Mutual gaze with a robot affects human neural activity and delays decision-making processes

In most everyday life situations, the brain needs to engage not only in making decisions but also in anticipating and predicting the behavior of others. In such contexts, gaze can be highly informative about others’ intentions, goals, and upcoming decisions. Here, we investigated whether a humanoid...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Science robotics 2021-09, Vol.6 (58), p.eabc5044-eabc5044
Hauptverfasser: Belkaid, Marwen, Kompatsiari, Kyveli, De Tommaso, Davide, Zablith, Ingrid, Wykowska, Agnieszka
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:In most everyday life situations, the brain needs to engage not only in making decisions but also in anticipating and predicting the behavior of others. In such contexts, gaze can be highly informative about others’ intentions, goals, and upcoming decisions. Here, we investigated whether a humanoid robot’s gaze (mutual or averted) influences the way people strategically reason in a social decision-making context. Specifically, participants played a strategic game with the robot iCub while we measured their behavior and neural activity by means of electroencephalography (EEG). Participants were slower to respond when iCub established mutual gaze before their decision, relative to averted gaze. This was associated with a higher decision threshold in the drift diffusion model and accompanied by more synchronized EEG alpha activity. In addition, we found that participants reasoned about the robot’s actions in both conditions. However, those who mostly experienced the averted gaze were more likely to adopt a self-oriented strategy, and their neural activity showed higher sensitivity to outcomes. Together, these findings suggest that robot gaze acts as a strong social signal for humans, modulating response times, decision threshold, neural synchronization, as well as choice strategies and sensitivity to outcomes. This has strong implications for all contexts involving human-robot interaction, from robotics to clinical applications.
ISSN:2470-9476
2470-9476
DOI:10.1126/scirobotics.abc5044