About this trial
Social cognition refers to the mental processes involved in social interactions, including social perception, motivation, communication, emotion recognition, and theory of mind. Face perception plays a key role in children's social development, but children with Autism Spectrum Disorder (ASD) tend to look less at social stimuli, especially faces, than typically developing (TD) peers. Eye-tracking studies highlight these visual exploration differences, linked to difficulties in joint attention, emotion recognition, and theory of mind, as well as in executive and memory functions. Standard diagnostic tests often require active participation and sufficient language, which makes assessment challenging for children with ASD and additional cognitive or language impairments.
This research project investigates how visual activity supports social cognition depending on cognitive and language levels, hypothesizing that eye-tracking can provide useful indicators for ASD screening and diagnosis.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Boys or girls diagnosed with Autism Spectrum Disorder (based on clinical tools and observations)
Aged between 4 and 10 years old
Affiliation with a social security scheme
Informed consent of those with parental authority
Disqualifiers
For ASD: Uncorrected visual or auditory impairments.
For DT: Intellectual disability, neurological or genetic disorders, autistic traits reported by teachers. The discrepancy between actual age and abilities calculated on the basis of standardised test scores
Trial design
Parallel
Treatments tested in this trial
eye-tracking
Other interventioneye-tracking
cognitive assessments
Other interventioncognitive assessments
Treatment groups
Trial outcomes
Primary outcomes
differences in visual exploration patterns between both groups
Differences in visual exploration patterns between both groups Visual exploration patterns are determined with TOM Test Battery, PPVT-5, Raven's 2 and FEE tests
Classification performance of machine learning algorithms in distinguishing ASD from TD
Classification performance of machine learning algorithms in distinguishing ASD from TD
Secondary outcomes
Correlations between eye-tracking measures and cognitive scores
Eye-tracking patterns are determined with TOM Test Battery, PPVT-5, Raven's 2 and FEE tests
Developmental trajectory analysis in TD children
Identification of cognitive subgroups within ASD group
Sponsors and contacts
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