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Pavalkyte, V.

Publications and source records attributed to Pavalkyte, V..

2 recordsLinked to original sources

Motor Learning Outside the Body: Broad Skill Generalisation with an Extra Robotic Limb

Our ability to transfer motor skills across tools and contexts is what makes modern technology usable. The success of motor augmentation devices, such as supernumerary robotic limbs, hinges on users capacity for generalised motor performance. We trained participants over seven days to use an extra robotic thumb (Third Thumb, Dani Clode Design), worn on the right hand and controlled via the toes. We tested whether motor learning was confined to the specific tasks and body parts involved in controlling and interacting with the Third Thumb, or whether it could generalise beyond them. Participants showed broad skill generalisation across tasks, body postures, and even when either the Third Thumb or the controller was reassigned to a different body part, suggesting the development of abstract, body-independent motor representations. Training also reduced cognitive demands and increased the sense of agency over the device. However, participants still preferred using their biological hand over the Third Thumb when given the option, suggesting that factors beyond motor skill generalisation, cognitive effort, and embodiment must be addressed to support the real-world adoption of such technologies.

neuroscience↗

Developing a Sensory Representation of an Artificial Body Part

Somatosensory feedback is essential for motor control, yet artificial limbs are thought to lack such feedback. We investigated how the body and brain gather informative sensory signals from a wearable augmentation interface (a robotic digit for motor augmentation), and whether naturally-mediated feedback can support technological embodiment. Participants intuitively interpreted natural feedback across perceptual tasks, performing comparably to state-of-the-art artificial feedback systems. fMRI revealed an immediate and distinct, topographically-organised representation of the robotic digit. After longitudinal training, this representation was further refined, becoming more similar to the biological digits, which correlated with increased subjective somatosensory embodiment. Our findings demonstrate that wearable devices naturally provide a powerful source of feedback which is immediately integrated with our body. Long-term use can then promote device-embodiment across the sensorimotor hierarchy.

neuroscience↗