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Electroencephalography and Magnetoencephalography


In this chapter, we present the main characteristics of electroencephalography (EEG) and magnetoencephalography (MEG). More specifically, this chapter is dedicated to the presentation of the data, the way they can be acquired and analyzed. Then, we present the main features that can be extracted and their applications for brain disorders with concrete examples to illustrate them. Additional materials associated with this chapter are available in the dedicated Github repository.
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Dates and versions

hal-03604421 , version 1 (10-03-2022)
hal-03604421 , version 2 (04-04-2022)


  • HAL Id : hal-03604421 , version 2


Marie-Constance Corsi. Electroencephalography and Magnetoencephalography. Olivier Colliot (ed.). Machine learning for brain disorders, Springer, In press. ⟨hal-03604421v2⟩
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