Chapter 6 – EEG imaging 199 exit questionnaire. Finally, a debriefing was conducted and participants were reimbursed for their participation. Data handling Analyses of behavioral data were performed for descriptive purposes and to confirm that a significant nocebo effect was induced. Next, specific hypotheses were tested, starting with resting-state EEG data. For all hypotheses, we looked at the frequency bands of interest (alpha, beta, and gamma) and two EEG parameters of interest (oscillatory power and Detrended Fluctuation Analysis). Our primary hypothesis was that there would be pre- to post-acquisition decreases in LRTC in the alpha band, given the role of alpha oscillations in pain processing as well as previous findings regarding the role of oscillatory complexity in cognitive functions. To test this, we assessed how nocebo acquisition affected EEG parameters during rest by examining differences from before to after nocebo acquisition. We then examined whether direct links could be observed between nocebo-induced changes in restingstate brain activity (pre- to post-acquisition) and the magnitude of induced nocebo hyperalgesia, with the aim to identify resting-state biomarkers of nocebo hyperalgesia. For this purpose, we correlated any pre- to post-acquisition changes in EEG parameters with the magnitude of reported nocebo hyperalgesia. We then examined EEG parameters during the experience of pain stimulations. We first asked whether the experience of control and nocebo trials during the acquisition and evocation phases would be characterized by divergent EEG biomarker values. We then focused on potential differences in brain activity during the experience of high pain at baseline and the experience of heightened pain under nocebo hyperalgesic conditions (i.e., when lower pain stimulation is perceived as high pain, during nocebo evocation). We thus compared the experience of baseline high-pain stimulations and nocebo-
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