NeuroPain Lab, Lyon Neuroscience Research Centre, CRNL - Inserm U 1028/CNRS UMR 5292, University of Saint-Etienne, University of Lyon, France; IRISSE Laboratory (EA4075), UFR SHE, University of La Réunion, Le Tampon, France.
NeuroPain Lab, Lyon Neuroscience Research Centre, CRNL - Inserm U 1028/CNRS UMR 5292, University of Saint-Etienne, University of Lyon, France; Neuro-Dol, Inserm 1107, University Hospital of Clermont-Ferrand, University of Clermont-Auvergne, Clermont-Ferrand, France.
Clin Neurophysiol. 2024 Oct;166:152-165. doi: 10.1016/j.clinph.2024.07.018. Epub 2024 Aug 5.
To assess the value of combining brain and autonomic measures to discriminate the subjective perception of pain from other sensory-cognitive activations.
20 healthy individuals received 2 types of tonic painful stimulation delivered to the hand: electrical stimuli and immersion in 10 Celsius degree (°C) water, which were contrasted with non-painful immersion in 15 °C water, and stressful cognitive testing. High-density electroencephalography (EEG) and autonomic measures (pupillary, electrodermal and cardiovascular) were continuously recorded, and the accuracy of pain detection based on combinations of electrophysiological features was assessed using machine learning procedures.
Painful stimuli induced a significant decrease in contralateral EEG alpha power. Cardiac, electrodermal and pupillary reactivities occurred in both painful and stressful conditions. Classification models, trained on leave-one-out cross-validation folds, showed low accuracy (61-73%) of cortical and autonomic features taken independently, while their combination significantly improved accuracy to 93% in individual reports.
Changes in cortical oscillations reflecting somatosensory salience and autonomic changes reflecting arousal can be triggered by many activating signals other than pain; conversely, the simultaneous occurrence of somatosensory activation plus strong autonomic arousal has great probability of reflecting pain uniquely.
Combining changes in cortical and autonomic reactivities appears critical to derive accurate indexes of acute pain perception.
评估结合大脑和自主测量值来区分疼痛的主观感知与其他感觉认知激活的价值。
20 名健康个体接受了 2 种类型的手部持续疼痛刺激：电刺激和浸入 10 摄氏度（°C）水中，与非疼痛的浸入 15°C 水中和应激性认知测试形成对比。连续记录高密度脑电图（EEG）和自主测量值（瞳孔、皮肤电和心血管），并使用机器学习程序评估基于电生理特征组合的疼痛检测准确性。
疼痛刺激引起对侧 EEGα 功率显著降低。心脏、皮肤电和瞳孔反应发生在疼痛和应激条件下。在逐个报告中，基于 leave-one-out 交叉验证折叠训练的分类模型，独立使用皮质和自主特征的准确性较低（61-73%），而它们的组合将准确性显著提高到 93%。
反映躯体感觉显著性的皮质振荡变化和反映唤醒的自主变化可以被许多除疼痛之外的激活信号触发；相反，躯体感觉激活加上强烈的自主唤醒的同时发生极有可能唯一地反映疼痛。
结合皮质和自主反应的变化似乎对于得出急性疼痛感知的准确指标至关重要。
