Human skin does not have receptors that sense wetness, so researchers looked into what is causing the "illusion."
The findings suggest the concept of "wetness" may simply be a perception our brain evokes based on previous stimuli we learned was associated with moisture, the American Physiological Society (APS) reported.
So how would a person know something was wet if they weren't expecting it to be? Researchers at Loughborough University and Oxylane Research proposed wetness perception is also based on factors such as temperature, pressure, and texture.
The team also hypothesized that, since hairy skin is more sensitive to thermal stimuli, it would be more perceptive to wetness than areas of the body such as the palms of the hands.
To make their findings the researchers exposed 13 healthy male college students to "warm, neutral and cold wet stimuli." They tested different parts of the participants' bodies such as the hairy forearms and bald fingertips. The tests were also performed both with and without a nerve block. The nerve block was achieved using an inflatable compression to cut off blood circulation to the A-nerve, which is believed to carry tactile information from the skin to the brain.
The researchers found wetness perception increased as temperature decreased, meaning cold and damp stimuli were easier to sense than warm. They also found sensitivity to moisture decreased when the A-nerve was blocked and hairier skin was also more perceptive to moisture.
"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," the research team wrote. "Our results provide evidence for the existence of a specific information processing model that underpins the neural representation of a typical wet stimulus."
The article "Whys wet feels wet? A neurophysiological model of human cutaneous wetness sensitivity" is published in the Journal of Neurophysiology.
