We have developed magnetoencephalography (MEG) measures that predict both a diagnosis of ASD and thedegree 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 impairmentin ASD and in other groups with a developmental disability; and (iii) lexical distinction (word versus non-wordlow-frequency neural oscillatory activity) both predicts language impairment as well as atypical hemisphericspecialization for language in ASD and, perhaps, in other neurodevelopmental groups. Prior imaging studies ofASD (including our own) have focused on an intellectually higher-functioning population (high-functioningautism, or HFA). One reason for this bias is that the majority of imaging studies entail magnetic resonanceimaging (MRI), which presupposes a participant's ability to remain motionless during the study, therebydisqualifying from study the large ASD population with language delay and intellectual disability (possibly ashigh as 50%). We seek to investigate the neural basis of autism and associated language and cognitiveimpairment 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 becompared 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 withintellectual disability (ID; N =40) but without ASD, matched for age and non-verbal IQ in order to isolate neuralabnormalities 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, therebyenabling a deeper understanding of the pathogenesis of disability across the ASD spectrum; and (b) A searchfor mechanisms of language impairment that are ASD-specific rather than a consequence of more generaleffects of low cognitive ability. To obtain high-quality MEG data, we will deploy a research strategy wedesignate “MEG-PLAN (MEG Protocol for Low-Language/Cognitive Functioning Ability Neuroimaging). Thekey elements of MEG-PLAN are: (1) Engage stakeholders (parents/providers) as “partners in research” todevelop a MEG scanning protocol that maximizes data collection success; (2) Examine automatic brainresponses elicited with passive auditory paradigms, thereby obviating the need for participants to attend to thetask or provide feedback; (3) Remove the need for an individual MRI to localize the MEG signal source byusing a MEG which is registered to an age-appropriate template MRI; (4) Achieve motion tolerance of up to 2cm via real-time MEG head tracking/motion compensation. This study addresses focus area #2 in the RFA –“Outcome Measures for Interventions or Treatments”.
Interagency Autism Coordinating Committee (IACC)
Autism Research Database (AFD)
