An open-source toolbox for Multi-patient Intracerebral EEG Analysis (MIA)

Intracerebral stereotaxic electroencephalography (SEEG) performed during the pre-surgical evaluation of refractory epilepsy provides a formidable opportunity to investigate the neurophysiology of human cognitive functions with unrivaled spatial and temporal precision. A difficulty of the SEEG approach for cognitive neuroscience, however, is the potential variability across patients in the anatomical location of implantations and in the functional responses recorded. In this context, we designed, implemented, and tested a user-friendly and efficient open-source software for Multi-Patient Intracerebral data Analysis (MIA). The software helps performing the analysis of SEEG signals while following good scientific practice recommendations such as building reproducible analysis pipelines and applying robust statistics. The signals can be analyzed in the temporal and time-frequency domains and the similarity of time courses can be assessed within anatomical regions, while visualizing the results in a variety of formats at every step of the analysis. Here, we illustrate the different features and steps of the analysis pipeline using a group dataset collected in a language task.