The predictive coding framework in motion and biological motion perception in ASD.

自闭症谱系障碍（ASD）是一种公认对社会功能有影响的发育性疾病。感官信息处理功能障碍最近被认为是一个关键的诊断标准（APA, 2013）。因此，了解自闭症患者如何处理感觉信息是理解和改进治疗方法的关键部分。我们的目标是测试一种重要的新方法来模拟自闭症的感觉和认知处理（Van de Cruys et al., 2014）。这种方法使用预测编码框架来检查期望和内部生成的世界模型之间的不匹配如何导致ASD患者大脑中大量的错误信号。这些错误信号导致功能失调的感觉处理，有可能造成焦虑和感知社会信号的困难。为了在自闭症谱系障碍中测试这一框架，我们将使用行为和脑成像实验，包括观察物体和人类（生物）运动。这将使我们能够研究有或没有社会成分的感觉信息的处理。为这一框架提供支持，将为在整个生命周期中专注于学习和环境丰富的治疗方法作为ASD干预措施提供证据基础。

Autism Spectrum Disorder (ASD) is a developmental condition with recognised impact on social functioning. Dysfunctional processing of sensory information has recently been acknowledged as a key diagnostic criterion (APA, 2013). Hence, understanding how sensory information is processed in autism is a crucial part of understanding and improving the way we treat it.We aim to test an important new approach for modelling sensory and cognitive processing in autism (Van de Cruys et al., 2014). This approach uses a predictive coding framework to examine how mismatches between expectations and internally generated models of the world can lead to an abundance of error signals in the brains of individuals with ASD. These error signals lead to dysfunctional sensory processing that has the potential for creating anxiety and difficulty in perceiving social signals. To test this framework in ASD we will use behavioural and brain imaging experiments that involve observing object and human (biological) motion. This will enable us to investigate the processing of sensory information with and without a social component. Providing support for this framework will provide an evidence base for therapies focusing on learning and environment enrichment throughout the lifespan as interventions in ASD.