Dataset Information

The Importance of Networking in Autism Gaze Analysis.

ABSTRACT: Visual scanning of faces in individuals with Autism Spectrum Disorder (ASD) has been intensively studied using eye-tracking technology. However, most of studies have relied on the same analytic approach based on the quantification of fixation time, which may have failed to reveal some important features of the scanning strategies employed by individuals with ASD. In the present study, we examined the scanning of faces in a group of 20 preschoolers with ASD and their typically developing (TD) peers, using both classical fixation time approach and a new developed approach based on transition matrices and network analysis. We found between group differences in the eye region in terms of fixation time, with increased right eye fixation time for the ASD group and increased left eye fixation time for the TD group. Our complementary network approach revealed that the left eye might play the role of an anchor in the scanning strategies of TD children but not in that of children with ASD. In ASD, fixation time on the different facial parts was almost exclusively dependent on exploratory activity. Our study highlights the importance of developing innovative measures that bear the potential of revealing new properties of the scanning strategies employed by individuals with ASD.

SUBMITTER: Guillon Q

PROVIDER: S-EPMC4619728 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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The Importance of Networking in Autism Gaze Analysis.

Guillon Quentin Q Afzali Mohammad H MH Rogé Bernadette B Baduel Sophie S Kruck Jeanne J Hadjikhani Nouchine N

PloS one 20151023 10

Visual scanning of faces in individuals with Autism Spectrum Disorder (ASD) has been intensively studied using eye-tracking technology. However, most of studies have relied on the same analytic approach based on the quantification of fixation time, which may have failed to reveal some important features of the scanning strategies employed by individuals with ASD. In the present study, we examined the scanning of faces in a group of 20 preschoolers with ASD and their typically developing (TD) pee ...[more]

PMID: 26496498

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Project description:ImportanceAtypical eye gaze is an early-emerging symptom of autism spectrum disorder (ASD) and holds promise for autism screening. Current eye-tracking methods are expensive and require special equipment and calibration. There is a need for scalable, feasible methods for measuring eye gaze.ObjectiveUsing computational methods based on computer vision analysis, we evaluated whether an app deployed on an iPhone or iPad that displayed strategically designed brief movies could elicit and quantify differences in eye-gaze patterns of toddlers with ASD vs typical development.Design, setting, and participantsA prospective study in pediatric primary care clinics was conducted from December 2018 to March 2020, comparing toddlers with and without ASD. Caregivers of 1564 toddlers were invited to participate during a well-child visit. A total of 993 toddlers (63%) completed study measures. Enrollment criteria were aged 16 to 38 months, healthy, English- or Spanish-speaking caregiver, and toddler able to sit and view the app. Participants were screened with the Modified Checklist for Autism in Toddlers-Revised With Follow-up during routine care. Children were referred by their pediatrician for diagnostic evaluation based on results of the checklist or if the caregiver or pediatrician was concerned. Forty toddlers subsequently were diagnosed with ASD.ExposuresA mobile app displayed on a smartphone or tablet.Main outcomes and measuresComputer vision analysis quantified eye-gaze patterns elicited by the app, which were compared between toddlers with ASD vs typical development.ResultsMean age of the sample was 21.1 months (range, 17.1-36.9 months), and 50.6% were boys, 59.8% White individuals, 16.5% Black individuals, 23.7% other race, and 16.9% Hispanic/Latino individuals. Distinctive eye-gaze patterns were detected in toddlers with ASD, characterized by reduced gaze to social stimuli and to salient social moments during the movies, and previously unknown deficits in coordination of gaze with speech sounds. The area under the receiver operating characteristic curve discriminating ASD vs non-ASD using multiple gaze features was 0.90 (95% CI, 0.82-0.97).Conclusions and relevanceThe app reliably measured both known and new gaze biomarkers that distinguished toddlers with ASD vs typical development. These novel results may have potential for developing scalable autism screening tools, exportable to natural settings, and enabling data sets amenable to machine learning.

Dataset Information

The Importance of Networking in Autism Gaze Analysis.

Publications

The Importance of Networking in Autism Gaze Analysis.

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