Neural Correlates of Perceiving Animacy in Robotic Objects
Authors/Creators
- 1. The Baruch Ivcher Institute for Brain, Cognition, and Technology, Baruch Ivcher School of Psychology, Reichman University
- 2. Max Planck Institute for Human Development, Research Group Adaptive Memory and Decision Making, Germany
- 3. Computational Psychiatry and Neurotechnology Lab, Department of Brain and Cognitive Sciences, Ben Gurion University
- 4. Proaction Laboratory, Faculty of Psychology and Educational Sciences, University of Coimbra
- 5. Digital Media Lab, Department of Mathematics and Computer Science, University of Bremen
- 6. Media Innovation Lab, Sammy Ofer School of Communications, Reichman University
- 7. Advanced Reality Lab, Sammy Ofer School of Communications, Reichman University
Description
The prevalence of robots in modern society calls for gaining a fundamental understanding of the underlying principles of human-robot interaction. In particular, we need to understand how people perceive robots and how different physical and social characteristics affect this perception. Here, we examined the neural correlates of observing simple gestures performed by a non-humanoid social robot, focusing on the role of the Ventral Occipitotemporal (VOT) cortex in processing perceived animacy. Our results reveal that a broad bilateral cortical network is activated, comprising areas related to action observation, the social brain, and the visual cortex, including the VOT. We also found a correlation between the level of neural responses in the VOT, especially in the left hemisphere, and individual animacy ratings of the robotic object. This correlation provides a physical basis for such subjective ratings. These results suggest a complex representation of perceived animacy across the lateral-medial axis of the VOT, explained by spatial cortical location and the amplitude of neural responses. Furthermore, we discuss the implications of these findings for understanding how people perceive robots, their behaviors and intentions, which are crucial for developing social robots that can interact with humans more naturally.
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