在深度神经网络中由Skye的斜格网产生的类似大脑的幻觉
Hongtao Zhang1, Shinichi Yoshida2, Zhen Li3,4
1Graduate School of Engineering, Kochi University of Technology, Kami, Kochi, Japan.
PloS one
|February 23, 2024
概括
深度神经网络 (DNN) 对视觉幻觉表现出类似人类的反应,表明它们作为大脑机制模型的潜力. 代表性相似性分析揭示了早期DNN层中的类似幻象的表示,反映了早期视觉皮层的处理.
科学领域:
- 计算神经科学是一种神经科学.
- 认知科学 认知科学
- 人工智能的人工智能
背景情况:
- 大脑深层神经网络 (DNN) 类比是神经科学越来越感兴趣的领域.
- 尽管存在局限性,但DNN为模拟特定大脑功能提供了有价值的框架.
- 视觉错觉为人类视觉处理机制提供了一个独特的窗口.
研究的目的:
- 研究DNN在模拟人类视觉错觉中的相关性.
- 为了比较人类对DNN的感知反应对Skye的斜格子幻象的反应.
- 探索DNN不同层中的幻象表示.
主要方法:
- 收集了人类对视觉错觉的感知数据.
- 训练有素的DNN用于虚幻和非虚幻图像的水平与非水平分类.
- 在DNN层上进行了表示相似性分析,以评估幻象表示.
主要成果:
- 在对虚幻图像进行分类时,DNN表现出类似人类的幻觉反应.
- 代表性相似性分析表明DNN中的幻觉类表示.
- 幻象表现在早期DNN层中最强,随着深度的增加而下降.
结论:
- 作为理解人类大脑中视觉错觉机制的计算模型,DNN显示出了希望.
- 研究结果表明,DNN处理和早期视觉区域 (如V1.1) 之间存在潜在的并行关系.
- 需要进一步的研究来阐明DNN与人类视觉通路之间的准确关系和差异.
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