Learning priors for Bayesian perception in normal and atypical development

为了驾驭环境并与他人互动，人们必须不断地根据不确定的信息做出决定。人类已经被证明以一种与贝叶斯决策理论一致的方式，将当前的感官证据与基于先前经验的期望结合起来。然而，关于如何学习先验，以及在典型和非典型发展中如何学习的基本问题仍然存在。该项目有两个临时目的：(1)表征正常发育儿童和成人贝叶斯先验学习的时间过程和特性(2)验证非典型贝叶斯先验学习是自闭症谱系障碍（ASD）中常见的感知异常的基础这一假设。

To navigate the environment and interact with others, people must constantly form decisions based on uncertain information. Humans have been shown to integrate current sensory evidence with expectations based on prior experience in a manner consistent with Bayesian decision theory. However, fundamental questions remain regarding how priors are learned, and how learning progresses in typical and atypical development.This project has two provisional aims:(1) To characterise the time-course and properties of Bayesian prior learning in normally developing children and adults(2) To test the hypothesis that atypical Bayesian prior learning underlies commonly reported perceptual anomalies in autism spectrum disorder (ASD)