ERP markers of action planning and outcome monitoring in human – robot interaction

Hinz, Nina-Alisa; Ciardo, Francesca; Wykowska, Agnieszka

doi:10.1016/j.actpsy.2020.103216

Cited by 14 publications

(9 citation statements)

References 45 publications

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“…As a consequence, they experience reduced SoA (Beyer et al, 2017;see also Vastano, Ambrosini, Ulloa, & Brass, 2020). Interestingly, the model has received support from recent evidence demonstrating that, at the electrophysiological level, being engaged in a joint task with the Cozmo robot reduces both outcome processing and monitoring (Hinz, Ciardo, & Wykowska, 2021), in line with previous findings investigating the effect of the social context when the co-agent was another human (Beyer et al, 2017;.…”

Section: Resultssupporting

confidence: 77%

Intentions with actions: The role of intentionality attribution on the vicarious sense of agency in Human–Robot interaction

Roselli

Ciardo

Wykowska

2021

Quarterly Journal of Experimental Psychology

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Sense of Agency (SoA) is the feeling of control over one’s actions and their consequences. In social contexts, people experience a “vicarious” SoA over other humans’ actions; however, the phenomenon disappears when the other agent is a computer. This study aimed to investigate the factors that determine when humans experience vicarious SoA in Human–Robot Interaction (HRI). To this end, in two experiments, we disentangled two potential contributing factors: (1) the possibility of representing the robot’s actions and (2) the adoption of Intentional Stance towards robots. Participants performed an Intentional Binding (IB) task reporting the time of occurrence for self- or robot-generated actions or sensory outcomes. To assess the role of action representation, the robot either performed a physical keypress (Experiment 1) or “acted” by sending a command via Bluetooth (Experiment 2). Before the experiment, attribution of intentionality to the robot was assessed. Results showed that when participants judged the occurrence of the action, vicarious SoA was predicted by the degree of attributed intentionality, but only when the robot’s action was physical. Conversely, digital actions elicited the reversed effect of vicarious IB, suggesting that disembodied actions of robots are perceived as non-intentional. When participants judged the occurrence of the sensory outcome, vicarious SoA emerged only when the causing action was physical. Notably, intentionality attribution predicted vicarious SoA for sensory outcomes independently of the nature of the causing event, physical or digital. In conclusion, both intentionality attribution and action representation play a crucial role for vicarious SoA in HRI.

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Section: Resultssupporting

confidence: 77%

Intentions with actions: The role of intentionality attribution on the vicarious sense of agency in Human–Robot interaction

Roselli

Ciardo

Wykowska

2021

Quarterly Journal of Experimental Psychology

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“…Therefore, we suggest that the neural activation we observe in our study resembles classic components. Our finding that robotic partners modulate action monitoring corroborates recent study (Hinz et al, 2021 ). However, there is a crucial difference between both studies: Participants in Hinz et al ( 2021 ) study performed a task sequentially (turn-taking), while in our study, participants interacted with each other in real-life.…”

Section: Discussionsupporting

confidence: 93%

Coordinating With a Robot Partner Affects Neural Processing Related to Action Monitoring

et al. 2021

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Robots start to play a role in our social landscape, and they are progressively becoming responsive, both physically and socially. It begs the question of how humans react to and interact with robots in a coordinated manner and what the neural underpinnings of such behavior are. This exploratory study aims to understand the differences in human-human and human-robot interactions at a behavioral level and from a neurophysiological perspective. For this purpose, we adapted a collaborative dynamical paradigm from the literature. We asked 12 participants to hold two corners of a tablet while collaboratively guiding a ball around a circular track either with another participant or a robot. In irregular intervals, the ball was perturbed outward creating an artificial error in the behavior, which required corrective measures to return to the circular track again. Concurrently, we recorded electroencephalography (EEG). In the behavioral data, we found an increased velocity and positional error of the ball from the track in the human-human condition vs. human-robot condition. For the EEG data, we computed event-related potentials. We found a significant difference between human and robot partners driven by significant clusters at fronto-central electrodes. The amplitudes were stronger with a robot partner, suggesting a different neural processing. All in all, our exploratory study suggests that coordinating with robots affects action monitoring related processing. In the investigated paradigm, human participants treat errors during human-robot interaction differently from those made during interactions with other humans. These results can improve communication between humans and robot with the use of neural activity in real-time.

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“…Importantly, our results do not only resemble previous research but contribute with a new finding: robot partners modulate action monitoring. This result is in line with the other EEG study comparing humans with robot partners (50). There is a crucial difference between both studies: Participants in (50) study performed a task sequentially (turn-taking), while in our study, participants interacted with each other in real-life.…”

Section: Discussionsupporting

confidence: 89%

Coordinating With a Robot Partner Affects Action Monitoring Related Neural Processing

Czeszumski

Keshava

König

2021

Preprint

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Robots start to play a role in our social landscape, and they are progressively becoming responsive, both physically and socially. It begs the question of how humans react to and interact with robots in a coordinated manner and what the neural underpinnings of such behavior are. This exploratory study aims to understand the differences in human-human and human-robot interactions at a behavioral level and from a neurophysiological perspective. For this purpose, we adopted a collaborative dynamical paradigm from Hwang et al. (2018). All 16 participants held two corners of a tablet while collaboratively guiding a ball around a circular track either with another participant or a robot. In irregular intervals, the ball was perturbed outward creating an artificial error in the behavior, which required corrective measures to return to the circular track again. Concurrently, we recorded electroencephalography (EEG). In the behavioral data, we found an increased velocity and positional error of the ball from the track in the human-human condition vs. human-robot condition. For the EEG data, we computed event-related potentials. To explore the temporal and spatial differences in the two conditions, we used time-regression with overlap-control and corrected for multiple-comparisons using Threshold-Free-Cluster Enhancement. We found a significant difference between human and robot partners driven by significant clusters at fronto-central electrodes. The amplitudes were stronger with a robot partner, suggesting a different neural processing. All in all, our exploratory study suggests that coordinating with robots affects action monitoring related processing. In the investigated paradigm, human participants treat errors during human-robot interaction differently from those made during interactions withother humans.

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ERP markers of action planning and outcome monitoring in human – robot interaction

Cited by 14 publications

References 45 publications

Intentions with actions: The role of intentionality attribution on the vicarious sense of agency in Human–Robot interaction

Intentions with actions: The role of intentionality attribution on the vicarious sense of agency in Human–Robot interaction

Coordinating With a Robot Partner Affects Neural Processing Related to Action Monitoring

Coordinating With a Robot Partner Affects Action Monitoring Related Neural Processing

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