Development of an Objective Autism Risk Index Using Remote Eye Tracking

Development and validation of an Arabic language eye-tracking paradigm for the early screening and diagnosis of autism spectrum disorders in Qatar

Abnormal eye gaze is a hallmark characteristic of autism spectrum disorder (ASD). The primary aim of the present research was to develop an Arabic version of an objective measure of ASD, the "autism index" (AI), based on eye gaze tracking to social and nonsocial stimuli validated initially in the United States. The initial phase of this study included the translation of English language eye-tracking stimuli into stimuli appropriate for an Arabic-speaking culture. During the second phase, we tested it on a total of 144 children with ASD, and 96 controls. The AI had excellent internal consistency and test-retest reliability. Moreover, the AI showed good differentiation of ASD from control cases (AUC = 0.730, SE = 0.035). The AI was significantly positively correlated with SCQ total raw scores (r = 0.46, p < 0.001). ADOS-2 scores were only available in the ASD group and did not show a significant relationship with AI scores (r = 0.10, p = 0.348), likely due to the restricted range. The AI, when implemented using Arabic-translated stimuli in a Qatari sample, showed good diagnostic differentiation and a strong correlation with parent-reported ASD symptoms. Thus, the AI appears to have cross-cultural validity and may be useful as a diagnostic aide to inform clinical judgment and track ASD symptom levels as part of the evaluation process.

Attention Allocation During Exploration of Visual Arrays in ASD: Results from the ABC-CT Feasibility Study

Visual exploration paradigms involving object arrays have been used to examine salience of social stimuli such as faces in ASD. Recent work suggests performance on these paradigms may associate with clinical features of ASD. We evaluate metrics from a visual exploration paradigm in 4-to-11-year-old children with ASD (n = 23; 18 males) and typical development (TD; n = 23; 13 males). Presented with arrays containing faces and nonsocial stimuli, children with ASD looked less at (p = 0.002) and showed fewer fixations to (p = 0.022) faces than TD children, and spent less time looking at each object on average (p = 0.004). Attention to the screen and faces correlated positively with social and cognitive skills in the ASD group (ps < .05). This work furthers our understanding of objective measures of visual exploration in ASD and its potential for quantifying features of ASD.

Eye-tracking measures of social versus nonsocial attention are related to level of social engagement during naturalistic caregiver-child interactions in autistic children

Eye-tracking (ET) measures indexing social attention have been proposed as sensitive measures related to autism, but less is known about the relationship between social and nonsocial attention and naturalistic measures of social engagement and whether sex moderates this relationship. This study investigated ET measures of social attention as predictors of social engagement during a naturalistic caregiver-child interaction (CCI). Participants included 132, 2-7-year-old autistic children (77% male) and their caregivers. Participants engaged in a CCI and an ET task in which they viewed a video of an actor making dyadic bids toward the child with toys in the background. Pearson correlations and multiple regression analyzes revealed that ET measures correlated with social engagement behaviors, including degree of attention to the caregiver and objects, joint engagement with the caregiver, and language-based joint engagement. Children who spent more time looking at toys were more likely to be unengaged during social interaction. Those who spent more time looking at the actor's mouth were more likely to engage in coordinated play with and without language. Sex moderated the relationship between time looking at toys and unengagement during play; males who spent more time looking at toys spent more time unengaged during play, whereas females who spent more time looking at toys spent less time unengaged during play. Overall, ET measures of social and nonsocial attention correlated with the level of social engagement during naturalistic play, with some sex differences. Eye-tracking measures that predict interaction patterns may provide insight into promoting social engagement between caregivers and their autistic children and can inform outcome monitoring and intervention development.

Effects of different types of visual music on the prefrontal hemodynamics of children with autism spectrum disorder based on functional near-infrared spectroscopy

BACKGROUND

Music therapy has been shown to improve communication in children with autism spectrum disorders (ASD), but little is known about how different types of music and images affect hemodynamic changes in the frontal lobe of the brain in children with ASD. This study aims to use functional near infrared spectroscopy (fNIRS) to explore the effects of different types of visual music on different brain regions of oxyhemoglobin (HbO) in the prefrontal lobe of children with ASD and children with typical development (TD), so as to provide evidence for better application of different types of visual music in the treatment of children with ASD.

METHODS

Seven children with ASD and nine matched children with TD were selected. Changes in HbO in their prefrontal lobes were determined by fNIRS after resting states and 12 different types of visual music tasks.

RESULTS

(I) Intra-group comparison: the influence of different types of light and music on ∆HbO in ROI (zone F) of ASD children is different, the activation degree shows that red light & positive music is less than green light & neutral music, red light & positive music is less than blue light & negative music, and there is no difference between green light & neutral music and blue light & negative music. (II) Comparison between groups: Visual musical tasks 1, 2, 3, 4, and 8 positively activated HbO in the prefrontal B and E regions of the brain in children with ASD and negatively activated HbO in TD children. Visual musical tasks 5, 9, 10, and 12 negatively activated HbO in the prefrontal F regions of the brain in children with ASD and positively activated HbO in TD children.

CONCLUSIONS

When the two groups of children received the same visual music task, the changes of HbO in different regions of the prefrontal lobe were different; The effects of different types of visual music on the frontal lobe of the brain in children with ASD are inconsistent.

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.

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.

Electrooculography and Tactile Perception Collaborative Interface for 3D Human-Machine Interaction

The human-machine interface (HMI) previously relied on a single perception interface that cannot realize three-dimensional (3D) interaction and convenient and accurate interaction in multiple scenes. Here, we propose a collaborative interface including electrooculography (EOG) and tactile perception for fast and accurate 3D human-machine interaction. The EOG signals are mainly used for fast, convenient, and contactless 2D (XY-axis) interaction, and the tactile sensing interface is mainly utilized for complex 2D movement control and Z-axis control in the 3D interaction. The honeycomb graphene electrodes for the EOG signal acquisition and tactile sensing array are prepared by a laser-induced process. Two pairs of ultrathin and breathable honeycomb graphene electrodes are attached around the eyes for monitoring nine different eye movements. A machine learning algorithm is designed to train and classify the nine different eye movements with an average prediction accuracy of 92.6%. Furthermore, an ultrathin (90 μm), stretchable (∼1000%), and flexible tactile sensing interface assembled by a pair of 4 × 4 planar electrode arrays is attached to the arm for 2D movement control and Z-axis interaction, which can realize single-point, multipoint and sliding touch functions. Consequently, the tactile sensing interface can achieve eight directions control and even more complex movement trajectory control. Meanwhile, the flexible and ultrathin tactile sensor exhibits an ultrahigh sensitivity of 1.428 kPa^-1 in the pressure range 0-300 Pa with long-term response stability and repeatability. Therefore, the collaboration between EOG and the tactile perception interface will play an important role in rapid and accurate 3D human-machine interaction.

Annual Research Review: Translational machine learning for child and adolescent psychiatry

Children and adolescents could benefit from the use of predictive tools that facilitate personalized diagnoses, prognoses, and treatment selection. Such tools have not yet been deployed using traditional statistical methods, potentially due to the limitations of the paradigm and the need to leverage large amounts of digital data. This review will suggest that a machine learning approach could address these challenges and is designed to introduce new readers to the background, methods, and results in the field. A rationale is first introduced followed by an outline of fundamental elements of machine learning approaches. To provide an overview of the use of the techniques in child and adolescent literature, a scoping review of broad trends is then presented. Selected studies are also highlighted in order to draw attention to research areas that are closest to translation and studies that exhibit a high degree of experimental innovation. Limitations to the research, and machine learning approaches generally, are outlined in the penultimate section highlighting issues related to sample sizes, validation, clinical utility, and ethical challenges. Finally, future directions are discussed that could enhance the possibility of clinical implementation and address specific questions relevant to the child and adolescent psychiatry. The review gives a broad overview of the machine learning paradigm in order to highlight the benefits of a shift in perspective towards practically oriented statistical solutions that aim to improve clinical care of children and adolescents.

Computer-Aided Screening of Autism Spectrum Disorder: Eye-Tracking Study Using Data Visualization and Deep Learning

Background

The early diagnosis of autism spectrum disorder (ASD) is highly desirable but remains a challenging task, which requires a set of cognitive tests and hours of clinical examinations. In addition, variations of such symptoms exist, which can make the identification of ASD even more difficult. Although diagnosis tests are largely developed by experts, they are still subject to human bias. In this respect, computer-assisted technologies can play a key role in supporting the screening process.

Objective

This paper follows on the path of using eye tracking as an integrated part of screening assessment in ASD based on the characteristic elements of the eye gaze. This study adds to the mounting efforts in using eye tracking technology to support the process of ASD screening

Methods

The proposed approach basically aims to integrate eye tracking with visualization and machine learning. A group of 59 school-aged participants took part in the study. The participants were invited to watch a set of age-appropriate photographs and videos related to social cognition. Initially, eye-tracking scanpaths were transformed into a visual representation as a set of images. Subsequently, a convolutional neural network was trained to perform the image classification task.

Results

The experimental results demonstrated that the visual representation could simplify the diagnostic task and also attained high accuracy. Specifically, the convolutional neural network model could achieve a promising classification accuracy. This largely suggests that visualizations could successfully encode the information of gaze motion and its underlying dynamics. Further, we explored possible correlations between the autism severity and the dynamics of eye movement based on the maximal information coefficient. The findings primarily show that the combination of eye tracking, visualization, and machine learning have strong potential in developing an objective tool to assist in the screening of ASD.

Conclusions

Broadly speaking, the approach we propose could be transferable to screening for other disorders, particularly neurodevelopmental disorders.

Contribution of Eye-Tracking to Study Cognitive Impairments Among Clinical Populations

In the field of psychology, the merge of decision-theory and neuroscientific methods produces an array of scientifically recognized paradigms. For example, by exploring consumer’s eye-movement behavior, researchers aim to deepen the understanding of how patterns of retinal activation are being meaningfully transformed into visual experiences and connected with specific reactions (e.g., purchase). Notably, eye-movements provide knowledge of one’s homeostatic balance and gatekeep information that shape decisions. Hence, vision science investigates the quality of observed environments determined under various experimental conditions. Moreover, it answers questions on how human process visual stimuli and use gained information for a successful strategy to achieve certain goals. While capturing cognitive states with the support of the eye-trackers progresses at a relatively fast pace in decision-making research, measuring the visual performance of real-life tasks, which require complex cognitive skills, is tentatively translated into clinical experiments. Nevertheless, the potential of the human eye as a highly valuable source of biomarkers has been underlined. In this article, we aim to draw readers attention to decision-making experimental paradigms supported with eye-tracking technology among clinical populations. Such interdisciplinary approach may become an important component that will (i) help in objectively illustrating patient’s models of beliefs and values, (ii) support clinical interventions, and (iii) contribute to health services. It is possible that shortly, eye-movement data from decision-making experiments will grant the scientific community a greater understanding of mechanisms underlining mental states and consumption practices that medical professionals consider as obsessions, disorders or addiction.

Evidence-based use of scalable biomarkers to increase diagnostic efficiency and decrease the lifetime costs of autism

Challenges associated with the current screening and diagnostic process for autism spectrum disorder (ASD) in the US cause a significant delay in the initiation of evidence-based interventions at an early age when treatments are most effective. The present study shows how implementing a second-order diagnostic measure to high risk cases initially flagged positive from screening tools can further inform clinical judgment and substantially improve early identification. We use two example measures for the purposes of this demonstration; a saliva test and eye-tracking technology, both scalable and easy-to-implement biomarkers recently introduced in ASD research. Results of the current cost-savings analysis indicate that lifetime societal cost savings in special education, medical and residential care are estimated to be nearly $580,000 per ASD child, with annual cost savings in education exceeding $13.3 billion, and annual cost savings in medical and residential care exceeding $23.8 billion (of these, nearly $11.2 billion are attributable to Medicaid). These savings total more than $37 billion/year in societal savings in the US. Initiating appropriate interventions faster and reducing the number of unnecessary diagnostic evaluations can decrease the lifetime costs of ASD to society. We demonstrate the value of implementing a scalable highly accurate diagnostic in terms of cost savings to the US. LAY SUMMARY: This paper demonstrates how biomarkers with high accuracy for detecting autism spectrum disorder (ASD) could be used to increase the efficiency of early diagnosis. Results also show that, if more children with ASD are identified early and referred for early intervention services, the system would realize substantial costs savings across the lifespan.

Social attention as a cross-cultural transdiagnostic neurodevelopmental risk marker

The primary objectives of this study were to evaluate the structure and age-related stability of social attention in English and Arabic-speaking youth and to compare social attention between children with autism spectrum disorder (ASD), other developmental disabilities (DD), and typically-developing controls. Eye-tracking data were collected from US (N = 270) and Qatari (N = 242) youth ages 1-17, including children evaluated for possible ASD. Participants viewed 44 stimuli from seven social paradigms. Fixation was computed for areas of interest within each stimulus. Latent variable models examined the structure of social attention. Generalized estimating equation models examined the effect of age, sex, culture, and diagnostic group on social attention. The best-fitting model included a general social attention factor and six specific factors. Cultural differences in social attention were minimal and social attention was stable across age (r = 0.03), but females showed significantly greater social attention than males (d = 0.28). Social attention was weaker in DD (d = -0.17) and lowest in ASD (d = -0.38) relative to controls. Differences were of sufficient magnitude across areas-of-interest to reliably differentiate DD from controls (AUC = 0.80) and ASD-only from all other cases (AUC = 0.76). A social attention dimension that represents an early-life preference for socially salient information was identified. This preference was cross-culturally consistent and stable across development but stronger in females and weaker in DD, especially ASD. Given rapid and easy-to-collect remote eye tracking administration, social attention measurement may be useful for developmental monitoring. Acquisition of population norms, analogous to height/weight/head circumference, might enhance early screening and tracking of neurodevelopment. LAY SUMMARY: This research found that social attention is a single dimension of behavior that represents a strong preference for social stimuli, is consistent across cultures, stable across age, and stronger in females. Children with developmental disabilities had lower levels of social attention than neurotypical children and children with autism spectrum disorder had the lowest levels of social attention.

A Unique Visual Attention Profile Associated With the FMR1 Premutation

Atypical visual attention patterns have been observed among carriers of the fragile X mental retardation gene (FMR1) premutation (PM), with some similarities to visual attention patterns observed in autism spectrum disorder (ASD) and among clinically unaffected relatives of individuals with ASD. Patterns of visual attention could constitute biomarkers that can help to inform the neurocognitive profile of the PM, and that potentially span diagnostic boundaries. This study examined patterns of eye movement across an array of fixation measurements from three distinct eye-tracking tasks in order to investigate potentially overlapping profiles of visual attention among PM carriers, ASD parents, and parent controls. Logistic regression analyses were conducted to examine whether variables constituting a PM-specific looking profile were able to effectively predict group membership. Participants included 65PM female carriers, 188 ASD parents, and 84 parent controls. Analyses of fixations across the eye-tracking tasks, and their corresponding areas of interest, revealed a distinct visual attention pattern in carriers of the FMR1 PM, characterized by increased fixations on the mouth when viewing faces, more intense focus on bodies in socially complex scenes, and decreased fixations on salient characters and faces while narrating a wordless picture book. This set of variables was able to successfully differentiate individuals with the PM from controls (Sensitivity = 0.76, Specificity = 0.85, Accuracy = 0.77) as well as from ASD parents (Sensitivity = 0.70, Specificity = 0.80, Accuracy = 0.72), but did not show a strong distinction between ASD parents and controls (Accuracy = 0.62), indicating that this set of variables comprises a profile that is unique to PM carriers. Regarding predictive power, fixations toward the mouth when viewing faces was able to differentiate PM carriers from both ASD parents and controls, whereas fixations toward other social stimuli did not differentiate PM carriers from ASD parents, highlighting some overlap in visual attention patterns that could point toward shared neurobiological mechanisms. Results demonstrate a profile of visual attention that appears strongly associated with the FMR1 PM in women, and may constitute a meaningful biomarker.

Saccade dysmetria indicates attenuated visual exploration in autism spectrum disorder

BACKGROUND

Visual exploration in autism spectrum disorder (ASD) is characterized by attenuated social attention. The underlying oculomotor function during visual exploration is understudied, whereas oculomotor function during restricted viewing suggested saccade dysmetria in ASD by altered pontocerebellar motor modulation.

METHODS

Oculomotor function was recorded using remote eye tracking in 142 ASD participants and 142 matched neurotypical controls during free viewing of naturalistic videos with and without human content. The sample was heterogenous concerning age (6-30 years), cognitive ability (60-140 IQ), and male/female ratio (3:1). Oculomotor function was defined as saccade, fixation, and pupil-dilation features that were compared between groups in linear mixed models. Oculomotor function was investigated as ASD classifier and features were correlated with clinical measures.

RESULTS

We observed decreased saccade duration (∆M = -0.50, CI [-0.21, -0.78]) and amplitude (∆M = -0.42, CI [-0.12, -0.72]), which was independent of human video content. We observed null findings concerning fixation and pupil-dilation features (POWER = .81). Oculomotor function is a valid ASD classifier comparable to social attention concerning discriminative power. Within ASD, saccade features correlated with measures of restricted and repetitive behavior.

CONCLUSIONS

We conclude saccade dysmetria as ASD oculomotor phenotype relevant to visual exploration. Decreased saccade amplitude and duration indicate spatially clustered fixations that attenuate visual exploration and emphasize endogenous over exogenous attention. We propose altered pontocerebellar motor modulation as underlying mechanism that contributes to atypical (oculo-)motor coordination and attention function in ASD.

Information and Communication Technologies to Support Early Screening of Autism Spectrum Disorder: A Systematic Review

&nbsp;The aim of this systematic review is to identify recent digital technologies used to detect early signs of autism spectrum disorder (ASD) in preschool children (i.e., up to six years of age). A systematic literature search was performed for English language articles and conference papers indexed in Pubmed, PsycInfo, ERIC, CINAHL, WoS, IEEE, and ACM digital libraries up until January 2020. A follow-up search was conducted to cover the literature published until December 2020 for the usefulness and interest in this area of research during the Covid-19 emergency. In total, 2427 articles were initially retrieved from databases search. Additional 481 articles were retrieved from follow-up search. Finally, 28 articles met the inclusion criteria and were included in the review. The studies included involved four main interface modalities: Natural User Interface (e.g., eye trackers), PC or mobile, Wearable, and Robotics. Most of the papers included (n = 20) involved the use of Level 1 screening tools. Notwithstanding the variability of the solutions identified, psychometric information points to considering available technologies as promising supports in clinical practice to detect early sign of ASD in young children. Further research is needed to understand the acceptability and increase use rates of technology-based screenings in clinical settings.&nbsp.

Attend Less, Fear More: Elevated Distress to Social Threat in Toddlers With Autism Spectrum Disorder

Differential emotional reactivity to social and nonsocial stimuli has been hypothesized but rarely examined empirically in ASD despite its potential importance for development of social motivation, cognition, and comorbid psychopathology. This study examined emotional reactivity, regulation, and attention to social and nonsocial threat in toddlers with ASD (n = 42, M_age : 22 months) and typically developing (TD) toddlers (n = 22, M_age : 23 months), and their mutual associations with autism symptom severity. Participants were exposed to social (stranger), nonsocial (mechanical objects), and ambiguous (masks) threats, and their intensity of distress (iDistress), attention to threat (Attention), and presence of emotion regulation (ER) strategies were measured. Autism symptom severity was quantified using the Autism Diagnostic Observation Schedule-2. In response to social threat, toddlers with ASD exhibited elevated iDistress (P < 0.038) but lower Attention (P < 0.002) and a wider variety of ER strategies (P < 0.040) compared to TD controls, though their ER strategies were less likely to be social. However, nonsocial and ambiguous threat elicited lower iDistress in ASD than in TD toddlers (P = 0.012 and P = 0.034, respectively), but comparable Attention and ER strategy use. Autism severity was not associated with iDistress. The study demonstrates elevated emotional salience but diminished attentional salience of social threat in ASD. A failure to attend adequately to social threats may restrict opportunities to appraise their threat value and engender often observed in ASD negative emotional responses to novel social situations. Early atypical emotional reactivity may independently contribute to the shaping of complex autism phenotypes and may be linked with later emerging affective and behavioral symptoms. LAY SUMMARY: Compared to typically developing toddlers, toddlers with ASD show diminished attention yet enhanced distress in response to social threat. Poor attention to potential social threat may limit opportunities to assess its threat value and thus contribute to often observed negative emotional responses to novel social situations. Identifying the precursors of atypical emotional reactivity in infancy and its links with later psychopathology will inform about novel treatment targets and mechanisms of change in the early stages of ASD. Autism Res 2021, 14: 1025-1036. © 2020 International Society for Autism Research, Wiley Periodicals, LLC.

Atypical Emotional Electrodermal Activity in Toddlers with Autism Spectrum Disorder

Past studies in autism spectrum disorder (ASD) indicate atypical peripheral physiological arousal. However, the conditions under which these atypicalities arise and their link with behavioral emotional expressions and core ASD symptoms remain uncertain. Given the importance of physiological arousal in affective, learning, and cognitive processes, the current study examined changes in skin conductance level (ΔSCL) in 41 toddlers with ASD (mean age: 22.7 months, SD: 2.9) and 32 age-matched toddlers with typical development (TD) (mean age: 21.6 months, SD: 3.6) in response to probes designed to induce anger, joy, and fear emotions. The magnitude of ΔSCL was comparable during anger (P = 0.206, d = 0.30) and joy (P = 0.996, d = 0.01) conditions, but significantly lower during the fear condition (P = 0.001, d = 0.83) in toddlers with ASD compared to TD peers. In the combined samples, ΔSCL positively correlated with intensity of behavioral emotional expressivity during the anger (r[71] = 0.36, P = 0.002) and fear (r[68] = 0.32, P = 0.007) conditions, but not in the joy (r[69] = -0.15, P = 0.226) condition. Finally, ΔSCL did not associate with autism symptom severity in any emotion-eliciting condition in the ASD group. Toddlers with ASD displayed attenuated ΔSCL to situations aimed at eliciting fear, which may forecast the emergence of highly prevalent internalizing and externalizing problems in this population. The study putatively identifies ΔSCL as a dimension not associated with severity of autism but with behavioral responses in negatively emotionally challenging events and provides support for the feasibility, validity, and incipient utility of examining ΔSCL in response to emotional challenges in very young children. LAY SUMMARY: Physiological arousal was measured in toddlers with autism exposed to frustrating, pleasant, and threatening tasks. Compared to typically developing peers, toddlers with autism showed comparable arousal responses to frustrating and pleasant events, but lower responses to threatening events. Importantly, physiological arousal and behavioral expressions were aligned during frustrating and threatening events, inviting exploration of physiological arousal to measure responses to emotional challenges. Furthermore, this study advances the understanding of precursors to emotional and behavioral problems common in older children with autism. Autism Res 2020, 13: 1476-1488. © 2020 International Society for Autism Research, Wiley Periodicals, Inc.

Requirements for Robotic Interpretation of Social Signals “in the Wild”: Insights from Diagnostic Criteria of Autism Spectrum Disorder

The last few decades have seen widespread advances in technological means to characterise observable aspects of human behaviour such as gaze or posture. Among others, these developments have also led to significant advances in social robotics. At the same time, however, social robots are still largely evaluated in idealised or laboratory conditions, and it remains unclear whether the technological progress is sufficient to let such robots move “into the wild”. In this paper, we characterise the problems that a social robot in the real world may face, and review the technological state of the art in terms of addressing these. We do this by considering what it would entail to automate the diagnosis of Autism Spectrum Disorder (ASD). Just as for social robotics, ASD diagnosis fundamentally requires the ability to characterise human behaviour from observable aspects. However, therapists provide clear criteria regarding what to look for. As such, ASD diagnosis is a situation that is both relevant to real-world social robotics and comes with clear metrics. Overall, we demonstrate that even with relatively clear therapist-provided criteria and current technological progress, the need to interpret covert behaviour cannot yet be fully addressed. Our discussions have clear implications for ASD diagnosis, but also for social robotics more generally. For ASD diagnosis, we provide a classification of criteria based on whether or not they depend on covert information and highlight present-day possibilities for supporting therapists in diagnosis through technological means. For social robotics, we highlight the fundamental role of covert behaviour, show that the current state-of-the-art is unable to characterise this, and emphasise that future research should tackle this explicitly in realistic settings.

Emotional vs. Neutral Face Exploration and Habituation: An Eye-Tracking Study of Preschoolers With Autism Spectrum Disorders

Diminished orienting to social stimuli, and particularly to faces, is a core feature of autism spectrum disorders (ASDs). Impaired face processing has been linked to atypical attention processes that trigger a cascade of pathological development contributing to impaired social communication. The aim of the present study is to explore the processing of emotional and neutral faces using an eye-tracking paradigm (the emotional faces task) with a group of 24 children with ASD aged 6 and under and a group of 22 age-matched typically developing (TD) children. We also measure habituation to faces in both groups based on the presentation of repeated facial expressions. Specifically, the task consists of 32 pairs of faces, a neutral face and an emotional face from the same identity, shown side by side on the screen. We observe differential exploration of emotional faces in preschoolers with ASD compared with TD. Participants with ASD make fewer fixations to emotional faces than their TD peers, and the duration of their first fixation on emotional faces is equivalent to their first fixation on neutral faces. These results suggest that emotional faces may be less interesting for children with ASD. We also observe a habituation process to neutral faces in both children with ASD and TD, who looked less at neutral faces during the last quarter of the task compared with the first quarter. By contrast, TD children show increased interest in emotional faces throughout the task, looking slightly more at emotional faces during the last quarter of the task than during the first quarter. Children with ASD demonstrate neither habituation nor increased interest in the changing emotional expressions over the course of the task, looking at the stimuli for equivalent time throughout the task. A lack of increased interest in emotional faces may suggest a lack of sensitivity to changes in expression in young children with ASD.

Functional neuroanatomy of the human eye movement network: a review and atlas

The human eye movement network is a complex system that requires the integration of sensory, motor, attentional, and executive processes. Here, we review the neuroanatomy of the eye movement network with an emphasis on functional neuroimaging applications. We consolidate the literature into a concise resource designed to be immediately accessible and applicable to diverse research interests, and present the novel Functional Oculomotor System (FOcuS) Atlas-a tool in stereotaxic space that will simplify and standardize the inclusion of the eye movement network in future functional neuroimaging studies. We anticipate this review and the FOcuS Atlas will facilitate increased examination of the eye movement network across disciplines leading to a thorough understanding of how eye movement network function contributes to higher-order cognition and how it is integrated with other brain networks. Furthermore, functional examination of the eye movement network in patient populations offers the potential for deeper insight into the role of eye movement circuitry in functional network activity, diagnostic assessments, and the indications for augmentative communication systems that rely on eye movement control.

Diagnostic Assessment Techniques and Non-Invasive Biomarkers for Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a complex heterogeneous neurological disorder that has led to a spectrum of diagnosis techniques. The screening instruments, medical and technological tools initiate the diagnosis process. Clinicians and psychologists propose therapies depending on the examination done by these methodologies. The literature has accounted dozens of diagnostic methods and alternative and complementary therapies but still lack in highlighting the proper biomarker for early detection and intervention. The emerging multi-modal neuro-imaging techniques have correlated the brain's functional and structural measures and diagnosed ASD with more sensitivity than individual approaches. The purpose of this review article is: (i) to provide an overview of the emerging ASD diagnosis methods and different markers and; (ii) to present the idea of integrating all the individual methods in to a multi-modal diagnostic system to enhance detection sensitivity. This system possesses the potential to diagnose and predict ASD clinically, neurologically & objectively with high detection sensitivity.

Four Social Brain Regions, Their Dysfunctions, and Sequelae, Extensively Explain Autism Spectrum Disorder Symptomatology

Autism spectrum disorder (ASD) is a challenging neurodevelopmental disorder with symptoms in social, language, sensory, motor, cognitive, emotional, repetitive behavior, and self-sufficient living domains. The important research question examined is the elucidation of the pathogenic neurocircuitry that underlies ASD symptomatology in all its richness and heterogeneity. The presented model builds on earlier social brain research, and hypothesizes that four social brain regions largely drive ASD symptomatology: amygdala, orbitofrontal cortex (OFC), temporoparietal cortex (TPC), and insula. The amygdala's contributions to ASD largely derive from its major involvement in fine-grained intangible knowledge representations and high-level guidance of gaze. In addition, disrupted brain regions can drive disturbance of strongly interconnected brain regions to produce further symptoms. These and related effects are proposed to underlie abnormalities of the visual cortex, inferior frontal gyrus (IFG), caudate nucleus, and hippocampus as well as associated symptoms. The model is supported by neuroimaging, neuropsychological, neuroanatomical, cellular, physiological, and behavioral evidence. Collectively, the model proposes a novel, parsimonious, and empirically testable account of the pathogenic neurocircuitry of ASD, an extensive account of its symptomatology, a novel physiological biomarker with potential for earlier diagnosis, and novel experiments to further elucidate the mechanisms of brain abnormalities and symptomatology in ASD.

Saliva MicroRNA Differentiates Children With Autism From Peers With Typical and Atypical Development

OBJECTIVE

Clinical diagnosis of autism spectrum disorder (ASD) relies on time-consuming subjective assessments. The primary purpose of this study was to investigate the utility of salivary microRNAs for differentiating children with ASD from peers with typical development (TD) and non-autism developmental delay (DD). The secondary purpose was to explore microRNA patterns among ASD phenotypes.

METHOD

This multicenter, prospective, case-control study enrolled 443 children (2-6 years old). ASD diagnoses were based on DSM-5 criteria. Children with ASD or DD were assessed with the Autism Diagnostic Observation Schedule II and Vineland Adaptive Behavior Scales II. MicroRNAs were measured with high-throughput sequencing. Differential expression of microRNAs was compared among the ASD (n = 187), TD (n = 125), and DD (n = 69) groups in the training set (n = 381). Multivariate logistic regression defined a panel of microRNAs that differentiated children with ASD and those without ASD. The algorithm was tested in a prospectively collected naïve set of 62 samples (ASD, n = 37; TD, n = 8; DD, n = 17). Relations between microRNA levels and ASD phenotypes were explored.

RESULT

Fourteen microRNAs displayed differential expression (false discovery rate < 0.05) among ASD, TD, and DD groups. A panel of 4 microRNAs (controlling for medical/demographic covariates) best differentiated children with ASD from children without ASD in training (area under the curve = 0.725) and validation (area under the curve = 0.694) sets. Eight microRNAs were associated (R > 0.25, false discovery rate < 0.05) with social affect, and 10 microRNAs were associated with restricted/repetitive behavior.

CONCLUSION

Salivary microRNAs are "altered" in children with ASD and associated with levels of ASD behaviors. Salivary microRNA collection is noninvasive, identifying ASD-status with moderate accuracy. A multi-"omic" approach using additional RNA families could improve accuracy, leading to clinical application.

CLINICAL TRIAL REGISTRATION INFORMATION

A Salivary miRNA Diagnostic Test for Autism; https://clinicaltrials.gov/; NCT02832557.

Detection of Stereotypical Motor Movements in Autism using a Smartwatch-based System

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that is often accompanied by stereotypical motor movements. Health professionals typically assess the severity of these behaviors during therapy, which limits observations to a structured clinical setting. Recent advancements in ubiquitous computing and wearable sensors enable an ability to monitor these motor movements objectively and in real-time while children with ASD are in different environments. In this paper, we present a smartwatch-based system designed to detect stereotypical motor movements. To validate the feasibility ofour approach, we collected data from adults imitating example behaviors captured in YouTube videos of children with ASD, and we then evaluated several classification methods for accuracy. The best model can identify stereotypical motor activities of hand flapping, head banging, and repetitive dropping with 92.6% accuracy (precision 88.8% and recall 87.7%) in the presence of confounding play-type activities. We present the trade-offs between accuracy ofthe assessments and power consumption due to sensing from multiple modalities. Cross-participant validation shows that the results ofusing the model on an unknown subject are promising.

Development and Validation of Objective and Quantitative Eye Tracking-Based Measures of Autism Risk and Symptom Levels

OBJECTIVE

The primary aim of this study was to develop and validate eye tracking-based measures for estimating autism spectrum disorder (ASD) risk and quantifying autism symptom levels.

METHOD

Eye tracking data were collected from youth during an initial evaluation visit, with administrators blinded to all clinical information. Consensus diagnoses were given by the multidisciplinary team. Participants viewed a 5-minute video that included 44 dynamic stimuli from 7 distinct paradigms while gaze was recorded. Gaze metrics were computed for temporally defined regions of interest. Autism risk and symptom indices aggregated gaze measures showing significant bivariate relationships with ASD diagnosis and Autism Diagnostic Observation Schedule, Second Edition (ADOS-2) symptom severity levels in a training sample (75%, n = 150). Receiver operating characteristic curve analysis and nonparametric correlations were used to cross-validate findings in a test sample (25%; n = 51).

RESULTS

Most children (n = 201, 92%) completed a valid eye tracking assessment (ages 1.6─17.6; 80% male; ASD n = 91, non-ASD n = 110). In the test subsample, the autism risk index had high accuracy for ASD diagnosis (area under the curve [AUC] = 0.86, 95% CI =0.75-0.95), whereas the autism symptom index was strongly associated with ADOS-2 total severity scores (r = 0.41, p < .001). Validity was not substantively attenuated after adjustment for language, nonverbal cognitive ability, or other psychopathology symptoms (r = 0.40-0.67, p > .001).

CONCLUSION

Eye tracking measures appear to be useful quantitative, objective measures of ASD risk and autism symptom levels. If independently replicated and scaled for clinical use, eye tracking-based measures could be used to inform clinical judgment regarding ASD identification and to track autism symptom levels.

A Meta-Analysis of Gaze Differences to Social and Nonsocial Information Between Individuals With and Without Autism

OBJECTIVE

Numerous studies have identified abnormal gaze in individuals with autism. However, only some findings have been replicated, the magnitude of effects is unclear, and the pattern of gaze differences across stimuli remains poorly understood. To address these gaps, a comprehensive meta-analysis of autism eye-tracking studies was conducted.

METHOD

PubMed and a manual search of 1,132 publications were used to identify studies comparing looking behavior to social and/or nonsocial stimuli between individuals with autism and controls. Sample characteristics, eye-tracking methods, stimulus features, and regions of interest (ROIs) were coded for each comparison within each study. Multivariate mixed-effects meta-regression analyses examined the impact of study methodology, stimulus features, and ROI on effect sizes derived from comparisons using gaze-fixation metrics.

RESULTS

The search yielded 122 independent studies with 1,155 comparisons. Estimated effect sizes tended to be small to medium but varied substantially across stimuli and ROIs. Overall, nonsocial ROIs yielded larger effect sizes than social ROIs; however, eye and whole-face regions from stimuli with human interaction produced the largest effects (Hedges g = 0.47 and 0.50, respectively). Studies with weaker study designs or reporting yielded larger effects, but key effects remained significant and medium in size, even for high-rigor designs.

CONCLUSION

Individuals with autism show a reliable pattern of gaze abnormalities that suggests a basic problem with selecting socially relevant versus irrelevant information for attention and that persists across ages and worsens during perception of human interactions. Aggregation of gaze abnormalities across stimuli and ROIs could yield clinically useful risk assessment and quantitative, objective outcome measurements.

Sensing Technologies for Autism Spectrum Disorder Screening and Intervention

This paper reviews the state-of-the-art in sensing technologies that are relevant for Autism Spectrum Disorder (ASD) screening and therapy. This disorder is characterized by difficulties in social communication, social interactions, and repetitive behaviors. It is diagnosed during the first three years of life. Early and intensive interventions have been shown to improve the developmental trajectory of the affected children. The earlier the diagnosis, the sooner the intervention therapy can begin, thus, making early diagnosis an important research goal. Technological innovations have tremendous potential to assist with early diagnosis and improve intervention programs. The need for careful and methodological evaluation of such emerging technologies becomes important in order to assist not only the therapists and clinicians in their selection of suitable tools, but to also guide the developers of the technologies in improving hardware and software. In this paper, we survey the literatures on sensing technologies for ASD and we categorize them into eye trackers, movement trackers, electrodermal activity monitors, tactile sensors, vocal prosody and speech detectors, and sleep quality assessment devices. We assess their effectiveness and study their limitations. We also examine the challenges faced by this growing field that need to be addressed before these technologies can perform up to their theoretical potential.