Electrophysiological correlates of processing native and non-native speech contrasts in infants at risk for autism spectrum disorders or language impairment

Background: Recent research has highlighted potential overlap in phenotype between children with autism and those with specific language impairment (SLI). A significant proportion of first-degree relatives of autism probands have language-related learning disabilities, and in a large epidemiological sample, siblings of SLI probands found an elevated risk of ASD. Several researchers have argued that ASD and SLI form overlapping populations with shared phenotypic features and potential genetic etiology.  Because the relatively few studies that have directly compared ASD and SLI have all been conducted with older children, it is not known whether there is overlap in the earliest manifestations for each of these disorders in specific symptoms or developmental timing. 
Objectives: We hypothesize that neural correlates of key aspects of language and social-communicative development in infants who later go on to show signs of language impairment or ASD emerge during this critical period between 3 and 12 months in both high risk groups. 

Methods: In the current longitudinal project we are employing high-density event-related potentials (ERPs) to examine the discrimination of familiar vs. unfamiliar speech contrasts among three groups of infants: (1) infants at risk for ASD (by virtue of 1 or more affected siblings), (2) infants at risk for SLI and (3) low risk infants.  Infants are being studied at 3, 6, 9 and 12 months.  The auditory ERP task involves a cross-linguistic double-odd ball paradigm design using Hindi as the non-native speech stimuli.    

Results: Thus far 30 infants have yielded useable ERP data and preliminary inspection of the data show discrimination between the native and non-native speech sounds at the P1, N250 and the MMN, with the ERP responses being different between the 3 groups.
Conclusions:   This exploratory project will lay the methodological foundation using neurobehavioral measures to determine the earliest signs of ASD and SLI in infancy.