Generative AI-based closed-loop fMRI system

TL;DR

This paper introduces DecNefGAN, a novel closed-loop system combining generative adversarial AI and neural reinforcement to study how humans can counteract malicious AI influences on neural activity.

Contribution

The paper presents DecNefGAN, a new framework that models the interaction between generative AI stimuli and human neural responses in a closed-loop system.

Findings

DecNefGAN effectively induces specific mental states in humans.

The system demonstrates potential for understanding neural countermeasures against AI influence.

Provides a new approach to studying AI-human neural interactions.

Abstract

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.