AI Interactions Shape Brain: A Neuroplastic Training Environment.

Everyday interactions with AI tools, from chatbots to image generators, involve a rapid cycle of requests and responses. This paper argues that this frequent contact creates a neuroplastic training environment. When AI outputs are disappointing, users often experience repeated cycles of frustration, impatience, or self-criticism. These repeated emotional responses, if uninterrupted, can inadvertently strengthen negative neural pathways through long-term potentiation. The research proposes a counter-approach: instead of immediately revising a prompt when dissatisfied, users can engage in "behind-the-scenes observation." This involves consciously noticing the pre-cognitive feeling tone that arises, creating a brief regulatory gap. By observing this neural process without completing the reactive cascade, the aim is to weaken the undesirable pathways through long-term depression. The framework outlines three layers of observation and two application modes: a user-guided mode requiring no tool changes, and an agent-assisted mode where AI is lightly configured to support this observation.