Ryu Jihye, Bar-Shalita Tami, Granovsky Yelena, Weissman-Fogel Irit, Torres Elizabeth B
Rutgers University Center for Cognitive Science, Psychology Department, Rutgers University, Piscataway, NJ 08854, USA.
Department of Occupational Therapy, School of Health Professions, Faculty of Medicine, Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 6997801, Israel.
J Pers Med. 2021 Feb 2;11(2):93. doi: 10.3390/jpm11020093.
The study of pain requires a balance between subjective methods that rely on self-reports and complementary objective biometrics that ascertain physical signals associated with subjective accounts. There are at present no objective scales that enable the personalized assessment of pain, as most work involving electrophysiology rely on summary statistics from a priori theoretical population assumptions. Along these lines, recent work has provided evidence of differences in pain sensations between participants with Sensory Over Responsivity (SOR) and controls. While these analyses are useful to understand pain across groups, there remains a need to quantify individual differences more precisely in a personalized manner. Here we offer new methods to characterize pain using the moment-by-moment standardized fluctuations in EEG brain activity centrally reflecting the person's experiencing temperature-based stimulation at the periphery. This type of gross data is often disregarded as noise, yet here we show its utility to characterize the lingering sensation of discomfort raising to the level of pain, individually, for each participant. We show fundamental differences between the SOR group in relation to controls and provide an objective account of pain congruent with the subjective self-reported data. This offers the potential to build a standardized scale useful to profile pain levels in a personalized manner across the general population.
疼痛研究需要在依赖自我报告的主观方法与确定与主观描述相关的身体信号的补充性客观生物特征识别方法之间取得平衡。目前尚无能够实现疼痛个性化评估的客观量表，因为大多数涉及电生理学的研究都依赖于基于先验理论总体假设的汇总统计数据。沿着这些思路，最近的研究提供了证据，表明感觉过度反应（SOR）参与者与对照组在疼痛感觉上存在差异。虽然这些分析有助于理解不同群体的疼痛情况，但仍需要以个性化方式更精确地量化个体差异。在此，我们提供了新的方法来利用脑电图（EEG）大脑活动的逐时刻标准化波动来表征疼痛，这种波动集中反映了个体在外周体验基于温度的刺激的情况。这类总体数据通常被视为噪声而被忽视，但我们在此展示了其在为每个参与者单独表征逐渐加剧至疼痛程度的不适感的持续感觉方面的效用。我们展示了SOR组与对照组之间的根本差异，并提供了与主观自我报告数据一致的疼痛客观描述。这为构建一个标准化量表提供了潜力，该量表可用于以个性化方式描绘普通人群的疼痛水平。
