arXiv:2604.08594q-bio.NCcs.AI2026-04被引 1

不同使用方式的AI对大脑和心理影响迥异,学习用更益智,情感依赖则易引发焦虑。

Mapping generative AI use in the human brain: divergent neural, academic, and mental health profiles of functional versus socio emotional AI use

  • 按用途分三类:通用型、功能型、情感型,分别对应不同脑区变化
  • 频繁用AI学习者成绩更好,前额叶和海马体结构更大,网络效率更高
  • 情感依赖型使用者抑郁焦虑更严重,颞上回和杏仁核体积更小

大学生广泛使用生成式人工智能对话代理(AICAs)构成了新型认知社交环境,其对发育中大脑的影响尚不明确。结合问卷调查与高分辨率结构磁共振成像,我们在222名年轻个体中研究了通用、功能性和情感性AICA使用模式,以及学业表现、心理健康与脑结构特征的关系。计算解剖学、元分析网络层次和行为解码分析均显示使用方式特异性关联:更高的通用与功能性使用频率与更好的学业成绩(GPA)、更大的背外侧前额叶皮层和枕叶灰质体积、更强的海马网络聚类与局部效率相关;而更频繁的情感性使用则与更差的心理健康状况(抑郁、社交焦虑)及更小的颞上回和杏仁核体积相关。结果表明,同一类AI工具因使用动机不同,会激活支持认知的前额叶-海马系统或反映压力的社交情绪系统。这些差异对设计既能发挥教育优势又能降低心理风险的AI环境至关重要。

原文摘要 · Abstract (English)

The widespread adoption of generative artificial intelligence conversational agents (AICAs) among university students constitutes a novel cognitive social environment whose impact on the maturing brain remains elusive. Combining surveys with high resolution structural MRI, we examined patterns of general, functional, and socio emotional AICA use, academic performance, mental health, and brain structural signatures in a comparatively large sample of 222 young individuals. Across computational anatomy, meta analytic network level, and behavioral decoding analyses, we observed use specific associations. Higher general and functional AICA use frequencies were linked to better academic outcomes (GPA), larger dorsolateral prefrontal and calcarine gray matter volume, and enhanced hippocampal network clustering and local efficiency. In contrast, more frequent socio emotional AICA use was associated with poorer mental health (depression, social anxiety) and lower volume of superior temporal and amygdalar regions central to social and affective processing. These findings indicate that the same class of AI tools exerts distinct effects depending on usage patterns and motivations, engaging prefrontal hippocampal systems that support cognition versus socio emotional systems that may track distress linked usage. These heterogeneities are crucial for designing environments that harness the educational benefits of AI while mitigating mental health risks.

生成式AI脑科学心理健康认知神经

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