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EN
Autism spectrum disorders (ASDs) are often not diagnosed until children reach 3–4 years of age. Early identification of young children with ASDs, possibly through a set of behavioral and neurophysiological indexes, is crucial in light of findings indicating that early intervention is much more effective than interventions starting in later childhood. Aim of our study is to identify early diagnostic markers through the assessment of neurobiological and developmental patterns in infant siblings of children with ASDs. We focused on age-specific motor and vocal repertoires which are known to be later impaired in ASD children and that have been found altered in other neurodevelopmental disorders. Analysis of infant crying revealed that high risk infants have a lower frequency of fundamental frequency and of the two resonance frequencies F1 and F2 as compared to full term subjects. General movements’ analysis revealed an unusual motor pattern in infants at high risk. Moreover, five high risk infants showed no responses to name, deficits in emotion recognition, and poor motor development. Our preliminary results showed the importance of monitoring high-risk infant development during the first six months of life and suggest the usefulness of these non-invasive tools to identify early diagnostic markers. However, the sample size, primarily of high risk subjects, needs to be increased.
EN
Male and female mice emit ultrasonic vocalizations during infancy when pups are separated from mother and littermates, as well as at adulthood in different experimental/social contexts. Mouse ultrasonic vocalizations had become now a popular assay for behavioral phenotyping throughout the life-span of models of autism since this response represents the best option to detect deficits within the social communication domain in the mouse species. In the present talk, I will describe the available methods to elicit and record mouse ultrasonic vocalizations in different social contexts and at different ages and behavioral data collected on Autism animal models in these paradigms/contexts. Thanks to the progresses of computer technology, researchers can now perform detailed analyses of the vocal repertoire (classifying ultrasonic vocalizations into different categories). Recently, these analyses have revealed unusual vocal patterns in selected mouse lines. This innovative approach allows detecting also qualitative alterations in the social communication repertoire usually not identified with the standard analysis of emission rate. Future studies should be aimed at performing quantitative and qualitative analyses of vocalization patterns also in preclinical studies evaluating potential treatments in validated autism mouse models.
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