Figure 3.

SEED-G performances in terms of computational time and percentage of realistic data generated: (a) Mean and standard deviation of the computational time computed over 300 iterations were shown as functions of the number of time series (Model size) and the number of existing connections (Network density). The number of real sources included is equal to 30%. Except for some 60-node models, all the simulated datasets composed by 100 trials were generated in less than 10 s. (*) encodes the fact that no dataset with that specific combination of features could be generated with 1000 attempts; (b) Mean and standard deviation of the percentage of EEG-like signals (EEGl-s) computed over 300 iterations were reported as functions of Model size and of the number of real sources included in the connectivity model (Real sources). The density of the network is equal to 10%. On average, more than 80% of the generated data reported EEG-like spectral properties.