Predictive coding in ASD: reduced adaptability of priors to environmental changes

Autor: Zhuanghua Shi, Laura A. Theisinger, Fredrik Allenmark, Rasmus L. Pistorius, Hermann J. Müller, Christine M. Falter-Wagner
Rok vydání: 2022
Popis: Individuals with autism spectrum disorder (ASD) have been widely reported to show atypicalities in predictive coding, though there remains a controversy regarding what causes such atypical processing. Suggestions range from overestimation of volatility to rigidity in the reaction to environmental changes. Here, we tested two accounts directly using duration reproduction of volatile and non-volatile interval sequences, which were generated from the same set of intervals (i.e., the same ensemble prior). We found that both individuals with ASD and matched controls were able to adjust the weight of the ensemble prior for the reproduction according to the volatility of the sequence. However, the ASD group, as compared to the control group, relied generally less on the prior while also exhibiting marked carry-over of the weight of the prior when environmental volatility changes. Of note, though, four extremes among the 32 ASD individuals showed a reproduction pattern on the opposite end of the spectrum: heavy reliance on the prior in the volatile environment. Overall, our findings suggest that it is not the learning of the prior per se that is compromised in ASD. Rather, a less adaptive response to a change of the volatility regimen or to a volatile environment causes a highly inflexible weighting of prediction errors and the prior.
Databáze: OpenAIRE