Toward Continuous Social Phenotyping: Analyzing Gaze Patterns in an Emotion Recognition Task for Children With Autism Through Wearable Smart Glasses.

BACKGROUND: Several studies have shown that facial attention differs in children with autism. Measuring eye gaze and emotion recognition in children with autism is challenging, as standard clinical assessments must be delivered in clinical settings by a trained clinician. Wearable technologies may be able to bring eye gaze and emotion recognition into natural social interactions and settings. OBJECTIVE: This study aimed to test: (1) the feasibility of tracking gaze using wearable smart glasses during a facial expression recognition task and (2) the ability of these gaze-tracking data, together with facial expression recognition responses, to distinguish children with autism from neurotypical controls (NCs). METHODS: We compared the eye gaze and emotion recognition patterns of 16 children with autism spectrum disorder (ASD) and 17 children without ASD via wearable smart glasses fitted with a custom eye tracker. Children identified static facial expressions of images presented on a computer screen along with nonsocial distractors while wearing Google Glass and the eye tracker. Faces were presented in three trials, during one of which children received feedback in the form of the correct classification. We employed hybrid human-labeling and computer vision-enabled methods for pupil tracking and world-gaze translation calibration. We analyzed the impact of gaze and emotion recognition features in a prediction task aiming to distinguish children with ASD from NC participants. RESULTS: Gaze and emotion recognition patterns enabled the training of a classifier that distinguished ASD and NC groups. However, it was unable to significantly outperform other classifiers that used only age and gender features, suggesting that further work is necessary to disentangle these effects. CONCLUSIONS: Although wearable smart glasses show promise in identifying subtle differences in gaze tracking and emotion recognition patterns in children with and without ASD, the present form factor and data do not allow for these differences to be reliably exploited by machine learning systems. Resolving these challenges will be an important step toward continuous tracking of the ASD phenotype.

Neural circuits underlying mother's voice perception predict social communication abilities in children.

The human voice is a critical social cue, and listeners are extremely sensitive to the voices in their environment. One of the most salient voices in a child's life is mother's voice: Infants discriminate their mother's voice from the first days of life, and this stimulus is associated with guiding emotional and social function during development. Little is known regarding the functional circuits that are selectively engaged in children by biologically salient voices such as mother's voice or whether this brain activity is related to children's social communication abilities. We used functional MRI to measure brain activity in 24 healthy children (mean age, 10.2 y) while they attended to brief (<1 s) nonsense words produced by their biological mother and two female control voices and explored relationships between speech-evoked neural activity and social function. Compared to female control voices, mother's voice elicited greater activity in primary auditory regions in the midbrain and cortex; voice-selective superior temporal sulcus (STS); the amygdala, which is crucial for processing of affect; nucleus accumbens and orbitofrontal cortex of the reward circuit; anterior insula and cingulate of the salience network; and a subregion of fusiform gyrus associated with face perception. The strength of brain connectivity between voice-selective STS and reward, affective, salience, memory, and face-processing regions during mother's voice perception predicted social communication skills. Our findings provide a novel neurobiological template for investigation of typical social development as well as clinical disorders, such as autism, in which perception of biologically and socially salient voices may be impaired.

Brain State Differentiation and Behavioral Inflexibility in Autism.

Autism spectrum disorders (ASDs) are characterized by social impairments alongside cognitive and behavioral inflexibility. While social deficits in ASDs have extensively been characterized, the neurobiological basis of inflexibility and its relation to core clinical symptoms of the disorder are unknown. We acquired functional neuroimaging data from 2 cohorts, each consisting of 17 children with ASDs and 17 age- and IQ-matched typically developing (TD) children, during stimulus-evoked brain states involving performance of social attention and numerical problem solving tasks, as well as during intrinsic, resting brain states. Effective connectivity between key nodes of the salience network, default mode network, and central executive network was used to obtain indices of functional organization across evoked and intrinsic brain states. In both cohorts examined, a machine learning algorithm was able to discriminate intrinsic (resting) and evoked (task) functional brain network configurations more accurately in TD children than in children with ASD. Brain state discriminability was related to severity of restricted and repetitive behaviors, indicating that weak modulation of brain states may contribute to behavioral inflexibility in ASD. These findings provide novel evidence for a potential link between neurophysiological inflexibility and core symptoms of this complex neurodevelopmental disorder.

COMT genotype predicts longitudinal cognitive decline and psychosis in 22q11.2 deletion syndrome.

Although schizophrenia is strongly hereditary, there are limited data regarding biological risk factors and pathophysiological processes. In this longitudinal study of adolescents with 22q11.2 deletion syndrome, we identified the catechol-O-methyltransferase low-activity allele (COMT(L)) as a risk factor for decline in prefrontal cortical volume and cognition, as well as for the consequent development of psychotic symptoms during adolescence. The 22q11.2 deletion syndrome is a promising model for identifying biomarkers related to the development of schizophrenia.

Effect of Wearable Digital Intervention for Improving Socialization in Children With Autism Spectrum Disorder: A Randomized Clinical Trial.

Importance: Autism behavioral therapy is effective but expensive and difficult to access. While mobile technology-based therapy can alleviate wait-lists and scale for increasing demand, few clinical trials exist to support its use for autism spectrum disorder (ASD) care. Objective: To evaluate the efficacy of Superpower Glass, an artificial intelligence-driven wearable behavioral intervention for improving social outcomes of children with ASD. Design, Setting, and Participants: A randomized clinical trial in which participants received the Superpower Glass intervention plus standard of care applied behavioral analysis therapy and control participants received only applied behavioral analysis therapy. Assessments were completed at the Stanford University Medical School, and enrolled participants used the Superpower Glass intervention in their homes. Children aged 6 to 12 years with a formal ASD diagnosis who were currently receiving applied behavioral analysis therapy were included. Families were recruited between June 2016 and December 2017. The first participant was enrolled on November 1, 2016, and the last appointment was completed on April 11, 2018. Data analysis was conducted between April and October 2018. Interventions: The Superpower Glass intervention, deployed via Google Glass (worn by the child) and a smartphone app, promotes facial engagement and emotion recognition by detecting facial expressions and providing reinforcing social cues. Families were asked to conduct 20-minute sessions at home 4 times per week for 6 weeks. Main Outcomes and Measures: Four socialization measures were assessed using an intention-to-treat analysis with a Bonferroni test correction. Results: Overall, 71 children (63 boys [89%]; mean [SD] age, 8.38 [2.46] years) diagnosed with ASD were enrolled (40 [56.3%] were randomized to treatment, and 31 (43.7%) were randomized to control). Children receiving the intervention showed significant improvements on the Vineland Adaptive Behaviors Scale socialization subscale compared with treatment as usual controls (mean [SD] treatment impact, 4.58 [1.62]; P = .005). Positive mean treatment effects were also found for the other 3 primary measures but not to a significance threshold of P = .0125. Conclusions and Relevance: The observed 4.58-point average gain on the Vineland Adaptive Behaviors Scale socialization subscale is comparable with gains observed with standard of care therapy. To our knowledge, this is the first randomized clinical trial to demonstrate efficacy of a wearable digital intervention to improve social behavior of children with ASD. The intervention reinforces facial engagement and emotion recognition, suggesting either or both could be a mechanism of action driving the observed improvement. This study underscores the potential of digital home therapy to augment the standard of care. Trial Registration: ClinicalTrials.gov identifier: NCT03569176.

Feasibility Testing of a Wearable Behavioral Aid for Social Learning in Children with Autism.

BACKGROUND: Recent advances in computer vision and wearable technology have created an opportunity to introduce mobile therapy systems for autism spectrum disorders (ASD) that can respond to the increasing demand for therapeutic interventions; however, feasibility questions must be answered first. OBJECTIVE: We studied the feasibility of a prototype therapeutic tool for children with ASD using Google Glass, examining whether children with ASD would wear such a device, if providing the emotion classification will improve emotion recognition, and how emotion recognition differs between ASD participants and neurotypical controls (NC). METHODS: We ran a controlled laboratory experiment with 43 children: 23 with ASD and 20 NC. Children identified static facial images on a computer screen with one of 7 emotions in 3 successive batches: the first with no information about emotion provided to the child, the second with the correct classification from the Glass labeling the emotion, and the third again without emotion information. We then trained a logistic regression classifier on the emotion confusion matrices generated by the two information-free batches to predict ASD versus NC. RESULTS: All 43 children were comfortable wearing the Glass. ASD and NC participants who completed the computer task with Glass providing audible emotion labeling (n = 33) showed increased accuracies in emotion labeling, and the logistic regression classifier achieved an accuracy of 72.7%. Further analysis suggests that the ability to recognize surprise, fear, and neutrality may distinguish ASD cases from NC. CONCLUSION: This feasibility study supports the utility of a wearable device for social affective learning in ASD children and demonstrates subtle differences in how ASD and NC children perform on an emotion recognition task.

Exploratory study examining the at-home feasibility of a wearable tool for social-affective learning in children with autism.

Although standard behavioral interventions for autism spectrum disorder (ASD) are effective therapies for social deficits, they face criticism for being time-intensive and overdependent on specialists. Earlier starting age of therapy is a strong predictor of later success, but waitlists for therapies can be 18 months long. To address these complications, we developed Superpower Glass, a machine-learning-assisted software system that runs on Google Glass and an Android smartphone, designed for use during social interactions. This pilot exploratory study examines our prototype tool's potential for social-affective learning for children with autism. We sent our tool home with 14 families and assessed changes from intake to conclusion through the Social Responsiveness Scale (SRS-2), a facial affect recognition task (EGG), and qualitative parent reports. A repeated-measures one-way ANOVA demonstrated a decrease in SRS-2 total scores by an average 7.14 points (F(1,13) = 33.20, p = <.001, higher scores indicate higher ASD severity). EGG scores also increased by an average 9.55 correct responses (F(1,10) = 11.89, p = <.01). Parents reported increased eye contact and greater social acuity. This feasibility study supports using mobile technologies for potential therapeutic purposes.

Risk factors for the emergence of psychotic disorders in adolescents with 22q11.2 deletion syndrome.

OBJECTIVE: The 22q11.2 deletion syndrome is the most common known genetic risk factor for the development of schizophrenia. The authors conducted a longitudinal evaluation of adolescents with 22q11.2 deletion syndrome to identify early risk factors for the development of psychotic disorders. METHOD: Sixty children, 31 with 22q11.2 deletion syndrome and 29 comparison subjects with idiopathic developmental disability matched for age and IQ, underwent a baseline evaluation between 1998 and 2000; of these, 51 children (28 and 23 in the two groups, respectively) underwent follow-up evaluation between 2003 and 2005. A standardized comprehensive psychiatric, psychological, and adaptive functioning evaluation was conducted in both waves. Participants with 22q11.2 deletion syndrome were also genotyped for the catechol O-methyltransferase (COMT) Met/Val polymorphism and underwent magnetic resonance imaging scans. RESULTS: The two groups had similar baseline neuropsychiatric profiles. At follow-up, 32.1% of subjects with 22q11.2 deletion syndrome had developed psychotic disorders as compared with 4.3% of comparison subjects. In the 22q11.2 deletion syndrome group, baseline subthreshold psychotic symptoms interacted both with the COMT genotype and with baseline symptoms of anxiety or depression to predict 61% of the variance in severity of psychosis at follow-up evaluation. Lower baseline verbal IQ was also associated with more severe psychotic symptoms at follow-up evaluation. CONCLUSIONS: Genetic, cognitive, and psychiatric risk factors for the evolution of psychotic disorders in 22q11.2 deletion syndrome during adolescence were identified. Early intervention in the subgroup of children with subthreshold signs of psychosis and internalizing symptoms (especially anxiety symptoms) may reduce the risk of developing psychotic disorders during adolescence.

Social phenotypes in neurogenetic syndromes.

Many of the known genetically based neurodevelopmental disorders are associated with a distinctive behavioral phenotype. As these behavioral phenotypes have been elucidated by clinical research, distinctive profiles of social traits have emerged as prominent syndromic features. This article reviews social phenotypic findings for fragile X syndrome, Down syndrome, Prader-Willi syndrome, Smith-Magenis syndrome, Turner syndrome, Williams syndrome, and velocardiofacial syndrome. An analysis of these social profiles raises several questions regarding the relationship between identified social impairments and autism and the relationship between social impairments in neurodevelopmental disorders and those found in normative child populations. The unique profile of certain of the known behavioral phenotypes also serves to distinguish several dimensions of sociability that are not readily observed in typical populations.

Psychotic symptoms in children and adolescents with 22q11.2 deletion syndrome: Neuropsychological and behavioral implications.

Individuals with 22q11.2 deletion syndrome (22q11DS) are at increased risk for developing schizophrenia: half of affected adolescents report transient psychotic experiences and up to 30% of adults are diagnosed with schizophrenia. Prospective studies have shown that psychotic symptoms in childhood are predictive of later schizophreniform disorders. The current study aimed to define the prevalence and correlates of psychotic symptoms (PS) in young children and adolescents with 22q11DS. Forty-three children and adolescents with 22q11DS (mean age = 10.62+/-11.19) participated in this study. The occurrence of PS and their neuropsychological and behavioral correlates were investigated through semi-structured interviews and standardized measures. Psychotic symptoms were reported in 28% of the total sample and 17% of pre-adolescent children, and associated with decreased verbal IQ scores [F(1) = 4.41, p = 0.042]. Compared to young patients without PS, young patients with PS were perceived by their parents as more anxious-depressed [F(1) = 4.76, p = 0.035] and withdrawn [F(1) = 7.63, p = 0.009], with reduced adaptive socialization skills [F(1) = 6.88, p = 0.012]. Results suggest that psychotic manifestations are present earlier than typically reported in youngsters with 22q11DS and are accompanied by reduced verbal IQ performance and decreased adaptative social skills. The symptomatic, neuropsychological and behavioral characteristics observed in the current study may constitute central markers of increased risk for psychosis in 22q11DS.

Psychiatric disorders and behavioral problems in children with velocardiofacial syndrome: usefulness as phenotypic indicators of schizophrenia risk.

BACKGROUND: Velocardiofacial syndrome (VCFS), a genetic deletion condition with numerous cognitive sequelae, is associated with a high rate of psychiatric disorders in childhood. More recently, VCFS has been identified as a high-risk factor for developing adult onset schizophrenia. However, it has never been demonstrated that the childhood psychiatric disorders found in children with VCFS differ from those found in children with a similar degree of cognitive impairment. Identification of a specific behavioral (psychiatric) phenotype in childhood VCFS offers the potential for elucidating the symptomatic precursors of adult onset schizophrenia. METHODS: Twenty-eight children with VCFS and 29 age- and cognitively matched control subjects received a standardized assessment of childhood psychiatric disorders and behaviors measured by the Child Behavior Checklist (CBCL). Findings from the two groups were compared. RESULTS: The rates and types of psychiatric disorder and behavior problems in VCFS and cognitively matched control subjects were very high, but showed no significant differences. CONCLUSIONS: Psychopathology in children with VCFS may not differ from that found in cognitively matched control subjects. Another explanation is that subtle phenotypic differences in behavior found in VCFS can not be observed using standard symptom inventories. The high rate of psychopathology in children with VCFS is not a useful phenotypic indicator of high risk for adult onset schizophrenia.

Responses and sustained interactions in children with mental retardation and autism.

Sustained interactions and responses to social bids made by children with autism and verbal-age-matched children with mental retardation were recorded in two naturalistic settings. Children with autism produced fewer positive responses and more "no responses" than children with mental retardation; both groups were more likely to make positive responses to adults and not to respond to other children. Furthermore, although the frequency of conversations was not different for the two groups, children with autism were significantly less likely to engage in sustained play compared to children with mental retardation. Results suggest that children with autism are able to master the more rote and need-oriented social skills, such as simple conversation, but may not develop other forms of social interactions, like play.

Asperger syndrome and DSM-5: a dilemma for a college freshman.

CASE: Angela is an 18-year-old college freshman who made an appointment with her pediatrician because of academic and social difficulties at college. She was diagnosed with Asperger disorder at age 6 based on difficulties relating to adults and peers, perseverative patterns of interest, and normal language development.She received special education services in middle school to help follow directions and complete assignments. She reports feeling very isolated during this time. In freshman year of high school, she insisted on discontinuing special education and managed with weekly private individual psychotherapy.In sophomore year, Angela learned strategies to get additional help from her teachers about assignments, and her grades improved. Socially, she formed a close friendship with a classmate who was also on the autistic spectrum, and she found a group of friends through this individual. As a senior with an upward grade trajectory and good SAT scores, she was admitted to a competitive 4-year college. In a precollege consult 6 months ago, she was anxious about fitting in.Angela began college classes without accommodations, but she now describes a challenging semester. She has not made many friends. She finds her courses difficult and does not fully understand assignments. She believes her peers dislike her. She thinks she would benefit from receiving note-taking and other services and asks you to document her disability for the college so that she might obtain accommodations.You point out that the DSM-5 eliminates the Asperger category. Angela is concerned. She does not believe that her profile is consistent with autism spectrum disorder, and she fears that being labeled as autistic will be prejudicial at school. Yet she is worried about retaining eligibility for services on the basis of a disability. How do you counsel her?

Salience network-based classification and prediction of symptom severity in children with autism.

IMPORTANCE: Autism spectrum disorder (ASD) affects 1 in 88 children and is characterized by a complex phenotype, including social, communicative, and sensorimotor deficits. Autism spectrum disorder has been linked with atypical connectivity across multiple brain systems, yet the nature of these differences in young children with the disorder is not well understood. OBJECTIVES: To examine connectivity of large-scale brain networks and determine whether specific networks can distinguish children with ASD from typically developing (TD) children and predict symptom severity in children with ASD. DESIGN, SETTING, AND PARTICIPANTS: Case-control study performed at Stanford University School of Medicine of 20 children 7 to 12 years old with ASD and 20 age-, sex-, and IQ-matched TD children. MAIN OUTCOMES AND MEASURES: Between-group differences in intrinsic functional connectivity of large-scale brain networks, performance of a classifier built to discriminate children with ASD from TD children based on specific brain networks, and correlations between brain networks and core symptoms of ASD. RESULTS: We observed stronger functional connectivity within several large-scale brain networks in children with ASD compared with TD children. This hyperconnectivity in ASD encompassed salience, default mode, frontotemporal, motor, and visual networks. This hyperconnectivity result was replicated in an independent cohort obtained from publicly available databases. Using maps of each individual's salience network, children with ASD could be discriminated from TD children with a classification accuracy of 78%, with 75% sensitivity and 80% specificity. The salience network showed the highest classification accuracy among all networks examined, and the blood oxygen-level dependent signal in this network predicted restricted and repetitive behavior scores. The classifier discriminated ASD from TD in the independent sample with 83% accuracy, 67% sensitivity, and 100% specificity. CONCLUSIONS AND RELEVANCE: Salience network hyperconnectivity may be a distinguishing feature in children with ASD. Quantification of brain network connectivity is a step toward developing biomarkers for objectively identifying children with ASD.

Psychiatric phenotypes associated with neurogenetic disorders.

Advances in understanding the human genome and clinical application have led to identification of genetically based disorders that have distinctive behavioral phenotypes and risk for serious psychiatric disorders. Some patients have unrecognized genetic disorders presenting as psychiatric symptoms. Practitioners must be knowledgeable about the association between symptoms and underlying genetic bases. Treatment of neurogenetic disorders includes providing information about causes and prognoses. Patients are served best if they remain long term with a multidisciplinary team of providers who recognize the realities of a lifetime course, the high risk for symptom recurrence, and the need for providing information and support to families and coordinating medical and psychiatric care.