No abstract

Objective. A major challenge for controlling a prosthetic arm is communication between the device and the user’s phantom limb. We show the ability to enhance phantom limb perception and improve movement decoding through targeted transcutaneous electrical nerve stimulation in individuals with an arm amputation. Approach. Transcutaneous nerve stimulation experiments were performed with four participants with arm amputation to map phantom limb perception. We measured myoelectric signals during phantom hand movements before and after participants received sensory stimulation. Using electroencephalogram (EEG) monitoring, we measured the neural activity in sensorimotor regions during phantom movements and stimulation. In one participant, we also tracked sensory mapping over 2 years and movement decoding performance over 1 year. Main results. Results show improvements in the participants’ ability to perceive and move the phantom hand as a result of sensory stimulation, which leads to improved movement decoding. In the extended study with one participant, we found that sensory mapping remains stable over 2 years. Sensory stimulation improves within-day movement decoding while performance remains stable over 1 year. From the EEG, we observed cortical correlates of sensorimotor integration and increased motor-related neural activity as a result of enhanced phantom limb perception. Significance. This work demonstrates that phantom limb perception influences prosthesis control and can benefit from targeted nerve stimulation. These findings have implications for improving prosthesis usability and function due to a heightened sense of the phantom hand.

No abstract

No abstract

To obtain deeper insights into the tactile processing pathway from a population-level point of view, we have modeled three stages of the tactile pathway from the periphery to the cortex in response to indentation and scanned edge stimuli at different orientations. Three stages in the tactile pathway are, (1) the first-order neurons which innervate the cutaneous mechanoreceptors, (2) the cuneate nucleus in the midbrain and (3) the cortical neurons of the somatosensory area. In the proposed network, the first layer mimics the spiking patterns generated by the primary afferents. These afferents have complex skin receptive fields. In the second layer, the role of lateral inhibition on projection neurons in the cuneate nucleus is investigated. The third layer acts as a biomimetic decoder consisting of pyramidal and cortical interneurons that correspond to heterogeneous receptive fields with excitatory and inhibitory sub-regions on the skin. In this way, the activity of pyramidal neurons is tuned to the specific edge orientations. By modifying afferent receptive field size, it is observed that the larger receptive fields convey more information about edge orientation in the first spikes of cortical neurons when edge orientation stimuli move across the patch of skin. In addition, the proposed spiking neural model can detect edge orientation at any location on the simulated mechanoreceptor grid with high accuracy. The results of this research advance our knowledge about tactile information processing and can be employed in prosthetic and bio-robotic applications.

No abstract

No abstract

No abstract