Skin Contact Interactions and Neural Encoding Mechanisms Underlying Social and Affective Touch

Author: ORCID icon
Hauser, Steven, Systems Engineering - School of Engineering and Applied Science, University of Virginia
Gerling, Gregory, EN-Eng Sys and Environment, University of Virginia

Our sense of touch provides an intuitive means of expressing social and emotional sentiment. For example, one might shake the hand of a coworker to show gratitude, or stroke the arm of a romantic partner to express love. When a “toucher” expresses a sentiment by using their hands to physically contact the forearm of a touch “receiver,” populations of thousands of sensory neural afferents in the skin of the receiver respond to this contact in a way that encodes the emotion. However, several steps in this pathway are not yet well understood. In prior efforts, the contact interactions that underlie social touch—i.e., how quickly someone moves their hands, or how they stretch the skin of the touch recipient—have been studied in only a qualitative fashion. Moreover, although certain sensory afferent types are thought to be involved in social touch—such as C-tactile afferents which respond to light, stroking touch—it is not yet clear how these afferents work alongside other mechanosensitive and muscle spindle afferents in encoding emotional percepts. In this work, our goal was to determine how social touch gestures are represented at the outermost level of tactile perception—or, more specifically, how physical contact resulting from emotive human touches might evoke a peripheral response. Towards this end, we employed methods such as motion tracking, psychophysics, and microneurography. First, we ran human-subjects experiments to determine how people naturally perform a set of 6 touch expressions, by employing external motion tracking systems to measure skin-to-skin contact “primitives” such as contact area and velocity of stroking across the arm. We found that the people were naturally good at expressing the touch expressions, with high recognition rates. We also noted several different strategies used to express each emotional word (between 2 and 5), with some being more immediately recognizable. Next, we developed algorithms to measure physical contact in microneurography experiments with simultaneous neural recordings, finding differences in the responses to C-tactile and fast-adapting type II (FA-II) afferents to basic touch gestures. Finally, we measured how a set of A-beta and C-tactile afferents responded to this measured physical contact via microneurography and motion tracking experiments performed with collaborators at Linköping University. We found that the six touch expressions could be differentiated by the firing patterns of a single afferent, namely a hair follicle afferent (HFA) or slowly-adapting type II afferent (SA-II), even amidst significant variability in how the touch gestures were performed. A better understanding of the social and emotional touch pathway could allow us to help those with social deficits to perform proper touch expressions, or create augmented means of communicating or recognizing them.

PHD (Doctor of Philosophy)
haptics, systems engineering, neuroscience, psychophysics, human computer interaction
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