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Updated: Feb 28, 2026

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基于Connectome的青少年问题性使用社交媒体的预测:来自ABCD研究的结果

Jennifer J Park¹, Cheryl M Lacadie², Yihong Zhao³

¹Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.

|February 25, 2026

概括

青少年有问题的社交媒体使用与不同的大脑连接模式有关. 这项研究使用机器学习来识别神经网络,预测问题性的社交媒体在青少年中使用严重程度.

科学领域:

神经科学是一个神经科学.
青少年心理学青少年心理学
计算精神病学是一种计算精神病学.

背景情况:

问题性使用社交媒体 (PUSM) 影响35%的青少年,构成重大公共卫生挑战.
关于使用数据驱动方法识别青少年PUSM神经预测因子的研究有限.

研究的目的:

采用基于连接体的预测建模 (CPM) 来预测青少年PUSM严重程度.
确定与PUSM相关的特定全脑功能连接网络.

主要方法:

利用了来自青少年大脑认知发育研究中的2294名青少年 (年龄为10岁) 的休息状态功能磁共振成像 (fMRI) 数据.
应用CPM与基线fMRI数据和四年后续PUSM得分的10倍交叉验证.
分析了大规模神经网络内部和之间功能连接.

主要成果:

在青少年中,CPM成功预测了PUSM得分.
确定了两种预测PUSM严重性的关键系统:一种认知控制/自我调节系统 (默认模式,前双面,中间前部网络) 和一种感知运动集成系统 (视觉区域1,感知运动网络).

结论:

这些发现为青少年对PUSM的脆弱性提供了机制性的见解.
识别的神经网络为个性化干预和未来研究提供了潜在的目标.
结果强调了认知控制和感官运动集成在PUSM中的重要性.

关键词:

让人上的行为成行为青少年青少年青少年强迫性行为强迫性行为.功能性磁共振成像技术功能性磁共振成像技术互联网成互联网成社交媒体社交媒体

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