The relationship between multisensory associative learning and multisensory integration.

Integrating sensory information from multiple modalities leads to more precise and efficient perception and behaviour. The process of determining which sensory information should be perceptually bound is reliant on both low-level stimulus features, as well as multisensory associations learned throughout development based on the statistics of our environment. Here, we explored the relationship between multisensory associative learning and multisensory integration using encephalography (EEG) and behavioural measures. Sixty-one participants completed a three-phase study. First, participants were exposed to novel audiovisual shape-tone pairings with frequent and infrequent stimulus pairings and completed a target detection task. EEG recordings of the mismatch negativity (MMN) and P3 were calculated as neural indices of multisensory associative learning. Next, the same learned stimulus pairs were presented in audiovisual as well as unisensory auditory and visual modalities while both early (<100 ms) and late neural indices of multisensory integration were recorded. Finally, participants completed an analogous behavioural speeded-response task, with behavioural indices of multisensory gain calculated using the Race Model. Significant relationships were found in fronto-central and occipital areas between neural measures of associative learning and both early and late indices of multisensory integration in frontal and centro-parietal areas, respectively. Participants who showed stronger indices of associative learning also exhibited stronger indices of multisensory integration of the stimuli they learned to associate. Furthermore, a significant relationship was found between neural index of early multisensory integration and behavioural indices of multisensory gain. These results provide insight into the neural underpinnings of how higher-order processes such as associative learning guide multisensory integration.

Exploring sensory phenotypes in autism spectrum disorder.

BACKGROUND: Atypical reactions to the sensory environment are often reported in autistic individuals, with a high degree of variability across the sensory modalities. These sensory differences have been shown to promote challenging behaviours and distress in autistic individuals and are predictive of other functions including motor, social, and cognitive abilities. Preliminary research suggests that specific sensory differences may cluster together within individuals creating discrete sensory phenotypes. However, the manner in which these sensory differences cluster, and whether the resulting phenotypes are associated with specific cognitive and social challenges is unclear. METHODS: Short sensory profile data from 599 autistic children and adults between the ages of 1 and 21 years were subjected to a K-means cluster analysis. Analysis of variances compared age, adaptive behaviour, and traits associated with autism, attention-deficit and hyperactivity disorder, and obsessive and compulsive disorder across the resultant clusters. RESULTS: A five-cluster model was found to minimize error variance and produce five sensory phenotypes: (1) sensory adaptive, (2) generalized sensory differences, (3) taste and smell sensitivity, (4) under-responsive and sensation seeking, and (5) movement difficulties with low energy. Age, adaptive behaviour, and traits associated with autism, attention-deficit and hyperactivity disorder, and obsessive and compulsive disorder were found to differ significantly across the five phenotypes. LIMITATIONS: The results were based on parent-report measures of sensory processing, adaptive behaviour, traits associated with autism, attention-deficit and hyperactivity disorder, and obsessive and compulsive disorder, which may limit the generalizability of the findings. Further, not all measures are standardized, or psychometrically validated with an autism population. Autistic individuals with an intellectual disability were underrepresented in this sample. Further, as these data were obtained from established records from a large provincial database, not all measures were completed for all individuals. CONCLUSIONS: These findings suggest that sensory difficulties in autistic individuals can be clustered into sensory phenotypes, and that these phenotypes are associated with behavioural differences. Given the large degree of heterogeneity in sensory difficulties seen in the autistic population, these sensory phenotypes represent an effective way to parse that heterogeneity and create phenotypes that may aid in the development of effective treatments and interventions for sensory difficulties.

Sex Differences in Age of Diagnosis and First Concern among Children with Autism Spectrum Disorder.

OBJECTIVE: Early identification of autism spectrum disorder (ASD) is an essential healthcare priority. Girls may be at risk for late diagnosis, although research is equivocal regarding how sex and other factors relate to ASD identification. The goals of the current investigation were to (1) identify how child sex, cognitive abilities, and demographic factors relate to age of first concern (AOC) and age of diagnosis (AOD), (2) evaluate trends in AOC/AOD over time, and (3) consider whether main effects of sex on AOC/AOD are moderated by cognitive abilities or time. METHOD: Children (N = 365; 20% female; 85.6% identified as White) with ASD participated through the Province of Ontario Neurodevelopmental Disorders (POND) Network. Study records included AOD, date/timing of diagnosis (between 1996 and 2017), age of first parent concern, demographics, and standardized cognitive testing results (24.7% of children had IQ scores below standard scores of 70). RESULTS: Average AOC occurred before 2 years of age whereas average AOD occurred after 5 years of age. Girls did not differ on AOC but had a later AOD than boys. Higher verbal IQ was associated with later AOD more strongly in girls than boys. Regarding time-related changes, average AOC and AOD increased across the study period, more strongly for girls. CONCLUSIONS: Results support that sex is a key factor underlying delays in ASD identification and highlight the urgent need to improve diagnostic practices among girls. Limitations and implications for improving the diagnostic process are discussed.Abbreviations: ASD=autism spectrum disorder; IQ=intelligence quotient; AOC=parental report of age of first concern; AOD=age of diagnosis.