tailored for each study based on the equipment used, the nature of the experiment, and the hypotheses under test. Even though most pipelines follow the same general logic (filtering, epoching, averaging, etc.), the number of options is large even for such standard steps. Scripting gives the flexibility to set those options once per study to handle the requirements of different M/EEG studies. Second, analyses conducted with help of documented scripts lead to more reproducible results and ultimately help improve the quality of the research results. Finally, studies that involve processing of data from dozens or hundreds of subjects are made tractable via scripting. This is particularly relevant in an era of large-scale data analysis with possibly more than a thousand subjects, cf., the Human Brain Project or the Human Connectome Project (Van Essen et al., 2012).
