protocolSection identificationModule nctId: NCT06332144, orgStudyIdInfo id: 1R56DC020208-01A1, type: NIH, link: https://reporter.nih.gov/quickSearch/1R56DC020208-01A1, briefTitle: Predicting Language and Literacy Growth in Children With ASD Using Statistical Learning, acronym: PLAUSL, statusModule overallStatus: RECRUITING, startDateStruct date: 2024-01-13, primaryCompletionDateStruct date: 2024-08-31, completionDateStruct date: 2024-08-31, studyFirstPostDateStruct date: 2024-03-27, lastUpdatePostDateStruct date: 2024-03-27, sponsorCollaboratorsModule leadSponsor name: Northeastern University, class: OTHER, collaborators name: University of Delaware, collaborators name: Boston University, collaborators name: Cornell University, descriptionModule briefSummary: The goal of this observational study is to test a reciprocal relationship between statistical learning and the development of language and literacy in first-graders with autism and their non-autistic peers. The main questions it aims to answer are:1. whether children's statistical learning abilities can predict their long-term improvement of language and literacy skills in school;2. how children's brains automatically learn patterns from speech and prints;3. whether children's learning in the lab reflects the language patterns they have learned over the years from their native language.First-grade students will participate in the study twice across three months.During Time 1, children will complete* a battery of language, reading, and cognitive assessments* a series of computer-based statistical learning games both inside and outside of functional MRI scanner.During Time 2, children will complete a battery of language and reading assessments to detect the growth in three months.Researchers will compare the autistic and the non-autistic groups to see if statistical learning plays a similar or different role in predicting children's language and literacy growth., conditionsModule conditions: Autism Spectrum Disorder, conditions: Language Development, conditions: Literacy, designModule studyType: OBSERVATIONAL, designInfo observationalModel: COHORT, timePerspective: PROSPECTIVE, enrollmentInfo count: 50, type: ESTIMATED, armsInterventionsModule interventions name: Structural vs. Random sequences of stimuli, interventions name: Intact vs. Degraded speech, interventions name: Repeating 5-syllable nonwords or 2-syllable nonwords, interventions name: Recall letter or syllable strings that either contain highly frequent bigram/trigram items or infrequent items according to English Corpus data., outcomesModule primaryOutcomes measure: Language Composite Score, primaryOutcomes measure: Reading Composite Score, primaryOutcomes measure: Language/Literacy Disorder Status, primaryOutcomes measure: Neural similarity between language and statistical learning tasks, primaryOutcomes measure: Orthographic statistical sensitivity, primaryOutcomes measure: Phonological statistical sensitivity, secondaryOutcomes measure: Linguistic SL composite scores, secondaryOutcomes measure: Neural sensitivity to statistical regularities during the statistical learning tasks, otherOutcomes measure: Neural activation to statistical regularities during the language tasks, eligibilityModule sex: ALL, minimumAge: 72 Months, maximumAge: 90 Months, stdAges: CHILD, contactsLocationsModule locations facility: Northeastern University, status: RECRUITING, city: Boston, state: Massachusetts, zip: 02115, country: United States, contacts name: Brynn Siles, BS, role: CONTACT, phone: 617-830-1530, email: plausl.project@gmail.com, contacts name: Zhenghan Qi, MD/PhD, role: PRINCIPAL_INVESTIGATOR, geoPoint lat: 42.35843, lon: -71.05977, locations facility: Boston University, status: ENROLLING_BY_INVITATION, city: Boston, state: Massachusetts, zip: 02215, country: United States, geoPoint lat: 42.35843, lon: -71.05977, hasResults: False