We have developed magnetoencephalography (MEG) measures that predict both a diagnosis of ASD and the degree of language impairment. Thus, (i) auditory encoding latency (M100) discriminates ASD versus non- ASD; (ii) auditory change detection latency (mismatch field, MMF) predicts severity of language impairment in ASD and in other groups with a developmental disability; and (iii) lexical distinction (word versus non-word low-frequency neural oscillatory activity) both predicts language impairment as well as atypical hemispheric specialization for language in ASD and, perhaps, in other neurodevelopmental groups. Prior imaging studies of ASD (including our own) have focused on an intellectually higher-functioning population (high-functioning autism, or HFA). One reason for this bias is that the majority of imaging studies entail magnetic resonance imaging (MRI), which presupposes a participant's ability to remain motionless during the study, thereby disqualifying from study the large ASD population with language delay and intellectual disability (possibly as high as 50%). We seek to investigate the neural basis of autism and associated language and cognitive impairment in an under-studied population of minimally verbal/non-verbal ASD children (MVNV-ASD, N = 40, aged 8 to 12 years). To this end, MVNV-ASD encoding, change detection, and lexical MEG measures will be compared with the same measures already available in age-matched HFA and typically developing (TD) children. Using the same tasks, MEG data will be obtained from a ?positive control? group of children with intellectual disability (ID; N =40) but without ASD, matched for age and non-verbal IQ in order to isolate neural abnormalities specific to MVNV-ASD and not consequent to impairment of general cognitive function. Thus, our primary goals are: (a) A search for pathogenic mechanisms common to HFA and MVNV-ASD, thereby enabling a deeper understanding of the pathogenesis of disability across the ASD spectrum; and (b) A search for mechanisms of language impairment that are ASD-specific rather than a consequence of more general effects of low cognitive ability. To obtain high-quality MEG data, we will deploy a research strategy we designate ?MEG-PLAN (MEG Protocol for Low-Language/Cognitive Functioning Ability Neuroimaging). The key elements of MEG-PLAN are: (1) Engage stakeholders (parents/providers) as ?partners in research? to develop a MEG scanning protocol that maximizes data collection success; (2) Examine automatic brain responses elicited with passive auditory paradigms, thereby obviating the need for participants to attend to the task or provide feedback; (3) Remove the need for an individual MRI to localize the MEG signal source by using a MEG which is registered to an age-appropriate template MRI; (4) Achieve motion tolerance of up to 2 cm via real-time MEG head tracking/motion compensation. This study addresses focus area #2 in the RFA ? ?Outcome Measures for Interventions or Treatments?.
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