Effective Neural Representations for Brain-Mediated Human-Robot Interactions

Buneo, Christopher A.; Tillery, Stephen Helms; Santello, Marco; Santos, Veronica J.; Artemiadis, Panagiotis

doi:10.1007/978-94-017-8932-5_8

Cited by 1 publication

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“…Other studies (Knoblich et al, 2011 ; Candidi et al, 2015 ; Pezzulo et al, 2017 ) of physical interactions have also shown that online sensorimotor communication and adaptation help individuals in aligning their task representations and improving joint action performance. This “co-representation” entails the sharing of internal representations of both the task and mental state of others (Sebanz et al, 2006 ; Knoblich et al, 2011 ; Buneo et al, 2014 ). It is worth mentioning that, to date, the mental and neural representation in physical interaction has not been systematically explored.…”

Section: Introductionmentioning

confidence: 99%

On the Role of Physical Interaction on Performance of Object Manipulation by Dyads

Mojtahedi

Santello

2017

Front. Hum. Neurosci.

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Human physical interactions can be intrapersonal, e.g., manipulating an object bimanually, or interpersonal, e.g., transporting an object with another person. In both cases, one or two agents are required to coordinate their limbs to attain the task goal. We investigated the physical coordination of two hands during an object-balancing task performed either bimanually by one agent or jointly by two agents. The task consisted of a series of static (holding) and dynamic (moving) phases, initiated by auditory cues. We found that task performance of dyads was not affected by different pairings of dominant and non-dominant hands. However, the spatial configuration of the two agents (side-by-side vs. face-to-face) appears to play an important role, such that dyads performed better side-by-side than face-to-face. Furthermore, we demonstrated that only individuals with worse solo performance can benefit from interpersonal coordination through physical couplings, whereas the better individuals do not. The present work extends ongoing investigations on human-human physical interactions by providing new insights about factors that influence dyadic performance. Our findings could potentially impact several areas, including robotic-assisted therapies, sensorimotor learning and human performance augmentation.

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