About 25% to 30% of children with ASD fail to acquire spoken language. This group of children and adolescents with ASD has been neglected in research conducted over the past 2 decades, in part because the field lacks the tools to assess them, and they often pose significant behavioral challenges that preclude their participation in research studies. Among the ~70% individuals with ASD who have spoken language skills, about 50% are language impaired; the remaining group have normal language scores on standardized tests. To date, studies of brain and cognitive mechanisms that underlie this heterogeneity in ASD remain limited. The goal of this study, which is part of the Autism Center of Excellence, is to provide a detailed description of phenotypic profiles found among minimally verbal individuals diagnosed with ASD. Participants with ASD ages 4 to 18 will be given comprehensive assessments, including standardized assessments of language, nonverbal cognitive abilities and adaptive functioning. Assessments will also include experimental tasks based on using eye-tracking, touch screen and electrophysiology technology (EEG), parent-report measures and parent-child interaction measures. The eye-tracking and touch screen assessments will target receptive language, word learning mechanisms, and social attention deployment to visual and auditory stimuli. The EEG/ERP assessments will target auditory processing and organization, with specific focus on mismatch negativity (MMN) markers of auditory processing. Based on these comprehensive assessments the investigators aim to generate a description of the cognitive-behavioral phenotypes common to minimally verbal autistic individuals. The investigators will also investigate age-related patterns in the development of behavioral phenotypes and the role of symptom severity in shaping phenotypic profiles in this population. The investigators expect that their findings will provide valuable insights into the etiology of profound expressive language deficits in a significant proportion of the ASD population and will lead to identifying subphenotypes within the minimally verbal population.