How to cite

If you used MEEGsim in your project, please consider citing the software using the DOI provided by Zenodo: https://doi.org/10.5281/zenodo.15106042

@software{MEEGsim,
    author = {Kapralov, Nikolai and Studenova, Alina and Jamshidi Idaji, Mina},
    license = {BSD-3-Clause},
    title = {{MEEGsim}},
    doi = {https://doi.org/10.5281/zenodo.15106042},
    version = {0.0.2},
    year = {2025}
}

In addition, please cite MNE-Python since MEEGsim re-uses lots of important functionality provided by this toolbox.

Finally, check the section below to find reference papers for methods behind MEEGsim.

Methods

Below we also provide reference papers for some of the approaches and functions provided by MEEGsim. By citing these references, you can guide the reader to the description of underlying methods:

Approach / Function	Reference
Global adjustment of the SNR	[1]
Local adjustment of the SNR	[2]
meegsim.coupling.ppc_constant_phase_shift()	[3]
meegsim.coupling.ppc_von_mises()	[3]

References

[1]

Stefan Haufe and Arne Ewald. A Simulation Framework for Benchmarking EEG-Based Brain Connectivity Estimation Methodologies. Brain Topography, 32:625–642, 2019. doi:10.1007/s10548-016-0498-y.

[2]

Vadim V Nikulin, Guido Nolte, and Gabriel Curio. A novel method for reliable and fast extraction of neuronal EEG/MEG oscillations on the basis of spatio-spectral decomposition. Neuroimage, 55(4):1528–1535, April 2011. doi:10.1016/j.neuroimage.2011.01.057.

[3] (1,2)

Mina Jamshidi Idaji. New machine learning methods for modeling nonlinear interactions in neural data. PhD thesis, Technical University of Berlin, 2022. doi:10.14279/depositonce-16416.