Eye-Tracking in Infants and Young Children at Risk for Autism Spectrum Disorder: A Systematic Review of Visual Stimuli in Experimental Paradigms

Seeing beyond words: Visualizing autism spectrum disorder biomarker insights

Objective

This study employs bibliometric and visual analysis to elucidate global research trends in Autism Spectrum Disorder (ASD) biomarkers, identify critical research focal points, and discuss the potential integration of diverse biomarker modalities for precise ASD assessment.

Methods

A comprehensive bibliometric analysis was conducted using data from the Web of Science Core Collection database until December 31, 2022. Visualization tools, including R, VOSviewer, CiteSpace, and gCLUTO, were utilized to examine collaborative networks, co-citation patterns, and keyword associations among countries, institutions, authors, journals, documents, and keywords.

Results

ASD biomarker research emerged in 2004, accumulating a corpus of 4348 documents by December 31, 2022. The United States, with 1574 publications and an H-index of 213, emerged as the most prolific and influential country. The University of California, Davis, contributed significantly with 346 publications and an H-index of 69, making it the leading institution. Concerning journals, the Journal of Autism and Developmental Disorders, Autism Research, and PLOS ONE were the top three publishers of ASD biomarker-related articles among a total of 1140 academic journals. Co-citation and keyword analyses revealed research hotspots in genetics, imaging, oxidative stress, neuroinflammation, gut microbiota, and eye tracking. Emerging topics included "DNA methylation," "eye tracking," "metabolomics," and "resting-state fMRI."

Conclusion

The field of ASD biomarker research is dynamically evolving. Future endeavors should prioritize individual stratification, methodological standardization, the harmonious integration of biomarker modalities, and longitudinal studies to advance the precision of ASD diagnosis and treatment.

Social and joint attention during shared book reading in young autistic children: a potential marker for social development

BACKGROUND

Atypical patterns of social engagement and joint attention behaviors are diagnostic criteria for people with autism spectrum disorder. Experimental tasks using eye-tracking methodologies have, however, shown inconsistent results. The development of tasks with greater ecological validity and relevance for developmentally appropriate social milestones has been identified as important for the field.

METHODS

We developed a novel, dynamic eye-tracking task emulating a shared book reading (SBR) scenario. Four SBR videos of an adult reader engaging with the viewer while reading a children's picture book and including sequenced bids for joint attention were developed. Participants included 90 children (N = 56 autistic children, N = 34 neurotypical children; aged 3-12). Social attention was also measured in a live free play task between participants and an experimenter.

RESULTS

Compared to neurotypical children, autistic children displayed reduced attention to socially salient stimuli including the reader's face and picture book across SBR videos and during joint attention bids specifically. In contrast, they showed increased attention to nonsalient background stimuli compared to their neurotypical peers. These attention patterns in autistic children were associated with reduced verbal and nonverbal cognitive skills and increased symptoms associated with autism. Interestingly, positive correlations in the frequency of eye gaze between SBR and free play suggested a potential predictive value for social attention in live social interactions.

CONCLUSIONS

Findings highlight the utility of SBR eye-tracking tasks in understanding underlying divergences in social engagement and joint attention between autistic and neurotypical children. This commonly practiced early childhood activity may provide insights into the relationship between social engagement and learning to reveal how such attentional patterns might influence broader developmental and educational outcomes.

Feasibility of a 2-minute eye-tracking protocol to support the early identification of autism

We tested the potential for Gazefinder eye-tracking to support early autism identification, including feasible use with infants, and preliminary concurrent validity of trial-level gaze data against clinical assessment scores. We embedded the ~ 2-min 'Scene 1S4' protocol within a comprehensive clinical assessment for 54 consecutively-referred, clinically-indicated infants (prematurity-corrected age 9-14 months). Alongside % tracking rate as a broad indicator of feasible assessment/data capture, we report infant gaze data to pre-specified regions of interest (ROI) across four trial types and associations with scores on established clinical/behavioural tools. Most infants tolerated Gazefinder eye-tracking well, returning high overall % tracking rate. As a group, infants directed more gaze towards social vs. non-social (or more vs. less socially-salient) ROIs within trials. Behavioural autism features were correlated with increased gaze towards non-social/geometry (vs. social/people) scenes. No associations were found for gaze directed to ROIs within other stimulus types. Notably, there were no associations between developmental/cognitive ability or adaptive behaviour with gaze towards any ROI. Gazefinder assessment seems highly feasible with clinically-indicated infants, and the people vs. geometry stimuli show concurrent predictive validity for behavioural autism features. Aggregating data across the ~ 2-min autism identification protocol might plausibly offer greater utility than stimulus-level analysis alone.

Digital tools for direct assessment of autism risk during early childhood: A systematic review

LAY ABSTRACT

The challenge of finding autistic children, and finding them early enough to make a difference for them and their families, becomes all the greater in parts of the world where human and material resources are in short supply. Poverty of resources delays interventions, translating into a poverty of outcomes. Digital tools carry potential to lessen this delay because they can be administered by non-specialists in children's homes, schools or other everyday environments, they can measure a wide range of autistic behaviours objectively and they can automate analysis without requiring an expert in computers or statistics. This literature review aimed to identify and describe digital tools for screening children who may be at risk for autism. These tools are predominantly at the 'proof-of-concept' stage. Both portable (laptops, mobile phones, smart toys) and fixed (desktop computers, virtual-reality platforms) technologies are used to present computerised games, or to record children's behaviours or speech. Computerised analysis of children's interactions with these technologies differentiates children with and without autism, with promising results. Tasks assessing social responses and hand and body movements are the most reliable in distinguishing autistic from typically developing children. Such digital tools hold immense potential for early identification of autism spectrum disorder risk at a large scale. Next steps should be to further validate these tools and to evaluate their applicability in a variety of settings. Crucially, stakeholders from underserved communities globally must be involved in this research, lest it fail to capture the issues that these stakeholders are facing.

Computer-aided autism diagnosis using visual attention models and eye-tracking: replication and improvement proposal

BACKGROUND

Autism Spectrum Disorder (ASD) diagnosis can be aided by approaches based on eye-tracking signals. Recently, the feasibility of building Visual Attention Models (VAMs) from features extracted from visual stimuli and their use for classifying cases and controls has been demonstrated using Neural Networks and Support Vector Machines. The present work has three aims: 1) to evaluate whether the trained classifier from the previous study was generalist enough to classify new samples with a new stimulus; 2) to replicate the previously approach to train a new classifier with a new dataset; 3) to evaluate the performance of classifiers obtained by a new classification algorithm (Random Forest) using the previous and the current datasets.

METHODS

The previously approach was replicated with a new stimulus and new sample, 44 from the Typical Development group and 33 from the ASD group. After the replication, Random Forest classifier was tested to substitute Neural Networks algorithm.

RESULTS

The test with the trained classifier reached an AUC of 0.56, suggesting that the trained classifier requires retraining of the VAMs when changing the stimulus. The replication results reached an AUC of 0.71, indicating the potential of generalization of the approach for aiding ASD diagnosis, as long as the stimulus is similar to the originally proposed. The results achieved with Random Forest were superior to those achieved with the original approach, with an average AUC of 0.95 for the previous dataset and 0.74 for the new dataset.

CONCLUSION

In summary, the results of the replication experiment were satisfactory, which suggests the robustness of the approach and the VAM-based approaches feasibility to aid in ASD diagnosis. The proposed method change improved the classification performance. Some limitations are discussed and additional studies are encouraged to test other conditions and scenarios.

The use of eye-tracking technology as a tool to evaluate social cognition in people with an intellectual disability: a systematic review and meta-analysis

BACKGROUND

Relatively little is known about social cognition in people with intellectual disability (ID), and how this may support understanding of co-occurring autism. A limitation of previous research is that traditional social-cognitive tasks place a demand on domain-general cognition and language abilities. These tasks are not suitable for people with ID and lack the sensitivity to detect subtle social-cognitive processes. In autism research, eye-tracking technology has offered an effective method of evaluating social cognition-indicating associations between visual social attention and autism characteristics. The present systematic review synthesised research which has used eye-tracking technology to study social cognition in ID. A meta-analysis was used to explore whether visual attention on socially salient regions (SSRs) of stimuli during these tasks correlated with degree of autism characteristics presented on clinical assessment tools.

METHOD

Searches were conducted using four databases, research mailing lists, and citation tracking. Following in-depth screening and exclusion of studies with low methodological quality, 49 articles were included in the review. A correlational meta-analysis was run on Pearson's r values obtained from twelve studies, reporting the relationship between visual attention on SSRs and autism characteristics.

RESULTS AND CONCLUSIONS

Eye-tracking technology was used to measure different social-cognitive abilities across a range of syndromic and non-syndromic ID groups. Restricted scan paths and eye-region avoidance appeared to impact people's ability to make explicit inferences about mental states and social cues. Readiness to attend to social stimuli also varied depending on social content and degree of familiarity. A meta-analysis using a random effects model revealed a significant negative correlation (r = -.28, [95% CI -.47, -.08]) between visual attention on SSRs and autism characteristics across ID groups. Together, these findings highlight how eye-tracking can be used as an accessible tool to measure more subtle social-cognitive processes, which appear to reflect variability in observable behaviour. Further research is needed to be able to explore additional covariates (e.g. ID severity, ADHD, anxiety) which may be related to visual attention on SSRs, to different degrees within syndromic and non-syndromic ID groups, in order to determine the specificity of the association with autism characteristics.

Face-to-face live eye-tracking in toddlers with autism: Feasibility and impact of familiarity and face covering

Studies utilizing eye-tracking methods have potential to promptly capture real-world dynamics of one of the core areas of vulnerability in autism spectrum disorders (ASD), selective social attention. So far, no studies have successfully reported utilizing the method to examine social attention in toddlers with neurodevelopmental vulnerabilities in real world and challenging settings such as an interactive face-to-face. This study examined the feasibility and validity of live eye-tracking method in response to live interaction occurring in several contexts in toddlers with and without ASD. Forty-seven toddlers with ASD, with atypical development (ATYP), or typically developing (TD), underwent a 30-s live eye-tracking procedure during a face-to-face interaction with a masked stranger using child-directed-speech (16 ASD, 14 ATYP, 17 TD; Mage  = 23.44 months, SD = 6.02). Out of this group of toddlers, 29 (10 ASD, 8 ATYP, 11 TD, Mage  = 21.97 months, SD = 5.76) underwent the same procedure with one of their maskless parent. Task completion rate, calibration accuracy, and affective response (feasibility measures) as well as attention to the task and the social partner (validity measures) were examined. Task completion rate and calibration accuracy were excellent. Despite the challenging context of face-to-face interaction, the toddlers exhibited a neutral affect, and high attention to the task and the speaker. As anticipated, toddlers with ASD looked less at the social partner compared with control groups. However, attention was comparable between the Stranger and Parent conditions, indicating that the effect was consistent regardless of presence of face covering or the familiarity of the interactive partner. The study demonstrates the high feasibility and validity of a live eye-tracking task involving face-to-face interaction in neurodiverse toddlers with social vulnerabilities. The effect of diminished attention to social partners in toddlers with autism is robust and present when interacting with an unfamiliar person and parent. The results suggest that a brief live eye-tracking method constitutes a promising ecologically valid candidate biomarker and potential intervention outcome in autism.

The first six months of life: A systematic review of early markers associated with later autism

There is now good evidence that behavioural signs of autism spectrum conditions (autism) emerge over the first two years of life. Identifying clear developmental differences early in life may facilitate earlier identification and intervention that can promote longer-term quality of life. Here we present a systematic review of studies investigating behavioural markers of later autism diagnosis or symptomology taken at 0-6 months. The following databases were searched for articles published between 01/01/2000 and 15/03/2022: Embase, Medline, Scopus, PubMed, PsycINFO, CINAHL, Web of Science and Proquest. Twenty-five studies met inclusion criteria: assessment of behaviour at 0-6 months and later assessment of autism symptomology or diagnosis. Studies examined behaviours of attention, early social and communication behaviours, and motor behaviours, as well as composite measures. Findings indicated some evidence of measures of general attention, attention to social stimuli, and motor behaviours associated with later autism diagnosis or symptomology. Findings were inconsistent regarding social and communication behaviours, with a lack of repeated or validated measures limiting drawing firm conclusions. We discuss implications of the findings and suggest recommendations for future research.

What are quantitative traits and how can they be used in autism research?

Quantitative traits are measurable characteristics distributed along a continuous scale thought to relate to underlying biology. There is growing interest in the use of quantitative traits in behavioral and psychiatric research, particularly in research on conditions diagnosed based on reports of behaviors, including autism. This brief commentary describes quantitative traits, including defining what they are, how we can measure them, and key considerations for their use in autism research. Examples of measures include behavioral report scales like the Social Responsiveness Scale and Broader Autism Phenotype Questionnaire, as well as biological measurements, like certain neuroimaging metrics; such measures can capture quantitative traits or constructs like the broader autism phenotype, social communication, and social cognition. Quantitative trait measures align with the Research Domain Criteria (RDoC) approach and can be used in autism research to help gain a better understanding of causal pathways and biological processes. They can also be used to aid identification of genetic and environmental factors involved in such pathways, and thereby lead to an understanding of influences on traits across the entire population. Finally, in some cases, they may be used to gauge treatment response, and assist screening and clinical characterization of phenotype. In addition, practical benefits of quantitative trait measures include improved statistical power relative to categorical classifications and (for some measures) efficiency. Ultimately, research across autism fields may benefit from incorporating quantitative trait measures as a complement to categorical diagnosis to advance understanding of autism and neurodevelopment.

Structured Multidisciplinary Follow-Up After Pediatric Intensive Care: A Model for Continuous Data-Driven Health Care Innovation

OBJECTIVES

Morbidity after PICU admission for critical illness is a growing concern. Sequelae may occur in various domains of functioning and can only appropriately be determined through structured follow-up. Here, we describe the process of designing and implementing a structured multidisciplinary follow-up program for patients and their parents after PICU admission and show the first results illustrating the significance of our program.

DESIGN

Prospective observational cohort study.

SETTING

Outpatient PICU follow-up clinic.

PATIENTS

Patients 0-18 years old admitted to our PICU.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

In our structured multidisciplinary follow-up program, follow-up care is provided by a pediatric intensivist and psychologist and in addition, depending on patient's critical illness and received PICU treatment(s), by a pediatric pulmonologist, cardiologist, neurologist, and/or neuropsychologist. All consultations are scheduled consecutively. Collected data are stored in a hospital-wide data warehouse and used for yearly health care evaluation sessions as well as scientific research. Challenges in organizing this follow-up program include technological challenges, providing time-efficient care, participation rate, and completeness of questionnaires. In our experience, a dedicated team is essential to tackle these challenges. Our first results, obtained in 307 of 388 referred patients (79.1%), showed the diversity of problems arising after PICU discharge, including physical, neurocognitive, and psychosocial sequelae. In addition, our data also reflected the risk of psychosocial problems among parents. Within the limited operation time of our follow-up program, the program has evolved based on our experiences and the data collected.

CONCLUSIONS

We successfully developed and implemented a structured multidisciplinary follow-up program for patients and their parents after PICU admission. This program may help to timely initiate appropriate interventions, improve the standard of care during and after PICU admission, and facilitate scientific research on outcome and prognosis after PICU admission.

Eye-tracking correlates of response to joint attention in preschool children with autism spectrum disorder

BACKGROUND

A number of differences in joint attention behaviour between children with autism spectrum disorder (ASD) and typically developing (TD) individuals have previously been documented.

METHOD

We use eye-tracking technology to assess response to joint attention (RJA) behaviours in 77 children aged 31 to 73 months. We conducted a repeated-measures analysis of variance to identify differences between groups. In addition, we analysed correlations between eye-tracking and clinical measures using Spearman's correlation.

RESULTS

The children diagnosed with ASD were less likely to follow gaze compared to TD children. Children with ASD were less accurate at gaze following when only eye gaze information was available, compared to when eye gaze with head movement was observed. Higher accuracy gaze-following profiles were associated with better early cognition and more adaptive behaviours in children with ASD. Less accurate gaze-following profiles were associated with more severe ASD symptomatology.

CONCLUSION

There are differences in RJA behaviours between ASD and TD preschool children. Several eye-tracking measures of RJA behaviours in preschool children were found to be associated with clinical measures for ASD diagnosis. This study also highlights the construct validity of using eye-tracking measures as potential biomarkers in the assessment and diagnosis of ASD in preschool children.

Effects of early exposure to phthalates on cognitive development and visual behavior at 24 months

BACKGROUND AND OBJECTIVES

Studies focusing on the neurodevelopmental effects of phthalates seldom consider exposure during infancy, a critical period for brain development. Most rely on parent-completed questionnaires to assess child neurodevelopment, which may be subject to reporting error. We studied the associations between prenatal and infancy exposure to phthalates and objective measures of neurodevelopment at the age of two.

METHODS

We relied on 151 mother-child pairs from the SEPAGES mother-child cohort. Women were asked to collect three spot urine samples per day over seven consecutive days during the second (median: 18.0 gestational weeks) and third (median: 34.2 gestational weeks) trimesters of pregnancy. They then collected one urine sample per day over seven consecutive days from their infants around the age of 12 months. Metabolites of phthalates and non-phthalate plasticizers were measured in within-subject and within-period pools of repeated urine samples. Eye tracking tasks were performed at two years allowing to compute four indicators linked with cognitive development and visual behavior: mean fixation duration, novelty preference, percent time spent looking at the eyes and mean reaction time.

RESULTS

Pre-natal exposure to monobenzyl phthalate at the second and third trimesters was associated with shorter fixation durations. In models allowing for interaction with child sex, these associations were only observed among girls. Exposure to di(2-ethylhexyl) phthalate at the third but not the second trimester was associated with increased time spent looking at a novel face and eyes. We observed faster reaction times and decreased time spent looking at the eyes in a face recognition task, with increased post-natal exposure to monoethyl, mono-iso-butyl and mono-n-butyl phthalates.

DISCUSSION

Relying on improved exposure assessment, we highlighted associations of pre- and post-natal exposure to phthalates with indicators derived from eye tracking tasks, mainly in girls. Some of these indicators have been affected in individuals with neurodevelopmental disorders.

Rendimiento de los estímulos visuales en el diagnóstico del TEA por Eye Tracking: Revisión Sistemática

El eye-tracking es una herramienta diagnóstica que tiene como   fin el estudio del comportamiento de la mirada a través del escaneo de ojos para observar el seguimiento ocular, cómo se distribuye la mirada y la precisión de los movimientos oculares. Este sistema se ha utilizado con niños/as del Trastorno del Espectro Autista. El objetivo de esta revisión sistemática ha sido analizar el rendimiento de los estímulos visuales en el diagnóstico del TEA por método eye tracking. Para ello, se siguió la metodología PRISMA, realizando una búsqueda en las bases de datos PubMed, Science Direct y Scopus, así como, Reseach Gate. Se seleccionaron 22 artículos que cumplían los criterios de inclusión con experimentos unifactoriales, experimentales factoriales y cuasiexperimentales. Todos los experimentos han tenido un grupo control compuesto de muestra con participantes con desarrollo normotípico y de un grupo de caso compuesto de muestra con participantes TEA. Esta revisión sintetiza en tres categorías en base a las características del estímulo usado en el diagnóstico (estímulos sociales, no sociales y por confrontación), el análisis del rendimiento de los estímulos visuales, de manera que los estímulos sociales y los estímulos por confrontación van a ser eficaces para establecer un diagnóstico preciso de TEA puesto que permiten realizar un cribado de ambos grupos y establecer un riesgo temprano del trastorno.

Characteristics of Visual Fixation in Chinese Children with Autism During Face-to-Face Conversations

Few eye tracking studies have examined how people with autism spectrum disorder (ASD) visually attend during live interpersonal interaction, and none with the Chinese population. This study used an eye tracker to record the gaze behavior in 20 Chinese children with ASD and 23 children with typical development (TD) when they were engaged in a structured conversation. Results demonstrated that children with ASD looked significantly less at the interlocutor's mouth and whole-face, and more at background. Additionally, gaze behavior was found to vary with the conversational topic. Given the great variability in eye tracking findings in existing literature, future explorations might consider investigating how fundamental factors (i.e., participant's characteristics, tasks, and context) influence the gaze behavior in people with ASD.

Machine learning based on eye-tracking data to identify Autism Spectrum Disorder: A systematic review and meta-analysis

BACKGROUND

Machine learning has been widely used to identify Autism Spectrum Disorder (ASD) based on eye-tracking, but its accuracy is uncertain. We aimed to summarize the available evidence on the performances of machine learning algorithms in classifying ASD and typically developing (TD) individuals based on eye-tracking data.

METHODS

We searched Medline, Embase, Web of Science, Scopus, Cochrane Library, IEEE Xplore Digital Library, Wan Fang Database, China National Knowledge Infrastructure, Chinese BioMedical Literature Database, VIP Database for Chinese Technical Periodicals, from database inception to December 24, 2021. Studies using machine learning methods to classify ASD and TD individuals based on eye-tracking technologies were included. We extracted the data on study population, model performances, algorithms of machine learning, and paradigms of eye-tracking. This study is registered with PROSPERO, CRD42022296037.

RESULTS

261 articles were identified, of which 24 studies with sample sizes ranging from 28 to 141 were included (n = 1396 individuals). Machine learning based on eye-tracking yielded the pooled classified accuracy of 81 % (I² = 73 %), specificity of 79 % (I² = 61 %), and sensitivity of 84 % (I² = 61 %) in classifying ASD and TD individuals. In subgroup analysis, the accuracy was 88 % (95 % CI: 85-91 %), 79 % (95 % CI: 72-84 %), 71 % (95 % CI: 59-91 %) for preschool-aged, school-aged, and adolescent-adult group. Eye-tracking stimuli and machine learning algorithms varied widely across studies, with social, static, and active stimuli and Support Vector Machine and Random Forest most commonly reported. Regarding the model performance evaluation, 15 studies reported their final results on validation datasets, four based on testing datasets, and five did not report whether they used validation datasets. Most studies failed to report the information on eye-tracking hardware and the implementation process.

CONCLUSION

Using eye-tracking data, machine learning has shown potential in identifying ASD individuals with high accuracy, especially in preschool-aged children. However, the heterogeneity between studies, the absence of test set-based performance evaluations, the small sample size, and the non-standardized implementation of eye-tracking might deteriorate the reliability of results. Further well-designed and well-executed studies with comprehensive and transparent reporting are needed to determine the optimal eye-tracking paradigms and machine learning algorithms.

Research-Based Intervention (RBI) for Autism Spectrum Disorder: Looking beyond Traditional Models and Outcome Measures for Clinical Trials

The rising prevalence of Autism Spectrum Disorders (ASD) has led to a quickly increasing need for effective interventions. Several criteria and measures have been developed to critically assess these interventions with particular focus on the evaluation of the efficacy. Given the huge diversity of ASD symptoms and the different levels of severity across individuals, identifying a one size fits all intervention approach is challenging, and the question What works and for whom? Remains still unanswered. Why do we seem to be dragging our feet on this fundamental issue? The main aim of this paper is to answer this question through four non-alternative points. First, there are a scarce number of studies with a solid methodology. Secondly, most trials on intervention efficacy for ASD are designed exclusively in terms of behavioral outcomes. Thirdly, there is a reduced use of biologically oriented outcome measures. Fourthly, in most clinical trials, appropriate practices emerging from research evidence are not systematically applied. A strong effort to improve the methodology of clinical trials is mandatory for the future of autism research. The development of a research-based intervention (RBI) perspective aimed at better integrating: (a) evidence-based approaches; (b) more sensitive behavioral outcome measures; and (c) biomarkers, with the aim of increasing a more detailed clustering of phenotypes, may strongly improve our approach to a precision medicine.

Development of a visual attention based decision support system for autism spectrum disorder screening

Visual attention of young children with autism spectrum disorder (ASD) has been well documented in the literature for the past 20 years. In this study, we developed a Decision Support System (DSS) that uses machine learning (ML) techniques to identify young children with ASD from typically developing (TD) children. Study participants included 26 to 36 months old young children with ASD (n = 61) and TD children (n = 72). The results showed that the proposed DSS achieved up to 87.5% success rate in the early assessment of ASD in young children. Findings suggested that visual attention is a unique, promising biomarker for early assessment of ASD. Study results were discussed, and suggestions for future research were provided.

Distance from Typical Scan Path When Viewing Complex Stimuli in Children with Autism Spectrum Disorder and its Association with Behavior

Eye-tracking is often used to study attention in children with autism spectrum disorder (ASD). Previous research has identified multiple atypical patterns of attention in children with ASD based on areas-of-interest analysis. Fewer studies have investigated gaze path, a measure which is dependent on the dynamic content of the stimulus presented. Here, rather than looking at proportions of looking time to areas of interest, we calculated mean fixations frame-by-frame in a group of typically developing children (36 to 72 months) and determined the distance from those typical fixations for 155 children with ASD (27-95 months). Findings revealed that distance from the typical scan path among the children with ASD was associated with lower communication abilities and greater ASD symptomatology.

Dynamic emotional messages differentially affect 6-month-old infants' attention to eyes and gaze cues

Infants often experience interactions in which caregivers use dynamic messages to convey their affective and communicative intent. These dynamic emotional messages may shape the development of emotion discrimination skills and shared attention by influencing infants' attention to internal facial features and their responses to eye gaze cues. However, past research examining infants' responses to emotional faces has predominantly focused on classic, stereotyped expressions (e.g., happy, sad, angry) that may not reflect the variability that infants experience in their daily interactions. The present study therefore examined forty-two 6-month-old infants' attention to eyes vs. mouth and gaze cueing responses across multiple dynamic emotional messages that are common to infant-directed interactions. Overall, infants looked more to the eyes during messages with negative affect, but this increased attention to the eyes during these message conditions did not directly facilitate gaze cueing. Infants instead showed reliable gaze cueing only after messages with positive and neutral affect. We additionally observed gender differences in infants' attention to internal face features and subsequent gaze cueing responses. Female infants spent more time looking at the eyes during the dynamic emotional messages and showed increased initial orienting and longer looking to gaze-cued objects following positive messages, whereas male infants showed these gaze cueing effects following neutral messages. These results suggest that variability in caregivers' communication can shape infants' attention to and processing of emotion and gaze information.

The feasibility of Gazefinder under 12 months of age infants

Eye-tracking to evaluate gaze patterns has developed as an assessment tool for children with autism spectrum disorder (ASD). Gazefinder is one of Eye-tracking devices and few studies have investigated whether it can measure the gaze data of infants under 12 months of age. We conducted a prospective cross-sectional study from April 2019 to March 2020 in a periodic health checkup in Ohchi County, Shimane, Japan. Participants included infants between 4 and 11 months of age who were not suspected the presence of developmental problems. Ninety-three participants’ datapoints were analyzed. The mean age was 6.5 months and mean developmental quotient was 88%. The mean fixation time percentage of all sequences was 81.0% (standard deviation; 4.4), and there was no significant difference in each age group. Infants in all groups showed a significantly higher predilection for eyes than for mouths. There was a positive association of age with human gaze and a negative association with geometric gaze. Moreover, we confirmed that joint attention skills were enhanced in accordance with their growth process. The eye-tracking data were almost corresponding to previous studies’ data of infant with typical development and Gazefinder could be applied to infants starting at 4 months of age.