Search

Contains fulltext : 235019.pdf (Publisher’s version ) (Open Access) Predictive Processing accounts of autism claim that autistic individuals assign higher precision to their prediction errors than non-autistic individuals, that is, autistic individuals update their predictions more readily when faced with unexpected sensory input. Since setting the level of precision is a fundamental part of perception and learning, we propose that such differences should be detectable in various domains at a very early age, before clinical symptoms have fully emerged. We therefore tested 3-year-old younger siblings of autistic children, with a high likelihood of later receiving an autism diagnosis themselves, and low-likelihood children with an older sibling without autism. We used a novel implicit learning paradigm to examine the effect of sensory noise on the predictions participants built. In order to learn a sequence, our participants had to select which visual information to attend to and disregard low-level prediction errors caused by the sensory noise, which the theory claims is more difficult for autistic individuals. Contrary to the proposed higher precision-weighting of prediction errors in autism, the high-likelihood children did not show signs of updating their predictions more readily when we added sensory noise compared to the low-likelihood children, either in their reaction times or in the recurrence and determinism of their response locations. These results raise challenges for Predictive Processing theories of autism, specifically for the notion that prediction errors are inflexibly highly weighted by individuals with autism. 11 p.

Predictive processing accounts of autism posit that individuals with autism rely less on expectations than those without autism when it comes to interpreting incoming sensory information. Since these expectations are claimed to underlie all information processing, we reason that any differences in how they are formed or adjusted should be persistent across multiple cognitive domains and detectable much earlier than clinicians can currently diagnose autism, around 3 years of age. This experiment is part of a longitudinal prospective study of young children with increased familial likelihood of autism. Around 20% of these children will receive an autism diagnosis, compared to 1% of the general population. The current electroencephalography study used an adaptation paradigm to investigate whether a reduced effect of expectations is already present in high-likelihood 2-year-olds, before autism can reliably be diagnosed. While we did not observe the adaptation aftereffect we expected, high-likelihood children habituated more than low-likelihood children, and the two groups did not differ in their overall responses to the manipulation, contrary to our hypotheses and previous findings. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Contains fulltext : 232366.pdf (Publisher’s version ) (Open Access) Most theoretical accounts of autism posit difficulties in predicting others' actions, and this difficulty has been proposed to be at the root of autistic individuals’ social communication differences. Empirical results are mixed, however, with autistic individuals showing reduced action prediction in some studies but not in others. It has recently been proposed that this effect might be observed primarily when observed actions are less predictable, but this idea has yet to be tested. To assess the influence of predictability on neural and behavioural action prediction, the current study employed an action observation paradigm with multi-step actions that become gradually more predictable. Autistic and non-autistic adolescents showed similar patterns of motor system activation during observation, as seen in attenuated mu and beta power compared to baseline, with beta power further modulated by predictability in both groups. Bayesian statistics confirmed that action predictability influenced beta power similarly in both groups. The groups also made similar behavioural predictions, as seen in three eye-movement measures. We found no evidence that autistic adolescents responded differently than non-autistic adolescents to the predictability of an observed action. These findings show that autistic adolescents do spontaneously predict others’ actions, both neurally and behaviourally, which calls into question the role of action prediction as a key mechanism underlying autism. 10 p.

Item does not contain fulltext Recent accounts of autism claim that due to altered predictive processing, autistic individuals cannot always identify signal from noise in sensory input, which leads to models of the world that are overfitted to specific experiences (Manning et al., 2015; van der Cruys et al., 2017). According to these accounts, information processing differences should be present at a very young age, even before autism can be reliably diagnosed. Due to the hereditary nature of autism, we can currently study the development of the condition by following younger siblings of autistic children. Here, we examined whether these younger siblings have difficulty in distinguishing signal from noise, by manipulating sensory noise in a touchscreen Serial Reaction Time Task (SRTT). In the task, a picture of a frog appeared in a sequence (see Figure 1), and the children were asked to press the frog. In block 1, the sequence was identical on every repetition, while in block 3, the frog's exact location included random jitter; it was possible to learn which lilypad the frog would appear on next, but not precisely where on the lilypad it would appear. According to Predictive Processing accounts of autism, high-risk siblings should show difficulty separating signal from noise, and should thus learn the pattern slower in the block with added jitter. This should be especially pronounced in the children who receive an autism diagnosis themselves. Data collection is ongoing, but so far the results suggest that high-risk children (N=12) do in fact learn the pattern when there is additional noise added to the signal. This is contrary to previous findings (Manning et al., 2015; van der Cruys et al., 2017) and raises questions around when autistic children’s performance is and is not influenced by noise in the signal. 1 p.