Generative AI-based closed-loop fMRI system
Mikihiro Kasahara Taiki Oka Vincent Taschereau-Dumouchel Mitsuo Kawato Hiroki Takakura Aurelio Cortese
While generative AI is now widespread and useful in society, there are
potential risks of misuse, e.g., unconsciously influencing cognitive processes
or decision-making. Although this causes a security problem in the cognitive
domain, there has been no research about neural and computational mechanisms
counteracting the impact of malicious generative AI in humans. We propose
DecNefGAN, a novel framework that combines a generative adversarial system and
a neural reinforcement model. More specifically, DecNefGAN bridges human and
generative AI in a closed-loop system, with the AI creating stimuli that induce
specific mental states, thus exerting external control over neural activity.
The objective of the human is the opposite, to compete and reach an orthogonal
mental state. This framework can contribute to elucidating how the human brain
responds to and counteracts the potential influence of generative AI.