Toward a Predictive Coding Account of Hypnotic Hypoalgesia: Integrating EEG Oscillations and Somatosensory Evoked Responses

Hypnotic hypoalgesia effectively reduces various types of pain, but its neurophysiological mechanisms remain unclear. EEG and somatosensory event-related potentials (SERPs) can help elucidate how hypnotic suggestions influence pain processing across sensory, emotional, and cognitive domains. This review synthesizes evidence on EEG oscillatory activity and SERP correlates in hypnotic pain modulation and interprets the findings through predictive coding and active inference frameworks. The review integrated relevant studies on EEG frequency-band oscillations, SERPs, and the modulation of pain by hypnosis, focusing on a convergent neurophysiological account of hypnotic pain modulation rather than on individual studies. Research indicates that hypnotic hypoalgesia is associated with concerted changes across multiple EEG frequency bands. Theta activity is linked to focused internal attention and the maintenance of suggestion-consistent representations, while increased alpha activity may indicate inhibitory sensory gating and reduced nociceptive gain. Beta oscillations enhance pain relief in cognitive and motor functions, while decreased gamma activity indicates reduced significance of pain signals. SERP findings show that hypnotic suggestions primarily affect late evaluative components (e.g., P200/P250, P300) rather than early sensory elements, suggesting changes in salience assignment and affective-cognitive appraisal rather than uniform suppression of nociceptive input. Predictive coding and active inference explain how hypnotic suggestions change pain-related expectations and bodily perceptions. This insight is key to enhancing personalized pain management and guiding future neuroscience research.