ArticleCognitive processing2015
Automatic imitation of the arm kinematic profile in interacting partners.
Article in Cognitive processing, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- The microstructure of intra- and interpersonal coordination.Proceedings. Biological sciences · 2023Article
- Multi-layer adaptation of group coordination in musical ensembles.Scientific reports · 2019Article
- The neural oscillatory markers of phonetic convergence during verbal interaction.Human brain mapping · 2019Article
- Effects of Interpersonal Sensorimotor Synchronization on Dyadic Creativity: Gender Matters.Frontiers in psychology · 2018Article
- Come together: human-avatar on-line interactions boost joint-action performance in apraxic patients.Social cognitive and affective neuroscience · 2017Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cognitive neuroscience, traditionally focused on individual brains, is just beginning to investigate social cognition through realistic interpersonal interaction. However, quantitative investigation of the dynamical sensorimotor communication among interacting individuals in goal-directed ecological tasks is particularly challenging. Here, we recorded upper-body motion capture of 23 dyads, alternating their leader/follower role, in a tower-building task. Either a strategy of joining efforts or a strategy of independent action could in principle be used. We found that arm reach velocity profiles of participants tended to converge across trials. Automatic imitation of low-level motor control parameters demonstrates that the task is achieved through continuous action coordination as opposed to independent action planning. Moreover, the leader produced more consistent and predictable velocity profiles, suggesting an implicit strategy of signaling to the follower. This study serves as a validation of our joint goal-directed non-verbal task for future applications. In fact, the quantification of human-to-human continuous sensorimotor interaction, in a way that can be predicted and controlled, is probably one of the greatest challenges for the future of human-robot interaction.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.