探索微价值在现象空间中的作用:来自相似性判断和深度学习模型的见解
Inès Mentec1, Ivan Ivanchei2, Axel Cleeremans1
1Center for Research in Cognition and Neurosciences, Université libre de Bruxelles, Avenue F. Roosevelt, 50 CP 191, 1050 Brussels, Belgium.
Neuroscience of consciousness
|March 2, 2026
概括
价值,经验的情感色调,影响我们如何感知对象相似性. 这项研究表明,即使是最小的价值 (微价值) 也会影响判断,并由深层神经网络处理.
科学领域:
- 认知心理学 认知心理学
- 神经科学是一个神经科学.
- 人工智能的人工智能
背景情况:
- 在有意识的经验中对价值的内在性质是有争议的.
- 假设所有有意识的感知至少具有最小的价值.
- 情感倾向可能会影响相似性判断.
研究的目的:
- 调查价值判断和相似性判断之间的相关性.
- 探索微价值在认知处理中的作用.
- 检查深度神经网络 (DNN) 中的价值相似性关系.
主要方法:
- 149名参与者对120个对象图像提供了价值和相似性判断.
- 使用奇数,空间排列和生日任务.
- 使用表示相似性分析和多维缩放分析了DNN激活.
主要成果:
- 微价值显著影响相似性判断,表明价值透到相似性空间.
- 在DNN中,价值-相似性关系不仅仅是基于感知特征.
- 低级视觉特征有助于在DNN中计算价值.
结论:
- 价值似乎是意识体验的内在维度,影响相似感知.
- 深度神经网络部分模拟了在人类认知中观察到的价值相似关系.
- 需要进一步的研究,以充分阐明低级特征和价值计算之间的相互作用.
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