SEED-G: Simulated EEG Data Generator for testing connectivity algorithms

SEED-G toolbox was developed in MATLAB environment (tested on version R2017a and R2020b) and released on the GitHub page https://github.com/aanzolin/SEED-G-toolbox (accessed date 12 April 2021). It is organized in the following subfolders: <strong>main</strong>: it is the core of the toolbox and contains all the functions for the generation of EEG data according to a predefined ground-truth network. <strong>dependencies</strong>: containing parts of other toolboxes required to successfully run SEED-G functions. The links to the full packages can be found in the documentation on the GitHub page. The additional packages are Brain Connectivity Toolbox (BCT) [40], FieldTrip [41], Multivariate Granger Causality Toolbox (MVGC) [24], and AsympPDC Package (PDC_AsympSt) [42,43]. Additionally, the implemented forward model is solved according to the New York Head (NYH) model, whose parameters are contained in the structure available on the ICBM-NY platform [28]. <strong>real data</strong>: containing real EEG data acquired from one healthy subject during resting state at scalp level (‘EEG_real_sources.mat’) and its reconstructed version in source domain (‘sLOR_cortical_sources.mat’). These signals can be employed to extract the AR components to be included in the model to generate data with the same spectral properties of the real ones. <strong>demo</strong>: containing examples of MATLAB scripts to be used to learn the different functionalities of the toolbox. For example, the code ‘run_generation.m’ allows to specify the directory containing the real sources and each specific input of the function ‘simulatedData_generation.m’. <strong>auxiliary functions</strong>: containing either original MATLAB functions or modified version of free available functions.