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Successful reproduction of a large EEG study across software packages
[article]
2022
bioRxiv
pre-print
As an active field of research and with the development of state-of-the-art algorithms to analyze EEG datasets, the parametrization of Electroencephalography (EEG) analysis workflows has become increasingly flexible and complex, with a great variety of methodological options and tools to be selected at each step. This high analytical flexibility can be problematic as it can yield to variability in research outcomes. Therefore, growing attention has been recently paid to understand the potential
doi:10.1101/2022.08.03.502683
fatcat:u2emlgrgafgqji5o4mu3cgh6ve