Filingeri Davide, Fournet Damien, Hodder Simon, Havenith George
Environmental Ergonomics Research Centre, Loughborough Design School, Loughborough University, Loughborough, United Kingdom; and.
Thermal Sciences Laboratory, Oxylane Research, Villeneuve d'Ascq, France.
J Neurophysiol. 2014 Sep 15;112(6):1457-69. doi: 10.1152/jn.00120.2014. Epub 2014 Jun 18.
Although the ability to sense skin wetness and humidity is critical for behavioral and autonomic adaptations, humans are not provided with specific skin receptors for sensing wetness. It has been proposed that we "learn" to perceive the wetness experienced when the skin is in contact with a wet surface or when sweat is produced through a multisensory integration of thermal and tactile inputs generated by the interaction between skin and moisture. However, the individual roles of thermal and tactile cues and how these are integrated peripherally and centrally by our nervous system is still poorly understood. Here we tested the hypothesis that the central integration of coldness and mechanosensation, as subserved by peripheral A-nerve afferents, might be the primary neural process underpinning human wetness sensitivity. During a quantitative sensory test, we found that individuals perceived warm-wet and neutral-wet stimuli as significantly less wet than cold-wet stimuli, although these were characterized by the same moisture content. Also, when cutaneous cold and tactile sensitivity was diminished by a selective reduction in the activity of A-nerve afferents, wetness perception was significantly reduced. Based on a concept of perceptual learning and Bayesian perceptual inference, we developed the first neurophysiological model of cutaneous wetness sensitivity centered on the multisensory integration of cold-sensitive and mechanosensitive skin afferents. Our results provide evidence for the existence of a specific information processing model that underpins the neural representation of a typical wet stimulus. These findings contribute to explaining how humans sense warm, neutral, and cold skin wetness.
尽管感知皮肤湿度和潮湿的能力对于行为和自主适应至关重要,但人类并没有专门用于感知潮湿的皮肤感受器。有人提出,我们通过皮肤与潮湿表面接触或出汗时产生的热觉和触觉输入的多感官整合来“学习”感知所经历的潮湿。然而,热觉和触觉线索的个体作用以及我们的神经系统如何在周围和中枢对这些线索进行整合,目前仍知之甚少。在这里,我们测试了一个假设,即由外周A神经传入纤维介导的冷觉和机械感觉的中枢整合可能是人类潮湿敏感性的主要神经过程。在定量感觉测试中,我们发现,尽管暖湿和中性湿刺激的水分含量相同,但个体感觉它们比冷湿刺激的潮湿程度要低得多。此外,当通过选择性降低A神经传入纤维的活动来减弱皮肤冷觉和触觉敏感性时,潮湿感知会显著降低。基于感知学习和贝叶斯感知推理的概念,我们开发了第一个以冷敏和机械敏皮肤传入纤维的多感官整合为核心的皮肤潮湿敏感性神经生理学模型。我们的结果为存在一种特定的信息处理模型提供了证据,该模型是典型湿刺激神经表征的基础。这些发现有助于解释人类如何感知温暖、中性和寒冷的皮肤潮湿。