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Automagic is a MATLAB based toolbox for preprocessing of EEG-datasets. It has been developed with the intention to offer a user-friendly pre-processing software for big (and small) EEG datasets. The software can be controlled with a graphical user interface (GUI) and does not require any knowledge about programming. It runs on Matlab (R2016b and newer releases). Due to the fact that the applications is compiled of several matlab functions that are compatible with EEGLAB (Delorme & Makeig 2004), one of the most used opens-source frameworks for EEG analysis) more experienced users can extend Automagic to their specific needs. Automagic is an open-source toolbox. Thus users can modify or add preprocessing features according to their own needs. However, given that we aimed to keep the workflow of the pipeline under some control (and safeguard inexperienced users from making intricate mistakes), we have decided against offering a specific way to add plugins. Instead we welcome the community to suggest new features and methods, which we then (if reasonable) can implement by ourselves or in collaboration (contact us!).

To give a short orientation, Automagic contains three basic sections, theproject section, theconfiguration section, and thequality assessment section. A typical workflow involves the following steps: In theproject section, the user defines the input and output folders of the processing and information about the EEG data, such as the format, channel locations or electrooculogram (EOG)- channels. Theconfiguration section allows to select various preprocessing steps with their settings that are applied to the EEG. After the preprocessing of the data and the interpolation of bad channels, the user can review the quality of the pre-processing in thequality assessment section. Here, EEG datasets can be displayed as heatmaps (with dimensions of channels and time) or classical EEG channel plots (using the eegplot function of EEGLAB), allowing the user to obtain a quick overview of the data quality. In addition, various quality criteria are computed such as the ratio of interpolated channels, remaining time windows of high voltage amplitudes and percentage of retained variance after ICA artifact correction. The user can finally set cutoffs for these quality criteria to objectively include datasets of good quality and exclude datasets of too poor quality.

You need MATLAB installed and activated on your system to useAutomagic.Automagic was developed and tested in MATLAB R2016b and newer releases.

1. Download and unzipautomagic-master to your favorite place on your hard drive.

Please note that if you would like to have the latest features developed inAutomagic, download the version on thedevelopment branch. In the latest version you can useICLabel in addition to other preprocessing steps. A better integration with the BIDS format is also implemented in the latest version.

1. To run automagic, start Matlab and change your working directory to the root folderautomagic-master.
   • Please doNOT addAutomagic to Matlab path manually.
2. TyperunAutomagic in Matlab command window.

For a comprehensive explanation on how to start and useAutomagic please see thewiki page.

The Automagic paper is published now inNeuroimage oras preprint inbioRxiv.

Please use the following citation if you use Automagic:

Pedroni, A., Bahreini, A., & Langer, N. (2019). Automagic: Standardized preprocessing of big EEG data. Neuroimage. doi: 10.1016/j.neuroimage.2019.06.046

You can find ushere.If you have any questions, feedbacks please email us at methlabuzh [at] gmail [dot] com