Tactile spatial attention enhances gamma-band activity in somatosensory cortex and reduces low-frequency activity in parieto-occipital areas.

We investigated the effects of spatial-selective attention on oscillatory neuronal dynamics in a tactile delayed-match-to-sample task. Whole-head magnetoencephalography was recorded in healthy subjects while dot patterns were presented to their index fingers using Braille stimulators. The subjects’ task was to report the reoccurrence of an initially presented sample pattern in a series of up to eight test stimuli that were presented unpredictably to their right or left index finger. Attention was cued to one side (finger) at the beginning of each trial, and subjects performed the task at the attended side, ignoring the unattended side. After stimulation, high-frequency gamma-band activity (60 –95 Hz) in presumed primary somatosensory cortex (S1) was enhanced, whereas alpha- and beta-band activity were suppressed in somatosensory and occipital areas and then rebounded. Interestingly, despite the absence of any visual stimulation, we also found time-locked activation of medial occipital, presumably visual, cortex. Most relevant, spatial tactile attention enhanced stimulus-induced gamma-band activity in brain regions consistent with contralateral S1 and deepened and prolonged the stimulus induced suppression of beta- and alpha-band activity, maximal in parieto-occipital cortex. Additionally, the beta rebound over contralateral sensorimotor areas was suppressed. Wehypothesize that spatial-selective attention enhances the saliency of sensory representations by synchronizing neuronal responses in early somatosensory cortex and thereby enhancing their impact on downstream areas and facilitating interareal processing. Furthermore, processing of tactile patterns also seems to recruit visual cortex and this even more so for attended compared with unattended stimuli

Tele-operated high speed anthropomorphic dextrous hands with object shape and texture identification

This paper reports on the development of two number of robotic hands have been developed which focus on tele-operated high speed anthropomorphic dextrous robotic hands. The aim of developing these hands was to achieve a system that seamlessly interfaced between humans and robots. To provide sensory feedback, to a remote operator tactile sensors were developed to be mounted on the robotic hands. Two systems were developed, the first, being a skin sensor capable of shape reconstruction placed on the palm of the hand to feed back the shape of objects grasped and the second is a highly sensitive tactile array for surface texture identification

Active End-Effector Pose Selection for Tactile Object Recognition through Monte Carlo Tree Search

This paper considers the problem of active object recognition using touch only. The focus is on adaptively selecting a sequence of wrist poses that achieves accurate recognition by enclosure grasps. It seeks to minimize the number of touches and maximize recognition confidence. The actions are formulated as wrist poses relative to each other, making the algorithm independent of absolute workspace coordinates. The optimal sequence is approximated by Monte Carlo tree search. We demonstrate results in a physics engine and on a real robot. In the physics engine, most object instances were recognized in at most 16 grasps. On a real robot, our method recognized objects in 2--9 grasps and outperformed a greedy baseline.Comment: Accepted to International Conference on Intelligent Robots and Systems (IROS) 201