Search for dissertations about: "C-tactile afferents"
Showing result 1 - 5 of 8 swedish dissertations containing the words C-tactile afferents.
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1. Investigations of human cortical processing of gentle touch. A study with time-resolved electro-magnetic signal analysis
Abstract : The present work summarizes investigations of the temporal correlates of brain activity elicited by gentle, moving touch on the hairy skin in healthy participants and in epilepsy patients. Light touch to the hairy skin activates two distinct afferent classes: fast conducting, Aβ afferents and slowly conducting C-tactile (CT) afferents. READ MORE
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2. Affective touch throughout life: from cortical processing in infancy to touch perception in adulthood
Abstract : Affective, interpersonal touch is important for forming and maintaining social bonds. In the hairy skin of humans there is a specific type of nerve fibers called C-tactile (CT) afferents which are optimally activated by a light stroking of the skin, like a caress. READ MORE
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3. The Perception and Evaluation of Pleasant Touch and the Development of "Satiety" for Hedonic Tactile Experiences
Abstract : Pleasant touch is a hedonic experience and one of the most powerful means for social bonding and for communicating affection. Touch similar to a human caress is detected by the “C tactile (CT) afferents”, a class of mechanoreceptors which respond preferentially to stroking velocities between 1 and 10 cm/s. READ MORE
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4. Hedonic, neural, and autonomic responses to prolonged gentle touch
Abstract : Physical contact among individuals, such as caressing and cuddling, is connoted by a strong emotional value, and is usually perceived as a pleasant and rewarding experience. C tactile (CT) afferents are a class of fibres that are specific channels for detecting touch at a caress-like veloc-ity (between 1 and 10 cm/s). READ MORE
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5. Machine learning for identification of brain activity patterns with applications in gentle touch processing
Abstract : Since the first mention of artificial intelligence in the 1950s, the field of machine learning has provided increasingly appealing tools for recognition of otherwise unintelligible pattern representations in complex data structures. Human brain activity, acquired using functional magnetic resonance imaging (fMRI), is a prime example of such complex data where the utility of pattern recognition has been demonstrated in a wide range of studies recently (Haynes et al. READ MORE