贝叶斯推理模型可以从光流估计中预测注意力对序列依赖的效应
Qi Sun1,2,3,4, Si-Yu Wang1,5, Lin-Zhe Zhan1,6
1Department of Psychology, Zhejiang Normal University, Jinhua, P. R. China.
Journal of vision
|September 13, 2024
概括
注意力影响方向估计从光学流. 减少注意力会降低准确性,并改变序列依赖性,显示出贝叶斯计算机制.
科学领域:
- 认知神经科学 认知神经科学
- 视觉感知 视觉感知 视觉感知
背景情况:
- 观察者从光流中准确地估计了自动运动方向 (方向).
- 注意力影响标题估计,但其对序列依赖的影响尚不清楚.
研究的目的:
- 为了研究注意力如何影响从光流中方向估计的序列依赖.
- 探索底层的贝叶斯计算机制.
主要方法:
- 进行了两项涉及标题估计任务的实验.
- 开发了一个贝叶斯推理模型,具有注意调制的概率.
主要成果:
- 随着注意力资源的减少,估计准确性下降.
- 观察到连续依赖,当前估计偏向于之前的标题.
- 对以前或当前刺激的注意分配调节了序列依赖的强度.
结论:
- 注意力在标题估计中显著影响着序列依赖.
- 这些发现揭示了一种贝叶斯计算机制,用于以注意力影响的标题估计.
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