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Agency Perception and Brain Synchrony: A Hyperscanning Study of Human-Human and Human-AI Interaction
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This study investigates how the human brain differentiates between intentional human agents and artificial intelligence (AI) agents during real-time social interaction. Using functional near-infrared spectroscopy (fNIRS) hyperscanning, we recorded prefrontal brain activity of participants as they played a one-on-one virtual tennis game, once against a human opponent and once against an AI-controlled opponent. Task-related cortical activation was evaluated using the General Linear Model (GLM), while inter-brain synchrony was assessed through Intersubject Correlation (ISC) analysis. Results revealed significantly stronger activation in the medial prefrontal cortex (mPFC) when participants interacted with human opponents, particularly in low-frequency hemodynamic bands (0.0098-0.0196 Hz). Moreover, neural synchrony between human dyads was significantly greater than in pseudo-paired controls, with distinct frequency-specific coupling patterns across channels. In contrast, AI interactions elicited reduced cortical engagement and no measurable inter-brain synchrony. These findings suggest that the perception of intentionality strongly modulates social brain responses, even when task structure and behavior remain constant. This work highlights the utility of fNIRS hyperscanning for studying naturalistic human interactions and provides neural evidence for the brain's sensitivity to perceived agency. The results have implications for the design of socially interactive AI systems that more effectively engage human cognition.
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Cited by 1 Pith paper
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Real-World fNIRS-Based Brain-Computer Interfaces: Benchmarking Deep Learning and Classical Models in Interactive Gaming
The paper reports high rest/task classification accuracy for fNIRS during a tennis game, but asymmetric augmentation of the rest class confounds the benchmark.
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