从视觉上直接感知情感价值
Saeedeh Sadeghi1,2, Zijin Gu3, Eve De Rosa4
1Department of Psychology, Cornell University, Ithaca, NY, USA. sdsd@caltech.edu.
Nature communications
|December 31, 2024
概括
感觉可以直接从视觉环境统计数据中解码. 一个机器学习模型表明,客观的图像属性,而不仅仅是含义,有助于主观的价值感知.
科学领域:
- 认知神经科学 认知神经科学
- 计算机视觉 计算机视觉
- 心理学 心理学 心理学
背景情况:
- 主观的感觉 (价值) 传统上与概念和身体状态有关.
- 客观视觉环境统计在塑造情感价值的作用是不太了解的.
研究的目的:
- 调查感觉的价值是否可以直接从视觉环境的客观生态统计数据中解码.
- 探索视觉价值 (VV) 对主观情感体验的贡献.
主要方法:
- 训练了一个机器学习模型 (VV模型) 从情感充满的照片中对低级图像统计进行训练.
- 在人类价值评级和抽象绘画上测试了VV模型的预测准确性.
- 检查了人类观察者与没有概念图像分析的价值体验.
- 在视觉大脑区域使用深度生成网络研究了VV的神经基础.
主要成果:
- VV模型准确地预测了人类的价值评级,并对抽象艺术进行了强有力的概括.
- 在人类中限制概念分析增加了VV对价值体验的影响,与机器感知保持一致.
- 低至中级视觉区域的神经活动与VV相关.
- 在生成网络中合成的图像反映了正向和负向VV.
结论:
- 主观价值体验至少有两种不同的模式:一种是间接的 (基于意义) 和一种是直接的 (基于生态统计).
- 视觉环境中的生态统计数据可以直接被视为一个客观的属性,有助于主观的价值.
- 这表明,在视觉输入中嵌入了情感价值的直接感知途径.
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