Installation

Compatibility and requirements

• The MVPAlab Toolbox has been designed to be fully compatible with MATLAB 9.0 (R2016a) and above. This restriction is only applicable to the graphic user interface, which has been developed using App Designer, introduced in the 9.0 version. Custom MVPAlab scripts can be executed under older MATLAB versions.

• Since this software has been developed using MATLAB and has no external dependencies, the MVPAlab Toolbox is fully supported by GNU/Linux, Unix, Windows and macOS platforms.

• Hardware requirements depend on the size of the analyzed dataset. While the CPU specifications only affects to the computation time, enough RAM capacity is required to store and process M/EEG data. For almost any process, the recommended RAM capacity is at least the double of the size of the dataset (measured in gigabytes). For more memory demanding processes, MVPAlab splits and stores EEG data on the hard drive, importing it again when needed. Since MVPAlab only uses the CPU for computation, the GPU specification does not affect to the toolbox performance.

• Some MATLAB built-in packages and functions are required for a correct functioning of this software. For the statistical analysis, the Image Processing Toolbox and the 'Bioinformatics Toolbox' are required to find clusters in significant masks. The Statistics and Machine Learning Toolbox provides functions to train and validate classification models, dimensionality reduction, feature selection, etc. The Signal Processing Toolbox is required for extracting M/EEG envelopes as features. The Parallel Computation Toolbox is not required but recommended to drastically reduce the computation time as it allows to divide the computational load in different processing threads.

• Finally, MVPAlab greatly benefits from other open source M/EEG toolboxes such as EEGlab and FieldTrip: some filtering functions require the EEGlab Toolbox installed and initiated for a correct operation. If MVPAlab finds an EEGlab installation it will initiate it automatically.

• Users should ensure that these dependencies are included in their MATLAB installation.

Installation steps

The MVPAlab toolbox installation is quite simple:

1. Download the latest MVPAlab toolbox release under the assets tab (Source Code .zip or tar.gz)

2. Extract the MVPAlab folder in your local directory.

3. Add the MVPAlab folder to the MATLAB path.

   • Open MATLAB
   • Click on Set Path button under the HOME menu.
   • Add mvpalab folder by clicking in add Folder... button.
   • Click on Save and Close button

Run MVPAlab Toolbox

1. The MVPAlab Toolbox can be initiated by typing the command mvpalab in the MATLAB command window: