Strengthening risk prediction using statistical learning in children with autism spectrum disorder

Advances in Autism, Ahead of Print. Purpose The purpose of this paper is to investigate the prediction ability in children with ASD in the risk-involving situations and compute the impact of statistical learning (SL) in strengthening their risk knowledge. The learning index and stability with time are also calculated by comparing their performance over three consecutive weekly sessions (session 1, session 2 and session 3). Design/methodology/approach Participants were presented with a series of images, showing simple and complex risk-involving situations, using the psychophysical experimental paradigm. The stimuli in the experiment were provided with different levels of difficulty in order to keep the legacy of the prediction and SL-based experiment intact. Findings The first phase of experimental work showed that children with ASD accurately discriminated the risk, although performed poorly as compared to neurotypical. The attenuated response in differentiating risk levels indicates that children with ASD have a poor and underdeveloped sense of risk. The second phase investigated their capability to extract the information from repetitive patterns and calculated SL stability value in time. The learning curve shows that SL is intact and stable with time (average session r=0.74) in children with ASD. Research limitations/implications The present work concludes that impaired action prediction could possibly be one of the factors underlying underdeveloped sense of risk in ch...
Source: Advances in Autism - Category: Child Development Source Type: research