Increased attention to snake images in cynomolgus monkeys: an eye-tracking study.

Joint attention (JA), whose deficit is an early risk marker for autism spectrum disorder (ASD), has two dimensions: (1) responding to JA and (2) initiating JA. Eye-tracking technology has largely been used to investigate responding JA, but rarely to study initiating JA especially in young children with ASD. The aim of this study was to describe the differences in the visual patterns of toddlers with ASD and those with typical development (TD) during both responding JA and initiating JA tasks. Eye-tracking technology was used to monitor the gaze of 17 children with ASD and 15 age-matched children with TD during the presentation of short video sequences involving one responding JA and two initiating JA tasks (initiating JA-1 and initiating JA-2). Gaze accuracy, transitions and fixations were analyzed. No differences were found in the responding JA task between children with ASD and those with TD, whereas, in the initiating JA tasks, different patterns of fixation and transitions were shown between the groups. These results suggest that children with ASD and those with TD show different visual patterns when they are expected to initiate joint attention but not when they respond to joint attention. We hypothesized that differences in transitions and fixations are linked to ASD impairments in visual disengagement from face, in global scanning of the scene and in the ability to anticipate object's action.

Deficits in responding to joint attention (RJA) are early symptoms of autism spectrum disorder (ASD). Currently, no automated tools exist for identifying and quantifying RJA behaviors. A few eye tracking studies have investigated RJA in ASD children but have produced conflicting results. In addition, little is known about the trajectory of RJA development through developmental age. Here, a new video was designed including 12 clips of an actor pointing to or looking at an object. Eye tracking technology was used to monitor RJA in three groups: 143 ASD children assessed with the Autism Diagnostic Interview-Revised (ADI-R) and the Autism Diagnostic Observation Schedule (ADOS) (4–7 years old), 113 age- and gender-matched typically developing children (TDC), and 43 typically developing adults (TDA) (19–32 years old). RJAfinder was developed in R and MATLAB to quantify RJA events from the eye tracking data. RJA events were compared among the three groups. Spearman correlation coefficients between total number of RJA events in ASD and the Social Responsiveness Scale (SRS) scores were calculated. A logistic regression model was built using the average valid sampling rate and the total number of RJA events as two predictive variables to classify ASD and TDC groups. ASD children displayed statistically significantly less RJA events than the TDC and TDA groups with medium-to-large-sized effects. ASD and TDC children both displayed more RJA events in response to pointing stimuli than to looking stimuli. Our logistic regression model predicted ASD tendency with 0.76 accuracy in the testing set. RJA ability improved more slowly between the ages of 4–7 years old in the ASD group than in the TDC group. In ASD children, RJA ability showed negative correlation with SRS total T-score as well as the scores of five subdomains. Our study provides an automated tool for quantifying RJA and insights for the study of RJA in ASD children, which may help improve ASD screening, subtyping, and behavior interventions.

SIR–In a recent article, Rossignol and Frye provided a very complete review of melatonin in pervasive developmental disorders (PDD). In this work, the authors usefully explored the scientific literature about the physiopathology of melatonin in PDD, and reported the first meta-analytic results of melatonin use in sleep-disturbed individuals with PDD. Our purpose in this letter is to discuss the legitimacy of considering Rett syndrome when meta-analysing sleep parameters in autism spectrum disorders (ASD). Rett syndrome proceeds from a progressive encephalopathy of monogenic origin and although its early clinical picture (between 1 and 3y) can include autistic-like manifestations, it is very rarely considered in the specialized community as forming a pertinent part of autism spectrum disorders (ASD). Indeed, in the proceedings of the ‘Autism and other pervasive developmental disorders conference’ Rett syndrome is characterized as a ‘non-ASD that presents with PDD symptoms’; it will be removed from ASD in the forthcoming fifth version of the Diagnostic and Statistical Manual of Mental Disorders, and also probably from the psychiatric section of the International Classification of Diseases, 11th revision. Sleep problems in Rett syndrome generally appear in the latest phase (IV) of the disease, whereas sleep problems in autism generally begin during early childhood. Moreover, sleep problems which are characteristically seen in Rett syndrome are irregular sleep ⁄wake patterns, excessive daytime sleep, and night-time emotional behavior (screaming, crying, and laughing), whereas those seen in autism are settling difficulties, long sleep latency, frequent ⁄ long nocturnal awakenings, and early-morning awakenings. Thus, sleep disturbances in Rett syndrome and autism can be considered different in nature. For these reasons, we believe that autism spectrum conditions and Rett syndrome should be considered separately in sleep studies, and therefore that the data collected in Rett syndrome should not be included in a meta-analysis of melatonin effects on sleep in individuals with ASD. In the research of Rossignol and Frye, this point of controversy could be resolved by verifying the stability of the meta-analytic results when removing the Rett syndrome data. To conclude, in the abstract, the authors wrote that ‘Melatonin administration in ASD is associated with ... better daytime behavior ...’; however, as mentioned later in the article (p 7), only a single study has explored this topic in a placebo-controlled manner, which reports no improvement in daytime behaviour with melatonin compared to placebo. Thus, despite the fact that it is often seen in clinical practice and has been repeatedly reported in open studies, improvement in behaviour in children with ASD with melatonin has not thus far been demonstrated. This argues for further research about the efficiency of melatonin in sleep-disturbed individuals with ASD.

IntroductionChildren with Autism Spectrum Disorder (ASD) often find it difficult to maintain eye contact, which is vital for social communication. Eye tracking (ET) technology helps determine how long children with ASD focus on someone, how frequently they do so, and in which direction their gaze moves. ET provides insights into social attention by enabling precise, real-time tracking of gaze patterns as individuals process social information visually. It is a dependable method for identifying and developing social attentional biomarkers, particularly in challenging conditions like ASD.ObjectiveThis study aims to implement deep learning (DL) algorithms using eye-tracking data from social attention tasks involving children with ASD.MethodsThe approach was tested using standard datasets collected from individuals with and without ASD through eye-tracking technology. Convolutional neural networks (CNNs) and long short-term memory (LSTM) models were used to analyze data from children with ASD. Data preprocessing techniques addressed missing data and converted categorical features into numerical values. Mutual information-based feature selection was employed to reduce the feature set by identifying the most relevant features, thereby improving system performance. These features were then analyzed using LSTM and CNN-LSTM models to evaluate their potential for diagnosing ASD.ResultsThe experimental results showed that the highest accuracy achieved was 99.78% with the CNN-LSTM model. Furthermore, the findings indicated that the proposed method outperformed previous studies.ConclusionThe system successfully diagnosed ASD using the ET dataset. This approach shows promise for clinical application, assisting healthcare professionals in diagnosing ASD more accurately through advanced artificial intelligence technology.

How to deal with the transition from Pervasive Developmental Disorders in DSM‐IV to Autism Spectrum Disorder in DSM‐V

Atypical visual exploration of both social and nonsocial scenes is often reported in Autism Spectrum Disorder (ASD) with less precise and longer saccades, potentially reflecting difficulties in oculomotor control. To assess a subset of oculomotor functions in ASD, 20 children with ASD and 21 age-matched typically developing (TD) children (2.6-11.5 years) partook in three tasks of increasing complexity, while no explicit instruction was provided: a prosaccade gap task, a color and a "categorical" visual search tasks (a face among butterflies and vice-versa). In addition to classical saccade metrics, we measured Distance error, (the distance between the target and the closest gaze position) and Time-to-target (the time taken to reach the target). In the prosaccade task, children with ASD were as accurate as TD children, yet faster to reach the stimulus. In the color visual search task, children with ASD were faster but less precise than TD children. In the categorical visual search, while TD children were more precise in orienting their gaze towards the face, children with ASD performed similarly in the two conditions; Time-to-target did not differ. Our results provide contradictory evidence regarding enhanced visual search ability in ASD: when considering response times, enhanced visual search performance was found in one task only, while when considering gaze precision no advantage was found. These three experiments demonstrate that the automatic saccadic system may function more rapidly in children with ASD. Nonetheless, a diminished sensitivity to bottom-up saliency and top-down influence might suppress this advantage in more complex visual environments. Autism Res 2019, 12: 212-224 © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Three experiments with no instructions were designed to assess oculomotor functions in children with Autism Spectrum Disorder (ASD). In a saccade task, children with ASD were faster than but as accurate as control children. In visual search tasks, accuracy and speed decreased with increasing complexity of visual environment. Children with ASD showed faster automatic visual orientation, but this might hinder exploratory behaviors, leading to difficulties in complex and social situations.

The cognitive phenotypes of Rett syndrome (RTT) remain unclarified compared with the well-defined genetic etiology. Recent clinical studies suggest the eye-tracking method as a promising avenue to quantify the visual phenotypes of the syndrome. The present study explored various aspects of visual attention of the methyl-CpG-binding protein 2 gene mutant RTT monkeys with the eye-tracking procedure. Comprehensive testing paradigms, including social valence comparison (SVC), visual paired comparison (VPC), and social recognition memory (SRM), were utilized to investigate their attentional features to social stimuli with differential valence, the novelty preferences, and short-term recognition memory, respectively. To explore the neurobiological mechanisms underlying the eye-tracking findings, we assessed changes of the brain subregion volumes and neurotransmitter concentrations. Compared with control monkeys, RTT monkeys demonstrated increased viewing on the more salient stare faces than profile faces in the SVC test, and increased viewing on the whole presented images composed of monkey faces in the VPC and SRM tests. Brain imaging revealed reduced bilateral occipital gyrus in RTT monkeys. The exploratory neurotransmitter analyses revealed no significant changes of various neurotransmitter concentrations in the cerebrospinal fluid and blood of RTT monkeys. The eye-tracking results suggested social-valence-related increased attention in RTT monkeys, supplementing the cognitive phenotypes associated with the syndrome. Further investigations from broader perspectives are required to uncover the underlying neurobiological mechanisms. Autism Res 2019, 00: 1-13. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Altered expressions of the methyl-CpG-binding protein 2 (MECP2) gene are usually associated with neurodevelopmental disorders, such as autism spectrum disorders, Rett syndrome (RTT), and so forth. The present eye-tracking study found social-valence-related increased attention in our firstly established MECP2 mutant RTT monkeys. The novel findings supplement the cognitive phenotypes and potentially benefit the behavioral interventions of the RTT syndrome.

Statistical reasoning in nonhuman primates and human children

Children with autism spectrum disorder (ASD) have the deficits in emotional facial expression recognition and understanding, which is considered as the core source of their social communication disorder and stereotype behaviour. Previous studies have suggested that individuals with ASD have the deficits in the perception of static emotional facial expressions, but results are inconclusive. The use of 3D or dynamic facial stimuli that express emotions at different levels of intensities may produce more robust results, since these resemble the expression of emotions in daily life to a greater extent. In this study, 30 children (aged 2–7 years) with ASD and 51 age-matched children with typical development (TD) performed an emotion recognition (ER) task, in which morphs, presented on a computer screen, depicted facial expressions associated with two basic emotions (happiness and fear) at four levels of emotional intensity(25%–100%). Using a hybrid-design experiment and eye-tracking technology, we explored the influencing factors of ER in children with ASD and their interaction. In addition, we analyzed the gaze characteristics and processing patterns of children with ASD during the ER, and their impact on ER. The results showed that the type of subject, expression category, and intensity of expression had the main effect on recognition accuracy, and there was interaction among the factors that affected the emotional face recognition ability of the children with ASD. Moreover, children with ASD and TD both had an advantage when recognizing dynamic expressions rather than static expressions in 2D or 3D. The recognition accuracy of 3D expressions of children with TD was higher than that of 2D expressions, but children with ASD had the opposite result. The recognition accuracy of fearful expression for both ASD and TD groups was significantly better than that of happy expression. There was an interaction effect between gender and expression category, but age was not significant. In particular, girls’ facial expression recognition ability was superior to that of boys. The eye-tracking results showed that children with ASD have face-specific processing mechanisms: avoidance of eye contact, increased focus on the mouth and background information, and a preference for local feature processing. In conclusion, this study suggests that the material, category, and intensity of facial expression combines with the age and gender of subjects to affect the emotional expression recognition ability of children with ASD. Children with autism have the advantage of dynamic processing and mouth-directed gaze. In addition, dynamic facial expressions may be used as effective training and intervention materials for ER. Abnormal face processing and eye-tracking characteristics can help to understand the social disorders of ASD and provide behavioral characteristic indicators for early identification of ASD.

Dysregulated brain immunity and neurotrophin signaling in Rett syndrome and autism spectrum disorders.

Effects of visual search vs. auditory tasks on postural control in children with autism spectrum disorder

Therapeutic Advances in Autism and Other Neurodevelopmental Disorders.

SIR–We appreciate the comments of Drs Guenole and Baleyte regarding our meta-analysis on the effectiveness of melatonin for sleep-disturbed individuals with autism spectrum disorder (ASD) and their commentary regarding the inclusion of individuals with Rett syndrome. We, too, were concerned with the inclusion of this group and thus specifically addressed this in the results section of the article where we state that ‘The inclusion or exclusion of the one study containing syndromic ASD did not significantly change the results of the meta-analysis.’ Since we did not present the changes in the meta-analysis with the exclusion of children with Rett syndrome, we present them below. The only study of the five double-blind placebo-controlled studies included in the meta-analysis that included patients with Rett syndrome was the study of McArthur et al. This study contained nine (16%) of the 57 participants in the metaanalysis. Removing the McArthur et al. study from the metaanalysis increases the Hedge’s g and Glass’s D effect sizes of sleep duration from 1.08 to 1.20 and 0.94 to 1.02 respectively, with virtually no change in the z-scores of the effect sizes (Hedge’s g z-score did not change from 3.58 and Glass’s delta z-score decreased slightly from 3.01 to 2.96). Similarly, removing the McArthur et al. study from the meta-analysis increases the Hedge’s g and Glass’s D effect sizes of sleep onset from 2.52 to 2.86 and 1.30 to 1.87 respectively, with a small increase in the z-scores (Hedge’s g z-score increased from 9.60 to 10.01 and Glass’s delta z-score increased from 4.12 to 5.18). Finally, removing the McArthur et al. study from the meta-analysis examining the number of night-time awakenings increases the Hedge’s g effect size from 0.50 to 0.57 and the Glass’s D effect size from 0.33 to 0.35, with small changes in the z-scores (Hedge’s g z-score increased from 1.74 to 1.79 and Glass’s delta z-score decreased from 1.11 to 1.06). The decision to include the study with participants with Rett syndrome within the meta-analysis was difficult since, as Drs Guenole and Baleyte point out, the characteristics of sleep disturbances as well as the neuropathology in Rett syndrome are different from those in children with idiopathic ASD. However, according to the current version of the DSM-IV, children with Rett syndrome are still considered to be within the category of pervasive developmental disorders. Removing the patients with Rett syndrome appears to increase the effect sizes of all of the variables analysed in our meta-analysis, suggesting that children with Rett syndrome may have a different and more difficult-to-treat sleep disorder. Our revised analysis supports the removal of Rett syndrome as a pervasive developmental disorder in the forthcoming version of the DSM. Finally, we also agree that further research on melatonin in individuals with both ASD and Rett syndrome is needed.

Eye-tracking studies have demonstrated that individuals with autism spectrum disorder sometimes show differences in attention and gaze patterns. This includes preference for certain nonsocial objects, heightened attention to detail, and more difficulty with attention shifting and disengagement, which may be associated with restricted and repetitive behaviors. This study utilized a visual exploration task and replicates findings of reduced number of objects explored and increased fixation duration on high autism interest objects in a large sample of individuals with autism spectrum disorder (n = 129, age 6-54 years) in comparison with a typically developing group. These findings correlated with parent-reported repetitive behaviors. Additionally, we applied recurrent quantification analysis to enable identification of new eye-tracking features, which accounted for temporal and spatial differences in viewing patterns. These new features were found to discriminate between autism spectrum disorder and typically developing groups and were correlated with parent-reported repetitive behaviors. Original and novel eye-tracking features identified by recurrent quantification analysis differed in their relationships to reported behaviors and were dependent on age. Trial Registration: NCT02299700. Autism Research 2018, 11: 1554-1566. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Using eye-tracking technology and a visual exploration task, we showed that people with autism spectrum disorder (ASD) spend more time looking at particular kinds of objects, like trains and clocks, and look at fewer objects overall than people without ASD. Where people look and the order in which they look at objects were related to the restricted and repetitive behaviors reported by parents. Eye-tracking may be a useful addition to parent reports for measuring changes in behavior in individuals with ASD.

In the post-epidemic era, an increasing number of individuals were accustomed to learning sports and physical activity knowledge online for fitness and health demands. However, most previous studies have examined the influence of e-learning materials and resources on learners and have neglected intrinsic factors such as experience and physiological characteristics. Therefore, we conducted a study to investigate the effect of exercise habits and gender on sports e-learning behavior via eye-tracking technology. We recruited a sample of 60 undergraduate students (mean age = 19.6) from a university in Nanjing, China. They were randomly assigned into 4 groups based on 2 genders × 2 exercise habits. Their gaze behavior was collected by an eye-tracking device during the experiment. The cognitive Load Test and Learning Effect Test were conducted at the end of the individual experiment. (1) Compared to the non-exercise habit group, the exercise habit group had a higher fixation count (P<0.05), a shorter average fixation duration (P<0.05), a smaller average pupil diameter (P<0.05), and a lower subjective cognitive load (P<0.05) and better learning outcome (P<0.05). (2) Male participants showed a greater tendency to process information from the video area of interest (AOIs), and had lower subjective cognitive load (P < 0.05) and better learning outcomes (P < 0.05). (3) There was no interaction effect between exercise habits and gender for any of the indicators (P > 0.05). Our results indicate that exercise habits effectively enhance sports e-learning outcomes and reduce cognitive load. The exercise habits group showed significant improvements in fixation counts, average fixation duration, and average pupil diameter. Furthermore, male subjects exhibited superior learning outcomes, experienced lower cognitive load, and demonstrated greater attentiveness to dynamic visual information. These conclusions are expected to improve sports e-learning success and address educational inequality.