文章基本信息

标题：Weak Priors versus Overfitting of Predictions in Autism: Reply to Pellicano and Burr (TICS, 2012)
本地全文：下载
作者：Sander Van de Cruys ; Lee de-Wit ; Kris Evers 等
期刊名称：i-Perception
电子版ISSN：2041-6695
出版年度：2013
卷号：4
期号：2
页码：95-97
DOI：10.1068/i0580ic
出版社：Pion Ltd.
摘要：Pellicano and Burr (2012) argue that a Bayesian framework can help us understand the perceptual peculiarities in autism. We agree, but we think that their assumption of uniformly flat or equivocal priors in autism is not empirically supported. Moreover, we argue that any full account has to take into consideration not only the nature of priors in autism, but also how these priors are constructed or learned. We argue that predictive coding provides a more constrained framework that very naturally explains how priors are constructed in autism leading to strong, but overfitted, and non-generalizable predictions.
关键词：autism ; vision ; perception ; predictive coding ; priors ; Bayes