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 spectroscopy (fNIRS), brain activity in 50 male participants during gameplay against both types of opponents was analyzed. The used methodological approach ensures ecological validity by simulating real-world decision-making scenarios while participants undergo fNIRS scanning, avoiding the constraints of traditional neuroimaging methods. Six prefrontal cortex channels are focused on, leveraging the 10-20 system, to capture nuanced differences in brain activity. Wavelet analysis was utilized to dissect the data into frequency-specific differences, revealing subtle variations across different channels and frequency bands. Moreover, activity was quantified by comparing average data signals between rest and play modes across all points using Generalized Linear Model (GLM). The 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, the study's findings underscore the potential of fNIRS in exploring complex cognitive phenomena beyond laboratory confines.