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Current research topics

A first topic of our current research is focused on the discovery of low-threshold mechanoreceptors with unmyelinated nerve fibres in the hairy skin, so-called C-tactile or CT afferents. Our research has showed that these respond vigorously to pleasant touch, such as slow stroking with a soft brush or with the hand. By correlating afferent activity recorded using microneurography with psychophysical studies, we have recently showed that CT afferents are important for encoding the pleasantness of touch. CT afferents project to the insular cortex of the brain, a region that is important for the sense of temperature or pain, and for emotion and the regulation of the body’s homeostasis. fMRI is done in collaboration with Dr. Göran Starck and colleagues at the Dept. of Radiology, Sahlgrenska University Hospital.

A second research topic is the tactile sense in the finger tips. This work is done in collaboration with a large EU consortium, with robotics research, materials science, experimental psychology, patient studies, bio-engineering, computer modelling, and mathematical data analysis. One aim is to construct artificial touch devices that can mimic the human sense of touch, to be used in advanced robotics or for industrial applications. The first EU project, NANOBIOTACT, was finished in May 2010, and the second project NANOBIOTOUCH was started in January 2010. This project will focus on higher-order or complex tactile experience, such as preference or perceived pleasantness of surfaces and objects.

A third research topic is tactile directional sensibility in perception and postural control, and the related brain mechanisms for processing this kind of tactile information. Tactile directional sensibility is provided both by spatio-temporal information provided by sensory receptors that are successively activated when a stimulus is moving on the skin, but also by patterns of skin stretch provided specifically by the SAII (Ruffini) afferents in the hairy skin. The research group has developed highly sensitive clinical tests on discriminative sensory function, which is now used to detect peripheral neuropathy, for example in diabetic patients.

A fourth topic is the development of new methods to analyze data from functional brain imaging (EEG and fMRI) using Machine Learning and pattern recognition techniques, based on multivariate mathematical methods, including Support Vector Machines or Artificial Neural Nets. These news tools are complementary to standard statistical (univariate) methods, and can provide higher sensitivity or improved resolution. The multivariate techniques may also be used reveal biologically relevant correlated patterns of brain activity, or to detect or discriminate brain states on a single-trial level, even in real time. Using new methods developed by Malin Björnsdotter, we have recently showed that CT afferent input to the posterior insula is somatotopically organized.

Page Manager: Annie Sundling|Last update: 9/1/2015

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