Comparison of the Effects of Interaction with Intentional Agent and Artificial Intelligence using fNIRS

As societal interactions increasingly involve both intentional and unintentional agents, understanding their effects on human cognition becomes paramount. This study investigates the neural correlates of interacting with intentional versus artificial agents in a simulated tennis game scenario. Employing functional near-infrared imaging spectroscopy (fNIRS), we analyzed brain activity in 50 male participants during gameplay against both types of opponents. Our methodological approach ensures ecological validity by simulating real-world decision-making scenarios while participants undergo fNIRS scanning, avoiding the constraints of traditional neuroimaging methods. We focus on six prefrontal cortex channels, leveraging the 10-20 system, to capture nuanced differences in brain activity. Utilizing wavelet analysis, we dissected the data into frequency-specific differences, revealing subtle variations across different channels and frequency bands. Moreover, we quantified activity by comparing average data signals between rest and play modes across all points. Our findings unveil significant differences in neural activation patterns, particularly in one specific channel and frequency range, suggesting distinct cognitive processing when interacting with intentional agents. These results align with previous neuroimaging studies and contribute to understanding the neural underpinnings of human-agent interactions in naturalistic settings. While acknowledging study limitations, including sample homogeneity and spatial accuracy constraints, our findings underscore the potential of fNIRS in exploring complex cognitive phenomena beyond laboratory confines.