Méthodologie de traitement conjoint des signaux EEG et oculométriques : applications aux tâches d'exploration visuelle libre

Abstract : Our research focuses on the issue of overlapping for evoked potential estimation. More specifically, this issue is a significant limitation for Eye-Fixation Related Potentials and Eye-Saccade Related Potentials estimations during a joint EEG and eye-tracking recording. Indeed, the usual estimation, by averaging the signal time-locked to the event of interest, is based on the assumption that a single evoked potential occurs during a trial. However, depending on the inter-stimulus intervals, this assumption is not always verified. This is especially the case in the context of Eye-Fixation Related Potentials and Eye-Saccade Related Potentials, given the fact that the intervals between fixations (or saccades) are not controlled by the experimenter and can be shorter than the latencies of the potentials of interest.The fact that this assumption is not verified gives a distorted estimate of the evoked potential due to overlaps between the evoked potentials.We have therefore used the Linear Model (GLM), a well-known linear regression method, to estimate the potentials evoked by ocular movements in order to take into account overlaps. First, we decided to introduce a term of Tikhonov regularization into this model in order to improve the signal-to-noise ratio of the estimate for a small number of trials. Then, we compared the GLM to the ADJAR algorithm in a context of joint EEG and eye-tracking recording during a task of visual exploration of natural scenes. The ADJAR ("ADJAcent Response") algorithm is an algorithm for iterative estimation of temporal overlaps developed in 1993 by M. Woldorff. The results showed that the GLM model was more flexible and robust than the ADJAR algorithm in estimating Eye-Fixation Related Potentials. Further, two GLM configurations were compared in their estimation of evoked potential at the onset of the stimulus and the eye-fixation related potential at the beginning of the testing. Both configurations took into account the overlaps between evoked potentials, but one additionally distinguished the potential evoked by the first fixation of the exploration from the potential evoked by the following fixations. It became clear that the choice of the GLM configuration was a compromise between the estimation quality of the potentials and the assumptions about the underlying cognitive processes.Finally, we conducted an extensive joint EEG and eye-tracking experiment on the exploration of static and dynamic natural emotional facial expressions. We presented the first results for the static modality. After discussing the estimation method of the evoked potentials according to the impact of the ocular movements on their latency window, we studied the influence of the type of emotion. We found modulations of the differential EPN (Early Posterior Negativity) potential, between 230 and 350 ms after the stimulus onset and the Late Positivity Potential (LPP) , between 400 and 600 ms after the stimulus onset. We also observed variations for the Eye-Fixation Related Potentials. Regarding the LPP component, a marker of conscious recognition of emotion, we have shown that it is important to dissociate information that is immediately encoded at the onset of the emotional stimulus from information encoded at the first fixations. This shows a differentiated pattern of activation according to the emotional stimulus valence. This differentiation is in agreement with the hypothesis of a faster treatment of negative emotional stimuli than of positive emotional stimuli.
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Emmanuelle Kristensen. Méthodologie de traitement conjoint des signaux EEG et oculométriques : applications aux tâches d'exploration visuelle libre. Ingénierie biomédicale. Université Grenoble Alpes, 2017. Français. ⟨NNT : 2017GREAS020⟩. ⟨tel-01693041⟩

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