Neuro-imagerie électromagnétique et localisation des oscillations cérébrales du sommeil

Abstract

This master thesis goal consist in studying the spindle and slow wave sleep oscillations by using the MEG and EEG fusion (MEEG) as a new neuro-imaging approach of sources localization by the maximum entropy on the mean (MEM). The new technic of sources localization is in the time-frequency domain obtained by using the discrete wavelet transform of the signals. So, the MEM uses the elements of information (wavelets coefficients) to obtain localization on the cortex. The goal of this project consists in the implementation of the MEEG fusion in the wMEM of Brainstorm software. The MEG contains information that the EEG doesn’t have and viceversa. So, the MEEG fusion will complete the localization. The tests have proved that MEEG fusion is more sensible and specific than individual modalities (MEG or EEG) for the sources localization. Sleep spindles localized by using the MEG only, shows that their dynamic are principally located on the parietal lobes of the cortex. The frontal lobe is considered also when we add the EEG modality to the localization. This is very important because we know that the spindles have this kind of dynamic. Sleep slow wave got sensibly the same problem when using the MEG only because the cortical activity of this kind of wave is on the frontal lobe. In the transition between the minimum and maximum of the slow wave, temporal activity occurs. So, MEG only is not enough sensible to the frontal activity. Adding the EEG is necessary to obtain the frontal dynamic of the sleep slow wave. Spindles could be close (temporarily) to a sleep slow wave. Results of the localization of this kind of spindle shows that they are concentrate in the frontal lobe, while the other kind, without slow wave, shows that they consider the parietal region of the cortex also. This is the main difference between these two kinds of spindles. Finally, the original contribution that consists in the implementation of the MEEG fusion in the time-frequency domain is useful for the sources localization of the sleep slow wave and spindles.

Date	26 Jan 2017
Original language	French
Awarding Institution	École de technologie supérieure
Supervisor	Jean-Marc Lina (Supervisor)