth notch filtering). Note that this is probably not appropriate for data that has had an online notch filter applied, and the authors of Zapline Plus do not recommend it's use for data sampled at higher than 250Hz.

Assets 3
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