Approximately 30% of children with ASD are minimally verbal past age 5. There is limited information about their understanding of spoken or written language despite anecdotal reports of great heterogeneity in these domains. There are few appropriate behavioral measures of language comprehension for this population, and these measures may not capture a child’s true abilities. This impedes our ability to characterize children’s abilities and target interventions. Biomarkers hold great promise to further our understanding of this population. Biomarkers are objectively measureable indicators of biologic processes that can be used to elucidate an individual’s cognitive state. This study has two aims: 1) Identify electrophysiological (EEG) biomarkers of language and literacy function in minimally verbal children with ASD in order to identify potential subgroups and 2) determine if these biomarkers are related to progress in a communication intervention. Participants will be drawn from an ongoing intervention study with minimally verbal 5-8 year old children with ASD, focused on increasing spoken language and communication with an augmentative and alternative communication device. Discovery of EEG biomarkers of language and literacy function will aid in characterizing minimally verbal children with ASD, predicting outcomes, and targeting interventions. To this end, this study will quantify high-frequency, resting state EEG oscillations as well as event-related potentials (ERPs) during spoken and written lexical knowledge paradigms. High-frequency oscillations have been shown to relate to language function and predict language abilities in typical developing children. Differences in resting EEG have been found in high functioning children with ASD but this has not been investigated in minimally verbal children with ASD. ERP data have been used to document lexical knowledge in patients who cannot respond to behavior assessments (e.g. traumatic brain injury) and hold promise for investigating this domain in minimally verbal children with ASD. These biomarkers will be analyzed in conjunction with behavioral data such as non-verbal IQ, expressive and receptive language in order to identify subgroups that may be related to treatment outcomes.