Social attention to activities in children and adults with autism spectrum disorder: effects of context and age

Evaluating the validity of eye-tracking tasks and stimuli in detecting high-risk infants later diagnosed with autism: A meta-analysis

Gaze abnormalities are well documented in infants at elevated risk for autism spectrum disorder (ASD). However, variations in experimental design and stimuli across studies have led to mixed results. The current meta-analysis aimed to identify which type of eye tracking task and stimulus are most effective at differentiating high-risk infants (siblings of children with ASD) who later meet diagnosis criteria from low-risk infants without familial autism. We synthesized 35 studies that used eye tracking to investigate gaze behavior in infants at high genetic risk for autism before 2 years of age. We found that stimulus features, regions of interest (ROIs) and study quality moderated effect sizes across studies. Overall, dynamic stimuli and socially-relevant regions in the social stimuli (i.e. the target and activity of characters' shared focus) reliably detected high-risk infants who later develop ASD. Attention disengagement task and stimuli depicting interactions between human and nonhuman characters could identify high-risk infants who later develop ASD and those who have autism-related symptoms but do not meet the diagnostic criteria as well. These findings provide sensitive and reliable early markers of ASD, which is helpful to develop objective and quantitative early autism screening and intervention tools.

Autistic preschoolers display reduced attention orientation for competition but intact facilitation from a parallel competitor: Eye-tracking and behavioral data

LAY ABSTRACT

Recent research suggests that we might have underestimated the social motivation of autistic individuals. Autistic children might be engaged in a social situation, even if they seem not to be attending to people in a typical way. Our study investigated how young autistic children behave in a "parallel" situation, which we call "parallel competition," where people participate in friendly contests side-by-side but without direct interaction. First, we used eye-tracking technology to observe how much autistic children pay attention to two video scenarios: one depicting parallel competition, and the other where individuals play directly with each other. The results showed that autistic children looked less toward the parallel competition video than their typically developing peers. However, when autistic children took part in parallel competitions themselves, playing physical and cognitive games against a teacher, their performance improved relative to playing individually just as much as their typically developing peers. This suggests that even though autistic children pay attention to social events differently, they can still benefit from the presence of others. These findings suggest complementing traditional cooperative activities by incorporating parallel activities into educational programs for young autistic children. By doing so, we can create more inclusive learning environments for these children.

[Machine learning algorithms for identifying autism spectrum disorder through eye-tracking in different intention videos]

OBJECTIVES

To investigate the differences in visual perception between children with autism spectrum disorder (ASD) and typically developing (TD) children when watching different intention videos, and to explore the feasibility of machine learning algorithms in objectively distinguishing between ASD children and TD children.

METHODS

A total of 58 children with ASD and 50 TD children were enrolled and were asked to watch the videos containing joint intention and non-joint intention, and the gaze duration and frequency in different areas of interest were used as original indicators to construct classifier-based models. The models were evaluated in terms of the indicators such as accuracy, sensitivity, and specificity.

RESULTS

When using eight common classifiers, including support vector machine, linear discriminant analysis, decision tree, random forest, and K-nearest neighbors (with K values of 1, 3, 5, and 7), based on the original feature indicators, the highest classification accuracy achieved was 81.90%. A feature reconstruction approach with a decision tree classifier was used to further improve the accuracy of classification, and then the model showed the accuracy of 91.43%, the specificity of 89.80%, and the sensitivity of 92.86%, with an area under the receiver operating characteristic curve of 0.909 (P<0.001).

CONCLUSIONS

The machine learning model based on eye-tracking data can accurately distinguish ASD children from TD children, which provides a scientific basis for developing rapid and objective ASD screening tools.

Intact or impaired? The understanding of give-and-take interactions in children with autism spectrum disorder

BACKGROUND

Understanding and predicting others' behavior in a dynamic and rapidly changing world is a fundamental aspect of social interactions. However, it remains unclear as to whether children with autism spectrum disorder (ASD) could understand and predict goal-directed social actions.

AIMS

To investigate the understanding of give-and-take interactions in children with ASD with the use of eye tracking.

METHODS AND PROCEDURES

Experiment 1 and 2 investigated the understanding of giving and taking respectively in 5-to 8-year-old Chinese children with ASD and typically developing children by using the eye-tracking technology.

OUTCOMES AND RESULTS

We found that children with ASD could predict actions, but they were less proficient in processing give-and-take interactions. Moreover, children with ASD showed impaired understanding of giving but not taking.

CONCLUSIONS

These results indicate that the basic mechanisms of action prediction are intact in children with ASD whereas there may be deficits in the top-down social processing of the giving gesture.

Diminished emotion recognition with reduced face gaze in complex situation in individuals with broad autism phenotype

Background/objective

Individuals with broad autism phenotype (BAP) showed a diminished ability to recognize emotion. This study aims to examine whether their decline in emotion recognition ability could be more clearly identified as task complexity increased and whether their decline could be influenced by their eye-gaze patterns.

Method

41 individuals with BAP and 40 healthy controls performed two types of emotion recognition tasks. After confirming conditions wherein the BAP group did not perform well compared to the control group, we compared gaze proportion on faces and context between groups when performing the conditions.

Results

The more difficult the task, the clearer the significant relationships between the level of autistic traits and emotion recognition ability. The BAP group showed lower accuracy compared to the control group when a face with mild emotional intensity was presented with context. In terms of gaze proportion, the BAP group looked less at faces when recognizing emotions compared to the control group.

Conclusion

These findings indicate that diminished emotion recognition ability in individuals with BAP may be influenced by face gaze.

ECG Recordings as Predictors of Very Early Autism Likelihood: A Machine Learning Approach

In recent years, there has been a rise in the prevalence of autism spectrum disorder (ASD). The diagnosis of ASD requires behavioral observation and standardized testing completed by highly trained experts. Early intervention for ASD can begin as early as 1-2 years of age, but ASD diagnoses are not typically made until ages 2-5 years, thus delaying the start of intervention. There is an urgent need for non-invasive biomarkers to detect ASD in infancy. While previous research using physiological recordings has focused on brain-based biomarkers of ASD, this study investigated the potential of electrocardiogram (ECG) recordings as an ASD biomarker in 3-6-month-old infants. We recorded the heart activity of infants at typical and elevated familial likelihood for ASD during naturalistic interactions with objects and caregivers. After obtaining the ECG signals, features such as heart rate variability (HRV) and sympathetic and parasympathetic activities were extracted. Then we evaluated the effectiveness of multiple machine learning classifiers for classifying ASD likelihood. Our findings support our hypothesis that infant ECG signals contain important information about ASD familial likelihood. Amongthe various machine learning algorithms tested, KNN performed best according to sensitivity (0.70 ± 0.117), F1-score (0.689 ± 0.124), precision (0.717 ± 0.128), accuracy (0.70 ± 0.117, p-value = 0.02), and ROC (0.686 ± 0.122, p-value = 0.06). These results suggest that ECG signals contain relevant information about the likelihood of an infant developing ASD. Future studies should consider the potential of information contained in ECG, and other indices of autonomic control, for the development of biomarkers of ASD in infancy.

Level of Attention to Motherese Speech as an Early Marker of Autism Spectrum Disorder

Importance

Caregivers have long captured the attention of their infants by speaking in motherese, a playful speech style characterized by heightened affect. Reduced attention to motherese in toddlers with autism spectrum disorder (ASD) may be a contributor to downstream language and social challenges and could be diagnostically revealing.

Objective

To investigate whether attention toward motherese speech can be used as a diagnostic classifier of ASD and is associated with language and social ability.

Design, Setting, and Participants

This diagnostic study included toddlers aged 12 to 48 months, spanning ASD and non-ASD diagnostic groups, at a research center. Data were collected from February 2018 to April 2021 and analyzed from April 2021 to March 2022.

Exposures

Gaze-contingent eye-tracking test.

Main Outcomes and Measures

Using gaze-contingent eye tracking wherein the location of a toddler's fixation triggered a specific movie file, toddlers participated in 1 or more 1-minute eye-tracking tests designed to quantify attention to motherese speech, including motherese vs traffic (ie, noisy vehicles on a highway) and motherese vs techno (ie, abstract shapes with music). Toddlers were also diagnostically and psychometrically evaluated by psychologists. Levels of fixation within motherese and nonmotherese movies and mean number of saccades per second were calculated. Receiver operating characteristic (ROC) curves were used to evaluate optimal fixation cutoff values and associated sensitivity, specificity, positive predictive value (PPV), and negative predictive value. Within the ASD group, toddlers were stratified based on low, middle, or high levels of interest in motherese speech, and associations with social and language abilities were examined.

Results

A total of 653 toddlers were included (mean [SD] age, 26.45 [8.37] months; 480 males [73.51%]). Unlike toddlers without ASD, who almost uniformly attended to motherese speech with a median level of 82.25% and 80.75% across the 2 tests, among toddlers with ASD, there was a wide range, spanning 0% to 100%. Both the traffic and techno paradigms were effective diagnostic classifiers, with large between-group effect sizes (eg, ASD vs typical development: Cohen d, 1.0 in the techno paradigm). Across both paradigms, a cutoff value of 30% or less fixation on motherese resulted in an area under the ROC curve (AUC) of 0.733 (95% CI, 0.693-0.773) and 0.761 (95% CI, 0.717-0.804), respectively; specificity of 98% (95% CI, 95%-99%) and 96% (95% CI, 92%-98%), respectively; and PPV of 94% (95% CI, 86%-98%). Reflective of heterogeneity and expected subtypes in ASD, sensitivity was lower at 18% (95% CI, 14%-22%) and 29% (95% CI, 24%-34%), respectively. Combining metrics increased the AUC to 0.841 (95% CI, 0.805-0.877). Toddlers with ASD who showed the lowest levels of attention to motherese speech had weaker social and language abilities.

Conclusions and Relevance

In this diagnostic study, a subset of toddlers showed low levels of attention toward motherese speech. When a cutoff level of 30% or less fixation on motherese speech was used, toddlers in this range were diagnostically classified as having ASD with high accuracy. Insight into which toddlers show unusually low levels of attention to motherese may be beneficial not only for early ASD diagnosis and prognosis but also as a possible therapeutic target.

Unique dynamic profiles of social attention in autistic females

BACKGROUND

Social attention affords learning opportunities across development and may contribute to individual differences in developmental trajectories, such as between male and female individuals, and in neurodevelopmental conditions, such as autism.

METHODS

Using eye-tracking, we measured social attention in a large cohort of autistic (n = 123) and nonautistic females (n = 107), and autistic (n = 330) and nonautistic males (n = 204), aged 6-30 years. Using mixed Growth Curve Analysis, we modelled sex and diagnostic effects on the temporal dynamics of proportional looking time to three types of social stimuli (lean-static, naturalistic-static, and naturalistic-dynamic) and examined the link between individual differences and dimensional social and nonsocial autistic traits in autistic females and males.

RESULTS

In the lean-static stimulus, average face-looking was higher in females than in males of both autistic and nonautistic groups. Differences in the dynamic pattern of face-looking were seen in autistic vs. nonautistic females, but not males, with face-looking peaking later in the trial in autistic females. In the naturalistic-dynamic stimulus, average face-looking was higher in females than in males of both groups; changes in the dynamic pattern of face looking were seen in autistic vs. nonautistic males, but not in females, with a steeper peak in nonautistic males. Lower average face-looking was associated with higher observer-measured autistic characteristics in autistic females, but not in males.

CONCLUSIONS

Overall, we found stronger social attention in females to a similar degree in both autistic and nonautistic groups. Nonetheless, the dynamic profiles of social attention differed in different ways in autistic females and males compared to their nonautistic peers, and autistic traits predicted trends of average face-looking in autistic females. These findings support the role of social attention in the emergence of sex-related differences in autistic characteristics, suggesting an avenue to phenotypic stratification.

Gaze and social functioning associations in autism spectrum disorder: A systematic review and meta-analysis

Autism spectrum disorder (ASD) is characterized by significant social functioning impairments, including (but not limited to) emotion recognition, mentalizing, and joint attention. Despite extensive investigation into the correlates of social functioning in ASD, only recently has there been focus on the role of low‐level sensory input, particularly visual processing. Extensive gaze deficits have been described in ASD, from basic saccadic function through to social attention and the processing of complex biological motion. Given that social functioning often relies on accurately processing visual information, inefficient visual processing may contribute to the emergence and sustainment of social functioning difficulties in ASD. To explore the association between measures of gaze and social functioning in ASD, a systematic review and meta‐analysis was conducted. A total of 95 studies were identified from a search of CINAHL Plus, Embase, OVID Medline, and psycINFO databases in July 2021. Findings support associations between increased gaze to the face/head and eye regions with improved social functioning and reduced autism symptom severity. However, gaze allocation to the mouth appears dependent on social and emotional content of scenes and the cognitive profile of participants. This review supports the investigation of gaze variables as potential biomarkers of ASD, although future longitudinal studies are required to investigate the developmental progression of this relationship and to explore the influence of heterogeneity in ASD clinical characteristics.

Large scale validation of an early-age eye-tracking biomarker of an autism spectrum disorder subtype

Few clinically validated biomarkers of ASD exist which can rapidly, accurately, and objectively identify autism during the first years of life and be used to support optimized treatment outcomes and advances in precision medicine. As such, the goal of the present study was to leverage both simple and computationally-advanced approaches to validate an eye-tracking measure of social attention preference, the GeoPref Test, among 1,863 ASD, delayed, or typical toddlers (12-48 months) referred from the community or general population via a primary care universal screening program. Toddlers participated in diagnostic and psychometric evaluations and the GeoPref Test: a 1-min movie containing side-by-side dynamic social and geometric images. Following testing, diagnosis was denoted as ASD, ASD features, LD, GDD, Other, typical sibling of ASD proband, or typical. Relative to other diagnostic groups, ASD toddlers exhibited the highest levels of visual attention towards geometric images and those with especially high fixation levels exhibited poor clinical profiles. Using the 69% fixation threshold, the GeoPref Test had 98% specificity, 17% sensitivity, 81% PPV, and 65% NPV. Sensitivity increased to 33% when saccades were included, with comparable validity across sex, ethnicity, or race. The GeoPref Test was also highly reliable up to 24 months following the initial test. Finally, fixation levels among twins concordant for ASD were significantly correlated, indicating that GeoPref Test performance may be genetically driven. As the GeoPref Test yields few false positives (~ 2%) and is equally valid across demographic categories, the current findings highlight the ability of the GeoPref Test to rapidly and accurately detect autism before the 2nd birthday in a subset of children and serve as a biomarker for a unique ASD subtype in clinical trials.

Comparing internal representations of facial expression kinematics between autistic and non-autistic adults

Recent developments suggest that autistic individuals require dynamic angry expressions to have a higher speed in order for them to be successfully identified. Therefore, it is plausible that autistic individuals do not have a 'deficit' in angry expression recognition, but rather their internal representation of these expressions is characterised by very high-speed movement. In this study, matched groups of autistic and non-autistic adults completed a novel emotion-based task which employed dynamic displays of happy, angry and sad point light facial (PLF) expressions. On each trial, participants moved a slider to manipulate the speed of a PLF stimulus until it moved at a speed that, in their 'mind's eye', was typical of happy, angry or sad expressions. Participants were shown three different types of PLFs-those showing the full-face, only the eye region, and only the mouth region, wherein the latter two were included to test whether differences in facial information sampling underpinned any dissimilarities in speed attributions. Across both groups, participants attributed the highest speeds to angry, then happy, then sad, facial motion. Participants increased the speed of angry and happy expressions by 41% and 27% respectively and decreased the speed of sad expressions by 18%. This suggests that participants have 'caricatured' internal representations of emotion, wherein emotion-related kinematic cues are over-emphasised. There were no differences between autistic and non-autistic individuals in the speeds attributed to full-face and partial-face angry, happy and sad expressions respectively. Consequently, we find no evidence that autistic adults possess atypically fast internal representations of anger.

Visual Exploration and Observation of Real-Life Interactions Between Children with ASD and Service Dogs

Two original studies explored relationships between visual attention of children with ASD (candidates for receiving a service dog) and their behaviors during their first interaction with a service dog. The first study consisted in video behavioural analyses of 16 children with ASD interacting with a service dog. During the interaction with a service dog, the time children with ASD spent looking towards social items vs objects was associated with how they interacted with the service dog. The second study was exploratory (i.e. 6 children), using the same behavioural approach but coupled with eye-tracking data. The more children with ASD looked at both their parent and the evaluator, as opposed to inanimate items, the more they interacted with the service dog.