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Natural exploration of textures involves active sensing, i.e., voluntary movements of tactile sensors (e.g., human fingertips or rodent whiskers) across a target surface. Somatosensory input during moving tactile sensors varies according to both the movement and the surface texture. Combining motor and sensory information, the brain is capable of extracting textural features of the explored surface. Despite the ecological relevance of active sensing, psychophysical studies on active touch are largely missing. One reason for the lack of informative studies investigating active touch is the considerable challenge of assembling an appropriate experimental setup. A possible solution might be in the realm of virtual tactile reality that provides tactile finger stimulation depending on the position of the hand and the simulated texture of a target surface. In addition to rigorous behavioral studies, the investigation of the neuronal mechanisms of active tactile sensing in humans is highly warranted, requiring neurophysiological experiments using electroencephalography (EEG), magnetoencephalography (MEG) and/or functional magnetic resonance imaging (fMRI). However, current neuroimaging techniques impose specific requirements on the tactile stimulus delivery equipment in terms of compatibility with the neurophysiological methods being used. Here, we present a user-friendly, MEG compatible, tactile virtual reality simulator. The simulator consists of a piezo-electric tactile stimulator capable of independently protruding 16 plastic pistons of 1 mm diameter arranged in a 4 × 4 matrix. The stimulator delivers a spatial pattern of tactile stimuli to the tip of a finger depending on the position of the finger moving across a 2-dimensional plane. In order to demonstrate the functionality of the tactile virtual reality, we determined participants' detection thresholds in active and passive touch conditions. Thresholds in both conditions were higher than reported in the literature. It could well be that the processing of the piston-related stimulation was masked by the sensory input generated by placing the finger on the scanning probe. More so, the thresholds for both the active and passive tasks did not differ significantly. In further studies, the noise introduced by the stimulator in neuromagnetic recordings was quantified and somatosensory evoked fields for active and passive touch were recorded. Due to the compatibility of the stimulator with neuroimaging techniques such as MEG, and based on the feasibility to record somatosensory-related neuromagnetic brain activity the apparatus has immense potential for the exploration of the neural underpinnings of active tactile perception.
