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Cross-Modal Multivariate Pattern Analysis
Published on: November 9, 2011
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贝叶斯因果推理计算在盲点上的多感官填充
Ailene Y C Chan1, Noelle R B Stiles1,2, Carmel A Levitan1,3
1California Institute of Technology, Division of Biology and Biological Engineering.
bioRxiv : the preprint server for biology
|December 3, 2025
概括
即使没有盲点的视觉输入,多感官集成仍然存在. 大脑适应感官不确定性,保持核心因果推理计算的感知.
科学领域:
- 神经科学是一个神经科学.
- 认知科学 认知科学
- 心理物理学的精神物理.
背景情况:
- 多感官感知依赖于整合来自不同感官的信息.
- 生理盲点缺乏直接的视网膜输入,这给视觉处理带来了挑战.
- 了解大脑在没有直接感官输入的情况下如何处理信息至关重要.
研究的目的:
- 调查视听集成是否发生在没有在盲点上的自下而上的视觉输入的情况下.
- 为了确定大脑是否调整盲点中的感官不确定性和先验.
- 评估因果推理计算是否保留在盲点中.
主要方法:
- 参与者评价了在盲点和控制位置上呈现的视听幻觉.
- 贝叶斯因果推理 (BCI) 模型被用来分析反应.
- 感官噪音,先验和因果推理策略被估计和比较.
主要成果:
- 视听幻觉在盲点和控制位置都很强大,表明完整的整合得到了保留.
- 贝叶斯因果推理模型揭示了较高的视觉不确定性和更广泛的先前预期在盲点.
- 审计准确度和因果关系先验保持稳定,表明灵活适应.
结论:
- 即使没有视网膜输入,感知推断仍然完好无损.
- 大脑灵活地适应内部感官不确定性,而不是改变核心多感官计算.
- 对因果推理的计算架构在感官剥夺的区域中被保留.
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