论文标题
贝叶斯的时间意识在生物和人造大脑中
Bayesian sense of time in biological and artificial brains
论文作者
论文摘要
关于生物大脑的潜在机制和新兴特性的询问具有悠久的理论假设和实验发现的悠久历史。如今，科学界倾向于对大脑认知基础的单一解释进行融合 - 它是贝叶斯推理机。这种当代观点自然是围绕计算和认知神经科学的最新发展的强大驱动力。特别令人感兴趣的是大脑处理时间流逝的能力，这是我们经验的基本维度之一。我们如何使用贝叶斯大脑假说来解释有关人类时间感知的经验数据？我们可以使用贝叶斯模型复制人类估计偏见吗？基于代理的机器学习模型可以为该主题提供什么见解？在本章中，我们回顾了时间感知领域的一些最新进步，并讨论了贝叶斯处理在时间模型构建中的作用。
Enquiries concerning the underlying mechanisms and the emergent properties of a biological brain have a long history of theoretical postulates and experimental findings. Today, the scientific community tends to converge to a single interpretation of the brain's cognitive underpinnings -- that it is a Bayesian inference machine. This contemporary view has naturally been a strong driving force in recent developments around computational and cognitive neurosciences. Of particular interest is the brain's ability to process the passage of time -- one of the fundamental dimensions of our experience. How can we explain empirical data on human time perception using the Bayesian brain hypothesis? Can we replicate human estimation biases using Bayesian models? What insights can the agent-based machine learning models provide for the study of this subject? In this chapter, we review some of the recent advancements in the field of time perception and discuss the role of Bayesian processing in the construction of temporal models.
