Human-AI Agent Interaction as a Neuroplastic Training Environment

This arXiv preprint argues that the repeated request-result-appraisal-revision loop in AI-agent use may act as a high-frequency neuroplastic training environment. Disappointing outputs could repeatedly trigger impatience, perfectionism, frustration, and self-criticism, potentially reinforcing reactive pathways. The authors propose inserting behind-the-scenes observation before an impulsive re-prompt, framing this as a way to weaken rather than strengthen the response pattern. The framework includes user-guided and agent-assisted modes, illustrated through generative image prompting. The claims are primarily conceptual and should not be read as established clinical or neuroscientific evidence.