Disentangling signal and noise in autism spectrum disorder

Predictive coding has recently been welcomed as a fruitful framework to understand autism spectrum disorder. Starting from an account centered on deficient differential weighting of prediction errors (based in so-called precision estimation), we illustrate that individuals with autism have particular difficulties with separating signal from noise, across different tasks. Specifically, we discuss how deficient precision-setting is detrimental for learning in unstable environments, for context-dependent assignment of salience to inputs, and for robustness in perception, as illustrated in coherent motion paradigms.