对象表示驱动情感模式跨越一个大和多样化的日常生活场景集
Chuanji Gao1, Susan Ajith2,3, Marius V Peelen4
1School of Psychology, Nanjing Normal University, Nanjing, China. chuanji.gao@njnu.edu.cn.
Communications biology
|May 5, 2025
概括
视觉对象处理帮助我们理解日常场景中的情绪. 大脑使用物体识别系统来解释情感内容,特别是当场景没有明确的情感时.
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:
- 对日常场景进行快速的情感评估对于人类互动至关重要.
- 视觉场景如何唤起情绪的神经基础尚未完全理解.
- 人们争论的是,情感模式是否依赖于对象处理,还是独立于对象处理.
研究的目的:
- 调查日常生活场景的情感评估是否依赖于对象处理系统.
- 确定在视觉场景中的情感感知背后的神经机制.
- 为了比较基于对象的与基于情感的计算模型的预测能力.
主要方法:
- 收集了来自300名参与者的4913个日常生活场景的情感评分.
- 使用深度神经网络 (AlexNet,EmoNet) 和功能磁共振成像 (fMRI) 来分析场景表示.
- 检查视觉皮层区域的活动模式,包括横向尾综合体 (LOC).
主要成果:
- 基于对象的模型 (AlexNet) 比基于情感的模型 (EmoNet) 更好地预测了一般场景情感评级.
- 在明确引人入胜的场景中,EmoNet的表现更好.
- 在对象识别系统中观察到层次化的情感信息处理.
- 在LOC中的fMRI活动可靠地预测了情绪评级,并且表现优于其他视觉区域.
结论:
- 对日常场景的情感评估主要通过视觉对象处理进行调解.
- 当对象内容对情感解释没有信息时,大脑会启动额外的机制.
- 研究结果支持在视觉系统内对情绪感知进行层次处理的模型.
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