Below we outline hardware and software requirements for EEGLAB and associated tools. Hardware requirements vary with the size of the datasets you want to process. We have outlined two levels of hardware needed for basic and advanced processing, respectively. It is also possible to process data on (some) less powerful platforms, but in trying to use them, you may end up spending much of your time trying to avoid “Out of Memory” errors. EEGLAB works on Windows, Linux, or Mac OS X. No operating system is better.
Minimum processing requirements (and/or highly desirable features) for processing up to 32 EEG channels per subject using core EEGLAB functions only:
- 8Gb of RAM (random access memory)
- At least 200 Gb of available hard drive space (SSD if possible)
- Newest version of MATLAB – no additional MATLAB toolboxes are required (but see below)
Normal processing requirements (and/or highly desirable features) for processing 64 or more EEG channels and/or using the most recent EEGLAB toolboxes:
- Quad processors cores (4 or more are desirable)
- 16 Gb or more of RAM (random access memory)
- At least 1 Tb of SSD (SSD will speed up read/write by a factor of up to 5x) or mixed system (SSD 128Gb and large hard drive)
- Newest version of MATLAB and the MATLAB signal processing, statistics, and optimization toolboxes, whose functions are used in some advanced EEGLAB plugins.
Although EEGLAB is free, the MATLAB software environment that it runs on is a commercial product of The Mathworks. Often, your school might have negotiated access (check here). EEGLAB also works on the free Octave environment (command-line only), and you may also download a compiled version of EEGLAB that does not require a MATLAB license.
For Ubuntu linux users: There are often graphics problems when MATLAB uses OpenGL graphics under Ubuntu. To avoid them, at the beginning of each MATLAB session enter
For GPU users: EEGLAB functions do not currently use GPUs’ capabilities (Graphic Processing Unit), which currently have the highest performance/cost ratio. However, we have made the first attempts at porting some functions to work with GPUs – click here for more information.