AI+瞳孔监测自动干预，减少创伤后闪回记忆
AI-guided digital intervention with physiological monitoring reduces intrusive memories after experimental trauma
- 用AI引导结合瞳孔测量，自动执行心理干预
- 100人实验显示干预组闪回记忆减少显著
- 瞳孔变化可预测效果，适合大规模推广
全球创伤发生率极高。现有数字治疗虽有效，但大多需人工指导，限制可扩展性。能否用生成式AI与神经技术替代？本研究测试了ANTIDOTE系统，结合AI引导与瞳孔测量，自动实施基于证据的影像竞争任务干预（ICTI），以减少心理创伤后的侵入性记忆。100名健康志愿者观看创伤视频后随机分至干预组或对照组。结果表明，干预组在随后一周内报告的侵入性记忆显著减少。事后评估确认AI成功执行干预。此外，瞳孔大小反映了参与度并预测症状改善，提示其可能作为疗效生物标志物。这些发现为可扩展的严格AI驱动数字干预开辟了道路。
原文摘要 · Abstract (English)
Trauma prevalence is vast globally. Evidence-based digital treatments can help, but most require human guidance. Human guides provide tailored instructions and responsiveness to internal cognitive states, but limit scalability. Can generative AI and neurotechnology provide a scalable alternative? Here we test ANTIDOTE, combining AI guidance and pupillometry to automatically deliver and monitor an evidence-based digital treatment, specifically the Imagery Competing Task Intervention (ICTI), to reduce intrusive memories after psychological trauma. One hundred healthy volunteers were exposed to videos of traumatic events and randomly assigned to an intervention or active control condition. As predicted, intervention participants reported significantly fewer intrusive memories over the following week. Post-hoc assessment against clinical rubrics confirmed the AI guide delivered the intervention successfully. Additionally, pupil size tracked intervention engagement and predicted symptom reduction, providing a candidate biomarker of intervention effectiveness. These findings open a path toward rigorous AI-guided digital interventions that can scale to trauma prevalence.
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