理解先前经历对疼痛感知和神经性疼痛影响的计算框架

Malin Ramne, Jon Sensinger
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引用次数: 0

摘要

疼痛感知不仅受到来自传入神经元的感觉输入的影响,还受到认知因素(如先验预期)的影响。有人认为,过于精确的先验预期可能是导致神经性疼痛等慢性疼痛状态的一个关键因素。然而,如何产生有利于疼痛的过度精确先验仍是一个未决问题。在这里,我们首次验证了贝叶斯方法可以描述先验预期和感觉输入的统计整合如何导致疼痛现象,如安慰剂低痛感、前兆高痛感、慢性疼痛和自发性神经病理性疼痛。我们的研究结果表明,由内部模型参数决定的先验值可能是导致这些现象的关键因素。接下来,我们采用分层贝叶斯方法,根据预测疼痛和感知疼痛之间的差异更新内部模型参数,以反映人们在未来预期中整合了先前的经验。与更简单的方法相比,这种层次模型结构能够显示安慰剂低痛感和欺骗性高痛感是如何以经典条件反射的形式从先前经验中产生的。我们还展示了抵消性镇痛现象,在这种现象中,有害刺激强度稍有降低,疼痛就会不成比例地大幅减轻。最后,我们转向神经病理性疼痛的模拟,我们的分层模型证实了持续的非神经病理性疼痛是去神经支配后发展成神经病理性疼痛的一个风险因素,此外,我们还提供了一个有趣的预测,即完全没有信息性疼痛体验也可能是一个类似的风险因素。综上所述,这些结果为我们提供了洞察力,使我们了解先前的经历如何在实验性疼痛和神经性疼痛中促进疼痛感知,进而为改进疼痛预防和缓解策略提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Computational Framework for Understanding the Impact of Prior Experiences on Pain Perception and Neuropathic Pain
Pain perception is influenced not only by sensory input from afferent neurons but also by cognitive factors such as prior expectations. It has been suggested that overly precise priors may be a key contributing factor to chronic pain states such as neuropathic pain. However, it remains an open question how overly precise priors in favor of pain might arise. Here, we first verify that a Bayesian approach can describe how statistical integration of prior expectations and sensory input results in pain phenomena such as placebo hypoalgesia, nocebo hyperalgesia, chronic pain, and spontaneous neuropathic pain. Our results indicate that the value of the prior, which is determined by the internal model parameters, may be a key contributor to these phenomena. Next, we apply a hierarchical Bayesian approach to update the parameters of the internal model based on the difference between the predicted and the perceived pain, to reflect that people integrate prior experiences in their future expectations. In contrast with simpler approaches, this hierarchical model structure is able to show for placebo hypoalgesia and nocebo hyperalgesia how these phenomena can arise from prior experiences in the form of a classical conditioning procedure. We also demonstrate the phenomenon of offset analgesia, in which a disproportionally large pain decrease is obtained following a minor reduction in noxious stimulus intensity. Finally, we turn to simulations of neuropathic pain, where our hierarchical model corroborates that persistent non-neuropathic pain is a risk factor for developing neuropathic pain following denervation, and additionally offers an interesting prediction that complete absence of informative painful experiences could be a similar risk factor. Taken together, these results provide insight to how prior experiences may contribute to pain perception, in both experimental and neuropathic pain, which in turn might be informative for improving strategies of pain prevention and relief.
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