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Seeking pleasant touch: Neural correlates of behavioral preferences for skin stroking

Journal article
Authors Irene Perini
Håkan Olausson
India Morrison
Published in Frontiers in Behavioral Neuroscience
Volume 9
Issue FEB
ISSN 1662-5153
Publication year 2015
Published at Institute of Neuroscience and Physiology, Department of Physiology
Language en
Links dx.doi.org/10.3389/fnbeh.2015.00008
Keywords Affective touch; CT afferents; FMRI; Interoception; Seeking behavior
Subject categories Neurophysiology

Abstract

Affective touch is a dynamic process. In this fMRI study we investigated affective touch by exploring its effects on overt behavior. Arm and palm skin were stroked with a soft brush at five different velocities (0.3, 1, 10, 3, and 30 cm s(-1)), using a novel feedback-based paradigm. Following stimulation in each trial, participants actively chose whether the caress they would receive in the next trial would be the same speed ("repeat") or different ("change"). Since preferred stroking speeds should be sought with greater frequency than non-preferred speeds, this paradigm provided a measure of such preferences in the form of active choices. The stimulation velocities were implemented with respect to the differential subjective pleasantness ratings they elicit in healthy subjects, with intermediate velocities (1, 10, and 3 cm s(-1)) considered more pleasant than very slow or very fast ones. Such pleasantness ratings linearly correlate with changes in mean firing rates of unmyelinated low-threshold C-tactile (CT) afferent nerves in the skin. Here, gentle, dynamic stimulation optimal for activating CT-afferents not only affected behavioral choices, but engaged brain regions involved in reward-related behavior and decision-making. This was the case for both hairy skin of the arm, where CTs are abundant, and glabrous skin of the palm, where CTs are absent. These findings provide insights on central and behavioral mechanisms underlying the perception of affective touch, and indicate that seeking affective touch involves value-based neural processing that is ultimately reflected in behavioral preferences.

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