PDF(Pubmed)
Abstract：
The placebo and nocebo effects highlight the importance of expectations in modulating pain perception, but in everyday life we don\'t need an external source of information to form expectations about pain. The brain can learn to predict pain in a more fundamental way, simply by experiencing fluctuating, non-random streams of noxious inputs, and extracting their temporal regularities. This process is called statistical learning. Here, we address a key open question: does statistical learning modulate pain perception? We asked 27 participants to both rate and predict pain intensity levels in sequences of fluctuating heat pain. Using a computational approach, we show that probabilistic expectations and confidence were used to weigh pain perception and prediction. As such, this study goes beyond well-established conditioning paradigms associating non-pain cues with pain outcomes, and shows that statistical learning itself shapes pain experience. This finding opens a new path of research into the brain mechanisms of pain regulation, with relevance to chronic pain where it may be dysfunctional.
摘要：
安慰剂和nocebo效应强调了预期在调节疼痛感知中的重要性，但是在日常生活中，我们不需要外部信息来源来形成对疼痛的期望。大脑可以学会以更基本的方式预测疼痛，简单地通过体验fi波动，非随机有害输入流，提取它们的时间规律性。这个过程被称为统计学习。这里,Weaddressakeyopenquestion:doesstatisticallearningmodulatepainperception?Weasked27participantstobothrateandpredictpardintensitylevelsinsequencesofflupportingheatpain.使用计算方法，我们表明,概率预期和信心被用来衡量疼痛感知和预测.因此，这项研究超越了将非疼痛线索与疼痛结果相关联的既定条件范式，并表明统计学习本身塑造了疼痛体验。这一发现为研究疼痛调节的大脑机制开辟了一条新途径，与可能功能失调的慢性疼痛有关。
