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面部年龄处理的三阶段神经认知模型:ERP,振荡动力学和功能连接的证据

Wenjuan Xing¹, Kepan Gao², Yuejia Luo³

¹College of Education for the Future, Beijing Normal University, Zhuhai 519087, China; School of Economics and Management, School of Chemistry and Chemical Engineering, Qilu Normal University, Jinan 250000, China.

|February 15, 2026

概括

大脑通过三个阶段处理面部年龄:初始的全球编码,局部原型匹配,以及以后的情感评估. 这揭示了面部年龄感知背后的神经认知机制.

科学领域:

神经科学是一个神经科学.
认知心理学认知心理学
社会认知是指社会认知.

背景情况:

面部年龄是一个关键的社会线索,影响人们的看法.
面部年龄处理的潜在神经认知机制尚未完全理解.

研究的目的:

提出和验证面部年龄处理的三阶段模型:结构编码,原型匹配和情感评估.
通过使用脑电图 (EEG) 来研究面部年龄感知的神经动力学.

主要方法:

在对四个年龄组 (10,30,50,70岁) 的面部进行年龄判断时进行EEG记录.
结合ERP (基于组件和质量不变),时间频率和功能连接分析.
分析特定的时间波段和频率功率 (乙,α) 在头和头-头传感器上.

主要成果:

观察到特定阶段的ERP效应:较老的面部引起了更大的N170,减少了P2,并增强了晚期积极潜力 (LPP).
早期的面部年龄编码 (∼100-200 ms) 涉及全球的theta/alpha阶段基于连接.
原型匹配 (∼200-300 ms) 显示局部的甲基活性,转向由LPP调制索引的情感评估 (>300 ms).

结论:

面部年龄的处理从早期的全球协调转向以后的局部处理.
这些发现提供了关于大脑如何从面部提取年龄信息的机械解释.
这种三阶段模型阐明了年龄感知及其社会影响的神经认知基础.

关键词:

阿尔法阿尔法阿尔法阿尔法阿尔法这是一个EEGEEGEEGEEGEEGEEGEEG.欧洲经济论坛 (ERP) 是一个欧洲经济论坛.面部年龄面部年龄功能连接性的功能连接性.泰达 (Theta) 是一个类型.质量不变分析 (MUA)

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