Palmisani Federico, Thiyagarajan Jawahar Sri Prakash, Horsey Joe, Hughes Sam W, Medina Sonia
Department of Clinical and Biomedical Sciences, University of Exeter, Exeter, UK.
Eur J Pain. 2025 Oct;29(9):e70113. doi: 10.1002/ejp.70113.
Persistent mismatches between predicted and actual pain-related signals, namely prediction errors (PEs), can cause maladaptive overestimation of pain intensity, a common feature of chronic pain states. Experimental protocols used to assess the contribution of central sensitisation (CS) to dysregulated prediction systems are lacking. To address this, we implemented a novel virtual reality (VR) paradigm to evoke PEs during mechanical stimulation following experimentally induced CS via the high-frequency stimulation (HFS) model.
Twenty healthy volunteers underwent HFS on the right forearm. Mechanical pain sensitivity (MPS) was assessed through pinprick stimuli before and 30 min post-HFS to evaluate secondary hyperalgesia. Following this, participants received mechanical stimuli at proximal (sensitised area) and distal (non-sensitised area) points from the HFS site, with visual cues presented on their arm via VR alongside hand tracking technology indicating the stimulus location, allowing participants to make pain predictions. Cues were either congruent (matching) or incongruent (mismatching) with the actual stimulus site to evoke PEs.
Results showed that MPS significantly increased following HFS, confirming secondary hyperalgesia. Stimuli in sensitised areas induced more pain than in non-sensitised areas. Incongruent cues successfully elicited PEs across all locations; however, expectations modulated pain perception only in non-sensitised areas. Similarly, during incongruent trials, PEs diminished over time (reflecting adaptive learning) only in non-sensitised areas.
These data demonstrate that pain expectations can influence pain perception differently in centrally sensitised and non-sensitised states. We propose this protocol as a good candidate to assess how cognitive and psychological manipulations influence PEs at various stages of CS.
We introduce a novel VR paradigm to show that secondary hyperalgesia alters how pain expectations and prediction errors influence pain perception, highlighting distinct adaptive learning patterns.
预测的与实际的疼痛相关信号之间持续存在不匹配,即预测误差(PEs),可能导致对疼痛强度的适应不良性高估,这是慢性疼痛状态的一个常见特征。目前缺乏用于评估中枢敏化(CS)对失调的预测系统的贡献的实验方案。为了解决这个问题,我们实施了一种新颖的虚拟现实(VR)范式,通过高频刺激(HFS)模型在实验诱导CS后进行机械刺激期间诱发PEs。
20名健康志愿者的右前臂接受HFS。在HFS前和后30分钟通过针刺刺激评估机械性疼痛敏感性(MPS),以评估继发性痛觉过敏。在此之后,参与者在HFS部位的近端(敏化区域)和远端(非敏化区域)接受机械刺激,通过VR在其手臂上呈现视觉线索以及手部跟踪技术指示刺激位置,使参与者能够进行疼痛预测。线索与实际刺激部位要么一致(匹配)要么不一致(不匹配),以诱发PEs。
结果显示HFS后MPS显著增加,证实了继发性痛觉过敏。敏化区域的刺激比非敏化区域诱发的疼痛更多。不一致的线索在所有位置均成功诱发了PEs;然而,期望仅在非敏化区域调节疼痛感知。同样,在不一致的试验中,仅在非敏化区域PEs随时间减少(反映适应性学习)。
这些数据表明,在中枢敏化和非敏化状态下,疼痛期望对疼痛感知的影响可能不同。我们提出该方案是评估认知和心理操作如何在CS的各个阶段影响PEs的良好候选方案。
我们引入了一种新颖的VR范式,以表明继发性痛觉过敏改变了疼痛期望和预测误差对疼痛感知的影响方式,突出了不同的适应性学习模式。