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Sleep is known to support the neocortical consolidation of declarative memory, including the acquisition of new language. Autism spectrum disorder (ASD) is often characterized by both sleep and language learning difficulties, but few studies have explored a potential connection between the two. Here, 54 children with and without ASD (matched on age, nonverbal ability and vocabulary) were taught nine rare animal names (e.g., pipa). Memory was assessed via definitions, naming and speeded semantic decision tasks immediately after learning (pre‐sleep), the next day (post‐sleep, with a night of polysomnography between pre‐ and post‐sleep tests) and roughly 1 month later (follow‐up). Both groups showed comparable performance at pre‐test and similar levels of overnight change on all tasks; but at follow‐up children with ASD showed significantly greater forgetting of the unique features of the new animals (e.g., pipa is a flat frog). Children with ASD had significantly lower central non‐rapid eye movement (NREM) sigma power. Associations between spindle properties and overnight changes in speeded semantic decisions differed by group. For the TD group, spindle duration predicted overnight changes in responses to novel animals but not familiar animals, reinforcing a role for sleep in the stabilization of new semantic knowledge. For the ASD group, sigma power and spindle duration were associated with improvements in responses to novel and particularly familiar animals, perhaps reflecting more general sleep‐associated improvements in task performance. Plausibly, microstructural sleep atypicalities in children with ASD and differences in how information is prioritized for consolidation may lead to cumulative consolidation difficulties, compromising the quality of newly formed semantic representations in long‐term memory., This polysomnography study examined the sleep‐associated consolidation of words for real but rare animals, in children with and without autism. Children with autism showed increased forgetting of novel features (e.g., an asp is a hairy caterpillar), relative to typical peers, one month after exposure. They also showed reduced sigma power (within the sleep spindle frequency range), and showed more general associations between overnight changes in task performance (for both novel and particularly familiar words) and sleep spindle parameters, in stark contrast to typical peers who showed selective associations between spindles and overnight changes in novel memory traces.

BackgroundThere is growing interest in linking vitamin D deficiency with autism spectrum disorders (ASDs). The association between vitamin D deficiency during gestation, a critical period in neurodevelopment, and ASD is not well understood.AimsTo determine the association between gestational vitamin D status and ASD.MethodBased on a birth cohort (n=4334), we examined the association between 25-hydroxyvitamin D (25OHD), assessed from both maternal mid-gestation sera and neonatal sera, and ASD (defined by clinical records; n=68 cases).ResultsIndividuals in the 25OHD-deficient group at mid-gestation had more than twofold increased risk of ASD (odds ratio (OR)=2.42, 95% confidence interval (CI) 1.09 to 5.07, P=0.03) compared with the sufficient group. The findings persisted in analyses including children of European ethnicity only.ConclusionsMid-gestational vitamin D deficiency was associated with an increased risk of ASD. Because gestational vitamin D deficiency is readily preventable with safe, inexpensive and readily available supplementation, this risk factor warrants closer scrutiny.

Typical adults can track reward probabilities across trials to estimate the volatility of the environment and use this information to modify their learning rate (Behrens et al., 2007). In a stable environment, it is advantageous to take account of outcomes over many trials, whereas in a volatile environment, recent experience should be more strongly weighted than distant experience. Recent predictive coding accounts of autism propose that autistic individuals will demonstrate atypical updating of their behaviour in response to the statistics of the reward environment. To rigorously test this hypothesis, we administered a developmentally appropriate version of Behrens et al.'s (2007) task to 34 cognitively able children on the autism spectrum aged between 6 and 14 years, 32 age‐ and ability‐matched typically developing children and 19 typical adults. Participants were required to choose between a green and a blue pirate chest, each associated with a randomly determined reward value between 0 and 100 points, with a combined total of 100 points. On each trial, the reward was given for one stimulus only. In the stable condition, the ratio of the blue or green response being rewarded was fixed at 75:25. In the volatile condition, the ratio alternated between 80:20 and 20:80 every 20 trials. We estimated the learning rate for each participant by fitting a delta rule model and compared this rate across conditions and groups. All groups increased their learning rate in the volatile condition compared to the stable condition. Unexpectedly, there was no effect of group and no interaction between group and condition. Thus, autistic children used information about the statistics of the reward environment to guide their decisions to a similar extent as typically developing children and adults. These results help constrain predictive coding accounts of autism by demonstrating that autism is not characterized by uniform differences in the weighting of prediction error.

BackgroundThere is a growing interest in using cognitive–behavioural therapy (CBT) with people who have Asperger syndrome and comorbid mental health problems.AimsTo examine whether modified group CBT for clinically significant anxiety in an Asperger syndrome population is feasible and likely to be efficacious.MethodUsing a randomised assessor-blind trial, 52 individuals with Asperger syndrome were randomised into a treatment arm or a waiting-list control arm. After 24 weeks, those in the waiting-list control arm received treatment, while those initially randomised to treatment were followed up for 24 weeks.ResultsThe conversion rate for this trial was high (1.6:1), while attrition was 13%. After 24 weeks, there was no significant difference between those randomised to the treatment arm compared with those randomised to the waiting-list control arm on the primary outcome measure, the Hamilton Rating Scale for Anxiety.ConclusionsTrials of psychological therapies with this population are feasible. Larger definitive trials are now needed.